Physical Exercise and Natural and Synthetic Products in Health and Disease (Methods in Molecular Biology, 2343) 1071615572, 9781071615577

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Methods in Molecular Biology 2343

Paul C. Guest Editor

Physical Exercise and Natural and Synthetic Products in Health and Disease

METHODS

IN

MOLECULAR BIOLOGY

Series Editor John M. Walker School of Life and Medical Sciences University of Hertfordshire Hatfield, Hertfordshire, UK

For further volumes: http://www.springer.com/series/7651

For over 35 years, biological scientists have come to rely on the research protocols and methodologies in the critically acclaimed Methods in Molecular Biology series. The series was the first to introduce the step-by-step protocols approach that has become the standard in all biomedical protocol publishing. Each protocol is provided in readily-reproducible step-bystep fashion, opening with an introductory overview, a list of the materials and reagents needed to complete the experiment, and followed by a detailed procedure that is supported with a helpful notes section offering tips and tricks of the trade as well as troubleshooting advice. These hallmark features were introduced by series editor Dr. John Walker and constitute the key ingredient in each and every volume of the Methods in Molecular Biology series. Tested and trusted, comprehensive and reliable, all protocols from the series are indexed in PubMed.

Physical Exercise and Natural and Synthetic Products in Health and Disease Edited by

Paul C. Guest Charlesworth House, Debden, Essex, UK

Editor Paul C. Guest Charlesworth House Debden, Essex, UK

ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-0716-1557-7 ISBN 978-1-0716-1558-4 (eBook) https://doi.org/10.1007/978-1-0716-1558-4 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Humana imprint is published by the registered company Springer Science+Business Media, LLC, part of Springer Nature. The registered company address is: 1 New York Plaza, New York, NY 10004, U.S.A.

Preface According to the World Health Organization, noncommunicable diseases impose the greatest burden on global health with staggering costs in daily associated living and to the healthcare services. Beyond traditional pharmaceutical approaches, thousands of studies have now been carried out with the aim of testing aerobic exercise, resistance training, special diets, additives, and natural products, which have led to new insights into the physiological and molecular aspects of health and disease. Many of these approaches have led to significant improvements in disease areas such as cardiovascular disease, cognitive dysfunction, diabetes, frailty, glioblastoma, metabolic syndrome, obesity, oxidative stress, and various cancers. This book presents a series of protocols covering such studies by research scientists and clinicians from five out of the six habitable continents. This includes countries such as Brazil, Canada, China, Germany, India, Indonesia, Iran, Oman, Philippines, Poland, South Africa, South Korea, Thailand, the United Kingdom, the United States of America, and Vietnam. This underscores the keen interest in the possibilities of natural remedies throughout the world. The book will be of high interest to researchers in the areas of chronic disease, exercise, and nutrition, as well as to clinical scientists, physicians, and the major drug companies since it gives insights into possibilities for the development of novel therapeutics, as well as the means of monitoring therapeutic response through measurement of molecular and physiometric biomarkers. It will also be of high interest to both technical and bench scientists as it gives detailed instructions on how to carry out the various presented methods along with important notes which give insights beyond the traditional protocols. It also provides important information on disease mechanisms and novel drug targets as each protocol is presented in the context of specific chronic diseases or different therapeutic areas. Finally, it will be of high interest to people in all walks of life considering that physical health has been linked to disease outcomes in the current COVID-19 pandemic. Debden, Essex, UK

Paul C. Guest

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Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

PART I

v xi

REVIEWS

1 The New Frontier of Three-Dimensional Culture Models to Scale-Up Cancer Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Caleb Jensen, Chloe Shay, and Yong Teng 2 Therapeutic Effects of Resveratrol on Nonalcoholic Fatty Liver Disease Through Inflammatory, Oxidative Stress, Metabolic, and Epigenetic Modifications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Mina Karimi, Behnaz Abiri, Paul C. Guest, and Mohammadreza Vafa 3 A Matter of Fat: Body Fat Distribution and Cardiometabolic Disease in Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Nasrin Goolam Mahyoodeen and Nigel J. Crowther 4 PGK1: An Essential Player in Modulating Tumor Metabolism . . . . . . . . . . . . . . . . 57 Leslie Duncan, Chloe Shay, and Yong Teng 5 The Association of Reproductive Aging with Cognitive Function in Sub-Saharan African Women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Nicole G. Jaff and Nigel J. Crowther 6 The Effects of Exercise on Lipid Biomarkers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Michael Vaughn F. Mendoza, Sergey M. Kachur, and Carl J. Lavie 7 Exercise Training Protocols to Improve Obesity, Glucose Homeostasis, and Subclinical Inflammation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Tiego A. Diniz, Barbara M. Antunes, Jonathan P. Little, Fabio S. Lira, and Jose´ Cesar Rosa-Neto

PART II

PROTOCOLS

8 A Protocol of Intradialytic Exercise for Improvements in Inflammatory Status, Body Composition, and Functional Capacity. . . . . . . . . . . . 149 Lorena Cristina Curado Lopes, Paula Alves Monteiro, ˜ o Felipe Mota and Joa 9 Evaluating the Anticancer Activity of Natural Products Using a Novel 3D Culture Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Chloe Shay and Yong Teng 10 Evaluation of Antidiabetic Properties of Adenosma Bracteosum Bonati Extracts in Mice with Streptozotocin-Induced Diabetes . . . . . . . . . . . . . . . 165 Giau Van Vo, Paul C. Guest, and Ngoc Hong Nguyen

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Testing the Effects of Cinnamon Extract Supplementation on Inflammation and Oxidative Stress Induced by Acrylamide. . . . . . . . . . . . . . . . Fatemeh Haidari, Majid Mohammadshahi, Behnaz Abiri, Paul C. Guest, Mehdi Zarei, and Mojdeh Fathi Proteomic Mapping of the Human Myelin Proteome . . . . . . . . . . . . . . . . . . . . . . . Paul C. Guest Testing for Thyroid Peroxidase and Antineuronal Antibodies in Depression and Schizophrenia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Johann Steiner, Winfried Stoecker, Bianca Teegen, Henrik Dobrowolny, Gabriela Meyer-Lotz, Katrin Borucki, Paul C. Guest, and Hans-Gert Bernstein Evaluation of Antimicrobial and Anticancer Activities of Bouea macrophylla Ethanol Extract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Giau Van Vo, Paul C. Guest, and Ngoc Hong Nguyen Evaluation of Anti-Hepatocellular-Cancer Properties of β-Sitosterol and β-Sitosterol-Glucoside from Indigofera zollingeriana Miq. . . . . . . . . . . . . . . . Giau Van Vo, Paul C. Guest, Thuy Trang Nguyen, and Tuong Kha Vo Label-Free Electrochemical Biosensors to Evaluate the Antioxidant Effect of Tocopherol in Ultraviolet Radiation . . . . . . . . . . . . . . . . . . . Lixia Gao and Yong Teng qRT-PCR Analysis of GLUT-4 and Assessment of Trolox as an Effective Antioxidant in Diabetic Cardiomyoblasts . . . . . . . . . . . . . . . . . . . . . . . . . . S. Asha Devi, Ravichandra Shivalingappa Davargaon, and M. V. V. Subramanyam Flow Cytometric Analysis of Hyperglycemia-Induced Cell Death Pathways in Cardiomyoblasts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ravichandra Shivalingappa Davargaon, M. V. V. Subramanyam, and S. Asha Devi Vietnamese Medicinal Plants as Potential Resources to Explore New Anticancer and Anti-inflammation: Established Assays for Pharmacological Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Trang Thi Phuong Nguyen, Dieu Thi Xuan Nguyen, and Triet Thanh Nguyen Testing the Effect of Curcumin on Proliferative Capacity of Colorectal Cancer Cells. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tannaz Jamialahmadi, Paul C. Guest, Amir R. Afshari, Muhammed Majeed, and Amirhossein Sahebkar Assessment of Topical and Transdermal Penetration of Curcuma heyneana Rhizome Extract in Rat Skin: Histological Analysis . . . . . . . . . . . . . . . . . Idha Kusumawati, Rohmania, Mega Ferdina Warsito, and Eka Pramyrtha Hestianah Measuring the Effects of Berberine on Serum Prooxidant–Antioxidant Balance in Metabolic Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tannaz Jamialahmadi, Paul C. Guest, Aida Tasbandi Khalid Al-Rasadi, and Amirhossein Sahebkar

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Testing the Anti-inflammatory Effects of Curcuminoids in Patients with Colorectal Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tannaz Jamialahmadi, Paul C. Guest, Aida Tasbandi, Muhammed Majeed, and Amirhossein Sahebkar Analytical Methods and Bioassays for Cytotoxicity and Antidiabetic Properties of Aquilaria crassna Leaf Extracts in HepG2 Cells . . . . . . . . . . . . . . . . Pinnara Rojvirat, Netiya Karaket, Phanupol Mongkolsiri, and Sarawut Jitrapakdee Testing the Physical and Molecular Effects of Nutritional Supplements and Resistance Exercise in Middle-Aged Females . . . . . . . . . . . . . . . . . . . . . . . . . . . Behnaz Abiri, Paul C. Guest, Parvin Sarbakhsh, and Mohammadreza Vafa Analysis of Cytotoxic Effects of Zerumbone in Malignant Glioblastoma Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mohammad Jalili-Nik, Amir R. Afshari, Khadijeh Mahboobnia, Paul C. Guest, Tannaz Jamialahmadi, and Amirhossein Sahebkar Protocol for Testing the Potential Antioxidant Effects of Curcuminoids on Patients with Type 2 Diabetes Mellitus . . . . . . . . . . . . . . . . . . . . Tannaz Jamialahmadi, Yunes Panahi, Muhammed Majeed, Paul C. Guest, and Amirhossein Sahebkar The Detection of Toxic Compounds in Extracts of Callilepis laureola (Oxeye Daisy) and Senecio latifolius (Ragwort) by Ultra-Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS/MS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tracy Snyman and Nigel J. Crowther Impact of Curcumin on Hepatic Low-Density Lipoprotein Uptake . . . . . . . . . . . Mohammad Jalili-Nik, Khadijeh Mahboobnia, Paul C. Guest, Muhammed Majeed, Khalid Al-Rasadi, Tannaz Jamialahmadi, and Amirhossein Sahebkar

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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401

Contributors BEHNAZ ABIRI • Department of Nutrition, Faculty of Paramedicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran AMIR R. AFSHARI • Department of Physiology and Pharmacology, School of Medicine, North Khorasan University of Medical Sciences, Bojnurd, Iran KHALID AL-RASADI • Medical Research Centre, Sultan Qaboos University, Muscat, Oman BARBARA M. ANTUNES • Exercise and Immunometabolism Research Group, Department of Physical Education, Universidade Estadual Paulista (UNESP), Presidente Prudente, SP, Brazil S. ASHA DEVI • Laboratory of Gerontology, Department of Zoology, Bangalore University, Bangalore, India HANS-GERT BERNSTEIN • Laboratory of Translational Psychiatry, University of Magdeburg, Magdeburg, Germany; Department of Psychiatry and Psychotherapy, University of Magdeburg, Magdeburg, Germany KATRIN BORUCKI • Institute of Clinical Chemistry and Pathobiochemistry, University of Magdeburg, Magdeburg, Germany NIGEL J. CROWTHER • Department of Chemical Pathology, National Health Laboratory Service, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa RAVICHANDRA SHIVALINGAPPA DAVARGAON • Department of Life Sciences, Bangalore University, Bangalore, India TIEGO A. DINIZ • Department of Cell and Developmental Biology, Institute of Biomedical Sciences, University of Sa˜o Paulo (USP), Sa˜o Paulo, Brazil HENRIK DOBROWOLNY • Laboratory of Translational Psychiatry, University of Magdeburg, Magdeburg, Germany; Department of Psychiatry and Psychotherapy, University of Magdeburg, Magdeburg, Germany LESLIE DUNCAN • Department of Oral Biology and Diagnostic Sciences, Dental College of Georgia, Augusta University, Augusta, GA, USA MOJDEH FATHI • Department of Nutrition, Faculty of Paramedicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran LIXIA GAO • International Academy of Targeted Therapeutics and Innovation, Chongqing University of Arts and Sciences, Chongqing, People’s Republic of China NASRIN GOOLAM MAHYOODEEN • Division of Endocrinology, Department of Internal Medicine, University of the Witwatersrand, Chris Hani Baragwanath Academic Hospital, Johannesburg, South Africa PAUL C. GUEST • Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, SP, Brazil; Charlesworth House, Debden, Essex, UK FATEMEH HAIDARI • Department of Nutrition, Nutrition and Metabolic Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran EKA PRAMYRTHA HESTIANAH • Veterinary Anatomy Department, Faculty of Veterinary, Airlangga University, Surabaya, East Java, Indonesia NICOLE G. JAFF • Department of Chemical Pathology, National Health Laboratory Service, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

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Contributors

MOHAMMAD JALILI-NIK • Department of Medical Biochemistry, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran TANNAZ JAMIALAHMADI • Department of Food Science and Technology, Quchan Branch, Islamic Azad University, Quchan, Iran; Department of Nutrition, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran CALEB JENSEN • Department of Oral Biology and Diagnostic Sciences, Dental College of Georgia, Augusta University, Augusta, GA, USA SARAWUT JITRAPAKDEE • Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok, Thailand SERGEY M. KACHUR • Department of Cardiovascular Diseases, John Ochsner Heart and Vascular Institute, Ochsner Clinical School, The University of Queensland School of Medicine, New Orleans, LA, USA; Department of Medicine, University of Central Florida School of Medicine, Orlando, FL, USA NETIYA KARAKET • Division of Interdisciplinary Studies, Mahidol University, Kanchanaburi, Thailand MINA KARIMI • Department of Nutrition, School of Public Health, Iran University of Medical Sciences, Tehran, Iran IDHA KUSUMAWATI • Pharmacognosy and Phytochemistry Department, Faculty of Pharmacy, Airlangga University, Surabaya, East Java, Indonesia CARL J. LAVIE • Department of Cardiovascular Diseases, John Ochsner Heart and Vascular Institute, Ochsner Clinical School, The University of Queensland School of Medicine, New Orleans, LA, USA FABIO S. LIRA • Exercise and Immunometabolism Research Group, Department of Physical Education, Universidade Estadual Paulista (UNESP), Presidente Prudente, SP, Brazil JONATHAN P. LITTLE • School of Health and Exercise Sciences, University of British Columbia, Kelowna, BC, Canada LORENA CRISTINA CURADO LOPES • Clinical and Sports Nutrition Research Laboratory (Labince), School of Nutrition, Federal University of Goia´s, Goiaˆnia, GO, Brazil KHADIJEH MAHBOOBNIA • Department of Biochemistry, Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran MUHAMMED MAJEED • Sabinsa Corporation, East Windsor, NJ, USA MICHAEL VAUGHN F. MENDOZA • Faculty of Medicine and Surgery, University of Santo Tomas, Manila, Philippines GABRIELA MEYER-LOTZ • Laboratory of Translational Psychiatry, University of Magdeburg, Magdeburg, Germany; Department of Psychiatry and Psychotherapy, University of Magdeburg, Magdeburg, Germany MAJID MOHAMMADSHAHI • Department of Nutrition, Hyperlipidemia Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran PHANUPOL MONGKOLSIRI • Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok, Thailand PAULA ALVES MONTEIRO • Exercise and Immunometabolism Research Group, Department of Physical Education, Universidade Estadual Paulista (UNESP), Presidente Prudente, Sa˜o Paulo, Brazil JOA˜O FELIPE MOTA • Clinical and Sports Nutrition Research Laboratory (Labince), School of Nutrition, Federal University of Goia´s, Goiaˆnia, GO, Brazil DIEU THI XUAN NGUYEN • Department of Pharmacognosy, Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam

Contributors

xiii

NGOC HONG NGUYEN • CirTech Institute, Ho Chi Minh City University of Technology (HUTECH), Ho Chi Minh City, Vietnam THUY TRANG NGUYEN • Faculty of Pharmacy, Ho Chi Minh City University of Technology (HUTECH), Ho Chi Minh City, Vietnam TRANG THI PHUONG NGUYEN • Medical Biology, Department of Psychiatry, Faculty of Medicine, Technische Universit€ at Dresden, Dresden, Germany; Faculty of Pharmacy, Ho Chi Minh City University of Technology (HUTECH), Ho Chi Minh City, Vietnam TRIET THANH NGUYEN • Department of Traditional Pharmacy, Faculty of Traditional Medicine, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam YUNES PANAHI • Pharmacotherapy Department, Faculty of Pharmacy, Baqiyatallah University of Medical Sciences, Tehran, Iran ROHMANIA • Pharmacognosy and Phytochemistry Department, Faculty of Pharmacy, Airlangga University, Surabaya, East Java, Indonesia PINNARA ROJVIRAT • Division of Interdisciplinary Studies, Mahidol University, Kanchanaburi, Thailand JOSE´ CESAR ROSA-NETO • Department of Cell and Developmental Biology, Institute of Biomedical Sciences, University of Sa˜o Paulo (USP), Sa˜o Paulo, Brazil AMIRHOSSEIN SAHEBKAR • Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran; Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran; School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran PARVIN SARBAKHSH • Department of Statistics and Epidemiology, School of Public Health, Tabriz University of Medical Sciences, Tabriz, Iran CHLOE SHAY • Department of Pediatrics, Emory Children’s Center, Emory University, Atlanta, GA, USA TRACY SNYMAN • Department of Chemical Pathology, National Health Laboratory Service and University of the Witwatersrand Faculty of Health Sciences, Parktown, Johannesburg, South Africa JOHANN STEINER • Laboratory of Translational Psychiatry, University of Magdeburg, Magdeburg, Germany; Department of Psychiatry and Psychotherapy, University of Magdeburg, Magdeburg, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany WINFRIED STOECKER • Institute for Experimental Immunology, Affiliated to EUROIMMUN AG, Luebeck, Germany M. V. V. SUBRAMANYAM • Department of Life Sciences, Bangalore University, Bangalore, India AIDA TASBANDI • Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran BIANCA TEEGEN • Institute for Experimental Immunology, Affiliated to EUROIMMUN AG, Luebeck, Germany YONG TENG • Department of Oral Biology and Diagnostic Sciences, Dental College of Georgia, Augusta University, Augusta, GA, USA; Georgia Cancer Center, Department of Biochemistry and Molecular Biology, Medical College of Georgia, Augusta University, Augusta, GA, USA; Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA, USA MOHAMMADREZA VAFA • Department of Nutrition, School of Public Health, Iran University of Medical Sciences, Tehran, Iran

xiv

Contributors

GIAU VAN VO • Department of Biomedical Engineering, School of Medicine, Vietnam National University – Ho Chi Minh City (VNU-HCM), Ho Chi Minh City, Vietnam; Research Center for Genetics and Reproductive Health, School of Medicine, Vietnam National University – Ho Chi Minh City (VNU-HCM), Ho Chi Minh City, Vietnam TUONG KHA VO • Vietnam Sports Hospital, Ministry of Culture, Sports and Tourism, Hanoi, Vietnam MEGA FERDINA WARSITO • Research Center for Biotechnology, Indonesian Institute of Sciences (LIPI), Cibinong, West Java, Indonesia MEHDI ZAREI • Department of Food Hygiene, Faculty of Veterinary Medicine, Shahid Chamran University of Ahvaz, Ahvaz, Iran

Part I Reviews

Chapter 1 The New Frontier of Three-Dimensional Culture Models to Scale-Up Cancer Research Caleb Jensen, Chloe Shay, and Yong Teng Abstract In vitro cancer research models require the utmost accuracy and precision to effectively investigate physiological pathways and mechanisms, as well as test the therapeutic efficacy of anticancer drugs. Although two-dimensional (2D) cell culture models have been the traditional hallmark of cancer research, increasing evidence suggests 2D tumor models cannot accurately recapitulate complex aspects of tumor cells and drug responses. Three-dimensional (3D) cell cultures, however, are more physiologically relevant in oncology as they model the cancer network and microenvironment better, allowing for development and assessment of natural products and other anticancer drugs. The present review outlines unprecedented ways in which multicellular spheroid models, organoid models, hydrogel models, microfluidic devices, microfiber scaffold models, and tissue-engineered scaffold models are used in this research. The future of cancer research lies within 3D cell cultures, and as this approach improves, cancer research will continue to advance. Keywords 3D cell cultures, Cancer cell models, Cancer research, Drug response, Natural products

Abbreviations 2D 3D 3DP AQP5 BGD CPDD CSC ECM EIT EMT FEM fFn Fn GelMA

Two-dimensional Three-dimensional 3D printing Aquaporin 5 Bendamustine, gemcitabine, dexamethasone Cisplatin Cancer stem cells Extracellular matrix Electrical impedance tomography Epithelial to mesenchyme transition Finite element method Fibrillar fibronectin Fibronectin Gelatin methacryloyl

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_1, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Caleb Jensen et al.

GSCs HCC HTS HUVECs Micro-CT MPM NAP1 NSCLC OC OXY PDAC PDGFBB PEG PEM PET PLA PLGA PVA SCAPs TE TRPV4

1

Glioblastoma stem cells Hepatocellular carcinoma High-throughput screening Human umbilical vein endothelial cells X-ray microcomputed tomography Malignant pleural mesothelioma Nck-associated protein 1 Non-small-cell lung cancer Ovarian cancer Oxyresveratrol Pancreatic ductal adenocarcinoma Platelet-derived growth factor BB Polyethylene glycol Pemetrexed Polyethylene terephthalate Polylactic acid Poly(lactide-co-glycolide) Poly(vinyl acetate) Stem cells from apical papilla Tissue engineering Transient receptor potential cation channel

Introduction Currently, the lowest clinical trial success rate of all major diseases lies with cancer therapeutics [1]. Most often, this is because tumor models inaccurately represent cancer cell responses to anticancer drugs. Two-dimensional (2D) cell cultures have been the method used to culture cells since the early 1900s and theyplay a vital role in research but have many limitations due to inaccurate representation of tissue cells in vitro [2, 3]. Three-dimensional (3D) cell culture methods have proven to be incredibly useful models to study various types of cancers (Table 1) due to their improved accuracy over 2D culture methods. Thus, they have played a pivotal role in advancing cancer research. For these reasons, the popularity of 3D cell culture methods is increasing, and they are quickly emerging as the leading method in cancer research (Fig. 1). The capability of 3D cultures to model a cell in vivo while being cultured in vitro has resulted in improvements in studies targeted toward morphology, cell number monitoring, proliferation, response to stimuli, differentiation, drug metabolism, and protein synthesis [4, 5]. Furthermore, new methods are continuously being established, while old methods are steadily being improved to develop and advance 3D cell culture techniques. 3D cell culturing allows different rates of growth in cells throughout respective models, allowing spheroids to be more diverse and thus more

The New Frontier of Three-Dimensional Culture Models to Scale-Up Cancer Research

5

Table 1 List of 3D cell culture models applied in cancer research Cancer types Name of cells

3D model

Applications

References

Glioblastoma

U87, U251, and SNB19

Multicellular Assessment of the effects when tumor exposed to a hypotoxic tumor spheroids microenvironment

[22]

Breast cancer

NUDT5

Multicellular Comparison of the role of NUDT5 in 2D and 3D models tumor spheroids

[23]

Breast cancer

MDA-MB-231

Multicellular Analyzation of the cytotoxic effects of oxyresveratrol tumor spheroids

[24]

Mesothelioma M14K, MSTO, ZL34, and MeT-5A

Multicellular Evaluation of the effects of cisplatin and pemetrexed tumor spheroids

[25]

Glioblastoma

Patient-derived glioblastoma cancer stem cells

Organoids

Successfully mimicked in vivo [27] hypoxic gradients and cancer stem cell heterogeneity

Ovarian cancer

Patient-derived ovarian cancer tissue and blood

Organoids

Encapsulation of intra- and interpatient heterogeneity

[30]

Breast cancer

MDA-MBA-231

Organoids

Study of breast cancer progression

[31]

Liver cancer

LX2 and HepG2

Hydrogels

Assessment of anticancer effects of doxorubicin

[34]

Glioblastoma

Glioblastoma stem cells

Hydrogels

Investigation of brain tumor multicellular interactions

[37]

Breast cancer

MCF7 and HUVECs

Microfluidic Devices

Inspection of the interactions between tumor and endothelial cells

[40]

Pancreatic cancer

S2-028

Microfluidic Devices

[41] Recapitulation of intratumoral pressure; Assessment of the cytotoxic effect of anticancer drug gemcitabine

Pancreatic cancer

AsPC-1 and PANC- Microfiber 1 scaffolds

Assessment of the cytotoxic effect of [43] anticancer drug CPI-613; Determination of molecular mechanism behind action of CPI-613

Oral cancer

HN12 and HN6

Microfiber scaffolds

Assessment and comparison of free [44, 45] and nanoparticle-associated drugs

Lung cancer

H661

Microfiber scaffolds

Determination of gene function in [45] cancer cell migration and invasion

Bladder cancer

5637

Assessment of the cytotoxic effect of [47] rapamycin and BGD (continued)

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Caleb Jensen et al.

Table 1 (continued) Cancer types Name of cells

3D model

Applications

References

Tissueengineered scaffolds Breast cancer

MCF-7

Enhancement of cancer cell adhesion [48] Tissueengineered scaffolds

Breast cancer

EMT6/GFP

TissueEvaluation in dynamic culture engineered conditions scaffolds

[52]

800 700

Publication Number

600 500 400 300 200 100 0 1975

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1985

1990

1995

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2005

2010

2015

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2025

Years Fig. 1 Number of publications per year (1979–2020) on 3D cell cultures as they relate to cancer research gathered from PubMed

representative of natural cell environments than uniformly grown 2D cells [6]. Another reason 3D cell cultures are beneficial is due to the fact that culturing cells in 3D display phenotypic heterogeneity [7, 8]. Mimicking the tumor microenvironment more accurately via 3D cell cultures ultimately allows the cells to change gene expression and behavior more like cells in vivo, and thus elicits a more accurate drug response [5, 9–11]. Natural products and their synthetic derivatives are a treasure trove to find potential candidates for novel drugs for treatment of human diseases. In addition to the benefits listed above, 3D culture

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models have been employed to test the treatment value of natural products for cancer as they more faithfully represent the cancer network ex vivo. Curcumin, a natural product of the turmeric plant, has been studied in 3D spheroid models that mimic colon, ovarian, and breast cancer [12–14]. The effects of camptothecin, isolated from the bark and stem of the Camptotheca acuminata tree, have been studied in hydrogels as well as spheroids in cervical and liver cancer [15, 16]. In addition, the effects of the plant alkaloid vinblastine on breast cancer have been tested in spheroid models, where it was determined to be more effective than ten other anticancer drugs when combined with standard radiotherapy [17]. Moreover, other plant alkaloids such as irinotecan have been studied in spheroid models with effects on colon cancer [18, 19], and taxol has been tested in hydrogel models and a fibroblastderived 3D matrix to study its effects in colon, lung, ovarian, pancreatic, and breast cancer [20, 21]. The present review outlines studies in which 3D multicellular spheroid, organoid, hydrogel, microfiber scaffold and tissueengineered scaffold models, and microfluidic devices have been used to advance this research.

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Contributions of 3D Cell Culture Models to Cancer Research

2.1 Multicellular Spheroid Models in Cancer Research

Multicellular spheroid models have become one of the most commonly used methods to culture cells in the 3D cell culture industry due to the adaptability and versatility that these models allow for. Cancer cell lines have been adapted for use as spheroid models indicating their high potential to be used in cancer research. For example, spheroid models have been used to explore how hypoxia affects tumor growth and progression. In a recent study, 3D tumor spheroids were used to simulate the tumor microenvironment to study the changes in glioblastoma growth, metastasis, metabolism, and angiogenesis under hypoxic conditions [22]. When studied in an environment with an oxygen concentration of 1%, it was determined that glioblastoma proliferation rates decreased, migratory tendencies were limited, and cellular metabolism was enhanced to adapt to the hypoxic environment [22]. Although results were limited and more research is needed, the use of the spheroid models allowed the researchers to conclude the impact of oxygen gradients should be studied further in glioblastomas. Given that 2D cultures cannot be used for this, it stands to reason 3D models must be the main avenue in advancing the understanding of oxygen gradients in glioblastomas. Interestingly, a comparative experiment was conducted to study the role of NUDT5 in breast cancer cells cultured in 2D as well as 3D oncospheres [23]. Upon generating NUDT5 knockout cells, it was concluded that NUDT5 plays a major role in oncogenic

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pathways as well as in the regulation of genes associated with cancer stem cell (CSC) maintenance, cell adhesion, and epithelial to mesenchyme transition (EMT) [23]. When NUDT5 was enzymatically inhibited, oncosphere formation was prevented [23]. Additionally, transmembrane proteins MCU1, MUCL1, and MUC5 exhibited greater expression, and higher levels of CEACAM 5, 6, and 7 in T47D cells were discovered in 3D oncospheres compared to 2D cultured cells. Transcription factor binding site motifs were also found to be improved within promoters of genes expressed under 3D conditions. Most importantly, EMT-related genes and numerous membrane proteins (EMP3, FGFR1, GHR, and IGF2R) were upregulated when switching from 2D to 3D [23]. The study using 3D oncospheres confirms that NUDT5 is a promising target for drug discovery since it is an upstream regulator of tumor drivers [23]. An investigation implemented spheroid models to ascertain the effects of Oxyresveratrol (OXY) on breast cancer cell proliferation [24]. MDA-MB-231 cells were cultured in spheroids and treated with different concentrations (20 μM and 40 μM) of OXY. The results showed OXY as a cytotoxic agent in the 3D tumor models, as shown previously in the less accurate 2D models. This confirmed the potential use of OXY as an anticancer therapeutic [24]. Another study used tumor spheroids to demonstrate the effectiveness of 3D culture models in the testing of drugs against malignant pleural mesothelioma (MPM) [25]. The goal of the experiment was to compare the effects of cisplatin (CPDD) and pemetrexed (PEM) on cell viability in tumor spheroid formation, collagen gel contraction, and tumor spheroid invasion 3D cell culture models [25]. Three different cell lines were used to analyze the effects of CPDD and PEM. (M14K epithelioid, MSTO biphasic, and ZL34 sarcomatoid cells, with MeT-5A cells as controls) [25]. CPDD, PEM, and CPDD combined with PEM reduced the cell viability of all cell types. The drugs that most effectively reduced MPM cell viability, however, were PEM and PEM combined with CPDD. MTSO and MeT-5A spheroids decreased in perimeter under all three treatments, while M14K and ZL34 spheroids only shrunk when treated with PEM or PEM combined with CPDD. This suggested M14K and ZL34 spheroid growth is resistant to CPDD alone. These findings highlight the growing importance and superiority of 3D in vitro models for cancer study and in vivo-like drug testing. 2.2 Organoid Models in Cancer Research

Organoids aggregate into spheroids by forming extracellular matrix (ECM) fibers that link single cells together via integrin binding and mimic the microenvironment of certain organs to allow researchers to model human diseases through the use of patient-derived pluripotent stem cells [26]. Furthermore, researchers can grow tumor models using organoids through the use of patient-derived tissue

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cancer cells, effectively allowing scientists to model tumors to test treatments on a patient-to-patient basis. An investigation implementing organoid glioblastoma models unveiled the promising potential of organoid models for cancer research. Hubert et al. crafted an organoid model composed of patient-derived glioblastoma CSCs that mimicked hypoxic gradients and system cell heterogeneity [27]. Although these traits are found in tumors in vivo, current 2D cell culture methods do not have the capability to recapitulate such conditions [28]. Consequently, this novel organoid system allowed researchers to study heterogeneous cell–cell relationships, as well as the coculture of nonhypoxic and hypoxic CSCs [27]. Despite brain tumors being among the most difficult cancers with respect to mimicking the complex tumor microenvironment, this study indicates that models of brain tumors are achievable through the use of 3D organoid models. Organoid models for ovarian cancer (OC) are in their infancy stages but have nevertheless begun to shed light on the potential improvements that could be made possible in OC research [29]. In a recent study conducted by Oded Kopper et al., a protocol was established for a long-term OC organoid model allowing for the study of intra- and interpatient heterogeneity that can be genetically modified allowing for drug-screening assays [30]. Furthermore, this OC organoid model permits xenografting for in vivo drug-sensitive assays, which is another advantage over 2D models as it may allow personalized medicine approaches [30]. An organoid model employing a hanging drop array system was implemented to create a high-throughput organoid culture in a 384-well format using the MDA-MBA-231 tumorigenic cell line [31]. The results showed that the breast organoids grown displayed an invasive phenotype much like that of invasive breast carcinoma in clinical tissue samples [31]. Additionally, the organoids underwent organoid-level morphological changes that were capable of being quantified to stratify organoid responses [31]. Unlike 2D models, cells in the 3D model effectively organized into distinct phenotypes mimicking small functional units of the breast [31]. This organoid model exhibits the potential for assay standardization and highthroughput testing and clearly portrays the benefits of using 3D organoid models. 2.3 Hydrogel Models in Cancer Research

Hydrogels are unique due to their ability to mimic the ECM while allowing soluble factors such as cytokines and growth factors to travel through the tissue-like gel [32]. Hydrogels are also versatile since they can be employed to create spheroids and can be prepared in multiple ways depending on the experiment being performed. Both natural and synthetic hydrogels exist, with natural gels commonly being made with natural polymers such as fibrinogen, hyaluronic acid, collagen, Matrigel, gelatin, chitosan, and alginate

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[33]. Synthetic hydrogels are typically made with synthetic polymers of polyethylene glycol (PEG), polylactic acid (PLA), or poly (vinyl acetate) (PVA) [33]. Additionally, hydrogels have been utilized to create viable tumor models. In an investigation to mimic the tumor ECM of hepatocellular carcinoma (HCC), hydrogels such as collagen and fibrinogen were used [34]. Using an inverted insert membrane of a Transwell™ system, LX2 and HepG2 cells were seeded in the hydrogel on one side of the membrane, while human umbilical vein endothelial cells (HUVECs) were seeded on the other side [34]. The effect of the chemotherapeutic drug doxorubicin was compared between this 3D model and 2D cultures, and the 3D tumor model displayed drug resistance that more closely resembles resistance commonly seen in HCC patients [34]. Furthermore, the 3D model was operational for 25 days and brought about metastatic tumor nodules after 17 days [34]. These findings indicated that the use of this liver tumor model could give rise to a new platform to study multifocal HCC in the future, as well as potentially help to recognize mechanisms that lead to early stages of metastasis [34]. Bone defects, as a result of cancer surgery, trauma, or other diseases, have been linked with functional disorders [35]. In an effort to study the bone defects caused by cancer surgery, a thermosensitive hydrogel was employed as a 3D scaffold to study the effects of platelet-derived growth factor BB (PDGFBB) on stem cells from apical papilla (SCAPs) [36]. The results of the study demonstrated that PDGFBB promoted proliferation of SCAPs in the 3D model as well as in rat models, demonstrating that thermosensitive hydrogels can be utilized as an effective scaffold for 3D cell culture studies [36]. Tang et al. created a glioblastoma hydrogel model using 3D printing (3DP) to compare the growth of glioblastoma stem cells (GSCs) alone or in combination with astrocytes and neural precursor cells, and with or without macrophages [37]. Immune cells were examined to observe the role that they play in gene expression, treatment responses, and invasive behaviors within glioblastomas [37]. The polarization of macrophages towards a protumoral M2 macrophage phenotype was seen indicating bidirectional crosstalk [37]. The scalability of this innovative model provides the potential to study drug testing and immunologic interactions in glioblastomas in more effective and accurate ways than could be achieved using 2D models [37]. 2.4 Microfluidic Devices in Cancer Research

Microfluidic devices have revolutionized the cell culture industry. Due to their small size, current large-scale applications can be performed on a much smaller scale by reducing the sample consumption to fractions of what it was before [38]. Moreover, microfluidic devices are beginning to play an increasingly important role in cancer research and tumor modeling.

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A microfluidic model was designed to study the effect of hyperosmotic stress on the migration, ion channel/transporter expression changes, and proliferation of metastatic cell lines in 2D vs 3D environments [39]. The metastatic cell lines studied were MDA-MB-231, A549, and T24, while the transporters studied were aquaporin 5 (AQP5) and the transient receptor potential cation channel (TRPV4) [39]. The results indicated large differences in the localization of AQP5 and TRPV4 (both of which play a role in osmoregulation and cancer progression) between the 2D and 3D microfluidic models [39]. Furthermore, the experiment highlighted the importance of using the 3D model as opposed to the 2D model as a result of the marked differences between these two methods. A limitation of 2D cell cultures is the fact that the interaction between tumor cells and endothelial cells cannot be visualized. Qian et al. developed a novel microfluidic device in which the interaction between MCF7 breast cancer cells and HUVECs could be monitored [40]. Furthermore, their novel microfluidic device chip possesses the capability to perform in situ measurements of cytokines secreted by cells [40]. By demonstrating the capability of a microfluidic device to investigate the interaction between tumor cells and endothelial cells, the potential for 3D application for cancer research instead of 2D models is the next step in improving modern cancer research techniques. A microfluidic device created by Kramer et al. was used to mimic the intratumoral pressure in pancreatic ductal adenocarcinoma (PDAC) [41]. Prior to this study, no 2D or 3D in vitro models were available for this purpose. In the experiment, exposure of S2-028 nonmetastatic pancreatic cancer cells to interstitial flow in the microfluidic device led to preservation of viability and inhibition of proliferation [41]. Most importantly, gemcitabine chemoresistance was greatly increased in the 3D model when compared to 2D monolayer cultures. These improvements on prior results from 2D culture experiments highlight the potential for refined efficacy in drug development for PDAC. 2.5 Microfiber Scaffold Models in Cancer Research

Much effort has been dedicated to developing microfiber scaffolds that can mimic native microenvironments to form disorganized, proliferative, and nonpolar colonies. SeedEZ is an inert and transparent glass microfiber scaffold, providing a more physiologically relevant instrument to the analysis of gene function and cell phenotype in cancer research and drug assessment [42]. CPI-613 is a novel lipoate analog which inhibits mitochondrial metabolism. Our group has employed SeedEZ to study how the rewiring of lipid metabolism triggers apoptosis upon CPI-613 treatment [43]. In line with the data from 2D cultures, CPI-613 dramatically decreased viability of AsPC-1 and PANC-1 in SeedEZ, suggesting it also exhibits strong cytotoxic effects in 3D cultures

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[43]. Recently, we developed a series of tumor-seeking nanoparticles to better treat oral cancer. These nano drugs included the Src inhibitor saracatinib and Akt inhibitor capivasertib single or dual drug-loaded nanoparticles, which exhibited similar cytotoxicity compared with the free drugs in the traditional cultures [44, 45]. Interestingly, when we used 3D cultures with the SeedEZ scaffold, the nanoparticle-encapsulated drugs displayed superior inhibitory effects compared to the free drugs [44, 45]. These observations clearly support the advantages of 3D microfiber scaffolds in anticancer drug assessment. We also employed SeedEZ to study cell migration and invasion since it recapitulates key aspects of these processes. Nck-associated protein 1 (NAP1/NCKAP1) is a tumor metastatic protein that is highly expressed in primary non-small-cell lung cancer (NSCLC) compared with adjacent normal lung tissues. Knockdown of NAP1 in high-invasive NSCLC H661 cells using an shRNA approach revealed significantly reduced cell migration and invasion using the scratch assay and the transwell cell invasion assay [45]. However, the possible destruction of the ECM coatings on the cell culture dish in the scratch assays and lack of time-lapse data of cell invasion in the transwell cell invasion assay potentially affected the outcome of the assays. To overcome these limitations, we utilized the SeedEZ rings to determine the cell invasion potential, which showed that H661 cells with NAP1 deficiency lost the capacity of invasion in 3D scaffolds [45]. This data was confirmed by experimental metastasis in mice, supporting the case that ex vivo microfiber scaffold models provide useful tools to assess aggressiveness of cancer cells. 2.6 Tissue-Engineered Scaffold Models in Cancer Research

Tissue engineering (TE) was first introduced in 1988 at the UCLA Symposia on Molecular and Cellular Biology by Professor Robert Nerem [46]. When designing an in vitro model for a cell, it is imperative that the environment accurately represents the natural environment of a cell in vivo. One of the ways to achieve this is through proper TE techniques. When designing a tissue, the most important aspect of the tissue model is to accurately mimic the porosity of the tissue in vivo. For this purpose, 3DP has revolutionized the way in which tissue scaffolds are engineered for cancer research and improvements in this technology are ongoing. Choi et al. compared 2D cell culture methods with a 3D-printed scaffold made of gelatin methacryloyl (GelMA) [47]. The study investigated the differences in the effects of drugs such as rapamycin, bendamustine, gemcitabine, and dexamethasone on bladder cancer cells in 2D and 3D models [47]. The findings indicated that the cancer-like environment of the 3D scaffold created by 3DP yielded more accurate results, and the effect of the drugs on cells growing in 2D culture was exaggerated

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[47]. Additionally, proliferation rates and cell-to-cell interactions in the 3DP model were higher than in the 2D model [47]. Geyik et al. developed novel porosity scaffolds from polylactic acid (PLA) and polyethylene terephthalate (PET) that allowed 3D growth of MCF-7 breast cancer cells [48]. Filaments of these nontoxic, dye-free polymers were loaded into a custom 3D printer and employed to make scaffolds suitable for 3D cell culturing [48]. The results indicated that MCF-7 cells adhered to the 3DP scaffolds better than traditional 2D cell cultures supporting further use and development of PLA and PET scaffolds for in vivo modeling of breast cancer [48]. Fibronectin (Fn) is among the most prominent ECM proteins in normal tissues, and increased Fn expression is associated with different cancers [49, 50]. Given that 3D in vitro culture models better recapitulate the ECM environment, it is common for Fn to be used in the form of adsorbed pre-coatings in an effort to mimic a cell-supporting environment [51]. However, these protein coatings often fail to accurately resemble fibrillar protein networks naturally deposited by cells [51]. Jordahl and colleagues created a novel fibrillar fibronectin (fFn) 3D network supported by tessellated polymer scaffolds [51]. The tessellated polymer scaffold made from poly(lactide-co-glycolide) (PLGA) was crafted via 3D jet writing and then loaded with a solution of human Fn [51]. The results of this study revealed that patient samples could be expanded, and engineered fFn networks are a viable 3D cell culture platform for the expansion of both primary and immortalized cancer cells in vitro [51]. In a recently conducted study by Penderecka et al., a 3D scaffold model was created by extracting silk from the cocoons of Bombyx mori to study breast cancer in dynamic culture [52]. Despite the fact that this model was not created using 3DP techniques, it highlighted the relevant advantages of a dynamic 3D breast cancer model over a static model. In this study, fibroblasts and breast cancer cells were mixed in a 9:1 ratio and seeded on the silk scaffolds for 21 days in both static and dynamic conditions [52]. The results showed that when dynamic culture conditions were applied to the 3D breast cancer model, cells effectively penetrated the inner parts of the scaffold and caused comparable changes regarding viability, cell morphology, and cellular ratios [52]. The dynamic 3D breast cancer model in this experiment has the potential to provide insight into breast cancer tumor biology more economically and efficiently and may be used in the future for screening of anticancer drugs [52].

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Challenges and Perspectives Although advantageous in many ways over 2D cultures, 3D cell cultures come with their own set of challenges. 3D cultures tend to be more expensive and it can be difficult to replicate cell microenvironments when using certain 3D culture methods, and matrices often have multiple components which make construction difficult [4, 32, 42]. Additionally, one of the largest problems facing the 3D cell culturing industry today is the automation of liquid handling for high-throughput screening (HTS). With so many different specific methods for 3D culturing, it is difficult to create a universally compatible automatic liquid handling system. Liquid handling for suspension media and ultra-low attachment can be easily automated but is more challenging for viscous liquids such as collagen- and Matrigel-containing hydrogels [53]. Temperaturesensitive polymerization in these gels requires swift liquid handling and tedious environmental control to avoid premature polymerization [54]. Automation can often be achieved for many 3D culturing techniques in 96- or 384-well plates but further automation in miniaturized models is often difficult due to limitations in pipetting volumes [54]. Despite the fact that imaging techniques are steadily improving, imaging still represents a unique challenge for 3D cell culture models. Imaging becomes burdensome when large scaffolds are used because there is a limit when scaling a single 3D format [4]. Plate incompatibility with microscopes and uncentered spheroids in well plates creates a difficult challenge for anchoragedependent cultures, as occurs with hanging-drop plates and ultralow attachment plates [53]. The most common way to analyze cellular phenotypes is by using conventional wide-field or confocal fluorescence microscopy [53]. Fluorescence microscopy is typically still challenging in 3D cell cultures since these must obtain a z stack by taking a series of xy images at fixed intervals in the vertical direction by automated microscopes [53]. Requiring a series of xy images to obtain a z stack often increases the time significantly, and as a result, higher magnification objectives (40–60) are currently not practical for high-throughput settings as these require too much time and storage space [53]. A 2010 survey from the HTS technologies revealed that two-thirds of people surveyed have plans to switch from 2D cell cultures to 3D cell cultures, with many of them having already made the transition [4]. As more researchers make this transition, new methodologies should be developed more rapidly to overcome the current limitations facing 3D cell cultures. The future of organoids remains promising, with the potential for developing alternative organ transplantation procedures as well as tumor models via patient-derived pluripotent stem cells [55]. Immunotherapy in 3D

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cell culture models is one of the most hopeful methods due to recent success relating to cancer treatment [56]. As 3D tumor models become more advanced, immunotherapy treatments will progress to the point where more clinical trials can be performed with the potential of eventually uncovering viable new cancer treatments.

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Conclusions 3D cell cultures provide more effective, reliable, and affordable tools for cancer research, making them more popular today than ever. 3D culture models, including multicellular spheroid, organoid, hydrogel, microfiber scaffold, and tissue-engineered scaffold models, have already contributed to a better understanding of cancer biology and provide a viable drug discovery platform as they have been proven to be more physiologically and pathologically relevant. The compatibility of testing natural products in 3D models has displayed the advantages of employing 3D cell cultures over 2D cell cultures, and thus highlights the merit of testing natural products for cancer treatment using 3D models. As technology progresses, the challenges currently facing many 3D cell culture techniques will be met and 3D cell cultures will become more commonplace.

Acknowledgments This work was supported in part by NIH grants R01DE028351 and R03DE028387 and CURS Summer Scholars (to Y. Teng). References 1. Cagan R, Meyer P (2017) Rethinking cancer: current challenges and opportunities in cancer research. Dis Model Mech 10(4):349–352 2. Ferreira LP, Gaspar VM, Mano JF (2018) Design of spherically structured 3D in vitro tumor models—advances and prospects. Acta Biomater 75:11–34 3. Costa EC, Moreira AF, de Melo-Diogo D, Gaspar VM, Carvalho MP, Correia IJ (2016) 3D tumor spheroids: an overview on the tools and techniques used for their analysis. Biotechnol Adv 34(8):1427–1441 4. Antoni D, Burckel H, Josset E, Noel G (2015) Three-dimensional cell culture: a breakthrough in vivo. Int J Mol Sci 16(3):5517–5527 5. Ravi M, Paramesh V, Kaviya SR, Anuradha E, Solomon FD (2015) 3D cell culture systems:

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Chapter 2 Therapeutic Effects of Resveratrol on Nonalcoholic Fatty Liver Disease Through Inflammatory, Oxidative Stress, Metabolic, and Epigenetic Modifications Mina Karimi, Behnaz Abiri, Paul C. Guest, and Mohammadreza Vafa Abstract The prevalence of nonalcoholic fatty liver disease (NAFLD) is increasing around the world, in association with the progressive elevation in overweight and obesity. The accumulation of lipids in NAFLD patients contributes to the development of insulin resistance, inflammation and oxidative stress in hepatocytes, and alteration of blood lipids and glycaemia. There are currently no effective pharmacological therapies for NAFLD, although lifestyle and dietary modifications targeting weight reduction are among the prevailing alternative approaches. For this reason, new approaches should be investigated. The natural polyphenol resveratrol represents a potential new treatment for management of NAFLD due to anti-inflammatory and antioxidant properties. Although preclinical trials have demonstrated promising results of resveratrol against NALFD, the lack of conclusive results creates the need for more trials with larger numbers of patients, longer time courses, and standardized protocols. Keywords Insulin resistance, Inflammation, Nonalcoholic fatty liver disease, NAFLD, Resveratrol, Polyphenols

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Introduction Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease as it affects up to 30% of adults in Western countries and 15% in Asian countries, with increasing numbers of affected children [1]. NAFLD is a disease spectrum ranging from pathological accumulation of triglycerides (TGs), steatosis, inflammatory response, nonalcoholic steatohepatitis (NASH), as well as end-stage liver diseases, such as cirrhosis and/or hepatocellular carcinoma [2, 3]. NAFLD is becoming an important health challenge globally due to its increasing prevalence and its metabolic complications. There is also an underlying insulin resistance, which may be linked to hyperlipidemia, hypertension, type 2 diabetes

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_2, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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mellitus (T2DM), cardiovascular diseases (CVDs), chronic kidney disease, and carotid atherosclerosis [4]. The disease also has a multifactorial pathogenesis, which can include genetic and dietary factors, insulin resistance, other endocrine disturbances, inflammation, and oxidative stress [5, 6]. The first step of the disease involves the development of steatosis that includes accumulation of greater than 5% triglycerides in hepatocytes. This can progress to NASH in approximately one-third of the cases, marked by the appearance of hepatic necroinflammation and fibrosis [6], and it can progress to hepatocellular carcinoma and NASH-associated cirrhosis in about one-quarter of the cases [6, 7]. To date, there is no effectual pharmacological treatment against NAFLD. Instead, the management of the disease is based on lifestyle modifications including dietary and exercise regimens focused on weight loss and improvement of insulin sensitivity [8]. While these modifications have been reported to be effective in some trials, they have had limited influence on the incidence and severity of NAFLD, most likely due to poor compliance [8]. Thus, there is a need to identify and develop new effective approaches for NAFLD management. This has promoted interest in bioactive food constituents as new approaches for NAFLD treatment. Polyphenols are found in plants and their regular consumption has been related to a decrease in the risk of some metabolic diseases, such as obesity, insulin resistance, hypertension, and CVD [9, 10]. The evidence supports the concept that a polyphenol-rich diet may also have a beneficial role in the prevention and treatment of NAFLD. Resveratrol is a natural polyphenol, synthesized as phytoalexin by plants in response to harm and can be found in grapes, berries, legumes, peanuts, and tea, although in low amounts [11, 12]. It has been ascribed as having pleiotropic potential because of its antioxidant, anti-inflammatory, and chemopreventive effects, as well as protective activity against age-associated disorders [13]. In addition, resveratrol has been demonstrated to ameliorate cellular and vascular function and improve metabolic health by increased glucose control and insulin sensitivity in obese and/or diabetes patients [11]. The advantageous impacts of resveratrol on obesity-associated complications derive in a large part from its ability to mimic the effects of calorie restriction [14]. This occurs through activation of key regulators of metabolic health, namely adenosine monophosphate–activated kinase (AMPK), nuclear factor (erythroid-derived)-like 2, and nicotinamide adenine dinucleotide NAD-dependent deacetylase (SIRT1) [15]. The aim of the present chapter was to investigate the efficacy of resveratrol in NAFLD and to discuss the key mechanisms which modulate its potential clinical advantages.

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Nonalcoholic Fatty Liver Disease NAFLD is mainly associated with obesity and metabolic syndrome [4]. There is a wide span of manifestations in NAFLD, as it also occurs in the most advanced forms of liver diseases including NASH, fibrosis, and hepatic cirrhosis [2, 3]. NAFLD is categorized as either primary or secondary. Primary NAFLD is associated with metabolic syndrome, obesity, T2DM, dyslipidemia, and insulin resistance, while the secondary type is related to external factors [16, 17]. The early stages of NAFLD are asymptomatic, which makes it difficult to determine its actual prevalence. Despite this difficulty, it has been established that NAFLD prevalence has increased over the last few decades [7]. Although NAFLD affects the general population, it is more common in men than women [18] and scarce in children (approximately 3%) but it may occur in approximately 50% of obese children [19, 20]. NAFLD has a complex pathophysiology, which is characterized by a two-hit hypothesis [21]. In this model, the first hit is the accumulation of fatty acids and TG in hepatocytes resulting in steatosis, which is caused by several mechanisms including: (1) elevated hepatic delivery and uptake of fatty acids related to elevated lipolysis in adipose tissue and/or elevated intake of dietary fats; (2) reduced fatty acid oxidation; (3) elevated hepatic de novo lipogenesis; and (4) diminished hepatic lipid export via very-lowdensity lipoproteins (VLDLs) [21]. The inability to regulate lipid partitioning results in the second hit, whereby an overtaxed fatty acid β-oxidation process leads to mitochondrial dysfunction which elevates reactive oxygen species (ROS) leading to continued oxidative stress and a reduction of the antioxidant defenses [22, 23]. The accumulation of fatty acid intermediates and the compromised oxidative–reductive status activate Kupffer cells generating inflammatory mediators, and dysregulated insulin signaling, which cause the progression from steatosis to NASH [8, 22]. The associated chronic inflammation and oxidative stress lead to hepatocyte apoptosis and activation of stellate cells which are main drivers in the progression to liver fibrosis [8, 23]. ROS production is generally regulated by several antioxidant mechanisms, and when ROS generation is higher than the antioxidant capacity, oxidative stress occurs [24]. NAFLD patients demonstrate high levels of ROS and oxidative stress biomarkers, with lower concentrations of antioxidants enzymes, such as superoxide dismutase (SOD) and catalase [25]. For this reason, some of the therapeutics administered in NAFLD include antioxidants like vitamin E, betaine, ursodeoxycholic acid, probucol, L-carnitine, pentoxifylline, metformin, and N-acetylcysteine [25]. Adipose tissue in patients with NAFLD is a major source of proinflammatory cytokines, which can elevate the inflammatory

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status and generate high levels of proinflammatory cytokines, including tumor necrosis factor-alpha (TNF-α), and interleukin-1 (IL-1) [26, 27]. ROS can also activate the nuclear factor-κB (NFκB), a transcription factor involved in regulation of TNF-α and some pro-inflammatory enzymes, including cyclooxygenase 2 and the inducible oxide nitric synthase (iNOS) [28, 29]. NFκB is also responsible for the decrease in peroxisome proliferatoractivated receptor (PPAR-γ) activity, which regulates fatty acid storage and glucose metabolism [29]. To combat the inflammatory process, organisms generate anti-inflammatory agents, such as some adipokines like adiponectin. Adiponectin decreases accumulation of fat in liver, ameliorates insulin resistance, and could prevent hepatic inflammation [26]. However, another adipokine, leptin, can have a proinflammatory or profibrogenic action and is associated with increased insulin resistance and body weight. In NAFLD, adiponectin is decreased whereas leptin levels are increased.

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Resveratrol Resveratrol (3,5,40 -trihydroxystilbene) is a natural polyphenol (Fig. 1) with phytoalexin activity that can cease the progression of some infections in plants. This polyphenol belongs to the family of stilbenes and can exist in cis or trans configurations, although only the trans form has been associated with health benefits. Although it is found in more than 70 species of plants, stilbenes are consumed in low amounts in the human diet and their levels differ substantially between different foods [11]. Some significant sources of resveratrol are cranberries, currants, blackberries, grapes, peanuts, dark chocolate, and cocoa liquor [30–32]. Metabolism of resveratrol leads to a rise in the activities of phase II hepatic detoxifying enzymes, and the gut microbiota may also play a role [33, 34]. In general, the low water solubility, short-half life, rapid metabolism, and low intestinal absorption of resveratrol limit its oral bioavailability [35]. In addition, most of the resveratrol consumed is converted into sulphate and glucuronide derivatives in the liver [36, 37]. Encapsulation of resveratrol provides a potential method for increasing its bioavailability, by promoting its solubility and stability against trans-to-cis isomerization [38]. Pharmacokinetic investigations have shown that this approach may be applied to protect resveratrol from degradation when it is administered as an oral supplement [38]. A number of toxic effects have been reported for resveratrol when given at doses of more than 1 g, and these consist of diarrhea, heartburn, mood changes, elevated or reduced appetite, hot flashes, flatulence, nausea, menstrual alteration in females,

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Fig. 1 Structure of resveratrol

insomnia, and abdominal pain or reflux [39]. On the other hand, resveratrol appears to have an impact on hepatic detoxification and metabolism of drugs and xenobiotics, via the modification of the cytochrome P450 enzyme system [40]. The impact of resveratrol on mitochondria is also dependent on its concentration. Low resveratrol levels induce defense mechanisms in antioxidant networks and activate the 50 AMP-activated protein kinase (AMPK) SIRT1 pathway, leading to cytoprotective impacts both in vitro and in vivo. By the activation of AMPK, SIRT1, and other routes such as antiinflammatory and antioxidant mechanisms, resveratrol may hinder the development or progression of steatosis and steatohepatitis (Fig. 2).

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In Vitro, Animal Models and Clinical Studies Several studies have concentrated on the effects of resveratrol as a means of ameliorating insulin sensitivity, its fat-lowering capability by hindering adipogenesis and promoting lipid mobilization, and as a potential hepatoprotective factor [11]. Like many other natural compounds, most studies have been carried out in vitro or in animal models, while clinical trials are still scarce and the findings of those which have been performed have shown conflicting results. An in vitro study showed that addition of 10 and 20 μM resveratrol decreased the levels of oleic and palmitic acid-induced steatosis and mitochondrial oxidative stress in HepG2 hepatocytes [41]. Another study by the same research group found that 20 μM resveratrol decreased glucose-induced steatosis and ameliorated mitochondrial performance [42]. Rafiei et al. showed that addition of 1–10 μM resveratrol to a HegG2 cell model of steatosis protected against oleic acid-induced ROS generation by reversing the effects on mitochondrial biogenesis, increasing expression of SOD, preventing the increase in TNF-α expression, and blocking the decrease in uncoupling protein 2 (UCP-2) [43]. In another study, administration of 100 mg/kg/day resveratrol over 4 weeks prevented hepatic steatosis by decreasing lipid accumulation and protected against fibrosis in a NAFLD mouse model [44]. In this research, the in vitro assays showed that resveratrol also elevated SIRT-3 protein levels in isolated hepatic stellate cells [44]. Another

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Resveratrol

SIRT1/FOXO

AMPK

Nrf2

Antioxidant molecules

NFk B

Proinflammatory cytokines

Inflammation

ROS

b-oxidaon

Fig. 2 Effects of resveratrol on ROS, inflammation, and mitochondrial function. AMPK 50 AMP-activated protein kinase, FOXO forkhead box protein, NF-kB nuclear factor kappa B, Nrf2 nuclear factor erythroid 2-related factor 2, ROS reactive oxygen species, SIRT sirtuin 1

study found that resveratrol reduced the hepatic steatosis, and decreased body weight, the liver enzymes alanine aminotransferase (AAT), and aspartate aminotransferase (AST), as well as the concentrations of lipids, glucose, and insulin, in a high-fat diet-induced rat model [45]. In a rat model of liver steatosis induced by a high-fat–carbohydrate diet for 4 weeks, 10 mg/day oral administration of resveratrol diminished hepatic fat accumulation [46]. Serum levels of TNF-α and glucose and liver levels of malondialdehyde (MDA) and iNOS were also decreased in the resveratrol group, while the antioxidant enzymes catalase, SOD, and glutathione peroxidase were enhanced. In another study, the administration of 100 mg/day resveratrol for 8 weeks to Wistar rats fed with a high-fat diet, led to a marked decrease in the grade of liver steatosis and normalized the TG content [47]. The protective activity was related to an elevated hepatic mitochondrial biogenesis and UCP-2 expression. In rats fed with a high-fat diet for 60 days, resveratrol (30 mg/kg/ day) diminished body weight, ameliorated plasma lipid profile, and decreased the concentrations of AAT, AST, and insulin [48]. The treatment with resveratrol ameliorated hepatic lipid metabolism by reducing expression of adipogenic-associated proteins acetyl-CoA carboxylase (ACC), PPAR-γ, and sterol regulatory elementbinding protein 1 (SREBP-1). In addition, it had antiinflammatory impacts by decreasing the expression of TNF-α,

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IL-6, and NFκB, potentially via upregulation of SIRT-1 expression. In a rat model of NAFLD, the protective impacts of resveratrol intake (10 mg/kg, daily) were evaluated after 4 weeks of treatment [49]. In this study, resveratrol ameliorated liver structure, as well as the lipid profile and glycemia, and it decreased circulating leptin levels and exerted antioxidant and anti-inflammatory effects. In another study, Khaleel et al. evaluated the impact of low doses of resveratrol (20 mg/kg, daily) over 8 weeks in a high-fat–fed rat model [50]. The resveratrol treatment reduced the progression of liver steatosis and enhanced insulin sensitivity. Another study found that resveratrol treatment (100 mg/kg/day for 12 weeks) of a rat model of NAFLD with hyperuricemia ameliorated uric acid excretion, liver structure and function, and decreased the grade of steatosis, oxidative stress, and inflammation via activation of the SIRT1 pathway [51]. On the other hand, 2–20 mg/kg daily treatments of resveratrol for 4 weeks did not suppress steatosis in a study of a high-fat diet mouse model of NAFLD [52]. Clinical trials on the influences of resveratrol on NAFLD patients are scarce and their results are inconclusive (Table 1). In one trial, overweight and obese males with NAFLD were divided into two groups receiving either 3000 mg resveratrol or a placebo daily for 8 weeks [53]. The resveratrol treatment did not ameliorate liver steatosis, abdominal fat, plasma lipid profiles, or insulin resistance with respect to basal values. In another controlled clinical trial with NAFLD patients, 500 mg resveratrol or placebo was supplemented daily for 12 weeks together with an energy-balanced diet and a physical activity program [54]. At the end of this study, anthropometric parameters, liver steatosis and function, and inflammatory biomarkers were ameliorated in both groups, although the reduction in AAT, inflammatory biomarkers, serum cytokeratin-18, and hepatic steatosis were greater in the group supplemented with resveratrol. In another randomized clinical trial, high doses of resveratrol (1500 mg/day, for 6 months) were administered to overweight patients with NAFLD [55]. Even though treatment with resveratrol led to minor improvements in liver lipid content and liver damage, there were no differences compared to effects seen in the control group. Moreover, no consistent impacts on histology, insulin sensitivity, markers of the metabolic syndrome or on microarray profile were demonstrated. Similarly, no significant advantageous impacts were found after 600 mg resveratrol administration for 12 weeks in adult NAFLD patients [56]. Similar negative findings were reported by two other trials which tested resveratrol treatment compared to placebo [57, 58]. Conversely, a study by Chen et al. showed that supplementation with 150 mg resveratrol twice daily for 12 weeks had beneficial effects as it ameliorated glucose and lipid metabolism, and insulin resistance, compared to the placebo group [59]. Furthermore,

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Table 1 The impacts of RES treatment in NAFLD patients First author (Reference no) Chachay [53]

Patients

Treatment, duration

Results

NAFLD patients (n ¼ 20)

3000 mg daily, 8 weeks

No alterations in liver, lipids, or insulin

Faghihzadeh NAFLD [54] patients (n ¼ 50)

500 mg daily, 12 weeks, along Reduction in: ALT, NFκB, cytokeratinwith diet and exercise 18, hepatic steatosis grade program

Heebøll [55] NAFLD patients (n ¼ 26)

1500 mg daily, 6 months

Amelioration in liver lipid content and liver damage

Asghari [56] NAFLD patients (n ¼ 60)

600 mg daily, 12 weeks

No advantageous

Kantartzis [57]

150 mg daily, 12 weeks

No alteration in liver fat content, cardiometabolic risk markers, and insulin resistant

Poulsen [58] NAFLD patients (n ¼ 16)

500 mg, 3 times per day, 6 months

No alteration in liver fat content

Chen [59]

NAFLD patients (n ¼ 60)

300 mg daily, 12 weeks

Amelioration in glucose and lipid metabolism and insulin resistance Reduction in NF-α, cytokeratin 18, and fibroblast growth factor 21 Elevation in adiponectin

Theodotou [4]

NAFLD patients (n ¼ 44)

50 and 200 mg daily, 6 months Reduction in liver lipid accumulation, enzymes, and insulin resistance

NAFLD patients (n ¼ 112)

ALT alanine transaminase

plasma levels of TNF-α, cytokeratin-18, and fibroblast growth factor 21 were decreased and adiponectin levels elevated in the resveratrol group. In addition, a clinical trial, which evaluated the impact of micronized resveratrol formulation over 6 months, found decreased hepatic lipid deposition, lower serum concentrations of liver enzymes, and diminished insulin resistance [4]. The apparent discrepancies in clinical studies could be due to differences in bioavailability of the resveratrol formulation used. In this sense, it is necessary to design more clinical trials with a significant number of patients and longer interventions to clarify the possible benefits of resveratrol to manage NAFLD.

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Mechanisms of Action

5.1 Effects of Resveratrol on Inflammation

It is widely established that hepatocytes and adipocytes inflammatory responses are correlated with obesity and involve lipid accumulation in liver, and this subsequently develops to hepatic steatosis in the course of NAFLD. Liver inflammation during the development of NAFLD is related to elevated secretion of inflammatory cytokines and adipokines in both white adipose tissue and hepatocytes [60, 61]. Various studies have now shown that resveratrol diminishes secretion of pro-inflammatory mediators, such as IL-1, IL-6, and TNFα in the liver [62, 63]. Furthermore, resveratrol treatment induces the expression of TNFβ, which has antiinflammatory impacts in a human lung epithelial cell line [64]. Also, some studies have reported that resveratrol supplementation modulates concentrations of autophagy biomarkers including microtubule-associated proteins 1A/1B light chain 3B (LC3-II) and sequestosome 1 (SQSTM1) [62]. NAFLD development is also associated with the presence of inflammasomes, which are pro-inflammatory caspase-activating complexes [65]. A study by Yang and colleagues showed that resveratrol prevented NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) inflammasome activation, which led to a reduction in the inflammatory response in lipid-overloaded hepatocytes [66]. Other studies showed that resveratrol decreased the activity of NF-κβ [48] and repressed TNF-induced phosphorylation and nuclear translocation of the p65 subunit of NF-κβ and NF-κβ-dependent gene transcription [67]. In an investigation by Li et al., resveratrol ameliorated the protein expression levels of Iκβα (an NF-κβ inhibitory regulator), leading to prevention of NAFLD development in an animal model [68]. Resveratrol treatment also diminished NF-κβ activity of the Janus kinase 2/STAT (JAK2/STAT) pathway involved in secretion of cytokines and growth factors in NAFLD [69, 70].

5.2 Effects of Resveratrol on Oxidative Stress

NAFLD is also associated with free-radical production and disturbances of the oxidative–reductive balance. A study showed that resveratrol significantly diminished the level of factors associated with oxidative stress and contributed to decline of hepatocyte destruction and NAFLD development [71]. Other studies showed that the levels of thiobarbituric acid reactive substrates (TBARS), ROS, and expression of other proteins related to oxidative stress in the liver were reduced following resveratrol treatment [72, 73], and other investigations suggested that such effects are mediated by the SIRT1/forkhead box protein 1 (FOXO1)/SOD/ROS pathway [74, 75]. SIRT1 interacts with FOXO transcription factors (FOXO1, FOXO3a, FOXO4), which results to production of ROS-detoxifying enzymes, such as catalase and SOD [76]. In vivo studies showed that resveratrol therapy upregulated the expression

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of hepatic UCP-2 which led to a reduction of mitochondriaderived ROS and inhibition of NAFLD development [47]. Also, resveratrol reduced mRNA expression of NOX4, a cell membrane enzyme that contributes to ROS production. Other studies found that resveratrol treatment elevated mRNA expression of SOD1 and glutathione peroxidase, enzymes involved ROS inactivation [77, 78]. Moreover, resveratrol protected vascular endothelial cells from high glucose–induced apoptosis via inhibition of NADPH oxidase activation-driven oxidative stress [78]. 5.3 Effects of RES on Lipid Metabolism

Lipid accumulation in hepatocytes is due to elevated free fatty acid levels associated with inadequate β-oxidation and/or esterification. In NAFLD patients, this process usually results from an inappropriate diet that causes dysregulation of liver metabolism. The pivotal molecules that play an important role in this process have been identified as SREBP-1, liver X receptor (LXR), and AMPK. SREBP-1 is a transcription factor which regulates de novo lipogenesis, which activates fatty acid synthase (FAS). The persistent activation of FAS in NAFLD leads to a worsening of steatosis. LXR is an SREBP-1 activator and one of the major liver metabolism activators. Its physiological inhibitor AMPK can hinder SREBP-1 either by direct phosphorylation or by blocking LXR activity. The major therapeutic impact of resveratrol supplementation is associated with the activation of AMPK [79, 80]. To date, most of the information regarding this has been obtained from studies at the in vitro (HepG2 cells and primary hepatocytes) and in vivo (rodents treated with either high palmitate or a high-fat diet) levels. These studies showed that resveratrol administration elevates AMPK phosphorylation, which becomes metabolically active and leads to LXR inhibition, which finally leads to reduced SREBP-1 levels [79]. Moreover, by decreasing the LXR activity, resveratrol indirectly decreases FAS activity and de novo lipogenesis, thereby reducing intracellular fat accumulation [81, 82]. In addition, some studies have demonstrated that resveratrol significantly influences lipid metabolism by increasing the high-density lipoprotein/ low-density lipoprotein (HDL/LDL) ratio [83] and expression of LDL receptors [82]. Other lipid-related effects of resveratrol supplementation include a reduction of plasma TG and ceramide levels [47, 48], a decreased membrane saturated/unsaturated fatty acids ratio [82], and lowered lipid peroxidation [68, 75] and fatty acid accumulation [81].

5.4 Effects of RES on Carbohydrate Metabolism

Surplus lipid accumulation in liver is usually associated with disruptions in the insulin signaling pathway [84]. A metabolic factor that enhances insulin sensitivity is AMPK, since both insulin and AMPK hinder the expression of the gluconeogenesis pathway [85]. Activation of cAMP signaling is another intracellular pathway that may stimulate AMPK and SIRT1, which influence glucose and lipid

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metabolism [86]. Resveratrol hinders cAMP-specific phosphodiesterases and thereby elevates the cAMP level [87] and stimulation of AMPK results in increased SIRT1 activity, enhancing insulin sensitivity [88]. Recent in vivo studies in rodents demonstrated that resveratrol is more effective than the antidiabetic drug metformin in promoting insulin sensitivity [11]. Hence, it was supposed that resveratrol can be used to treat metabolic syndrome. In line with this, studies have shown that resveratrol ameliorates insulin resistance [89]. Also, it has been established that resveratrol decreases hyperglycemia [90], increases insulin secretion [91, 92], and hinders NAFLD development [93]. 5.5 Effects of RES on Gut Microbiota

NAFLD patients, specifically those with NASH, are characterized by bacterial overgrowth in the small intestine that can change the intestinal tight junction and intestinal permeability, favoring the translocation of harmful elements including lipopolysaccharides into the circulation [94]. This leads to hepatic expression of tolllike receptor 4 (TLR4) and generation of proinflammatory mediators involved in inflammation, choline deficiency, and insulin resistance in NAFLD [95, 96]. Resveratrol has been shown to enhance intestinal expression of the fasting-induced adipose factor, an important gene negatively controlled by the intestinal microbes and adipogenic genes in adipose tissues. In a mouse model, resveratrol therapy (75 and 100 mg/kg, daily, for 16 weeks) normalized the serum lipid profile and decreased endotoxemia and inflammatory and oxidative stress parameters in the liver and brain [97]. Also, resveratrol treatment at 300 mg/kg, daily, for 16 weeks modulated microbiota composition, modified lipid metabolism, decreased inflammation, and ameliorated intestinal barrier function [98]. However, in another investigation, resveratrol (15 mg/kg, daily, for 6 weeks) had no effect on gut bacteria profiles in a high-fat diet rat model [99]. The reasons for these differences are not clear but may be due to the different dosages used.

5.6 Effects of Resveratrol on Epigenetic Modification

The nuclear factor erythroid 2-related factor 2 (Nrf2) pathway is involved in suppression of oxidative stress and lipogenesis, with important effects in prevention of metabolic diseases including NAFLD and diabetes [100, 101]. Thus, understanding the mechanisms involved in regulation of this pathway could lead to new targets for therapeutic intervention. Studies have shown that epigenetic modifications such as DNA methylations are an important factor involved in regulation this pathway [101, 102]. Interestingly, the effects of resveratrol on health may result from effects on this pathway [103–105] as treatment led to upregulation of Nrf2 at both the mRNA and protein levels in in vivo and in vitro models of NAFLD. It also caused downregulation of lipogenic genes and

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upregulation of antioxidant genes in liver tissues of high-fat diet mice and HepG2 cells treated with high glucose diet.

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Conclusions Taken together, the studies described in this review have shown that resveratrol may have a positive impact on improving at least some of the symptoms associated with NAFLD. Preclinical studies have shown that it has positive impacts on inflammatory, oxidative stress, metabolic, and epigenetic effects involved in NAFLD. However, the results of some clinical studies have been inconclusive and often contradictory. These inconsistent results may be due to high heterogeneity across the studies in terms of the patient groups as well as the dosages and formulations of the resveratrol treatments used. Therefore, additional larger and longer duration trials are required to estimate the effectiveness of resveratrol in this patient group and to evaluate new forms of administration of this natural product, including nanoparticle delivery systems with enhanced bioavailability. Positive findings would help to revolutionize treatment of NAFLD, which has increased in line with the rising obesity and T2DM epidemics across the world, with devastating effects at the individual, societal, and healthcare levels.

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Chapter 3 A Matter of Fat: Body Fat Distribution and Cardiometabolic Disease in Africa Nasrin Goolam Mahyoodeen and Nigel J. Crowther Abstract Africa is a complex and diverse continent that faces numerous challenges. It is a region in epidemiological transition which is currently experiencing a dual burden of communicable and non-communicable diseases. The high prevalence of cardiometabolic disease (CMD) on the continent is driven largely by the increasing prevalence of obesity in the more affluent African nations. Although epidemiological studies demonstrate that a greater level of total body fat is associated with a higher risk for CMD, there is a complex association between body fat distribution and CMD risk. Thus, visceral adipose tissue (VAT) is considered a prime etiological agent for CMD, while subcutaneous adipose tissue (SAT) may act as a protective factor. The literature demonstrates positive correlations of VAT with type 2 diabetes, hypertension, and atherogenic dyslipidemia. However, the mechanisms via which VAT and SAT modulate CMD risk in African patients require further investigation. In addition, studies from high-income countries have shown that HIV and antiretroviral therapy (ART) are associated with changes in body fat distribution and higher risk for CMDs. The prevalence of HIV infection is at its highest in sub-Saharan Africa. However, cross-sectional studies from this region have produced contradictory results on the association of HIV and ART with CVD risk factors, and data is required from large prospective studies to clarify these relationships. Keywords Obesity, Visceral fat, Gluteofemoral fat, Africa, Cardiometabolic disease, Diabetes, Hypertension

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Introduction Africa has a vast and complex population of approximately 1.34 billion [1]. Although the continent is recognized by the United Nations (UN) Statistics Division as a single region, it is characterized by significant demographic and ethnic heterogeneity. Over 80% of Africa’s population resides in sub-Saharan Africa (SSA) [1] where the current per capita gross domestic product (GDP) is US$ 1525 as compared to US$ 2823 in North Africa [2]. Even within the SSA region, there is wide variation in GDP ranging from US$ 834 in East Africa to US$ 5934 in Southern

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_3, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Africa [2]. Economically, the continent lags far behind the developed world with the United States having a GDP of US$ 60,055 [2]. Furthermore, literacy rates across the continent differ significantly varying from 22% in Chad to 92% in Namibia as compared to the global average of 86% [3]. More recently, evidence has emerged of greater genetic diversity within African in comparison to Eurasian populations [4, 5]. It is also recognized that Africa is a region in epidemiological transition. The life expectancy at birth has increased from 37 years in 1950 to over 60 years at present, while the infant mortality rate has decreased from 183 to 42 per 1000 live births over the same time period [1, 2]. Historically, communicable diseases, including malaria, tuberculosis, and human immunodeficiency virus (HIV) infection, have been the major health challenges facing Africa [6]. However, over the last 15 years, there has been increasing evidence that the spectrum of disease has broadened to include non-communicable diseases (NCD), such as type 2 diabetes (T2D), cardiovascular disease (CVD), chronic respiratory diseases, and malignancies [7, 8]. Urbanization, with its attendant changes in diet and lifestyle, i.e., the consumption of energy-rich processed foods, and a propensity to physical inactivity, is in part responsible for this shift [9]. Overall, the proportion of the population residing in urban areas has increased by almost 20% from 1975 to a current level of 25–44% [1]. Urbanization and increased access to highly calorific Western diets is driven by economic development within SSA. Thus, Fig. 1 shows a strong positive correlation between GDP 45

Prevalence of obesity (%)

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40 35 30 25 20 15 10 5 0

0

3000

6000

9000

12000

15000

18000

GDP ($) Fig. 1 Relationship between GDP and national prevalence levels of female obesity in sub-Saharan Africa. The correlation of GDP with obesity prevalence was r ¼ 0.75 ( p < 0.0001). The result for male obesity was similar (r ¼ 0.87; p < 0.0001). Obesity data obtained from the World Obesity Federation [10] and GDP figures from the World Bank [3]

A Matter of Fat: Body Fat Distribution and Cardiometabolic Disease in Africa

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and the national prevalence levels of obesity in both females and males in SSA [3, 10]. Although the mortality from communicable diseases in Africa has decreased, the continent is now facing a dual burden of infectious diseases and the development of NCDs as the population ages and grows more obese. Obesity is a well-established risk factor for cardiometabolic disease (CMD) [11] and is associated with both increased morbidity and mortality [12, 13]. Although the prevalence of obesity is highest in high-income countries (HIC) [12], the prevalence of obesity across Africa and in other low- and middle-income countries (LMIC) has increased over the last three decades [14]. Furthermore, the past decade has seen an attenuation in the rise of overweight and obesity in HIC, while continued increases are still predicted for LMIC [12, 15]. Although total adiposity correlates with CMD risk, the generalization that “all fat is harmful” is overly simplistic. Current evidence underscores the role of body fat distribution as a predictor of CMD risk [16]. Although mortality increases with body mass index (BMI), visceral adipose tissue (VAT), often inferred by the surrogate marker, waist circumference (WC) [17], is a stronger predictor of cardiovascular mortality [18]. Conversely, there is evidence that fat deposited in the gluteofemoral area may be protective against CMD [19]. The aim of this review is to explore the impact of body fat distribution on CMDs in Africa, with particular emphasis on SSA.

2

Beyond Body Mass Index Body mass index is a widely used anthropometric measurement of weight adjusted for height that is used to quantify whole body adiposity [20]. Specifically, BMI measurements may be categorized into underweight (30.0 kg/m2) [20]. Studies have reported that the relationship between BMI and mortality may be represented by a J-shaped curve [21]. However, the thresholds defining overweight and obesity have limitations, including the potential need for ethnic variations in BMI cut-points. Thus lower thresholds for individuals of Asian descent, in whom obesity-associated diseases are observed at lower levels of BMI than in other populations, have been proposed [22]. In addition, many studies have now shown that CMD risk is better described by body fat distribution than measures of total body fat such as BMI. Another limitation of BMI is that it is a marker of whole body fat which is predominantly subcutaneous adipose tissue (SAT) while VAT typically comprises only around 15% of total body fat [23].

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In one of the earliest descriptions of body fat distribution and CMD, the French physician Jean Vague demonstrated that his cohort of obese patients with diabetes or CVD had central (android) adiposity. He also observed that the gynoid distribution of body fat (greater adipose tissue in the gluteofemoral region and legs) was rarely associated with cardiometabolic complications [24]. These findings were not widely accepted until the early 1980s when clinical and epidemiological studies confirmed that the waist-to-hip ratio (WHR) was more predictive of cardiovascular outcomes than BMI [25, 26]. Anthropometric measurements such as the WHR and WC are often used as surrogate markers of visceral fat but are limited in that they do not distinguish between VAT and SAT [27]. However, anatomical imaging methodologies such as computed tomography (CT), magnetic resonance imaging (MRI), and dual-energy X-ray absorptiometry (DXA) scanning provide precise and reliable tools whereby body fat distribution may be quantified and related to disease risk [28].

3

Defining Fat Distribution: Separate, But Not Equal The main body fat compartments are the SAT and the VAT depots [29]. The former, located directly below the skin, includes abdominal, gluteofemoral, and leg fat depots [30], while the latter is located within the abdominal cavity and is more strongly associated with CMD risk [29]. In addition, excess VAT accumulation predisposes to further ectopic adipose tissue deposition in major organs such as the heart, liver, and pancreas [27]. Large epidemiological studies like the Framingham Heart Study and the Jackson Heart Study have provided evidence from CT imaging that VAT and ectopic fat deposition are independently associated with CMD [31–33]. There are a number of pathogenetic mechanisms that may explain the association between obesity and CMD; however, the production of pro-inflammatory mediators, i.e., adipokines, by adipose tissue [34–36] is the most well-studied. Lipid uptake into adipose tissue (mainly in the form of triglycerides) is accommodated by adipocyte hypertrophy (with some hyperplasia), which initially occurs preferentially in the SAT depot. However, as this site reaches its storage capacity, VAT lipid uptake increases [37]. Various factors modulate VAT deposition such as gender, ethnicity, aging, genetic factors, smoking, and endocrine factors (cortisol and sex hormones) [27]. Excessive fat deposition in the visceral depot coupled with the high lipolytic rate of this tissue leads to the “overflow” of free fatty acids into the portal circulation and a concomitant increase in the secretion of adipokines [27]. Adipokines mediate the metabolic effects of adipose tissue. Leptin, visfatin, and resistin as well as other pro-inflammatory

A Matter of Fat: Body Fat Distribution and Cardiometabolic Disease in Africa

41

mediators, such as tumor necrosis factor and interleukin 6, are produced by all adipose depots [38]. Adiponectin is the principal anti-inflammatory adipokine. It is now known that there are differences in adipokine secretion from the visceral and subcutaneous fat depots. Subcutaneous fat, particularly gluteofemoral and leg fat, is associated with a beneficial adipokine profile [23]. Thus, higher gluteofemoral fat mass has been shown to be associated with higher adiponectin levels and greater insulin sensitivity [19]. There is also evidence that abdominal subcutaneous fat may attenuate CMD risk. Thus, studies from South Africa have shown that leg fat is associated with lower triglyceride levels [39], while abdominal subcutaneous fat is associated with lower fasting glucose levels [39] and reduced hepatic steatosis [40]. A large multinational study has shown that the latter fat depot is associated with a reduced risk of type 2 diabetes [41], and a study from Israel demonstrated that in diabetic patients it is associated with lower HbA1c and fasting glucose levels [42]. Thus, multiple subcutaneous fat depots seem to protect against CMDs, and it has been hypothesized that this is due to the ability of SAT to act as a reservoir for free fatty acids and triglycerides, reducing their deposition in the visceral depot [43]. Studies have assessed ethnic differences in adipose tissue biology [44]. Despite African women having lower VAT, they are more insulin resistant than their white counterparts [44]. In studies investigating the inflammatory profile of adipose tissue, there is no difference between African-American and Caucasian women [45, 46]. However, a study comparing black and white South African women demonstrated higher abdominal and gluteal SAT inflammatory gene expression in black women [47]. These results conflict with other studies demonstrating that these fat depots are associated with reduced levels of particular CMDs and associated risk factors [19, 39–42]. Other proposed mechanisms for ethnic differences in adipose tissue biology include differences in estrogen receptor gene expression, increased hypoxia, and increased oxidative stress [44].

4

Obesity in Africa... A Growing Problem The prevalence of obesity varies widely across Africa (see Table 1) [10]. In Ethiopian women, the prevalence of obesity is 7.3% compared to 41% and 42% in their South African and Egyptian counterparts, respectively [15]. In addition to economic and behavioral factors, sociocultural perceptions unique to the continent influence body shape. Being overweight or obese is associated with positive connotations such as affluence, fertility, and well-being [48, 49]. This perception is further compounded by the HIV epidemic in SSA, with a lean body habitus being associated with

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Table 1 Prevalence of obesity in males and females in selected countries Country

Year of study

Age group

Male (%)

Female (%)

England

2018

16+

26.0

29.0

Poland

2017

18+

17.9

16.1

USA

2017/2018

18+

41.8

42.2

Argentina

2018

18+

31.4

33.4

Australia

2017/2018

18+

32.5

30.2

Indonesia

2014/2015

18+

8.5

8.5

United Arab Emirates

2017/2018

18+

25.1

30.6

Morocco

2017/2018

18+

11.0

29.0

Kenya

2015

18–69

4.3

13.7

Mauritius

2015

18+

11.1

25.6

South Africa

2016

15+

11.0

41.0

Uganda

2016

15–49

1.2

7.2

Zambia

2017

18–69

3.0

12.3

Zimbabwe

2015

15–49

2.3

12.6

Data from World Obesity Federation [10]

the acquired immune deficiency syndrome (AIDS) and tuberculosis. Many individuals, therefore, favor being overweight or obese [50]. In addition, these perceptions are more prevalent in women [48, 50]. Epidemiological studies have demonstrated that the prevalence of obesity is significantly higher in African females compared to males, and particularly so for middle-aged females residing in urban areas [51–53]. In a study from Nigeria, significantly more women than men were found to have central adiposity (defined by an increased WC). Similarly in rural Ghana, in a study that used both clinical and sonographic markers to measure body fat, all anthropometric indices were significantly higher in women than men with the exception of VAT [54]. In Southern Africa, in a study conducted in both urban and rural Malawi, both BMI and WHR were higher in women than men, and the prevalence of each was higher in urban compared to rural areas [55]. The data in Table 1 demonstrates this gender difference in the prevalence of obesity in African nations and also shows that this is not observed in HIC such as the United States [10]. It is concerning that the burden of overweight and obesity in the African population is also increasing in young females with the prevalence of overweight and obesity in SSA being 15.4% and 3.9%, respectively, in girls aged from 5 to 17 years

A Matter of Fat: Body Fat Distribution and Cardiometabolic Disease in Africa

43

[56]. The highest prevalence of obesity in SSA is in urban, black mid-life South African women (69.3%) [15, 57]. The reasons for the higher prevalence of obesity in African females are complex and may include sociocultural factors, urbanization, physical inactivity, and poor dietary practices [58]. Maternal and early life factors such as low birth weight, prematurity, and undernutrition in infancy, which are common in Africa, have also been linked to obesity in later life [59]. Furthermore, the COHORTS initiative demonstrated size at birth was linked to metabolic syndrome in five LMICs including South Africa [60].

5

In Point of Fa(c)t... Data from Africa In light of a paucity of data from the African continent, anthropometric thresholds such as WC cut points derived from Caucasian populations were recommended for assessment of CVD risk in African populations [17]. There is, however, ethnic variation in anthropometric cut points, e.g., the risk of metabolic syndrome in patients of Asian descent is higher at WC cut points below those defined for European populations [61]. Recent literature suggests that WC thresholds derived from Caucasians may be inappropriate for African subjects [62–64]. For example, it is known that African women have lower VAT than Caucasian women when matched for WC [65]. In an analysis of cross-sectional data from 17 studies in SSA, the optimal WC cut point for identifying men in SSA with metabolic syndrome was lower than the current recommended threshold taken from European populations (81.5 cm vs 94 cm), while the threshold recommended for women was appropriate [62]. However, in this analysis, there was wide regional variation in WC cut points in both men and women [62]. A study from South Africa determined that the optimal WC cut points for diagnosing metabolic syndrome in both men and women differed from those recommended for Caucasians [63]. In this cohort, the identified cut points were 86 cm and 92 cm for men and women, i.e., lower and higher than the global recommendations, respectively [63]. Overall, it appears that the WC cut points currently used to diagnose metabolic syndrome in SSA are too low in African women, which results in an overestimation of disease prevalence, but too high in African males. Although, it is agreed that current thresholds are suboptimal, available data from Africa does not provide a consensus on the WC that best defines metabolic syndrome. This may, in part, be related to the heterogeneity of the population.

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Body Fat Distribution and Human Immunodeficiency Virus Infection Almost 70% of the world’s population of people living with HIV (PLHIV) reside in SSA with more than half of these being women [66, 67]. The use of effective antiretroviral therapy prevents the development of HIV-associated complications and allows PLHIV to have near-normal life spans [68]. However, these individuals may then face a dual burden of cardiometabolic risk imparted by both traditional risk factors (such as aging, diet, sedentary lifestyle) as well as HIV- and ART-related factors (i.e., chronic inflammation and increases in markers of endothelial damage) [68]. Data from HIC indicate that HIV infection and antiretroviral therapy (ART) are independent risk factors for CVD [69]. Both HIV infection and ART have an impact on body fat distribution. Untreated, HIV infection is associated with malnutrition and the HIV wasting syndrome, both of which cause significant weight loss [70]. Moreover, the development of infections such as tuberculosis and diarrheal diseases further exacerbates weight loss. For these reasons, it has been suggested that the burden of HIV infection in Africa could mask the impact of rising levels of obesity on the continent [71]. Furthermore, lipodystrophy is a well-documented consequence of ART with peripheral lipoatrophy and concomitant increased visceral and ectopic fat accumulation [72]. Initiation of antiretroviral therapy is associated with increases in total and LDL cholesterol, without a commensurate change in HDL cholesterol [73]. In 2018, 64% of PLHIV in Africa were treated with ARVs [74]. However, there is wide variability within the continent with treatment prevalence as low as 15% in Sudan and as high as 88% in Zimbabwe [74]. The association of CMD with both HIV and ART has not been conclusively demonstrated in Africa with currently available studies yielding conflicting results. A recent crosssectional study from a rural South African population showed that PLHIV had a more favorable CVD risk profile than HIV-negative participants. Paradoxically, the former group had increased carotid intima-media thickness [75]. A meta-analysis of 52 African studies showed that ART use was associated with a lower glycated hemoglobin and HDL cholesterol level compared to untreated patients [76]. Data from South Africa also shows that antiretroviral therapy is associated with increasing lipid levels [77] and lipoatrophy [78, 79]. This data highlights the need for further studies, particularly prospective studies, addressing CVD endpoints in African participants.

A Matter of Fat: Body Fat Distribution and Cardiometabolic Disease in Africa

7

45

Diabetes in Africa Although SSA is responsible for the smallest proportion of the population of people living with T2D worldwide, it has the highest projected rate of increase in the disease over the next two decades [80]. This trend appears to be closely related to the rising prevalence of obesity in Africa [81]. The role of obesity-related insulin resistance in the pathogenesis of T2D has been well-described; however, there is a paucity of data on the β-cell dysfunction predisposing to T2D in the African population. Studies that have been conducted on this aspect of T2D include those from South Africa [82, 83], West Africa (Nigeria and Ghana) [84, 85], and North Africa [86, 87]. Demographic and socioeconomic factors also influence the prevalence of diabetes. In a study in rural South Africa, the prevalence of diabetes was 3.9% [88] while in an urban population the prevalence was 11.9% [89]. In the former study, mean WC was significantly higher in participants with dysglycemia (T2D or impaired glucose tolerance) compared to normoglycemic individuals (94.1 cm vs 94.0 cm vs 84.6 cm, respectively, p < 0.001) [88]. In a cross-sectional study of T2D prevalence in urban vs. rural Malawi, the overall prevalence was higher in the urban setting and the divergence between the groups was more pronounced with older age and, in women, in parallel with the increase in obesity [55]. The mortality associated with T2D is also higher in women than men [90]. The AWI-Gen Collaborative Centre is part of the Human Heredity and Health in Africa (H3A) Consortium study which aims to look at the influence of sociodemographic, behavioral, genetic, and anthropometric variables on CMD risk in middleaged African populations across six multinational sites [91]. Data from this group confirms the findings of many smaller studies and demonstrates a higher prevalence of T2D in women compared to men [60]. This trend paralleled the prevalence of obesity and was most prominent in urban sites such as Soweto, South Africa, compared to rural sites such as Nanoro, Burkina Faso (see Table 1) [60, 92]. These studies demonstrate that diabetes in African populations is associated with obesity, particularly central obesity. However, the relationship between visceral adiposity and insulin resistance in SSA populations is complex. Thus, studies have shown that African subjects are more insulin resistant than BMI-matched subjects of European ancestry, yet the former group have lower levels of visceral fat [82]. Similar findings have been reported in African Americans [93]. Furthermore, these ethnic differences in insulin sensitivity are not explained by differences in ectopic fat deposition, as levels are similar between these groups [94]. A possible

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explanation for these differences is that visceral and/or ectopic fat have greater effects on insulin sensitivity in African than European populations, although currently there is no experimental evidence supporting this hypothesis.

8

Hypertension Globally, hypertension is a major public health concern that is a significant contributor to morbidity and mortality. Africa has the highest prevalence of hypertension, compared with other regions of the world with an overall prevalence of 46% [95]. However, there is also a wide regional variation in prevalence. Data from the H3A Consortium demonstrate prevalence levels of hypertension ranging from 35% to 75% across 13 countries in SSA [95]. Like diabetes, hypertension is most prevalent in regions with the highest prevalence of obesity as well as in urban compared to rural areas (see Table 2). It is thought that black Africans have a genetic predisposition to salt and water retention with low plasma renin activity [96]. Other pathogenetic mechanisms that may explain the higher prevalence of hypertension in Africa include abnormalities in sodium epithelial channels, and increased peripheral vascular resistance [96, 97]. In a study from Tanzania, socioeconomic status was inversely related to hypertension prevalence [98]. However, urbanization has also been associated with increases in the prevalence of hypertension [97]. Both underweight and obesity are associated with hypertension, with the former, potentially related to low birth weight [99]. In a large pan-African study, obese individuals were twice as likely as non-obese to have hypertension [95]. Although

Table 2 Prevalence of obesity, diabetes, and hypertension in males and females at AWI-Gen study sites Obesity (%)

Hypertension (%)

Diabetes (%)

Site

Female

Male

Female

Male

Female

Male

Soweto (SA)

66.6

17.5

53.7

50.2

11.4

6.3

Dikgale (SA)

51.4

2.8

44.1

28.8

8.1

6.6

Agincourt (SA)

42.3

11.8

52.5

38.4

4.7

5.2

Nairobi (Kenya)

32.1

5.2

29.7

21.3

9.9

4.1

Navrongo (Ghana)

4.2

1.2

20.8

20.7

1.6

1.6

Nanoro (B Faso)

1.3

2.2

10.8

19.6

1.8

5.1

Data from Ramsay et al. [53], George et al. [92]; approximately 2000 subjects per site with age range of 40–60 years; SA South Africa, B Faso Burkina Faso

A Matter of Fat: Body Fat Distribution and Cardiometabolic Disease in Africa

47

men had a higher prevalence of hypertension than women, the association with obesity was stronger in women [95]. Studies focusing on body fat distribution and its relationship with hypertension in African populations have shown in both crosssectional [100] and longitudinal [101] analyses that measures of central obesity, such as visceral fat area and WC, correlate more strongly with blood pressure indices than do measures of whole body obesity. The mechanisms by which visceral fat may influence blood pressure include secretion of inflammatory cytokines and angiotensinogen and increased activation of the sympathetic nervous system [102]. Within the context of hypertension in African populations, however, few mechanistic studies have been undertaken to investigate the molecular mechanisms linking central obesity to raised blood pressure. Although hypertension is largely asymptomatic, it is the most common risk factor for both ischemic and hemorrhagic stroke [103], which in turn is the second most common cause of mortality worldwide [104]. In HICs, abdominal adiposity and, in particular, an elevated waist-to-hip ratio (WHR) have been shown to be more strongly associated with stroke than BMI [105]. There is limited data on the association of body fat distribution with stroke in Africa. A cross-sectional study of cohorts from Nigeria and Ghana demonstrated elevated WHR as a risk factor for stroke with an odds ratio of 2.58 [106].

9

Dyslipidemia A recent meta-analysis has demonstrated a high prevalence of dyslipidemia in Africa [107]. Overall, the prevalence of increased total cholesterol was 25.5%, although low HDL cholesterol level was the most common lipid abnormality observed, with a prevalence of 37.4% [107]. As with other CMDs, there is a significantly higher prevalence of dyslipidemia in urban versus rural areas, as well as in individuals with hypertension, T2D, and HIV [107]. African populations are known to have more favorable lipid profiles when compared to other ethnic groups [108]. The reason for this is not fully understood, and few studies have been undertaken in SSA populations to identify possible mechanisms. However, a study performed in South Africa did analyze the relationship between body fat distribution and serum lipid levels in black and white women [109]. It demonstrated that higher triglyceride and lower HDL levels were associated with increased central obesity and reduced leg fat in both populations. In white women, total cholesterol and LDL cholesterol levels were positively associated with central obesity, while both these lipid species were negatively associated with abdominal SAT in black women. This and a previous study [110] conducted in African American, white, and

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Hispanic subjects clearly show ethnic differences in the association between body fat distribution and serum lipid levels. These data suggest that in African subjects SAT is protective in terms of totaland LDL cholesterol levels while in white subjects central fat is associated with higher levels of these cholesterol species. Further studies are required to determine whether these associations are causative and determine the mechanisms driving these differential effects of body fat depots on cholesterol levels in these two population groups.

10

Nonalcoholic Fatty Liver Disease Nonalcoholic fatty liver disease (NAFLD), defined as the presence of liver steatosis without significant ethanol intake, includes a broad spectrum of hepatic pathology ranging from fatty infiltration and progressing through to nonalcoholic steatohepatitis (NASH), fibrosis, and cirrhosis. In a recent study using either liver biopsy or imaging, the prevalence of NAFLD in Africa was estimated to be 13.5% compared to a global prevalence of 25.2% [111]. Insulin resistance is strongly implicated in the etiopathogenesis of NAFLD [112], and it is considered to be the hepatic manifestation of the metabolic syndrome. With the upsurge of T2D and obesity in Africa, one would expect a concomitant rise in the burden of NAFLD. However, there is a dearth of data on NAFLD from the African continent. In a study from South Africa involving overweight/obese participants who were predominantly of mixed race, the prevalence of simple steatosis, NASH, and advanced liver fibrosis, diagnosed from liver biopsies, was 51%, 36%, and 17%, respectively [113]. All these subjects were diabetic or insulin resistant. In a second South African study, African women were shown to have lower hepatic fat compared to Asian Indian and Caucasian women [40]. The lower prevalence of NAFLD in Africa may be related to differences in body fat distribution with lower VAT levels in Africans protecting against the development of NAFLD. At present there is uncertainty regarding the prevalence and impact of NAFLD in Africa and investigation into the prevalence and etiology of NAFLD remains an unmet need.

11

Cardiometabolic Aspects of Systemic Diseases In addition to the traditional risk factors for CMDs such as age, smoking, and obesity described above, the presence of other systemic diseases and/or their treatment may further predispose to increased CMD risk. This has been well-described in patients with rheumatoid arthritis (RA) and other rheumatological disorders in HICs [114]. There is limited data on this risk in African

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49

populations. Small studies from South Africa in patients with RA have shown increased CVD risk in these patients [115]. An increased prevalence of CMDs has also been observed in South African patients with psoriasis and psoriatic arthritis compared to matched controls [116] with VAT and its mediators being associated with CMDs in these patients [117]. Studies in AfricanAmerican women with polycystic ovary syndrome have demonstrated increased CVD risk in this group [118]; however, there is currently no data from Africa on this group of patients.

12

Obesity Interventions Lifestyle intervention, with or without pharmacological therapy, is the primary method for reducing body fat mass. Large, populationbased lifestyle intervention studies are rare in SSA populations. A recent meta-analysis of such studies concluded that little data is available from non-white populations [119]. However, one study from the USA has compared the effect of a Mediterranean diet in African-American and European groups and shown greater weight loss in the former population [120]. Bariatric surgery is used for the treatment of severe obesity that is associated with multiple comorbid diseases. A number of studies have demonstrated that the weight loss induced by bariatric surgery is less in subjects of African ancestry when compared to those from other population groups [120, 121]. One of these studies observed that baseline clinical, demographic, or behavioral characteristics could not explain these differences [122], and further studies are therefore required to determine the source of these race-based differential responses. Bariatric surgery is not a viable method for treating obesity at a population level, and with a lack of lifestyle intervention studies in SSA, it is not currently possible to recommend the most efficient and cost-effective method for treating obesity in this resource-limited environment. It is essential that population-based, pan-African lifestyle intervention studies are carried out to answer this question as the rising prevalence of obesity within Africa further drains the scant resources of the public healthcare sector.

13

Conclusions This chapter highlights the high prevalence of CMD in Africa and the complexity of its association with body fat distribution. Although visceral adiposity, and its accompanying pro-inflammatory milieu, is thought to be in the mechanistic pathway driving CMDs, the protective effects of SAT deposition, predominantly gluteofemoral fat, require further investigation. In

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addition, current data from SSA is contradictory with regard to the association of HIV and ART with CMD risk. Many of the studies investigating the relationship of body fat distribution, HIV, and ART with cardiovascular risk factors and endpoints have been small and cross-sectional. Large, pan-African, prospective studies, such as the AWI-Gen collaboration are essential to answer these questions. In addition, lifestyle intervention studies are required to determine the most cost-effective methods for reducing body fat mass, and hence CMD risk, in SSA populations.

Acknowledgments The AWI-Gen Collaborative Centre was funded by the National Human Genome Research Institute (NHGRI), Office of the Director (OD), Eunice Kennedy Shriver National Institute Of Child Health & Human Development (NICHD), the National Institute of Environmental Health Sciences (NIEHS), the Office of AIDS research (OAR) and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), of the National Institutes of Health (NIH) under award number U54HG006938 and its supplements, as part of the H3Africa Consortium. Additional funding was leveraged from the Department of Science and Technology, South Africa, award number DST/CON 0056/2014. References 1. Worldometers. https://www.worldometers. info/world-population/africa-population/. Accessed 3 May 2020 2. UN Statistics Division (2019) World statistics pocketbook. UN Statistics Division, New York. https://unstats.un.org/unsd/ publications/pocketbook/ 3. The World Bank. https://data.worldbank. org/indicator/SE.ADT.LITR.Zs. Accessed 3 May 2020 4. Campbell MC, Tishkoff SA (2008) African genetic diversity: implications for human demographic history, modern human origins, and complex disease mapping. Annu Rev Genomics Hum Genet 9:403–433 5. Yu N, Chen FC, Ota S, Jorde LB, Pamilo P, Patthy L et al (2002) Larger genetic differences within africans than between Africans and Eurasians. Genetics 161:269–274 6. Yusuf S, Reddy S, Ounpuu S, Anand S (2001) Global burden of cardiovascular diseases: part I: general considerations, the epidemiologic transition, risk factors, and impact of urbanization. Circulation 104:2746–2753

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Chapter 4 PGK1: An Essential Player in Modulating Tumor Metabolism Leslie Duncan, Chloe Shay, and Yong Teng Abstract Phosphoglycerate kinase 1 (PGK1) is the first enzyme in glycolysis to generate a molecule of ATP in the conversion of 1,3-bisphosphoglycerate (1,3-BPG) to 3-phosphoglycerate (3-PG). In addition to the role of glycolysis, PGK-1 acts as a polymerase alpha cofactor protein, with effects on the tricarboxylic acid cycle, DNA replication and repair. Posttranslational modifications such as methylation, phosphorylation, and acetylation have been seen to activate PGK1 in cancer. High levels of intracellular PGK1 are associated with tumorigenesis and progression, and chemoradiotherapy resistance. However, high levels of extracellular PGK1 suppress angiogenesis and subsequently counteract cancer malignancy. Here we have summarized the current knowledge on the mechanisms and effects of PGK1 in various tumor types and evaluated its potential prognostic and therapeutic value in cancer. The data summarized here aims at providing molecular information and new ideas of employing natural products to combat cancer associated with PGK1. Keywords PGK1, Metabolism and cancer, Molecular modification, Regulation, Natural products

Abbreviations 1,3-BPG 3-PG ADP AKT ATP BECN1 CAF CXCL12 CXCR4 DNMT EGCG ERK1/2 GDH GLUT1 GLUT2 HDAC3

1,3-Bisphosphoglycerate 3-Phosphoglycerate Adenosine diphosphate Protein kinase B Adenosine triphosphate Beclin 1 Cancer-activated fibroblasts Chemokine ligand 12 Chemokine receptor 4 Maintenance DNA methyltransferase Epigallocatechin gallate Extracellular signal-regulated protein kinases 1 and 2 Glutamate dehydrogenase Glucose transporter 1 Glucose transporter 2 Histone deacetylase 3

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_4, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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HIF-1α HKII KAT9 LDH-A mTOR NSCLC NSF O-GlcNAc PCAF PDH PDHK1 PGK1 Rab11FIP2 SAM SIRT7 TCA TOM U2AF2

1

Hypoxia inducible factor 1-alpha Hexokinase II Lysine acetyltransferase Lactate dehydrogenase-A Mechanistic target of rapamycin Non-small-cell lung cancer Normal fibroblasts O-linked N-acetylglucosamine P300/CBP-associated factor Pyruvate dehydrogenase Pyruvate dehydrogenase kinase 2 Phosphoglycerate kinase 1 RAB11 family-interacting protein 2 S-adenosyl methionine Sirtuin 7 Tricarboxylic acid cycle Translocase of the outer membrane U2 small nuclear RNA auxiliary factor

Introduction Phosphoglycerate kinase 1 (PGK1) is a glycolytic enzyme that catalyzes the conversion from 1,3-bisphosphoglycerate (1,3-BPG) to 3-phosphoglycerate (3-PG). This is the seventh reaction that takes place in glycolysis and uses PGK1 which is one of two enzymes that produces adenosine triphosphate (ATP). As such it plays a rate-limiting role in the production of ATP and 3-PG. The PGK1 enzyme is monomeric with two similar sized Rossman fold domains [1]. The N terminus binds to 1,3-BPG or 3-PG while the C terminus binds to ATP. The domains then fold in a hinge motion, bringing them together to bind the substrates in a closed confirmation [1, 2]. There are two different isoforms, PGK1 and PGK2 [3– 7]. Although these have a similar structure and function, they are encoded and expressed differently. PGK1 is located on the X-chromosome and is expressed in all cells, while PGK2 is located on an autosomal chromosome and is only expressed in spermatogenesis [1]. In addition to the role in glycolysis, PGK1 acts as a polymerase alpha cofactor protein affecting the tricarboxylic acid cycle (TCA), DNA replication and repair, which is deeply involved in numerous physiological and pathological processes. PGK1 has been associated with multiple different oncogenic signaling pathways. However, these pathways have been found to differ among the different cancers (Table 1). The HIF-1α/PGK1 and the PGK1/AKT/mTOR pathways are the most prominent pathways seen in cancer cells [1, 8–10]. Cancer cells favor the glycolytic metabolism even in low oxygen environments in an

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Table 1 PGK1 signaling in cancer development and progression

Type of cancer

Pathway PGK1 is involved in

Function of the signaling pathway

Lung cancer

PGK1/AKT/mTOR Promotes metastasis, Warburg effect, and tumorigenesis; suppresses tumor growth

Breast cancer

HIF-1α/PGK1 MYC/PGK1

Brain cancer

HIF-1α/PGK1 Promotes tumorigenesis PGK1/CXCR4 Promotes metastasis PGK1/ Promotes migration and invasion CXCR4/β-catenin

Gastric cancer

PGK1/AKT/mTOR Promotes oncogenic properties PGK1/ Promotes metastasis CXCR4/β-catenin

Hepatocellular carcinoma

HIF-1α/PGK1 Promotes metastasis PGK1/AKT/mTOR Induces glycolysis MYC/PGK1 Inhibits growth

Promotes epithelial mesenchymal transition Promotes development

event known as the Warburg effect. HIF-1α is a transcription factor regulating PGK1 gene expression and is upregulated in hypoxic environments inducing primarily glycolytic metabolism [8]. With increased PGK1 levels, glycolysis is elevated aiding in the growth of hypoxic cancer cells. Similarly, the PGK1/AKT/mTOR pathway is seen to induce glycolysis and promote metastasis as well as oncogenic properties [9, 10]. By interacting with other targets, PGK1 promotes tumorigenesis through involvement in the AKT/mTOR pathway. Overexpression of a protein known as gankyrin diminishes cellular oxidative stress and increases oncogenic properties of gastric cancer by activating PGK1/AKT/mTOR pathway. In nonsmall-cell lung cancer (NSCLC) cells, this pathway also enhances the Warburg effect and tumorigenesis via an RNA auxiliary factor known as U2AF2. PGK1 can also inactivate the AKT/mTOR pathway by interacting with Rab11FIP2, a family-interacting protein. As AKT/mTOR signaling increases, HIF-1α and PGK1 levels are elevated, and glycolysis increases ultimately. It is well known that cancer cells metabolically reprogram themselves to favor glycolysis and lactic acid fermentation even in the presence of oxygen. However, how they do this is far from understood. This adaptation enables an abundance of building materials to be accumulated by the cells to increase chances of survival in the highly oxidative environment that they live in [11]. The translocation of PGK1 into mitochondria also occurs, which suppresses mitochondrial pyruvate metabolism [10– 12]. Mitochondrial translocation is induced by hypoxia, activation

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of epidermal growth factor receptors (EGFRs), and expression of oncogenic gene mutations. Acting as a protein kinase, mitochondrial PGK1 phosphorylates pyruvate dehydrogenase kinase 1 (PDHK1) activating PDHK1 and inhibiting the pyruvate dehydrogenase (PDH) complex. The PDH complex converts pyruvate and coenzyme A into carbon dioxide and acetyl-coenzyme A. When this process is inhibited, the pyruvate oxidation in mitochondria is depleted and lactate production is enhanced. Recent studies have focused on the use of natural compounds in treatment of cancer or as an adjunct to standard chemo- or radiotherapy. As many of these compounds target metabolism, this review explores the potential molecular targets involved in the PGK1 pathway in cancer.

2

2.1

The Molecular Regulation of PGK1

Methylation

Mutated forms of PGK1 have been identified in different cancer cells. Specifically, the nucleotide mutations have been found in the 3-PG binding region, the ATP binding region, and the hinge region. The catalytic activity and conformational stability of PGK1 are affected by these nucleotide mutations that are found in different locations on the PGK1 molecule. PGK1 can also be activated by posttranslational modifications such as acetylation, methylation, and phosphorylation (Table 2). These posttranslational modifications are made by adding or removing functional groups from the PGK1 molecule. The modifications aid in regulating tumor growth and metastasis as well as the metabolism of the cells (Fig. 1). The removal of a methyl group from the PGK1 molecule in an event known as hypomethylation is associated with poor prognosis in cancer patients. DNA methylation regulates the expression of

Table 2 Posttranslational modifications and their function of PGK1 in cancer Posttranslational modification

Modification site Function

Phosphorylation

S203 T243

Promotion of Warburg effect, cancer development M2 macrophage-mediated glycolysis, proliferation of cancer cells

Acylation

T255

Activates PGK1 activity, enhances lactate production, induces translocation of PGK1 into the mitochondria

Acetylation

K220 K323

Inhibits PGK1 activity Promotes enzymatic activity, cancer metabolism, glucose uptake, and tumorigenesis

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Glucose

PGK1

Low activity

1,3-BPG Post-translational modifications

PGK1

High activity

PGK1

3-PG

PDHK1 TCA cycle PDH

Pyruvate

Lactate

Pyruvate

Acetyl-CoA

Tumor Growth, metastasis…

Fig. 1 Summary of functional alterations of PGK1 in regulation of glycolysis and the TCA cycle to promote tumor growth and metastasis

genes and is an indicator of tumor progression and metastasis. The methylation of DNA is accomplished by a family of enzymes known as DNA methyltransferase (DNMT) and uses a methyl group from a donor molecule known as S-adenosyl methionine (SAM) [13]. Cancers have been found to have overall DNA hypomethylation with region-specific hypermethylation. In the case of PGK1, the hypomethylation has been seen to occur predominantly in the promoter regions. It has also been theorized that the promoter hypomethylation may be a mechanism in which PGK1 expression is induced [13–16]. Recently it was shown that relationship of high PGK1 mRNA levels and promoter hypomethylation was associated with advanced stage cancer and short overall survival in multiple cancer types. Similarly, some studies have shown that the alterations in the genome to metabolic enzymes lead to malignant transformation, adaptation to poor nutrition, and tumor development. For this reason, DNA methylation involving the PGK1 gene has been studied and hypomethylation of the PGK1 promotor was found to be a prognostic biomarker for some cancers. 2.2

Phosphorylation

The phosphorylation of PGK1 at serine 203 (S203) correlates with the promotion of the Warburg effect, hypoxia, expression of oncogenic genes, and cancer development. The phosphorylation is carried out by extracellular signal-regulated kinase 1/2 (ERK1/2).

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When PGK1 is phosphorylated, this starts a signaling cascade that is recognized by the translocase of the outer mitochondrial membrane (TOM) enabling the translocation of mitochondrial PGK1 and the previously stated ensuing steps [1]. Once in the mitochondria, PGK1 functions as a protein kinase and phosphorylates pyruvate dehydrogenase kinase 1 (PDHK1) at T338. This now activated PDHK1 is able to phosphorylate the PDH complex suppressing the activity, increasing lactate production, and promoting tumorigenesis. The phosphorylations at S203 and T338 were found to be positively correlated with each other and with poor prognosis in patients. These phosphorylation gene modifications to PGK1 were found to be independent prognostic biomarkers and to be associated with clinical behaviors of cancer patients [16]. Phosphorylation is also seen at threonine 243 (T243) and is thought to be necessary for M2 macrophage-mediated glycolysis and proliferation of cancer cells [1]. M2 macrophages secrete interleukins increasing PGK1 phosphorylation at T243. The equilibrium of the PGK1 catalyzed reaction toward glycolysis is facilitated by the phosphorylation at T243 which also reduces the affinity for PGK1 with 3-PG [1]. 2.3

Acylation

Another posttranslation modification is acylation. Specifically, the attachment of O-linked N-acetylglucosamine (O-GlcNAc) to serine and threonine is known as O-GlcNAcylation. This is regulated by two main enzymes known as O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA) [10, 17, 18]. O-GlcNAcylation is critical in the normal physiology of the human body and its expression is associated with many different diseases including cancer. The OGlcNAc-cycling enzymes are thought to serve in cell signaling, gene expression, and homeostasis. The GlcNAcylation at T255 activates PGK1 activity, enhancing lactate production as well as inducing PGK1 translocation into the mitochondria. This translocation promotes the use of glycolysis and suppresses oxidative phosphorylation. Blocking the T255 O-GlcNAcylation of PGK1 has been found to suppress the Warburg effect, decrease cancer cell proliferation, and inhibit tumor growth. When combined with phosphorylation, acylation is involved in an important mechanism for intracellular signaling as seen by the regulation by different cellular metabolic stressors. A more extensive role for O-GlcNAcylation is currently being examined and has been convincingly demonstrated that it is an important mechanism in coordinating glucose flux through metabolic pathways in order to promote cell proliferation. With this new purpose for acylation emerging, a new treatment targeting these altered posttranslational modifications to normalize the metabolic flux may provide a new strategy for treating cancer patients.

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3

Acetylation

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The most commonly seen modification, acetylation, is a specific type of acylation with the difference being the presence of a methyl group instead of a multicarbon chain. Acetylation at the K220 location on the enzyme is associated with inhibited PGK1 activity. By blocking the binding of PGK1 with ADP, PGK1 enzyme activity is inhibited. KAT9 and HDAC3 are thought to regulate the acetylation at K220 [1]. HDAC3 is a deacetylase that activates PGK1 by removing an acetyl group. KAT9 is an acetyltransferase that increases the acetylation of PGK1 and decreases the activity. The inhibition of PGK is reversed when the AKT/mTOR pathway is activated [1, 10, 19]. This pathway increases HDAC3 phosphorylation and promotes deacetylation of PGK1 by HDAC3, resulting in activation of PGK1. Acetylation at K323 is important for promoting enzymatic activity, cancer metabolism, glucose uptake, and tumorigenesis [1, 20]. The upstream regulators PCAF and SIRT7 regulate the K323 acetylation [1]. SIRT7 is a deacetylase removing an acetyl group after binding to PGK1. PCAF is an acetyltransferase adding an acetyl group when interacting with PGK1. Acetylation is also seen at K388 and is thought to promote autophagy which in turn promotes tumor growth. Patients with high PGK1 acetylation at K388 have a shorter survival when compared to patients with little or no acetylation at K388.

Multi-faced PGK1 in Cancer Development and Progression Tumors consist of an abnormal growth of tissue and can be benign or malignant. Benign tumors are noncancerous and do not invade nearby tissue or spread to other areas of the body. Conversely malignant tumors are cancerous and invade surrounding tissues. Malignant tumors arise when there are mutations in the genes that regulate the growth and death of cells. Aside from genetic mutations, the microenvironment in which tumors reside is of utmost importance in oncogenesis and cancer progression in many different tissues and cancer types. Cancer cells interact with each other along with other cell types such as those of the extracellular matrix, endothelial cells, inflammatory cells, and fibroblasts. The complexity of such an environment is largely affected by the multifaceted stroma and extracellular matrix that is present [19, 20]. Stroma consists of connective tissue and is the supportive tissue of epithelial organs or tumors. Tumor stroma has a higher number of fibroblasts than in an organ stroma. Alterations in stroma often coincide with malignant conversion of epithelial cells. The fibroblasts present in tumor stroma have been described as cancer-associated fibroblasts (CAFs) and differ from normal fibroblasts (NSFs) in the reactivity. Activation of CAFs has been shown to lead to cancer progression; however, how is unclear. The overexpression of PGK1 in NSFs facilitates the conversion of NSFs into cells with a CAF phenotype

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[19]. CAFs induce tumor growth and progression as well as stromal–epithelial interactions. It has been theorized that PGK1 is the central molecule concerning tumor growth [21]. It has also been speculated that PGK1 is involved in the onset of malignancy as it is a suppressor to proangiogenic factors [22, 23]. It is known that cancer cells invade other cells by expressing a chemokine receptor that binds to a specific chemokine ligand on other cells. In many different types of cancer, it has been found that the chemokine receptor 4 (CXCR4) and the corresponding chemokine ligand 12 (CXCL12) are involved in the progression and growth of cancer. PGK1 regulates the expression of CXCR4 and vice versa. However, when CXCR4 was inhibited in cells overexpressing PGK1, there was only a small amount of invasiveness reduced, suggesting that PGK1 is crucial in itself in tumor invasiveness [22–26]. As part of the microenvironment, nourishment is also a necessity for tumors. In some cases, cancer can be promoted and provided nourishment through a metabolic process known as autophagy. Autophagy, or macro autophagy, is a cellular defense process in which the body consumes its own tissue in response to stress. Glutamine deprivation and hypoxia are two specific stressors that trigger autophagy. Under glutamine deprivation, PGK1 is acetylated at K388 which ultimately leads to the phosphorylation of a molecule known as Beclin 1 (BECN1) which induces autophagy [27–33]. Deprivation of glutamine in tumors occurs when they have outgrown the existing vasculature and can no longer obtain nutrients. At this point, the tumors get nutrients from autophagy by consuming surrounding tissues. Similar to glutamine deprivation, hypoxia stimulation shows increased PGK1 acetylation at K388 and BECN1 phosphorylation leading to autophagy. Although PGK1 production was found to be increased in tumors, its secretion was inhibited which caused a decrease in the molecule angiostatin [34, 35]. Angiostatin inhibits angiogenesis, which is the new formation of blood vessels. With angiostatin inhibited, angiogenesis can occur, enabling the addition of blood vessels to tumors. The increased blood and nutrients allow tumors to grow and eventually metastasize [36, 37]. The expression and secretion of PGK1 are regulated by the actions of CXCR4and CXCL12 [38]. As PGK1 oversecretion can lead to the restriction of tumors by enabling angiostatin to inhibit angiogenesis and therefore the nutrient source for the tumor, it is essential for PGK1 to be properly balanced in order to benefit cancer [30, 38–42]. As such, disruption of the balance of PGK1 can serve as a possible treatment in constricting tumor growth and metabolism.

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The Role of PGK1 in Treatment Resistance By understanding the role of PGK1 in the human body and how it provides assistance to cancer, PGK1 can be used as a target to stop the progression of tumors and therefore cancer. Hypoxic cells are known to be the most chemoresistant cells and are often found in the highly hypoxic core areas of tumors [43]. The lack of oxygen available to these cells inherently makes them more resilient, forcing them to adopt strategies like enhanced glycolysis and overexpression of antiapoptotic factors. As PGK1 is a glycolytic enzyme, it is more highly expressed in these hypoxic cells. It is also regulated by the transcription factor HIF-1α and induced by hypoxia. Some studies have shown that the inhibition of glycolysis is a possible way to overcome the drug resistance of certain tumors [44]. The inhibition of glycolysis would also deplete the ATP levels, offering another approach for treatment of malignancies. PGK1 is active in both the nucleus and cytosol of malignant cells but its most important role is to act as a transcription factor in the nucleus of metastatic cells. Recently a research finding demonstrated that PGK1 is involved in metabolic changes linking metabolism and tumor differentiation, ultimately affecting the cellular differentiation and vulnerability. This idea has since been applied to treatment of resistance as well as recurrence. Inhibition of PGK1 is thought to make the cells more sensitive to chemotherapeutic agents by inducing differentiation and breaking the resistance to therapy in cancer. By inducing progenitor cells into differentiation, the vulnerability of cancer cells can be increased to overcome the resistance to therapy. Another newly found treatment to overcome resistance is the use of oncolytic viruses [43]. Oncolytic viruses preferentially infect and kill cancer cells, and as the cancer cells are destroyed, they release new virions which destroy the remaining tumors [44]. Reovirus and adenovirus are two specific examples that have shown some oncolytic effects. The success of eliminating resistance with oncolytic viruses has been limited, with no long-term benefits seen. This may be due to the lack of a specific target in the viral therapy such as the inhibition of PGK1. Combination therapies have been suggested using chemotherapeutic agents and an oncolytic virus with a specific target. One study used an adenovirus-mediated PGK1 inhibition combined with therapeutic application and this revealed increased vulnerability and tumor killing [43–45]. Lastly, autophagy stimulation by DNA damage-inducing drugs may offer a means of improving clinical outcomes. Because of the importance of DNA, cells have DNA damage repair mechanisms in place to correct defacement of the genome. Damage repair can be induced in cells under stress and is believed to play a protective role in DNA-targeted drug treatments [46]. The effectiveness of the drugs depends on the balance between damage and repair. Damage

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can be managed by triggering the repair mechanisms to restore the damage and promoting cell survival therefore promoting resistance. Severe damage, however, cannot be repaired causing cell death. Thus, further studies are needed to increase our understanding of the repair mechanisms and the stressors that regulate DNA damage as a means of overcoming chemoresistance [7, 46].

5

The Clinical Value of PGK1 in Cancer It has been reported that the levels of production and secretion of PGK1 in cells correlate with prognosis. In some cancers, the high levels of expression of PGK1 decrease the overall survival rate in patients, although, in a few cancers, high PGK1 levels increase the overall survival rate. In breast cancer, PGK1 is seen to be elevated in cancer tissues and serves as a prognostic factor for poor overall survival [43, 47]. Likewise, endometrial cancer showed a stepwise elevation in the expression of PGK1 with a significant association with the cancer grade [48]. In neuroblastoma, PGK1 expression was found to be positively correlated with CXCR4 expression along with tumor dissemination to the bone marrow. The molecule was also associated with a negative impact on the overall survival of neuroblastoma patients [49]. An increase in expression of PGK1 along with several other hypoxia markers has also been observed in glioblastoma. PGK1 may play a relevant role in tumor progression in oral cancer as well, specifically as high abundance of PGK1 was found in locoregional recurrence and with lymph node relapse [50]. Unlike the previously stated cancer types, patients with gallbladder cancer had lower expression of PGK1 than in normal gallbladder tissue [51]. It is not fully understood why one molecule can increase and decrease tumor growth and metastasis. This is an area under intensive study as it might give insights into the treatment of specific cancers.

6

Application of Natural Products to PGK1-Associated Cancer Cancer is considered as a metabolic disease. Therefore, developing novel metabolism-targeted therapeutic approaches, such as targeting the glycolytic enzyme PGK1, is now emerging in cancer therapy. The use of plant-derived natural bioactive compounds for this endeavor is especially promising, which may be attributed to their diverse structures, antioxidant properties, and biological activity. Accumulating evidence has shown that therapeutic compounds from natural products are effective at different metabolic targets and can subsequently block cancer development and progression. For example, many natural compounds, such as Annonaceous acetogenins, the long-chained fatty acid derivatives extracted from

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several tropical plants, have been reported as potential modulators of glucose transporters (including GLUT1, HKII, and LDH-A) to counteract cancer cell proliferation and motility [52]. Epigallocatechin gallate (EGCG), the main catechin present in green tea, is an interesting bioactive anticancer molecule controlling the activity of glucose transporter glutamate dehydrogenase (GDH) by recognizing and binding to the site of the allosteric regulator ADP [53, 54]. Recently, our research team showed that EGCG has the great potential to inhibit PGK1 expression in oral cancer, with a favorable profile in terms of its anticancer effect and no obvious toxicity. These novel findings support the potential use of natural products and their derivatives with improved bioavailability in the treatment of PGK1-associated cancers.

7

Conclusions PGK1 is the key enzyme that catalyzes the formation of ATP in the aerobic glycolysis pathway. More than just regulating glycolytic metabolism, PGK1 is also involved in autophagy initiation, DNA replication and repair in mammal cell nuclei. Posttranslational modifications such as methylation, phosphorylation, and acetylation are important in the regulation of PGK1. Recently, PGK1 has become a compelling target in cancer research, as this enzyme is linked to the development and progression of many types of cancers. However, it remains in question how intertwined PGK1 is in other metabolic pathways and what are the functional consequences of targeting this enzyme in cancer cells. Future studies are needed for better understanding of its underlying mechanisms involved in metabolic reprogramming before any treatment is a possibility. Given the fact that nature represents a massive “database” of different and diversified molecular scaffolds, it is time to identify the promising antimetabolic natural compounds that inhibit cancer, especially those associated with PGK1 and other glycolytic enzymes. It will also be critical to improve their anticancer activities and facilitate their pharmacological use and efficiency with the advent of new concepts, technologies, and methodologies.

Acknowledgments This work was supported in part by NIH grants R01DE028351 and R03DE028387 and CURS Summer Scholars (to Y. Teng).

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Chapter 5 The Association of Reproductive Aging with Cognitive Function in Sub-Saharan African Women Nicole G. Jaff and Nigel J. Crowther Abstract Life expectancy in sub-Saharan African women is increasing, and by the late 2020s an estimated 76% of postmenopausal women globally will be living in developing countries. Menopause transition has been associated with cognitive decline in a wide range of studies, but data on cognition and reproductive aging are lacking in sub-Saharan African women. Approximately 72 million people in the region are expected to suffer from dementias and neurocognitive decline by 2050. Studies show that compromised cognitive health in low-income countries has significant implications for adult quality of life and socioeconomic development. There is now an urgent need to further examine risk factors for cognitive decline in these aging women and to understand the ability of public health programs to diagnose and treat cognitive dysfunction. This review examines studies assessing cognition and aging in sub-Saharan African adults, while addressing the significant research gaps. It examines data on the association of the menopause transition with cognitive function and describes how validated tools should be available to assess both menopausal stage and symptoms. Culturally appropriate and validated neurocognitive measures are required to better understand the relationship of reproductive aging with cognition. Longitudinal population-based studies are needed to assess the effect of lifestyle interventions, such as diet and exercise, on cognitive health in sub-Saharan African populations, with an emphasis on women as they transition into menopause. Keywords Menopausal symptoms, Menopausal stage, Cognition, Sub-Saharan Africa, Neurocognitive decline

1

Introduction Life expectancy in sub-Saharan African populations, specifically women, is increasing. However, there is a paucity of studies on cognitive functioning and impairment in this population. Therefore, there is an urgent need to examine risk factors for cognitive decline in this group, with modeling suggesting that globally 72 million people may be suffering from Alzheimer’s disease and various types of dementias by 2050 [1].

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_5, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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In addition to an increasingly aging population in sub-Saharan Africa, the World Health Organization has estimated that 1.2 billion women will be 50 or over by 2030. This means that the number of women who were in that age bracket in 1990 will have tripled [2]. It is projected that by the late 2020s, 76% of postmenopausal women will be living in developing countries [3], and there will be approximately five million women aged 50 in sub-Saharan Africa. Although HIV-AIDS may lessen the number of women reaching menopausal age, many of those women can expect to live for several decades after menopause [4]. It is relevant that research has shown that women living in poor socioeconomic conditions may reach menopause at a younger age [5], which may negatively affect their life span, since menopause at an older age is associated with a greater longevity [6] and less morbidity [7]. Furthermore, there are a wide range of Western studies indicating that the menopausal transition is associated with an increased risk of cardiometabolic disease, and changes in cognitive function [8]. However, the data on these associations, especially on cognition, are scant in sub-Saharan African women [9]. Research has shown that in low-income countries, decreased cognitive function and compromised cognitive health have significant implications for adult quality of life and socioeconomic development, but the part these play in the global disease problem is not well understood [10]. There are very few studies about reproductive aging in sub-Saharan African women, specifically those where menopause transition has been accurately staged. The challenges presented in defining menopausal stages are compounded by difficulty in accurately confirming the date of the final menstrual period (FMP). This may be because accurate recall is lower depending on the increasing number of years since the time of a woman’s FMP [11]. Research has shown that women in high-income countries appear to have a fairly precise idea of the date of their FMP up to nearly 20 years later [12]. However, it is likely that women in low-income countries have less access to annual healthcare examinations or gynecological consultations, and therefore have less incentive to recall the date of their FMP. It has also been suggested that since the transition into menopause is gradual, women must remember an exact date across a fairly long time period so the date of FMP may be difficult to recall especially in those women who have had a natural menopause [13]. Accurate age at FMP is easier to determine in longitudinal studies [14], although data from a large cross-sectional study of black South African women found that the mean age at FMP was similar to that of other sub-Saharan African women [15]. Finally, given the different perspectives that women in different cultures have about menopause, it is often difficult to understand and compare how menopausal symptoms are experienced by women of diverse cultures [9].

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This review will examine the available data on cognition in perimenopausal and menopausal sub-Saharan African women, identify research gaps in this area, and suggest ways in which these might be addressed in future research studies.

2 Cognition and the Menopausal Transition in Western, European, Latin American, and Asian Women As discussed earlier, a number of studies of Western women, particularly those in the USA, have analyzed the relationship between the menopause transition and cognitive function [8]. The most prominent of these studies was the Study of Women Across the Nation (SWAN), which had the time and resources to examine a vast range of factors associated with the perimenopause and menopause including cognitive functioning [16]. Studies using appropriate neuropsychological tests found that both the menopause transition [17–19] and severe menopausal symptoms are related to decreased processing speed and memory [16, 20]. In addition, SWAN and another large longitudinal study, the Penn Ovarian study, found that stage, specifically the perimenopause, affects verbal memory [18, 21]. This was also found to be the case in cross-sectional investigations [19] (Fig. 1). The decreased cognitive function Late reproductive Late perimenopause

Early perimenopause Early postmenopause

1.0

Adjusted z-scores

0.5 0.0 -0.5

+

-1.0 -1.5

*+

+*

Verbal learning

Verbal memory

*+

-2.0

Fine motor skills

Working memory

Fig. 1 Cross-sectional analysis of various domains of cognitive function in women at different stages of menopause transition. Data are presented as mean z-score with standard errors; *p < 0.05 vs late reproductive stage, +p < 0.05 vs late perimenopause stage. Subject numbers for each menopausal stage were as follows: late reproductive, n ¼ 34; early perimenopause, n ¼ 28; late perimenopause, n ¼ 41; early postmenopause, n ¼ 14. The four cognitive domains were assessed using a battery of tests for each domain from which averaged z-scores were obtained. Data taken from Weber et al. [19]

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observed in the SWAN longitudinal studies appeared to be associated with the symptoms of anxiety and depression and late perimenopause [21]. Data from a large British Birth Cohort Study suggests that it is possible that both reproductive events and fluctuating hormonal levels during the perimenopause affect verbal memory [22], and further data from the same cohort suggest that cognitive function appears to decrease during menopause. The study found that later age at FMP was related to better verbal memory, but not to processing speed [23]. In addition, the researchers found that a range of environmental and genetic factors and certain reproductive events, including induced or premature menopause, may influence cognitive function throughout the life span [23]. Some research suggests that longer lifetime exposure to endogenous estrogen is related to better cognitive processes in older women [24]. Cross-sectional data from a sample of 120 pre-, peri-, and postmenopausal Australian women showed that the menopausal transition and vasomotor symptoms are associated with poorer cognitive performance including processing speed [25]. In the French Three City Study, researchers found that premature menopause (40 years), whether due to premature ovarian failure or surgery, was related to decreased verbal fluency and visual memory in later years, regardless of treatment with menopausal hormone therapy (MHT) [26]. In addition, a longitudinal study examining the role of estrogen on cognitive functioning [27] found that MHT and certain estrogen-related reproductive events were related to several aspects of improved cognitive functioning, but did not impact dementia risk, either positively or negatively. An extremely large population-based study of Chinese women found that earlier age at menopause was associated with decreased cognitive function, while use of oral contraceptives and treatment with MHT lowered the risk of cognitive impairment in older women [28]. A cross-sectional study of symptomatic midlife Japanese women observed a wide component of psychological issues which may be related to menopausal symptoms, specifically vasomotor symptoms [29]. However, a longitudinal population-based study of rural Taiwanese women found that while transitioning into menopause may be related to verbal fluency, it does not appear to be significantly related to decreased cognitive function. As described above, data from several studies found that earlier age at menopause was implicated in changes in cognitive function, while a later menopause predicted better cognitive function [30]. Data from a very large multicenter, cross-sectional study showed that women from the Caribbean and Latin America have an earlier median age at menopause than women in higher income countries, where there is a lower risk of impaired cognitive processes [5]. A higher median age at menopause is associated with

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Table 1 Age at menopause in selected countries Country

Age at menopause (years)

Australia

50.4

USA

51.3

France

52.0

Sweden

50.9

Russia

49.0

Turkey

47.8

United Arab Emirates

47.3

Japan

49.3

China

49.0

Philippines

48.0

Mexico

46.5

Ghana

48.0

South Africa

49.2

Nigeria

48.4

Data taken from Thomas et al. [31]

high-income countries (Table 1) [31]. Velez et al. described the poor cognitive function found in these Latin American women, but explained that, in addition to earlier age at FMP, this appeared to be associated with childhood disadvantages, which in turn may lead to earlier age at menopause, poor socioeconomic conditions, restricted access to healthcare, and scant secondary education [32]. The challenges of poor socioeconomic conditions and reduced access to education and healthcare described above also apply to midlife sub-Saharan African women [15].

3

Cultural Perspectives of Cognitive Change and Menopausal Symptoms A variety of studies have examined the effect of ethnicity and race in relation to menopausal symptoms and cognition, but suggest that there are multiple challenges associated with describing this experience between different races and cultures [33]. Data have shown that menopausal symptoms, particularly vasomotor symptoms, may be described differently, although these are widely present [34]. Understanding cultural difference is thus very important when assessing symptoms [35], and a biocultural approach where both biological and cultural factors and the way in which these

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affect midlife women should be taken into account when examining menopausal symptoms and related variables across ethnic groups. In addition, heterogeneity within these groups may vary so the methodology used in this type of research should be very carefully designed [36]. This type of research should also be well-controlled by paying attention to a wide range of confounding factors, including socioeconomic status, lifestyle, and level of education [33].

Staging of the Menopause Transition and the Assessment of Symptoms In order to understand the connection between menopausal stage and cognitive function, it is essential to be able to stage menopause accurately [37]. Bleeding patterns during menstruation appear to be the most valid criteria for determining menopausal stage, with levels of follicle-stimulating hormone (FSH) and estrogen used as supportive criteria [38]. The levels of these hormones change significantly during the menopause transition, with FSH levels rising and estrogen levels falling [39] (Fig. 2). An obstacle in assessing menopausal stages in both low- and middle-income countries is the lack of resources which prevents the use of blood assays to assess menopause. In order to develop criteria for staging reproductive changes in women, the Staging Reproductive Aging in Women+10 (STRAW +10) working group assessed the data from available cohort studies of midlife women. While they acknowledged that estradiol (E2) levels change across the various reproductive stages, the 350

80

300

70 60

250

50

200

40 150

30

100

FSH (IU/L)

estrogen (pmol/L)

4

20

50

10

0

0 -3b

-3a

-2

-1

1a, b

1c

2

Menopause Stage Fig. 2 Estradiol and FSH median levels by menopause stage in a cohort of South African women. The number of subjects per menopausal stage were as follows: 3b, n ¼ 164; 3a, n ¼ 31; 2, n ¼ 49; 1, n ¼ 74; 1a, 1b, n ¼ 38; 1c, n ¼ 116; 2, n ¼ 133. Estradiol levels are shown by the solid line and FSH levels by the hashed line. Adapted from Jaff et al. [15]

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consensus was that only FSH showed consistent measurements in the clinical setting. Thus, the measurement of FSH was recommended as the sole supportive criterion in assessing menopausal stage through self-reported bleeding patterns [38]. However, some studies clearly demonstrated that E2 concentrations, particularly before and after the FMP, might be used as a criterion to verify menopausal stage [40]. The working group agreed that, generally, an FSH serum blood level of >25 IU/L could define the late menopausal transition and that E2 levels will decline. In a study of sub-Saharan African women, it was decided to use both E2 and FSH levels as supportive criteria for self-reported bleeding patterns since they are the defining endocrine changes occurring across the menopause transition [15]. It was found that FSH levels increased gradually across the transition stages, while there was a consistent decrease in E2 levels, and that these changes in both biomarkers were similar to those found in a large longitudinal study that investigated these endocrine changes during reproductive aging [39, 40]. Anti-mu¨llerian hormone (AMH) has been shown to be the gold-standard hormone to asses ovarian aging, and the Food and Drug Administration (FDA) has recently approved a test for this biomarker which may help improve diagnoses of menopause, and assist in preventive care for cardiometabolic diseases and osteoporosis associated with the menopause transition [41]. However, this test is extremely costly, and it is unlikely that it will be widely available in low- and middle-income countries. Research has shown that the STRAW+10 guidelines (Table 2), which have been widely used in high-income countries, both in its earlier iteration [42] and a revised version, is a useful tool in staging menopause in low-income countries that rely on self-reported bleeding patterns. In such environments, it is both cost effective and easy to use, although its accuracy is improved when the interviewer questions are validated [38], and the terminology is simplified to ensure wider comprehension and report accuracy [9, 15]. The internationally validated Menopause Rating Scale, which measures symptom severity and prevalence and quality of life, is a reliable tool that has been translated into nine languages [43, 44]. This scale has been used to examine various aspects and effects of the menopause transition in several population groups in varying countries, including several sub-Saharan countries (e.g., Oman, Nigeria, and South Africa) where the description of the symptoms and their severity was found to be both reliable and valid [9, 45–47].

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Ethnic Differences in Cognition Changes During the Menopause Transition Data from a comprehensive examination of cross-sectional data from two national internet studies of racial and ethnic differences

Variable

Low

Antral follicle count

Symptoms

Descriptive characteristics

Low Low

FSH AMH Inhibin B

Endocrine:

3a

Low

Variable Low

Variable Regular Regular Subtle changes in to flow and regular length

Supportive criteria

Menstrual cycle

Principal criteria

Duration

Late

3b

Low

" Variable Low Low

Variable length persistent 7-day difference in length of consecutive cycles

Variable

Menopausal transition Early Perimenopause

2 +1c

Very Low

" Variable Low Low

2 years (1 + 1)

Late

+2

Very low

Stabilizes Very low Very low

Increasing symptoms of urogenital atrophy

3–6 years Remaining life span

Postmenopause Early

+1b

Vasomotor Vasomotor symptoms likely symptoms most likely

Low

" >25 IU/L Low Low

Interval of Amenorrhea of 60 days

1–3 years

Late

1 +1a

4

5

Terminology Reproductive Early Peak

Stage

FMP #

Menarche #

Table 2 The STRAW+10 criteria for staging reproductive aging in women. Adapted from Harlow et al. [38]

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in cognitive symptoms experienced by four major ethnic groups in the USA found significant differences in both the number of cognitive symptoms experienced by a group of perimenopausal midlife women and the severity of their symptoms. The study was comprised of 1054 midlife women, classified as Hispanic, Non-Hispanic (NH) Whites, NH African Americans, and NH Asians. It appeared that NH Asians had fewer and less severe cognitive symptoms than the other three groups and that Caucasian women were more likely to battle with more severe levels of cognitive symptoms [48]. Other research has shown that fluctuating hormone levels during the menopause transition are also related to ethnicity. In the large multiethnic SWAN cohort study, it was found that in Chinese and Japanese-American women there were differences in their cycles and hormone level patterns [49]. However, the data were crosssectional, these women were becoming menopausal more slowly than the other groups, and there were fewer participants in this group with premature menopause. Randolph et al. found that there were lower levels of serum estrogen and sex hormone binding globulin in Chinese women than the other racial/ethnic groups in the SWAN study, after controlling for body size [50]. In the large-scale longitudinal SWAN study, where associations of cognitive function with menopausal stage and symptoms were examined in groups of women of different races (Black, Hispanic, Chinese, Japanese, Caucasian), it was found that even when race and ethnicity were adjusted for, perimenopausal women were more likely to report loss of memory than those who were premenopausal [21]. However, the six-year follow-up was important in determining this relationship [16]. The longitudinal Penn Ovarian Study examined several aspects of reproductive aging in pre- to postmenopausal women and found that verbal memory was compromised and became worse during the menopause transition. They also noted that there was no association between race and menopause stage in worsening verbal memory performance, which was similar in both Caucasian and African American women [18]. However, in all four of the cognitive tasks set, African American women performed less well compared to Caucasian women. Cross-sectional data from two national internet surveys of multiethnic groups of midlife women found that there were ethnic differences in cognitive function. Perimenopausal white women had worse and more severe cognitive symptoms than the other groups, while Asian women had fewer and less severe cognitive symptoms [48]. These findings were also described in the SWAN study [51], and in a comprehensive review of the literature examining racial and ethnic differences in menopause-associated cognitive function [52].

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5.1 Cognition, Menopausal Symptoms, and Stage in Sub-Saharan African Women

A recent large population-based study of older rural South African adults found that cognitive function decreased with age in older adults, and this finding was comparable to other studies of aging in sub-Saharan Africans. The authors found that being female was a consistent risk for dementia, although even a small amount of education mitigated this risk [1]. However, reproductive aging was not measured in these women so it was not possible to determine whether these women manifest greater cognitive impairment as a result of the menopause transition. It appears that there is only one study of cognitive performance and its association with menopause stage and menopausal symptoms in sub-Saharan African women [9]. This study found that menopausal symptoms, specifically anxiety and vasomotor symptoms, were related to worse processing speed, while severe mood symptoms were related to poorer incidental recall. Menopausal stage was not found to be associated with any aspect of cognitive function. As in the above study, data from the USA showed that decreased cognitive function in the areas of processing speed and memory was associated with severe menopausal symptoms, but also related to perimenopausal stage [17, 18]. Menopausal mood including anxiety and depressive symptoms were related to cognitive function in a small observational study [53], but, in the large longitudinal SWAN study, decreased cognitive function was related to depressive mood symptoms and anxiety [17]. As far as the association between memory and menopausal stage is concerned, two of the largest longitudinal studies, SWAN and the Penn Ovarian Aging Study, found that verbal memory worsens in the perimenopause, but not in premenopause stage [16, 18]. In addition, the cross-sectional Rochester Investigation of Cognition and Memory study found that certain cognitive aspects may differ during the menopause transition where a subtle decrease in some cognitive processes including verbal learning and verbal memory were found [19]. Two reviews examined the literature on Alzheimer’s disease [50] and cognitive function [51] in older sub-Saharan African adults. The former study found that the greatest risk factors for Alzheimer’s disease in this population was female gender and advanced age [54], and the latter study showed that dementia was more prevalent in women but greater age was also associated with both dementia and cognitive dysfunction in both males and females. However, as described in several Western studies, women were at greater risk for both cognitive outcomes than men [55]. In spite of these findings, and although there are studies examining the effect of lifestyle, aging and cardiometabolic disease, and cognition in aging adults in sub-Saharan Africa, data on menopause and cognition in black sub-Saharan African women are lacking. The large population-based study of 5059 adults, Health and Aging in Africa: A longitudinal Study of an INDEPTH Community

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in South Africa (HAALSI), focuses on the relationship of cardiometabolic disease risk factors and cognitive processes. Although a wide range of measures including cognitive function, health measures, behavioral risk factors, and sociodemographic factors were examined in adults 40 years and older, menopause was not staged in the female participants. The initial data from this study is crosssectional but should provide a baseline for future longitudinal research. The study found that body mass index (BMI) was positively associated with cognitive processes, while age, diabetes, and current smoking were negatively associated [56]. In a separate study in the same population group, it was found that women were more likely to have lower cognitive scores than males, while no education was also associated with decreased cognitive function [1]. The analysis of menopause staging was not undertaken in either study. The Malawi Longitudinal Study of Families and Health investigated the demographics of cognitive health. Data from this longitudinal cohort study found that women have significantly poorer cognitive function than men and with a greater age gradient. Once again reproductive aging was not included in the outcomes measured [10]. A cross-sectional study of participants aged 50 years in Cameroon showed that women were more likely to have cognitive dysfunction than males and, similar to other sub-Saharan studies, found that greater age and lower educational levels were associated with cognitive impairment [57]. Menopause is associated with changes in body fat distribution and an increase in BMI [58]. Studies have also shown that higher BMI in midlife is associated with a greater risk of dementia in later life, while at older ages there is a protective effect of BMI on cognitive function [59]. However, the relationship between BMI and cognition in African populations is understudied, and in the investigations that have been undertaken, the results have been conflicting. In a large cross-sectional study of black urban midlife South African women, 68% were obese [15], although their BMI was not associated with cognitive performance [9]. Conversely, BMI was positively associated with cognition in another South African study [52]. Prospective studies are required to investigate the relationship between BMI and cognitive function in sub-Saharan African populations with a particular emphasis on chronological and reproductive aging.

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Cognition and HIV Research has shown that of the 35 million people who are infected with HIV globally, 52% live in sub-Saharan Africa and 57% of these are women [60]. As described earlier, 76% of postmenopausal women will be living in developing countries [3], and

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approximately 5 million women aged 50 will be found in subSaharan Africa. This means that a large group of HIV-infected women will be menopausal. The increased life spans of these women is due in part to the improved distribution of antiretroviral treatment (ART) [61]. In addition, both HIV-infection and the menopause transition have been associated with compromised cognitive function [62]. The relationship between HIV and cognitive function in African women has been examined in few studies, and menopausal status has generally not been dealt within these investigations. However, the association between HIV-infection, the menopause transition, and cognition has been widely examined in Western women [62]. A comprehensive review describing the association between HIV and menopause suggested that researchers and clinicians should be cognizant of the implications of the physiological and psychological symptoms that accompany the menopause transition, specifically bone fragility, cardiovascular related morbidities, and altered cognitive function, which may all be increased by HIV infection and its treatment [60]. In particular, it is known that when the virus is found in the tissues of the central nervous system, HIV-infected women may suffer from related neurological problems [63]. An in-depth review of HIV-positive women and cognitive function found that neuropsychological studies of HIV-positive women were fewer than those examining cognition in HIV-infected men [64]. In addition, some studies showed that neurocognitive dysfunction was greater among HIV-positive women than in those who were HIV-negative, and this was greater in women who were not on antiretroviral medication. Finally, both age and depression increased the risk of cognitive impairment. The Women’s Interagency HIV study (WHIS) is one of the largest cohort studies of neurophysiological effects in HIV-positive women examining the association of HIV infection with cognition plus other factors relating to cognition [62]. In this large crosssectional study of ethnically diverse women, in which two-thirds of the women were HIV-positive, it was found that HIV infection had a small effect on cognitive function, although HIV-positive women performed worse in both verbal memory and learning measures, processing speed and attention. The average age of the women in the study was 47 years, and the authors noted that verbal memory worsens during menopause transition, although assessment of menopausal stage was not included as a variable. A follow-up study found that a high level of perceived stress was associated with poorer verbal memory in these women [65]. When both menopausal stage and menopausal symptoms were included in a large cross-sectional study of the women in WIHS, the data showed that certain menopausal symptoms, vasomotor, depressive, and anxiety but not menopausal stage, were associated

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with decreased cognitive performance in both HIV-positive and HIV-negative women [65]. Worse verbal learning was related to anxiety only in HIV-positive women. In a study performed in South African women, who were HIV-positive and who had undergone a wide range of neuropsychological tests, with a 12-month follow-up, HIV infection was associated with poorer processing speed [66]. Although a wide range of demographic and clinical factors were captured in the study, menopausal stage and symptoms were not included. In a cross-sectional study of midlife South African women, menopausal symptoms were associated with poorer cognitive function while menopausal stage and HIV status were not [9].

7

Screening Tools for Assessing Cognition There has been an increased interest in the association that either menopausal stage or menopausal symptoms may have on certain cognitive functions. An extensive review of the literature on the screening tools used to determine this relationship showed that although a wide range of neuropsychological tests were used to determine how the menopause transition affected cognitive processes, the results from these tests were varied [67]. One of the challenges in assessing cognitive function in sub-Saharan African women is the paucity of screening tools that are suitable for participants where English is either a second language or not spoken. It has been suggested that low- and middleincome countries will probably face an increased burden of aging adults with dementia and cognitive decline in the future, since models project that at least 70% of 80 million people with dementia will live in those countries. However, there is a scarcity of appropriate cognitive assessment tools to evaluate cognition in these populations [68]. In addition, many of these adults have not had any formal education, and there is generally a low level of literacy [69] which may also compromise the cognitive measures. Dementia screening tests based on language are not appropriate in countries where there are language discrepancies, or there is a low rate of literacy [68]. A recent review suggests that translation errors and variances in administration methods as a result of language and culture differences found in these assessment tools predispose these measurements to bias and differential item functioning, affecting scores in multinational research studies [70]. The authors suggest that the ideal tool should be able to measure cognitive function with a minor influence from the wide range of cultural and ethnic differences at play in various study populations and explain that, while certain visual based language neural tests may be effective in removing these biases, they need to be internationally validated.

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The Oxford Cognitive Screen (OCS-Plus) is a domain-specific cognitive assessment that was specifically designed for adults with low-literacy in low- and middle-income countries and validated in a large cross-sectional sample of 1402 adults [68]. The authors found that the OCS-Plus was well-received among this population of low-income, low-education older adults in South Africa, who were familiar with electronic devices. Furthermore, since it avoids the challenges mentioned above and makes use of language and memory domain measures with minimal language content, the results indicated that both task compliance and validity were good, and improve the way in which cognitive performance in aging adults of varying education levels is understood [68]. The use of the nonverbal Symbol Digit Modalities Test (SDMT) to assess processing speed followed by a nonverbal incidental memory test was found to be valid in a cross-sectional study of midlife black urban African women, where both menopausal stage and symptoms were assessed [9]. This test was chosen because there are multiple languages spoken in South Africa, the participants had little formal education, and English was their second language. The SDMT has been shown to be useful in these settings because it is not associated with levels of education [71] and has previously been used to measure neurocognition in HIV-positive adults in South Africa [72]. The SDMT was also used to assess processing speed in the large longitudinal SWAN study [16, 17].

8

Treatments to Improve Cognitive Function Since the menopausal transition is associated with decreasing levels of estrogen [73] and decreased cognitive function in midlife women [8, 74], the question arises as to whether MHT may be effective in improving cognition in this group of women. The data on the efficacy of this is mixed. Data have suggested that the menopausal transition may be a critical window for increased risk for depressive symptoms and impaired cognitive function [74]. Therefore, clinicians and researchers have suggested that this might be an important timeframe to initiate preventative strategies or MHT [75]. In fact, data from the SWAN study showed that MHT given before the FMP may benefit cognitive function, while processing speed and verbal memory were not improved when used postmenopause [17]. This is supported by data which showed that when women aged 65 or older took MHT (estrogen alone (O) or estrogen plus progestogen (O + P)), it did not prevent increased cognitive impairment [76]. These data, from the Women’s Health Initiative Memory Study (WHIMS), the biggest randomized control trial to assess the efficacy of continuous MHT (O or O + P) on the cognitive function of older women, showed that estrogen was not protective

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of cognitive function in postmenopausal women. Results from the study showed that after 5 years there was a significantly greater risk of possible all-cause dementia in women with natural menopause in the treatment group (approximately 72 years old), but no difference among the groups as far as mild cognitive decreases were concerned. In addition, those women who had taken conjugated equine estrogen with medroxyprogesterone acetate for four years were at greater risk for cognitive decline, compared to the placebo group. However, a reanalysis showed that those participants who were taking estrogen before the age of 65 when they enrolled in the WHI, had a 50% smaller chance of developing all-cause dementia than those women who did not use it. These findings suggest that MHT may play a neuroprotective role when taken by younger menopausal women, but not when taken postmenopause [77]. Two other studies hoped to find some beneficial effects from MHT: the Kronos Early Estrogen Prevention Study (KEEPS) [78] and the ELITE [79]. The KEEPS study randomized participants to two different MHT formulations (oral conjugated equine estrogen at 0.45 mg/day or transdermal 17b-oestradiol at 50 mg/day) and found that, while there were no adverse results of either treatment on cognitive function, there was also no significant positive effect [78]. The KEEPS participants will continue to be studied with follow-up assessments of their cognitive function and the final results are due in 2023. Hopefully by then researchers will have a clearer concept of the long-term effect of MHT on healthy aging and cognitive function in older women. In the ELITE trial, women were randomized to a placebo group, oral estradiol, or oral estradiol plus vaginal progesterone if they still had a uterus [79]. They were also randomized into two groups: early menopause (within 6 months of menopause) and late menopause (10 years or more after menopause). The results showed that both treatments had no effect on a range of cognitive functions, including verbal memory and processing speed, and there was no adverse or beneficial effect from the estrogen despite the time since FMP. The North American Menopause Society has specific recommendations about the use of MHT and its effects, beneficial or detrimental on cognitive function. Generally, MHT is not recommended to stop or treat either dementia or cognitive processes, although it is the first-line treatment for vasomotor symptoms. However, it appears that there may be some benefit for future cognitive function, if MHT is prescribed immediately after an early surgical menopause, and they suggest that the beneficial effects of estrogen depends on the level of cognitive function at baseline [80]. Other research suggests that younger menopausal women who take MHT for a shorter time to alleviate symptoms are not at increased risk for Alzheimer’s disease [81]. However, recent data from 2147 women in a large populationbased study, the Cache County Study on Memory in Aging

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(CCSMA), examined the accumulation of estrogen exposure throughout the women’s lifetime and its association with decreased cognitive function and found that the greater the length of time that a woman was exposed to endogenous estrogen, the better her cognitive function in later life [24]. Since estrogen is thought to be neuroprotective, this finding was not unexpected [82]. The authors of the Cache County study also found that extended use of MHT enhanced this effect, and furthermore, when MHT was started earlier in menopause, cognitive function was better than in those women who had begun taking it later, which supports the critical window hypothesis mentioned earlier [24]. There is a paucity of data about the use of MHT in sub-Saharan African women, which might reflect the resource limited healthcare systems or inadequate knowledge about the menopause per se and the associated health-related issues, including menopausal symptoms [83]. In a large descriptive cross-sectional study of menopausal women in Benin City, Nigeria, the authors found that only 7.3% knew about MHT, and not a single participant was taking it or had ever taken it [84]. Several factors that are protective of cognitive function as well as factors that increase the risk of cognitive decline have been identified [85], and a number of these are related to lifestyle choices. A study of Sri Lankan adults, of whom nearly 66% were women, showed that exercise in general, social interaction with family members, educational status, and solitary leisure activities such as reading, watching television, listening to the radio, and exercising, were positively associated with cognitive function. Interestingly no significant difference was found in cognitive function between men and women [86]. The large population-based study, Cognitive Function and Aging Study Wales (CFAS-Wales), measured cognition (function and reserve) in 2315 adults over 65 years of age and found that cognitive reserve, as potentiated by lifestyle factors, appears to facilitate both improved cognitive function in later life and conserving cognitive health [87]. Although the data were cross-sectional, certain modifiable lifestyle factors including social, cognitive, and physical activities, moderate alcohol use, and a healthy diet appeared to improve cognitive function in aging adults. Data from the Malawi Longitudinal Study of Families and Health suggested that cognitive function decreases with age in both men and women, although this was worse in women with lower education, and that quality of life in individuals with poorer cognitive function was significantly lower than adults with better cognitive health and abilities [10]. As noted in the CFAS study, a rich social life, close relationships, and involvement in community activities predicated better cognitive function. The latter also related to those living in higher income households and those with better physical health.

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Conclusions Life-expectancy is increasing in low-income countries, and since aging adults can expect to experience cognitive decline, there is an urgent need for cognitive function to be assessed, and gaps in our knowledge to be addressed. This should be carried out in conjunction with the ability of public health programs to diagnose and treat cognitive dysfunction. At present, there are several large longitudinal studies which are assessing cognition in aging sub-Saharan adults but there are still significant gaps in the research. Specifically, a large number of aging women will be living in sub-Saharan Africa by the late 2020s, and since it has been clearly demonstrated that decreases in cognitive function have been associated with the menopause transition, there is an urgent need for better research examining this association. Such studies should make use of tools to assess both menopausal stage and symptoms, as well as culturally appropriate and validated neurocognitive measures to better understand the implication of reproductive aging on cognition. In addition, longitudinal population-based studies are required to assess the effect of lifestyle interventions on cognitive health in sub-Saharan African populations with an emphasis on women as they transition through the menopause. The use of MHT with regard the timing of its initiation relative to the FMP and its effects on cognition and cardiometabolic health also needs to be assessed in this population.

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Chapter 6 The Effects of Exercise on Lipid Biomarkers Michael Vaughn F. Mendoza, Sergey M. Kachur, and Carl J. Lavie Abstract The World Health Organization has declared obesity to be a global epidemic that increases cardiovascular disease (CVD) mortality risk factors, such as hypertension, diabetes, dyslipidemia, and atherosclerosis. The increasing ratio of time spent in sedentary activities to that spent performing physically demanding tasks increases the trends to obesity and susceptibility to these risk factors. Dyslipidemia is the foundation of atherosclerotic buildup and lipoproteins serve as cofactors to the inflammatory processes that destabilize plaques. Increasing cardiorespiratory fitness and muscular strength helps attenuate concentrations of low-density lipoproteins (LDLs), such as LDL cholesterol, and increase levels of high-density lipoprotein cholesterol, as well as reduce proprotein convertase subtilisin kexin type 9 expression. Effects of physical activity on the inflammatory pathways of atherosclerosis, specifically C-reactive protein, are more closely related to reducing the levels of adiposity in tandem with increasing fitness, than with exercise training alone. The purpose of this review is to describe the physiology of dyslipidemia and relate it to CVD and exercise therapies. Keywords Dyslipidemia, C-reactive protein, Cardiovascular diseases, Exercise therapy

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Introduction Dyslipidemia (DLD) is the abnormal accumulation of lipids or lipoprotein in the blood, and it has been strongly associated with the development of coronary heart disease (CHD), the leading cause of death in the USA [1]. Remarkably, about one-third of the US population suffers from DLD according to the 2017 update of Heart Disease and Stroke Statistics [2]. The pathophysiology by which deranged lipid levels can induce cardiovascular diseases (CVDs) involves the interaction of atherosclerosis with inflammatory mechanisms, wherein lipid biomarkers play a significant role. Lifestyle modification is one of the leading prevention strategies in reducing CVD-related mortality through the modification of risk factors such as DLD. A sedentary lifestyle is becoming increasingly common as our global economy transitions to

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full-automation, and obesity epidemics are already present in numerous first-world nations, including the USA and China. Thus, the promotion of healthy lifestyle habits is paramount in reducing premature mortality risks. The combination of high levels of physical activity (PA) and diet modification has been shown to reduce CVD mortality by as much as 20–30% [1, 3]. In fact, numerous health organizations, such as the American College of Sports Medicine (ACSM), American Heart Association (AHA), and the 2018 Federal Physical Activity Guidelines (PAGs), recommend increasing PA, exercise training (ET), and cardiorespiratory fitness (CRF) for the prevention of CVD [4, 5]. In this chapter, we will focus on PA, ET, and CRF and their distinct effects on lipid biomarkers and, ultimately, CVD outcomes. Before moving forward, it is important to define the simple distinctions between PA, ET, and CRF, since these are frequently interchanged when talking about levels of activity. PA encompasses any bodily movements that result in the utilization of energy expenditure. ET is a structuralized and repetitive use of PA, such as in cardiac rehabilitation, with an end goal of increasing or maintaining CRF [6]. CRF is a measure of assessing PA and efficacy of ET. Means of assessing CRF vary from standardized cutoffs for tolerated PA, such as metabolic equivalents (METs), to evaluation of metabolism, such as maximal oxygen consumption (VO2). This review will encompass four major topics regarding the effects of exercise on lipid biomarkers, and ultimately CVD outcomes: (1) impact of lipid biomarkers on CVD and mortality; (2) impact of ET on CVD and mortality; (3) impact of exercise on lipid biomarkers; and (4) current ET guidelines.

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Impact of Lipid Biomarkers on CVD and Mortality Lipid biomarkers in DLD are measurable laboratory entities that have clinical significance in the development of CVD. The two groups of biomarkers for DLD include lipid profiles and inflammatory markers. The lipid profile is composed of two major components: lipids such as fatty acids (FAs) and triglycerides (TGs) and lipoproteins, such as low-density-lipoprotein cholesterol (LDL-C), high-density-lipoprotein cholesterol (HDL-C), very-low-densitylipoprotein cholesterol (VLDL), and lipoprotein-a (Lpa). Many studies have concluded that low levels of HDL-C and high levels of total cholesterol (TC) and/or LDL-C, as well as Lpa, increase the risk of developing CVD [7, 8]. In a 30-year follow-up from the Framingham Study, the risk of all-cause mortality and CVD-related deaths under the age of 50 increases by 5% and 9%, respectively, for every 10 mg/dL increase in cholesterol. Conversely, low levels of cholesterol prior to the age of 50 are most associated with improved longevity

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[9]. This occurs because circulating apolipoprotein B-100 (apo-B)containing lipids and lipoproteins measuring less than 70 nm in diameter traverse the arterial endothelium where they are retained and incite a maladaptive inflammatory process. This leads to formation of an atheroma, which, when combined with inflammatory processes, is prone to rupture, thereby causing acute thrombosis and subsequent ischemia and infarction in the distal vascular bed. Additionally, the deleterious effects of DLD are determined by both the concentration of circulating apo-B-containing lipids and the total duration of an individual’s exposure to them [10]. Thus, early screening and lifestyle modification are essential aspects in the primary and secondary prevention of CVD. The second major process seen in atherosclerosis is inflammation. This process can be measured by different inflammatory biomarkers such as myeloperoxidase, lipoprotein-associated phospholipase A2, pentraxin-3, interleukin-6 (IL-6), matrix metalloproteinase-9, and high-sensitivity C-reactive protein (hs-CRP). The latter is the most reliable due to its chemical stability and its lack of diurnal variation, and it is the most widely available laboratory test among them. hs-CRP is not only a useful biomarker for CVD risk stratification as numerous studies have described CRP levels as a significant co-target for CVD prevention in addition to lipid levels. The PROVE IT TIMI-22 investigators found that reductions in CRP levels ( 12 weeks). The protocol that elicited changes in body fat in this study was, on average: 1. Intensity: 60 to 90% of HRmax. 2. Volume: 2–3 h per week/35 to 40 min per day. 3. Frequency: 3–4 days per week. In 2017, Wewege et al. [15] performed a meta-analysis aiming to assess the effects of MICT and HIIT on body composition. In this part, we describe only the MICT effects. They found that MICT resulted in a loss of, on average, 2.1 kg of total body fat mass. Collectively, the MICT protocol of the included studies was:

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_ 2 max : 1. Intensity: 60 to 75% of HRmax or 50 to 60% of VO 2. Volume: 42 min per day. 3. Frequency: 3–4 days per week. In addition, in a sub-analysis, the authors found that running was superior to cycling to improve body composition, especially total body fat. Two particular studies of the meta-analysis deserve a spotlight in their protocols. In the first one, Kemmler et al. [16] performed a crossover randomized controlled clinical trial in 81 healthy untrained middle-aged males (~43 years-old), in which individuals showed an average decrease of 9.5% body fat mass, analyzed by bioimpedance. The MICT protocol was: 1. Intensity: 70 to 82.5% of the HR relative anaerobic threshold. 2. Mode of training: Running. 3. Volume: Progressively increased during the protocol, ranging from 35 to 90 min per session. 4. Frequency: Began with two sessions and rose up to four sessions until the end. 5. Length: 16 weeks. In another study from this meta-analysis, Shepherd et al. [17] performed a randomized controlled clinical trial, in which they prescribed 10 weeks of MICT using cycling as the exercise mode. The improvement of body composition with this protocol was 1.0 kg total body fat reduction and 1.0% relative body fat mass. The MICT protocol used was: _ 2 max . 1. Intensity: 70% of HRmax or ~65% VO 2. Mode of training: Cycling. 3. Volume: Progressively increased during the protocol, ranging from 30 (1 weeks) to 45 (10ª week) min per session. 4. Frequency: 3 supervised sessions and 2 unsupervised sessions. 5. Length: 10 weeks. Our group also investigated the effects of HIIT protocols in participants with obesity [18]. We found that when 10  1 min _ 2peak) protocol for 6 weeks, 3 times for week was HIIT (at 100% VO compared with MICT protocol (with same energy expenditure), the results were similar for physiological parameters, except we found no changes in body fat after either training modality. Bringing all of the information together, it seems that when MICT is prescribed using running instead of cycling, the results upon body composition are better. Furthermore, the ideal MICT protocol in order to elicit body composition changes should:

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1. Have more than 30 min of duration and, perhaps, progressively increase during the protocol. 2. Be prescribed with the intensity in between 60 and 75% of _ 2 max : HRmax or the corresponding VO 3. Be longer than 10 weeks. It is worth mentioning one of the disadvantages of MICT. In most of the studies included in the Wewege et al. [15] metaanalysis, the dropout rate of MICT was higher than HIIT. This could be explained by the greater time commitment intrinsic in MICT protocols that are generally longer than other protocols, such as HIIT (MICT ¼ 158 min/week; HIIT ¼ 95 min/week). It is also possible that completing MICT training sessions repeatedly over time in an exercise trial leads to boredom as the sessions are the same throughout [19]. On the other hand, one of the advantages of MICT protocols is that they are easy to learn and can be performed almost without costs. Studies regarding HIIT effects on human health started to grow exponentially in 2013, and an increasing number of such studies continue to be published. Therefore, there is now evidence suggesting that HIIT is a safe protocol that could be prescribed for several clinical populations, including individuals who were overweight or obese, elderly, or had T2DM or cardiovascular diseases. A recent meta-analysis [20] summarized the HIIT effects of body composition in adults. The authors showed that HIIT was able to reduce approximately 2 kg of total body fat within 12 weeks. On average, the protocols used in the studies were consisted of: 1. Mode of training: Cycling (60%) and running (40%). 2. Intensity: >90% of HRmax. 3. Number of sets: 4 sets was the most common. 4. Bouts duration: 4 min at high-intensity was widely used. 5. Recovery between bouts: 3 min was the most common (generally performed actively). 6. Frequency: 3 sessions per week (ranging from 2 to 5). 7. Length: 12 weeks (ranging from 4 weeks to 6 months). Again, we discuss three particular studies from the metaanalysis that deserve a highlight in their protocols. The first one is the study conducted Nikseresht et al. [21], in which the obese individuals who participated in the HIIT group lost 3.1 kg of fat mass, on average. The protocol used was: 1. Mode of training: Running. 2. Intensity: 80 to 90% of HRmax. 3. Number of sets: 4.

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4. Bouts duration: 4 min. 5. Recovery between bouts: 3 min at 55 to 65% of HRmax. 6. Frequency: 3 sessions per week. 7. Length: 12 weeks. The second one was performed by Zhang et al. [22] and included young female participants who were overweight or obese. The authors used cycling as the exercise mode and found that the HIIT group decreased body fat by 2.5% after 12 weeks. The protocol used was: 1. Mode of training: Cycling. _ 2 max : 2. Intensity: 90% of VO 3. Number of sets: until 300 kJ. 4. Bouts duration: 4 min. 5. Recovery between bouts: 3 min passively. 6. Frequency: 3 sessions per week. 7. Length: 12 weeks. Another way to subjectively quantify the intensity of exercise is using the well-known 6–20 point rated perceived exertion (RPE) scale (or Borg scale). After familiarizing the participants with the scale, RPE can be used to prescribe exercise intensity. For example, an RPE of 9–13 is considered between “very light” to “somewhat hard” and an RPE of 16–17 is considered “very hard” intensity. This method was used by Hallsworth et al. [23] to prescribe the intensity of HIIT in obese adults diagnosed with fatty liver disease. The authors found that the HIIT group lost 1.8 kg of body fat mass. The protocol used was: 1. Mode of training: Cycling. 2. Intensity: RPE of 16 to 17. 3. Number of sets: 5. 4. Bouts duration: Started with 2 min with 10 s added per week. The final duration 3:50 min. 5. Recovery between bouts: 3 min. 6. Frequency: 3 sessions per week. 7. Length: 12 weeks. Therefore, we can conclude that HIIT is indeed able to improve body composition, especially using running as the mode of exercise. It seems that for people who are overweight or obese, bouts lasting 4 min at intensity approaching or higher than 90% of _ 2 max equivalent) has significant effects on fat mass HRmax (or VO parameters. However, one of disadvantages is that HIIT protocols generally require supervision and are performed on a treadmill or

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cycle ergometer. The execution of HIIT training outdoors using running or cycling may make it more difficult to reach the prescribed intensity for the proper duration. However, several recent studies have demonstrated that home-based HIIT [24] and interval-walking HIIT [25–27] are potentially viable options with health benefits for individuals with prediabetes, T2DM, and for older adults. There is currently a debate on the literature on whether HIIT protocols may elicit a superior effect of fat mass loss when compared with MICT protocols. In this line, several meta-analyses have been performed with most showing no superior effects of HIIT compared to MICT. Wewege et al. [15] analyzed 11 studies that compared MICT and HIIT regarding fat mass loss, and they found no statistical differences between them. Another meta-analysis conducted by Keating et al. [28] aimed to compare MICT with HIIT and sprint interval training (SIT; a kind of low-volume high-intensity training usually prescribed in “all-out” manner; >100% of power at VO2max) on . This meta-analysis included 31 studies of which 17 used an HIIT protocol and 14 employed SIT protocols. The authors found no differences between protocols, although a tendency favoring MICT occurred when the workload of this training was higher. In other words, both protocols resulted in the same improvement of body composition, especially when the workload was similar. 2.2 Insulin Resistance and Sensitivity

In general, insulin resistance can be defined as a state of decreased responsiveness of target tissues (e.g., liver, adipose tissue, skeletal muscle) to normal circulating levels of insulin, playing a primary role in the development of T2DM. According to the International Diabetes Federation, T2DM currently affects more than a four billion people worldwide and has annual worldwide healthcare costs exceeding half a trillion US dollars [29]. It is estimated that in 2045 more than six billion of people will have T2DM worldwide [29]. These numbers are staggering and threaten to bankrupt healthcare systems around the world. Therefore, strategies that prevent, treat, or at least attenuate this condition are crucial. Exercise training, alongside nutrition and pharmacological interventions, is recognized as one of the cornerstones in the treatment of T2DM [5]. In fact, the guidelines for T2DM comprise exercise as therapy [30]. In this section, we will describe the effects of aerobic training (MICT and HIIT) on markers of insulin resistance and sensitivity of people living with T2DM. The underlying mechanisms by which exercise training is thought to improve insulin resistance is well discussed elsewhere [31] and, therefore, will be not addressed here. Before going further into the protocols of exercise training, it is important to know how insulin resistance and its reciprocal insulin sensitivity, as well as glucose control, are measured in humans.

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There are several ways to assess these parameters, each with pros and cons. Glucose control could be an indirect measure of insulin sensitivity because an improvement in glucose levels, or reduced glycosylated hemoglobin (HbA1C), is associated with better insulin signaling in several tissues, culminating in glucose uptake. Several of the most frequently used measures of glucose control and insulin resistance/sensitivity are depicted in Table 2.

Table 2 Methods used to measure insulin resistance/sensitivity and glucose control in humans Method

Description

Glycosylated hemoglobin (HbA1C%)

Glucose molecules nonenzymatically bind to hemoglobin molecules, thus higher levels of glucose found in patients with diabetes induce the increase in HbA1C% in blood. Due to the life span of red blood cells, the glycosylated hemoglobin measure provides an estimate of chronic (2–3 months) glucose control Classification: Normal 42 mmol/mol or below 6%; prediabetes 42 to 47 mmol/ mol or between 6% and 6.4%, and diabetes 48 mmol/mol or over or 6.5% or over

Fasting glucose (mg/dL or mmol/L)

It is an acute measure of glucose in blood assessed after an overnight (typically >8 h) fast. Classification: Normal less than 100 mg/dL; prediabetes between 100 and 125 mg/ dL, and diabetes 126 mg/dL or higher. The improvement of fasting glucose could be a measure of better insulin sensitivity within organs, such as liver, adipose tissue, and skeletal muscle

Homeostatic model assessment of insulin resistance (HOMA-IR)

It is a general noninvasive method to estimate insulin resistance based on fasting blood sample. HOMA-IR is determined by equation: (fasting plasma insulin X fasting plasma glucose)/ 22.5. Insulin (mU/L) and glucose (mmol/L)

OGTT-derived measures (e.g., Matsuda Assessed based on relationship between blood glucose and index, OGIS, Cedarholm) insulin levels following an oral glucose (typically 75 g) or meal tolerance test. Norms have been established for different indices but there are no universal cutoff points or diagnostic thresholds Hyperinsulinemic-euglycemic clamp

Insulin is infused at a constant high rate, which inhibits liver glucose production and signals tissues (primarily skeletal muscle) to take up glucose from the blood (i.e., hyperinsulinemic). Glucose is infused at a variable rate to maintain basal/fasting glucose concentrations (i.e., euglycemic). The rate of glucose infusion is directly proportional to (peripheral tissue) insulin sensitivity. There are no universal cutoff points or diagnostic thresholds but individuals with type 2 diabetes have the lowest values compared to individuals with obesity, followed by lean participants

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Although the focus of this topic is individuals with T2DM, it should be mentioned that for individuals who are not obese or do not have T2DM, aerobic training can also improve insulin sensitivity [32–34]. In this case, training volume might be the most important variable to add this benefit [32–34]. Regarding patients with T2DM, there are many meta-analyses, both historical and recent ones, showing that classical aerobic training is a safe and efficacious strategy to improve insulin resistance and glycemic control [35–41]. However, in T2DM individuals, the evidence suggests that intensity might play a crucial role in improving insulin sensitivity in MICT interventions. Boule´ et al. [41] performed the first meta-analysis to show this outcome. This consisted of seven studies, with data for nine randomized trials, comparing exercise and control groups. They found that MICT programs especially _ 2 max ) prescribed at the high-intensity zone (e.g., 70 to 75% of VO optimized the reductions in HbA1C. As described by the previous study and others [38], one of the protocols that optimized insulin sensitivity was applied by Mourier et al. [42], in which they found an improvement of 21% in insulin sensitivity, a decrease up to 2.6 in HbA1C% and 20% in fasting insulin levels. The protocol employed was: _ 2peak _ 2peak (twice a week) and 85% of VO 1. Intensity: 75% of VO (once a week). 2. Mode of training: Cycling. 3. Volume: 45 min per session. 4. Frequency: 3 sessions per week. 5. Length: 8 weeks. Consistent with the importance of intensity in the MICT protocol in subjects with T2DM, Hansen et al. [43] randomized the sample into either low-intensity or high-intensity continuous training for 6 months. The high-intensity group displayed the greater improvement in whole-body insulin sensitivity and glycemic control. The protocol used in the high-intensity MICT was: _ 2peak . 1. Intensity: 75% of VO 2. Mode of training: Walking, cycling, and cross-country ski-type. 3. Volume: 40 min per session. 4. Frequency: 3 sessions per week. 5. Length: 6 months. In another study with patients with T2DM, Choi et al. [44] randomized 75 individuals into either control or exercise group. Exercised group improved several markers of insulin resistance and glucose control, such as HbA1C%, the homeostatic model of

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insulin resistance (HOMA-IR), and fasting glucose. Different from the aforementioned study, this one used a simply MICT protocol: 1. Intensity: Moderate, assessed by accelerometer. 2. Mode of training: Walking. 3. Volume: 60 min per session. 4. Frequency: 5 sessions per week. 5. Length: 12 weeks. Therefore, although high-intensity MICT evokes potentially better adaptations on glucose homeostasis in T2DM subjects, moderate-intensity training adds benefits as well. In terms of HIIT protocols, it is known that even extremely short duration programs improve insulin action in healthy and insulin-resistance subjects [45–47]. In T2DM patients, some meta-analyses concluded that HIIT protocols are efficient to improve HbA1C and insulin levels [47–49]. The most common protocol used in the articles included in the referred meta-analyses was: 1. Mode of training: Cycling followed by running. _ 2 max equivalent). 2. Intensity: 85 to 95% of HRmax (or VO 3. Number of sets: 4. 4. Bouts duration: 4 min. 5. Recovery between bouts: 3 min. 6. Frequency: 3 sessions per week. 7. Length: > 10 weeks. Therefore, we can argue that protocols which evoke an improvement in insulin sensitivity and/or glucose control are similar with the protocols used to treat obesity. In this point of view, since obesity and its outcomes (e.g., ectopic fat accumulation) are one of the main causes of insulin resistance, high-volume HIIT (e.g., 4 min effort at >90% maximum) can be used to treat both conditions and potentially prevent the onset of insulin resistance. However, it is still not entirely clear if HIIT is superior to MICT to improve insulin sensitivity. In order to address this question, we describe the results found by Jelleyman et al. [47] and Liu et al. [48], who performed metaanalyses aiming to compare the effects of HIIT and MICT on insulin resistance. These studies included 36 controlled trials, pooling more than 2000 people who were either healthy, had T2DM or were overweight/obese, of which 1383 performed an HIIT intervention. The authors found that compared with MICT intervention, HIIT had a small but superior effect on insulin resistance, meaning that HIIT optimized insulin sensitivity. Regarding glucose homeostasis, they found no differences between the protocols on fasting glucose and HbA1C levels. However, Liu et al. [48] found

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some divergent results. In this meta-analysis, the authors included 345 subjects with T2DM of which 163 underwent HIIT intervention. Within this population, HIIT had a superior effect when compared with MICT only in HbA1C levels, whereas fasting glucose, fasting insulin, and HOMA-IR were similar across the interventions. Taken together, it seems that HIIT may be superior to improve glucose control, either by improving insulin resistance markers or lowering HbA1C levels, when compared with MICT protocols in clinical populations, such as those with T2DM. 2.3 Subclinical Inflammation

Subclinical inflammation, also referred as low-grade chronic inflammation, is characterized by increased levels of plasma cytokines, which contribute to insulin resistance and cardiometabolic diseases. Cytokines are glycoproteins produced by immune and nonimmune cells which regulate the communication between and within these cells and organs, in a paracrine, autocrine, and endocrine fashion. Table 3 summarizes the main inflammatory markers (cytokines and others) and their function within the body. In a holistic point of view, subclinical inflammation can be caused by the interaction of the immune system with the stromal fraction and cells of metabolic organs, such as those in the liver, brain, pancreas, and adipose tissue, which generally disrupts energy homeostasis and leads to metabolic and aging-related diseases. Therefore, counteracting subclinical inflammation has been reported to improve a subject’s overall health [3]. In this line, a body of evidence shows that physical training (e.g., MICT and HIIT) can modulate subclinical inflammation in a range of clinical populations, including those with cancer, heart failure, obese, and T2DM [50–52]. It should be mentioned that here we describe the long-term exercise training effects rather than acute ones on inflammatory markers. For example, the IL-6 response to acute exercise session is different from long-term changes. IL-6 is a well-known myokine released during acute exercise and has immune and metabolic effects in this context [53]. However, in long-term adaptations, especially in clinical populations, the goal has to be to diminish subclinical inflammation markers, including circulating IL-6 levels. Looking at long-term exercise adaptations, Pearson et al. [51] performed a meta-analysis with 14 independent trials showing that aerobic training lowered systemic cytokine levels, mainly those of tumor necrosis factor-alpha (TNF-α) and IL-6 from heart failure patients. Systemic levels of vascular health markers, such as fibrinogen, vCAM, and sICAM, were not lowered in the experimental groups. Similar findings regarding vascular health molecules markers were found by Ramos et al. [54]. In a meta-analysis including patients with T2DM, Hayashino et al. [52] found a positive effect of physical training, chiefly MICT,

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Table 3 Inflammatory and regulatory molecules associated with metabolic health Molecule

Abbreviation Function

Interleukin-6

IL-6

IL-6 is a phase acute protein. In clinical conditions, plasma IL-6 can be used to determinate the grade of inflammation. However, IL-6 is also released from muscle during exercise and may help regulate skeletal muscle metabolism

Tumor necrosis factor-alpha

TNF-α

TNF-α is a pro-inflammatory cytokine driven mainly by classical NFkB activation in immune cells and other tissues. It is typically found in higher levels in participants with obesity and T2D, believed to originate from adipose tissue and/or adipose tissue macrophages. The metabolic effects include direct induction of insulin resistance in adipose and other tissues

C-reactive protein CRP

CRP is a clinical marker of phase acute response produced in liver and higher in inflammatory and infectious condition. This is more commonly measured in clinical practice compared to cytokines and has a demonstrated role in CVD risk

Interleukin-1beta IL-1beta

IL-1beta is produced by activation of inflammasome and it is increased in inflammatory conditions

Adiponectin

Adiponectin

It is an antidiabetogenic adipokine (produced and released by adipose tissue). Adiponectin promotes anti-inflammatory response, inhibition on LPS response, and improvement of glucose homeostasis with increase on glucose uptake, and improvement on insulin sensitivity. Adiponectin levels tend to be reduced in obesity and T2D

Leptin

Leptin

Leptin is generally regarded as a pro-inflammatory adipokine that is involved in body weight regulation. The increase in leptin induces the anorexigenic response, but in metabolic disorders the effects of leptin are reduced by increase in resistance of action of this hormone. Higher levels of circulating leptin appear to promote a pro-inflammatory response

on systemic levels of C-reactive protein (CRP) and IL-6. Interestingly, the authors were able to establish that the length of the protocol, session volume, and weekly frequency were inversely associated with the reduction of IL-6 levels. In other words, it appeared that the greater the volume of exercise training, the greater the reduction in inflammatory markers. MICT may also lower circulating inflammatory markers in healthy individuals. One example of this is the recent meta-analysis performed by Zheng et al. [55] in which they analyzed 1250 participants from 11 randomized controlled trials. Circulating levels of CRP, TNF-α, and IL-6 were reduced following MICT interventions. However, the heterogeneity of meta-analyses was far above than recommended in this kind of analysis (>90%), meaning

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that there was a divergence among the protocols used by the studies. Regarding HIIT interventions, results on inflammatory markers are not as consistent as MICT results are. Khalafi and Symonds [56] performed a meta-analysis in which they compared the effects of HIIT interventions with control and MICT groups in a clinical population. The meta-analysis included 29 studies with 841 participants. The authors found that: (a) Compared with MICT, there were no differences between the interventions in inflammatory markers. (b) Compared to a control group, HIIT improved only TNF-α levels. (c) They also found an improvement in adiponectin (increased) and leptin (decreased) levels when HIIT was compared with the control group. There are also some meta-analyses which have concluded that neither HIIT nor MICT improved inflammatory markers [54, 57]. Taking a deep look into those studies, most aimed to analyze other primary outcome rather than inflammatory markers, perhaps adding a bias into the analysis. On the other hand, metaanalyses that aimed to assess the effects of physical training interventions on inflammatory markers as the primary outcome have generally concluded that IL-6, CRP, and TNF-α are positively modulated by physical training, especially an MICT one [51, 52, 55, 56, 58]. Therefore, it sounds plausible to argue that MICT, and to a lesser extent HIIT, can be prescribed to improve inflammatory markers in a range of populations. However, it is not clear which protocol leads to greater reductions in subclinical inflammation. In relation to MICT protocols, Tartibian et al. [59] performed a randomized controlled clinical trial aiming to describe the effects of long-term MICT on inflammatory markers, such as IL-6 and TNF-α, in postmenopausal women. The authors found a reduction of 25% and 15% in TNF-α and IL-6 levels, respectively, within 24 weeks of training intervention. The protocol used by the author was divided into two segments of 12 weeks. The segment was: 1. Intensity: 45 to 55% of HRmax. 2. Mode of training: Running/walk. 3. Volume: 25–30 min. 4. Frequency: 3–4 sessions. 5. Length: 12 weeks.

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The second segment was: 1. Intensity: 55 to 65% of HRmax. 2. Mode of training: Running/walk. 3. Volume: 40–45 min. 4. Frequency: 4–6 sessions. 5. Length: 12 weeks. In another study from the same group, Tartibian et al. [60] randomized 24 postmenopausal women into MICT and control groups for 16 weeks. The authors found reductions in the MICT group of 40, 41, and 33 in IL-6, IL-1β, and TNF-α, respectively. The protocol used by the authors was similar than the previous one: 1. Intensity: 45 to 55% of HRmax. 2. Mode of training: Running/walk. 3. Volume: 25–30 min. 4. Frequency: 3–4 sessions. 5. Length: 16 weeks. Taken together, these results showed that long- and mediumterm MICT interventions clinically improve inflammatory markers in this specific clinical population. As mentioned above, studies that used HIIT interventions tended to generate divergence results regarding subclinical inflammation [56]. One study found a robust effect of HIIT but did not use an experimental control group [61]. One found no effect on IL-6 levels [62], some found an increase [63, 64] while one found a decrease [65]. One found an increase on TNF-α levels [65] and another found a decrease [66], whereas others found no effect [62, 67, 68]. These findings are not surprising given that plasma cytokine levels tend to be highly variable between participants and the assays used, which increases the chances of type I error (false positive) in small sample size studies. In our latest study, we investigated the effects of 6 weeks of a _ 2peak) protocol in obese participants 10  1 min HIIT (at 100% VO and found that neither MICT nor HIIT led to improved subclinical inflammatory markers [18]. However, we showed that both training protocols were able to augment the ability of immune cells to secrete anti-inflammatory cytokines after the exercise bout [69]. Due to these confounders, we are not able to draw a conclusion regarding HIIT protocols to improve subclinical inflammation. However, as described in other topics, high-volume HIIT exerts better adaptations in several components and might be a strategy to improve subclinical inflammation. More studies are certainly needed to examine how HIIT impacts inflammatory markers, particularly in clinical populations.

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Therefore, as presented in this topic, MICT protocols appear to have an advantage when compared with HIIT to rescue subclinical inflammation. MICT protocols should be prescribed using: _ 2 max equivalent). 1. Intensity: 45 to 65% of HRmax (or VO 2. Mode of training: Running/walking. 3. Volume: 30–45 min. 4. Frequency: 3–4 sessions. 5. Length: >12 weeks.

3

3.1

Combined Training

Obesity

MICT and HIIT programs have been also used in a combination with resistance training, usually referred as combined or concurrent training. This kind of training promises to deliver the physiological adaptations of both kind of training concomitantly and enables meeting physical activity guidelines that recommend both aerobic and strengthening (resistance) training. Therefore, combined training may be an excellent strategy among clinical populations to achieve cardiorespiratory, musculoskeletal, and other adaptations. As aforementioned, overweight and obesity are defined as excessive fat accumulation that presents a risk to health. Therefore, in this topic, we describe the effects of different combined/concurrent training protocols on components of body composition related with obesity. We have accumulated significant data in the last decade regarding combined training effects upon body composition in clinical population, especially in menopausal women [70– 76]. Our research, and that of others, has shown that combined training indeed improves body composition, including fat-free mass, abdominal and total fat mass, and can therefore serve as a non-pharmacological strategy to decrease obesity per se and its comorbidities [71, 73, 75, 77–79]. The combined training protocol we used was 8 to 16 weeks of 27 min of strength exercise, including nine whole-body exercises with the load increased every 4 weeks, followed by 30 min of aerobic exercise prescribed at anaerobic threshold [75]. This combined training protocol is described in Table 4. This protocol was able to improve the body composition of menopausal women [73, 75]. These morphological changes are crucial for clinical populations, because they tend to deteriorate over time. Moreover, we tracked menopausal women for one year to evaluate whether or not the combined training effects upon body composition would last. We found that for total body, lower and upper limb fatness, the effects lasted up to one year [71, 74]. Although it is clear that combined training improves body composition, one question remained unanswered: is combined

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Table 4 Our combined training protocol Exercise order

Resistance training

Aerobic training

Intensity

65 to 80% of 1RM

Anaerobic threshold

Mode

Gym-based exercises

Walking

Volume

27 min

30 min

Frequency

Three times per week

Three times per week

training better than aerobic training to improve body composition? Some of the studies which compared combined training with aerobic training showed that the effects of combined training on body composition were similar or superior to aerobic training. However, the amount of exercise performed in combined training group is generally higher than in aerobic ones [77, 80–84]. This confounds the comparison between training modalities, which impairs our ability to understand which kind of exercise mode elicits better adaptations. In an effort to answer this question while reducing this confounding factor, we equalized the training load using a rating of perceived exertion and duration of the session for combined training and aerobic training for 16 weeks. We found that when the training load was similar, there were no differences between body fatness variables between combined training and aerobic training [75]. This was the first study to investigate differences between the two modes of exercise using such a practical approach and suggested that for equal training effort, combined training is not superior to aerobic training. Taken together, when combined training is performed with higher volume and/or load, the effects on body composition seem to be superior to aerobic training, although when the load performed by both kind of training is similar, the effects are generally similar. 3.2 Insulin Resistance and Sensitivity

Currently, there is a body of evidence showing the positive effects of exercise interventions on insulin sensitivity and glucose homeostasis, including combined training protocols [35, 38, 40, 85]. The methods used to evaluate insulin sensitivity and glucose homeostasis are depicted in Table 2 in the aerobic training topic. In a classical study, Balducci et al. [86] randomized 120 subjects to perform either control or combined training intervention for one year. The workers found robust changes in fasting glucose (36 mg/ dL) and percentage of HbA1C (1.21%) in the combined training intervention. The protocol used is depicted in Table 5.

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Table 5 Protocol used by Balducci et al. [85] for control or combined training over one year Exercise order

Aerobic training

Resistance training

Intensity

40–80% of HRR

40–60% of a 1RM

Mode

Stationary cycling and elliptical trainers

Gym-based exercises

Volume

30 min

30 min

Frequency

3 times per week

3 times per week

In the same line, Tessier et al. [87] found an improvement in glucose excursion during the oral glucose tolerance test (OGTT), a measurement of glucose uptake, after 16 weeks of combined training in elderly participants with T2DM. The protocol comprised 20 min of 60–79% HRmax and 20 min of two sets of 20 repetitions of major muscle groups in resistance training. Moreover, several meta-analyses aimed to evaluate combined training effects on insulin sensitivity and glucose homeostasis [35, 38, 40, 85]. Collectively, these meta-analyses support the idea that this kind of training can improve HbA1C levels, fasting glucose, and insulin sensitivity [35, 38, 40, 85]. However, there were relatively low numbers of studies in the individual meta-analyses with high heterogeneity, indicating that more studies are needed to confirm the beneficial effects of combined training. As discussed before, the knowledge of which kind of exercise training evokes better adaptations on insulin sensitivity and glucose homeostasis parameters is important to the health professionals to be able to prescribe the best practice based on evidence. Thus, the comparison between exercise modes is an important question with practical relevance. It is common to find in the literature, for example, studies that report superior effects of aerobic training when compared with combined training. Lucotti et al. [88] compared aerobic plus resistance training and aerobic training alone in participants with T2DM and obesity and found that both training programs caused similar improvements on the body weight, but aerobic training effects on HOMA-IR was superior than the combined training. Therefore, the authors recommended aerobic training as the best strategy to rescue insulin resistance in T2DM subjects. However, gain of lean body mass, rather associated with resistance training than aerobic training, would be hypothesized to be important for the maintenance of glucose homeostasis over the long term. Skeletal muscle is one of the major contributors to glucose uptake and storage and is therefore crucial in the treatment of patients with T2DM [89]. Since combined training comprises resistance training in the protocol, it seems logical that it would be important in the

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Table 6 Average protocols comparing aerobic, resistance, and the combination of both on glycemic control in type 1 and 2 diabetes Combined training Intensity

AT ¼ moderate (50–70% of HRmax) RT ¼ moderate to high (30–80% one of 1RM)

Volume

61 min per session (30 to 90 min)

Frequency

3.3 times per week (3 to 4 times)

Length

34 weeks (12 to 104 weeks)

AT aerobic training, RT resistance training

management of insulin resistance and glucose homeostasis. Corroborating with this idea, a recent systematic review performed by Ro¨hling et al. [90], comparing aerobic, resistance, and the combination of both forms of exercise on glycemic control in type 1 and type 2 diabetes, found that combined training (11 studies) may improve glycemic control to a greater extent than single forms of exercise, with a decrease of 8.5% in relative HbA1C. The general protocols are shown in Table 6. Most of the global diabetes associations, such as the American Diabetes Association (ADA), Diabetes Canada (DC), European Association for the Study of Diabetes (EASD), and German Diabetes Association (DDG), recommend the addition of resistance training in the exercise programs in order to improve glycemic control in T2DM [90–92]. Therefore, it seems reasonable that health professionals recommend this kind of exercise alongside aerobic ones to treat insulin resistance. However, it is important to note that resistance training studies generally involve supervised exercise in a gym or laboratory setting, making the translation of this type of exercise potentially challenging for individuals with obesity or T2D who may not have access to, or be comfortable with, an appropriate fitness facility. Aerobic training (e.g., walking, jogging, cycling) is generally more accessible for the majority of inactive individuals, and more research is needed to examine resistance training and combined training interventions that translate to the real world for patients. Overall, the recommendation of these associations for combined training interventions comprises supervised training sessions of moderate- to high-intensity aerobic exercise (50–85% HRmax or equivalent) and 30–80% one of 1RM for major muscles. In conclusion, combined training interventions should be recommended in order to achieve long-term results in glycemic control for people living with insulin resistance and/or T2DM.

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Regarding subclinical inflammation, the results from the studies are mostly conflicting. In breast cancer survivors, a recent systematic review conducted by Brazilian researchers found that none of the seven included studies showed reduced inflammatory markers after combined training intervention [93], suggesting that new highquality studies should be performed aiming to investigate subclinical inflammation among cancer survivors. However, in individuals with obese and T2DM, combined training interventions caused different adaptations regarding inflammatory markers [81, 94]. Jin et al. [81] randomized 20 obese subjects for aerobic or combined training for 8 weeks and found a statistically significant reduction in TNF-α only in combined training group. Annibalini et al. [94] observed that after 16 weeks of combined training (3 per week), there was reduction in the plasma concentrations of leptin (33.9%), retinol-binding protein 4 (21.3%), IL-6 (25.3%), TNF-α (19.8%), and monocyte chemoattractant protein-1 (MCP-1; 15.3%), parallel with modulation of IL-6 mRNA in the peripheral blood mononuclear cells. The combined training protocol used by Annibalini et al. [94] is shown in Table 7. An investigation by Parhampour et al. [95] compared aerobic, resistance, and combined training effects in overweight adults with moderate hemophilia A. They observed after 6 weeks that only combined training intervention (45-min exercise sessions performed 3 per week) was able to significantly decrease pro-inflammatory biomarkers, such as CRP, IL-6, and TNF-α, suggesting that aerobic plus resistance training is the most effective training mode for decreasing pro-inflammatory cytokines. Moreover, the authors found increased levels of the anti-inflammatory cytokine IL-10 in overweight patients who underwent combined training intervention. These findings highlight the idea that combined aerobic and resistance training can improve T2D-related metabolic abnormalities and has the potential to reduce the chronic low-grade inflammation associated with obesity and T2DM. Therefore, we can

Table 7 Combined training protocol used by Annibalini et al. [93] to assess inflammation Exercise order

Aerobic training

Resistance training

Intensity

Gradually increased from 40% to 65% of HRR

Gradually increased from 40% to 60% of a 1RM

Mode

Treadmill walking

Gym-based exercises

Volume

30 to 60 min per session

2 to 4 sets of 20 to 12 repetitions in 4 exercises

Frequency

2 to 3 sessions per week

2 to 3 sessions per week

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consider that combined training is likely to be an effective tool for improving subclinical inflammation. However, it should be noted that this training model is complex and requires a variety of equipment to be fully executed, and thus, it is a costly and potentially inaccessible for most people.

4

Conclusions In conclusion, exercise training is an excellent tool to reduce the risk of development of chronic diseases and may help conditions related to chronic inflammation (obesity, T2DM, auto-immune diseases, neurological disorders, cancer, cardiovascular diseases) in order to improve quality and quantity of life. This chapter was written with the intent to help the better choice of exercise training protocol for reduction of sedentary behavior in the general population and for individuals to reduce this behavior and consequently improve their health status, with safety and specificity. Exercise training as tool to improve health should be practiced with specific aims and an adequate mode, intensity, frequency, and volume to be safe and effective. Physical exercise should be considered as an effective and low-cost non-pharmacological therapy.

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Part II Protocols

Chapter 8 A Protocol of Intradialytic Exercise for Improvements in Inflammatory Status, Body Composition, and Functional Capacity Lorena Cristina Curado Lopes, Paula Alves Monteiro, and Joa˜o Felipe Mota Abstract Skeletal muscle wasting has been well-documented among hemodialysis patients. This catabolic condition can be induced by numerous factors, including low-grade inflammation, and is associated with impairments in functional capacity and quality of life, as well as an increased mortality risk. We previously showed that 12 weeks of intradialytic resistance training increases lean mass, functional capacity, and the quality of life of hemodialysis patients. This chapter provides the details of a protocol of intradialytic exercise that leads to improvements in inflammatory status, body composition, and functional capacity. Keywords Chronic kidney failure, Dialysis, Exercise, Resistance training, Cytokines, Physical performance, Quality of life

1

Introduction Patients with chronic kidney disease who are on maintenance hemodialysis treatment could experience reductions in muscle mass and strength, marked by muscle atrophy and increased amounts of noncontractile tissue [1]. This catabolic condition results in impairment of functional capacity, indirectly reducing their quality of life. Additionally, losses of muscle mass and physical strength have been recognized as independent predictors of poor clinical outcomes and mortality among patients on hemodialysis [2–4]. Low-grade inflammation is a hallmark feature of patients on hemodialysis. Their serum cytokine concentrations are significantly higher (up to 25-fold) relative to healthy individuals [5]. This inflammatory environment has been linked to the etiology of their loss of muscle mass and function [6]. Among chronic kidney

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_8, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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disease patients, there is an inverse association between muscular thigh area and their serum levels of C-reactive protein and IL-6 [6]. It has been well-established that inflammatory status is influenced by lifestyle factors such as physical activity levels. Thus, increases in physical exercise may improve the inflammatory status and increase the levels of anti-inflammatory cytokines such as interleukin 10 (IL-10) [7]. Furthermore, muscle hypertrophy induced by resistance training is associated with reductions in inflammation [8]. Likewise, Moraes et al. [9] showed that 6 months of resistance training decreased several inflammatory biomarkers in patients on hemodialysis treatment. Taking into account that inflammation and muscle loss are common predictors of adverse health outcomes in hemodialysis patients, resistance training is a potential strategy to reduce their inflammatory profile, which may attenuate or even reverse the muscle catabolism induced by the disease. The following chapter will outline a protocol of intradialytic resistance training that can lead to improvements in inflammatory status, body composition, quality of life, and functional capacity.

2

Materials

2.1 Anthropometric and Body Composition Assessments

1. Stadiometer accurate to 0.1 cm. 2. Body weight digital scale accurate to 0.1 kg, with a capacity of 150 kg. 3. Dual-energy X-ray absorptiometry (DXA) (GE© Lunar densitometer; DPX NTVR, with ENCORE 2011 software, version 13.60, GE Healthcare).

2.2 Dietary and Functional Assessment

1. Three food records performed by a registered dietitian. 2. Avanutri® software (https://www.avanutri.com.br/softwares). 3. Chair without an armrest. 4. Chronometer. 5. Hydraulic hand dynamometer (Crown®, Industrial Oswaldo Filizola LTDA, Sa˜o Paulo, Brazil).

2.3 Intradialytic Resistance Training and Quality of Life Assessment

1. Elastic bands color-coded to represent different tensile strengths (Thera-band®, Akron, USA). 2. Different weights of ankle sandbags. 3. Rating of perceived exertion (RPE) [10]. 4. Kidney Disease Quality of Life instrument (KDQOL) [11].

2.4

Blood Collection

1. Venous blood collection tubes. 2. Plastic microtubes (aliquots of 200 and 500 μL).

A Protocol of Intradialytic Exercise for Improvements in Inflammatory. . .

3. Freezer

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80  C.

4. Centrifuge (Hitachi CF16RN, Hitachinaka, Ibaraki, Japan). 2.5 Analysis of Cytokines (See Note 1)

1. Capture antibodies: pre-titrated, purified antihuman cytokines antibody (IL-10, IL-6, and TNF-α) supplied as enzyme-linked immunoadsorbent assay (ELISA) kits (eBioscience). 2. Detection antibody: pre-titrated, biotin-conjugated antispecies secondary antibodies targeting the above primary antibodies. 3. Standards: recombinant human cytokines for generating standard curves and calibrating the samples (two vials of lyophilized human IL-10, IL-6, and TNF-α, 300 pg/mL, 200 pg/mL, and 500 pg/mL upon reconstitution, respectively). 4. Coating buffer phosphate-buffered saline (PBS; pH 7.4): 10 mM Na2HPO4, 1.8 mM KH2PO4, 2.7 mM KCl, 137 mM NaCl. 5. 5 ELISA immunosorbent spot (ELISPOT) diluents. 6. 250 avidin-horseradish peroxidase (HRP) concentrate. 7. Substrate solution: tetramethylbenzidine (TMB) substrate solution. 8. 96-well plates: Corning Costar 9018 (see Note 2).

2.6 Other Materials Needed

1. Wash buffer DZ: PBS, 0.05% Tween™-20 or eBioscience™ wash buffer. 2. Stop solution: 1 M H3PO4 or 2 N H2SO4 or eBioscience™ stop solution. 3. Freezers:

20  C for kits and

80  C for samples.

4. 96-well ELISA plate reader (microplate spectrophotometer). 5. Microplate shaker (optional) (see Note 3). 6. Online randomization tool (http://www.randomization.com/).

3 3.1

Methods Participants

1. Register the clinical trial in a publicly accessible database before recruitment [12]. 2. Obtain ethics committee approval and informed signed consent from all participants (see Note 4). 3. Begin recruitment in hemodialysis centers according to the following criteria: Inclusion (a) Age 30–75 years. (b) Hemodialysis treatment for at least 3 months.

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(c) Venous access through a fistula. (d) Adequately dialyzed (Kt/V  1.2). (e) Medical approval to perform physical exercise. Exclusion (a) Mobility issues. (b) Less than 80% compliance with the training. (c) Taking continuous inflammatory medications. 4. Use the online tool to perform randomization (see Note 5). 5. Give preview instructions to the volunteers to not change their routine dietary intake or physical activity. 6. At baseline and after 12 weeks of resistance training, assess body composition (see Note 6), functional capacity, quality of life, and blood samples. 7. To evaluate body composition through DXA, ask the volunteer to remove all metal objects. Position the patient straight and centered on the DXA platform and instruct to avoid moving during scanning (see Note 7). 8. Measure body weight with a calibrated balance (the patient should be wearing minimal clothing). 9. Perform the height measurement with a stadiometer (without shoes). 3.2 Functional Capacity and Dietary Intake

1. To assess functional capacity using the timed up and go test, register the time it takes the volunteer to rise from a chair, walk 3 m, turn, walk back, and sit down [13] (see Note 8). 2. Establish a short battery physical performance score through the sum of the three tasks below, using a 4-point scale for each task [14]: (a) Balance test: The participant should maintain three different standing positions for 10 s each (feet side by side, feet in a semi-tandem stance, and one foot touching the heel of the other foot). (b) Gait speed test: time how long it takes the volunteer to walk 4 m (do this twice and record the fastest time). (c) Low body strength: Ask the patients to rise from a chair with no armrests five times and record the time required to complete this task. 3. Determine handgrip strength using a hand-held hydraulic dynamometer on the arm without the fistula, in a seated position with the arm flexed to 90 (register the best of the three measures (see Note 9).

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4. Assess dietary intake using a dietitian with a 3-day dietary intake record (including one on a hemodialysis day, one on an interdialytic day, and one on a weekend day). 5. Determine nutrients using the Avanutri® software. 6. Use KDQOL to assess their quality of life. 7. Ask the volunteer to undergo an 8 h fast before collecting 10 mL predialysis blood samples. 8. Collect the blood samples immediately into serum clot activator and heparinized tubes. 9. Store tubes in the refrigerator after collection. 10. Centrifuge at 2000  g for 15 min at 4  C. 11. Place supernatants in plastic microtubes and store at 3.3

Training

80  C.

1. Before starting the training period, perform at least 1 week of familiarization with power speed endurance (PSE) and the exercises, which should be performed with light loads. 2. Start the 12 weeks of supervised intradialytic resistance training, three times per week, during the first 2 h of hemodialysis (see Note 10). 3. Adapt the protocol of the exercises to a hemodialysis chair (Fig. 1). 4. Encourage patients to perform the repetitions until failure. 5. Test the load frequently, and when the patient is able to perform more repetitions than the prescribed training zone, increase the weight sufficiently to bring the number of repetitions back within the repetition maximum training zone (Table 1). 6. Register frequency training, load, and RPE of each exercise. 7. Use statistical software to test the distribution of the data using the Shapiro–Wilk test. 8. Compare the baseline and after training time points with ANOVA repeated measures (3 groups  2 moments). 9. Compare RPE with Student’s t-test.

3.4 Analysis of Blood Samples (Inflammatory Markers) (See Note 11)

1. Dilute the 250 capture antibody 1:250 in coating buffer (see Note 12). 2. Add 100 μL capture antibody to each well (see Note 13). 3. Seal the plate and incubate overnight at 4  C (see Note 14). 4. Aspirate the wells and wash three times with >250 μL/well wash buffer (see Note 15). 5. Allow time for soaking (~1 min) during each wash step to increase effectiveness of the washes.

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Fig. 1 Resistance exercise protocol. (a) Hip flexion, (b) knee flexion, (c) seated calf raise, (d) knee extension, (e) leg press

Table 1 Resistance training periodization High-intensity training

Moderate-intensity training

Control

Week 0–4

1  15–20 RM

1  15–20 RM

Stretching exercise

Week 5–8

3  8–10 RM

2  16–28 RM

Week 9–12

4  10–12 RM

3  18 20 RM

RM repetition maximum

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6. Blot the plate on absorbent paper to remove any residual buffer. 7. Add 200 μL of 1 ELISA/ELISPOT diluent to block the wells and incubate at room temperature for 1 h (see Note 16). 8. Reconstitute human IL-10, IL-6, and TNF-α standards in 1 ELISA/ELISPOT diluent. 9. Swirl or mix gently to ensure complete and homogeneous solubilization. 10. Mix well prior to making any dilutions (see Note 17). 11. Aspirate and wash at least once with wash buffer. 12. Perform twofold serial dilutions of the standards to make a standard curve with a total of eight points (see Note 18). 13. Add 100 μL/well samples to the appropriate wells and 100 μL ELISA/ELISPOT diluent to the blank well (see Note 19). 14. Seal the plate and incubate at room temperature for 2 h (or overnight at 4  C for maximum sensitivity). 15. Dilute the 250 detection antibody 1:250 in 1 ELISA/ELISPOT diluent. 16. Aspirate and wash as above for a total of 3–5 washes. 17. Tap the plate on absorbent paper to remove any residual buffer. 18. Add 100 μL/well of the diluted detection antibody to all wells. 19. Seal the plate and incubate at room temperature for 1 h. 20. Prepare the avidin-HRP and dilute 1:250 in 1 ELISA/ELISPOT diluent for analysis of IL-10. 21. Dilute the 100 HRP concentrate 1:100 in 1 ELISA/ELISPOT diluent. 22. Aspirate and wash above for a total of 3–5 washes. 23. Tap the plate on absorbent paper to remove any residual buffer. 24. Add 100 μL/well of diluted avidin-HRP. 25. Seal the plate and incubate at room temperature for 30 min. 26. Aspirate and wash as above, making sure to allow time for soaking for 1–2 min prior to aspiration. 27. Repeat for a total of 5–7 washes. 28. Add 100 μL/well of 1 TMB solution. 29. Incubate at room temperature for 15 min. 30. Add 100 μL/well of stop solution. 31. Read the plate at 450 nm.

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Notes 1. All ELISA measurements were performed using eBioscience kit components. These and other reagents should be stored at 2–8  C. 2. The use of ELISA plates that are not high-affinity proteinbinding plates will result in suboptimal performance, e.g., a low-signal or inconsistent data. Do not use tissue culture plates or low-protein absorption plates. Use only the Corning™ Costar™ 9018 or Nunc™ MaxiSorp™ 96-well plates provided or suggested. 3. To ensure optimal results from using this kit, use only the components included in the set. Exchanging of components is not recommended because a change in performance may occur. 4. This should be obtained before beginning experiments. This project was approved by the Research Ethics Committee of the Federal University of Goia´s. 5. A person not involved in the study protocol randomized the participants into the three groups. 6. The assessment of body composition should be performed after the midweek session (Wednesday, Thursday) because that is when the patients are more stable with lower interdialytic weight gain [15]. 7. Before starting the measurement of body composition with DXA, make sure that the volunteer is not currently pregnant or had an X-ray with contrast material in the last 7 days. 8. It is important to choose one-blinded researcher to perform the measures of body composition and functional capacity. 9. The handgrip assessment should be performed before hemodialysis because the procedure negatively affects patient strength [16]. 10. It is suggested that the training occurs during the first 2 h, because from the second hour, the occurrence of adverse events increases. 11. Human IL-10, IL-6, and TNF-α-uncoated ELISA kits contain all of the necessary reagents, standards, buffers, and diluents for performing quantitative ELISA. ELISA kits are specifically engineered for accurate and precise measurement of Human IL-10, IL-6, and TNF-α protein levels from liquid samples including serum, plasma, and supernatants from cell cultures. The analysis procedures for each cytokine are similar, although the capture antibody, detection antibody, and standard reagents are specific for each cytokine (IL-10, IL-6, and TNF-α).

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12. If crystals form in buffer concentrates, warm the containers gently until the crystals completely dissolve. 13. Be certain that no sodium azide is present in the solutions used in this assay, as this inhibits HRP enzyme activity. 14. Shaking is recommended for all incubation steps. In the case of incubation without shaking, the obtained optical density values may be decreased. Nevertheless, the results are still valid. 15. Prepare approximately 500 mL of wash buffer for each plate. 16. Prepare approximately 50 mL of diluent concentrate for each plate. 17. The standard has to be used immediately after reconstitution and cannot be stored (range of the standard curve: IL-10: 2–300 pg/mL, IL-6: 2–200 pg/mL, and TNF-α: 4–500 pg/ mL). 18. To do that, add 200 μL of ELISA/ELISPOT diluent (1) to the wells leaving the first wells empty. Add 400 μL/well of the standard concentration to the first empty wells A1/A2. Transfer 200 μL of the standard from wells A1/A2 to wells B1/B2. Mix the contents of the wells B1 and B2 by repeated aspiration and ejection and transfer 200 μL to wells C1/C2. Take care not to scratch the surface of the microwells. Continue this procedure five times (see Fig. 2). 19. It is suggested that the sample be added in duplicate or triplicate.

Top standard concentration

Add 400 μL

Add 200 μL

A1/A2

Add 200 μL

B1/B2 200 μL

Add 200 μL

C1/C2 200 μL

Add 200 μL

D1/D2 200 μL

Add 200 μL

E1/E2 200 μL

ELISA/ELISPOT Diluent (1X) IL-10 – 300 pg/mL TNF - pg/mL IL-6 - pg/mL

Fig. 2 Standard curve procedure

Add 200 μL

F1/F2 200 μL

G1/G2 200 μL

H1/H2 200 μL

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References 1. Johansen KL, Shubert T, Doyle J, Soher B, Sakkas GK, Kent-Braun JA (2003) Muscle atrophy in patients receiving hemodialysis: effects on muscle strength, muscle quality, and physical function. Kidney Int 63:291–297 2. Isoyama N, Qureshi AR, Avesani CM, Lindholm B, Ba`ra`ny P, Heimbu¨rger O et al (2014) Comparative associations of muscle mass and muscle strength with mortality in dialysis patients. Clin J Am Soc Nephrol 9:1720–1728 3. Pereira RA, Cordeiro AC, Avesani CM, Carrero JJ, Lindholm B, Amparo FC et al (2015) Sarcopenia in chronic kidney disease on conservative therapy: prevalence and association with mortality. Nephrol Dial Transplant 30:1718–1725 4. Roshanravan B, Robinson-Cohen C, Patel KV, Ayers E, Littman AJ, de Boer IH et al (2013) Association between physical performance and all-cause mortality in CKD. J Am Soc Nephrol 24:822–830 5. Cheema B, Abas H, Smith B, O’Sullivan AJ, Chan M, Patwardhan A et al (2010) Investigation of skeletal muscle quantity and quality in end-stage renal disease. Nephrology 15:454–463 6. Kaizu Y, Ohkawa S, Odamaki M, Ikegaya N, Hibi I, Miyaji K et al (2003) Association between inflammatory mediators and muscle mass in long-term hemodialysis patients. Am J Kidney Dis 42:295–302 7. da Cruz LG et al (2018) Intradialytic aerobic training improves inflammatory markers in patients with chronic kidney disease: a randomized clinical trial. Motriz: rev educ fis 24(3): e017517. https://doi.org/10.1590/s1980657420180003e017517 8. Ogawa K, Sanada K, MacHida S, Okutsu M, Suzuki K (2010) Resistance exercise traininginduced muscle hypertrophy was associated with reduction of inflammatory markers in elderly women. Mediat Inflamm

2010:171023. https://doi.org/10.1155/ 2010/171023 9. Moraes C, Marinho SM, Da Nobrega AC, de Oliveira Bessa B, Viana Jacobson L, Barcza Stockler-Pinto M et al (2014) Resistance exercise: a strategy to attenuate inflammation and protein-energy wasting in hemodialysis patients? Int Urol Nephrol 46:1655–1662 10. Borg G, Hassme´n P, Lagerstro¨m M (1987) Perceived exertion related to heart rate and blood lactate during arm and leg exercise. Eur J Appl Physiol Occup Physiol 56:679–685 11. Hays RD, Kallich JD, Mapes DL, Coons SJ, Carter WB (1994) Development of the kidney disease quality of life (KDQOLTM) instrument. Qual Life Res 3:329–338 12. WHO (2008) International Standards for Clinical Trial Registries. https://apps.who.int/iris/ handle/10665/76705 13. Podsiadlo D, Richardson S (1991) The timed “up & go”: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 39:142–148 14. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG et al (1994) A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol 49(2):M85–M94 15. Bae SY, Jeon JW, Kim SH, Baek CH, Jang JW, Yang WS et al (2019) Usefulness of mid-week hemoglobin measurement for anemia management in patients undergoing hemodialysis: a retrospective cohort study. BMC Nephrol 20:295. https://doi.org/10.1186/s12882019-1492-x 16. Delanaye P, Quinonez K, Buckinx F, Krzesinski JM, Bruye`re O (2018) Hand grip strength measurement in haemodialysis patients: before or after the session? Clin Kidney J 11:555–558

Chapter 9 Evaluating the Anticancer Activity of Natural Products Using a Novel 3D Culture Model Chloe Shay and Yong Teng Abstract Natural products, particularly as anticancer agents, continue to provide prototypes for pharmacologically active compounds. Compared with traditional two-dimensional (2D) approaches, 3D cell cultures have shown a clear role in drug discovery and development as they more closely resemble in vivo cell environments and come closer to capturing the in vivo functions of organs and tissues. The growing interest in using more physiological in vitro cancer models has driven the adoption of 3D cell cultures in evaluating anticancer activities of natural products. Here, we establish a protocol to use a novel 3D culture system to evaluate the therapeutic efficacy of epigallocatechin gallate (EGCG), a plant-based natural compound, in head and neck cancer cells. Our findings reveal that the sensitivity of natural products in 3D culture models may differ markedly from that obtained using 2D cultures, suggesting that 3D models will become a more reliable alternative to minimize misleading data. Keywords 3D cell culture, Natural products, Epigallocatechin gallate, EGCG, Anticancer

1

Introduction Natural products from plants and animals, especially phytochemicals, have long been used as a scaffold for drug design, as their already noted bioactivity can help accelerate the development of novel treatments [1–3]. Some of these compounds have displayed anticancer activities by interfering with the critical steps during cancer development and progression through inhibiting cellular proliferation and aggressiveness and/or increasing apoptosis. Epigallocatechin gallate (EGCG) is the most abundant and powerful antioxidant in green tea, which has been proven as a promising natural product used in the discovery and development of potential drug leads (Fig. 1). Due to its features, EGCG has been extensively studied as a potential treatment in various kinds of cancer [4– 6]. Particularly, EGCG can suppress tumor proliferation and invasion and has significant chemopreventive effects with no adverse

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_9, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Fig. 1 The structure of EGCG and its main functions

effects against normal cells and tissues. For these reasons, EGCG has been considered to be a readily applicable, acceptable, and accessible chemotherapy drug for cancer control and management. Traditional in vitro studies have relied heavily on two-dimensional (2D) cell culture models, which only allow cells to grow on flat and hard plastic surfaces. In cancer research, the 2D culture condition does not reflect the essential features of tumor tissues, since it does not support the complex and dynamic cell-cell communications and cell-matrix interactions that occur during cancer development and progression [7–10]. These drawbacks, along with lack of spatial depth and cell connectivity, limit its potential to accurately test or predict cancer cell responses to pharmacologically active compounds. To better elucidate cancer biology mechanisms and evaluate the efficiency of anticancer treatments, various 3D cell culture systems that recapitulate the tumor features and mimic the native tumor microenvironments have been developed through advances in microfabrication techniques and tissue engineering. Many 3D cell tumor models now exist, ranging from the simple cell spheroid models to complex tissue, offering an affordable and more efficient and accurate tool in anticancer drug discovery studies [7]. 3D cell culture systems can be classified into two categories known as scaffold and scaffold-free techniques. In this study, we utilized SeedEZ, an inert and transparent glass microfiber scaffold, to assess the efficacy of EGCG in head and neck cancer. The results showed that EGCG at the same dose displays less-efficient anticancer activity in SeedEZ than 2D culture, suggesting that drug sensitivity in 3D culture models differs markedly from that obtained

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using 2D culture. One potential reason for this is that 3D culture can be more heterogeneous than 2D culture, and, therefore, the potential for EGCG nonspecificity may be increased due to the more complex culture conditions used. Although interpretation of data obtained from 3D models is more challenging, it is more accurate and informative and, therefore, has greater utility in drug screening.

2

Materials 1. EGCG (see Note 1). 2. SeedEZ™ scaffold (Lena Biosciences) (see Note 2). 3. Corning™ Costar™ Flat Bottom Cell Culture Plates. 4. Hausser Scientific Bright-Line™ Counting Chamber (Fisher Scientific). 5. Trypsin—ethylenediaminetetraacetic acid (EDTA) solution 1. 6. Poly-D-lysine (PDL) hydrobromide. 7. Head and neck cancer HN12 and HN6 cell lines (see Note 3). 8. Dulbecco’s Modified Eagle Medium: nutrient mixture F-12 (DMEM/F12). 9. Fetal bovine serum. 10. alamarBlue™ Cell Viability Reagent (Invitrogen). 11. Multiwell microtiter plates. 12. Sterile forceps or tweezers.

3

Methods

3.1 Culture of Cancer Cells Using 2D Culture Method

1. Detach HN6 and HN12 cells (90% confluency) by adding 1 mL trypsin-EDTA and incubate the cells at 37  C for 10–15 min. 2. Neutralize the trypsinization reaction with supplemented complete culture medium until most of the cells (>90%) are detached (see Note 4). 3. Determine cell density using a counting chamber. 4. Transfer cells into the microcentrifuge tubes and centrifuge the cells at 1000  g for 5 min at room temperature. 5. Gently resuspend cell pellet in complete culture medium and transfer 300 μL medium containing 1  105 cells into each well of a 24-well microplate. 6. Cover plate with lid and place cells in a humidified incubator.

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3.2 Culture of Cancer Cells Using SeedEZ

1. Remove SeedEZ scaffolds (SC-C048) from sterile pouch and place into a multiwell plate using sterile forceps or tweezers. 2. Pre-wet scaffolds with 50 μL sterile, deionized water (see Note 5). 3. Coat SeedEZ scaffold with 50 μL 100 μg/mL PDL hydrobromide per well in the 48-well plate and incubate for at least 6 h (see Note 6). 4. Aspirate PDL solution, wash the scaffold with sterile deionized H2O three times, and dry it. 5. Detach HN6 and HN12 cells (90% confluency) by adding 1 mL trypsin-EDTA and incubate the cells at 37  C for 10–15 min. 6. Neutralize the trypsinization reaction with supplemented complete culture medium until most of the cells (>90%) are detached. 7. Determine cell density using a counting chamber. 8. Transfer 1  106 cells per sample into the microcentrifuge tubes. 9. Centrifuge the cells at 1000  g for 5 min at room temperature. 10. Gently resuspend cell pellet in 40 μL complete culture medium at room temperature. 11. Transfer 40 μL medium containing 1  106 cells into each scaffold by dispensing near the center of the scaffold (see Note 7). 12. Cover the plate and transfer to incubator for at least 30 min. 13. Add 250 μL complete culture medium per well to cells by slowly pipetting down the sides of the wells. 14. Cover plate with lid and place cells in a humidified incubator.

3.3 Treatment with EGCG and Determination of Its Efficacy (See Note 8)

1. After 1 week of cell culturing, remove the old medium and replace with 250 μL fresh medium containing EGCG at the final concentrations of 0, 25, 50, 100, 200, and 400 μM (see Note 9). 2. After 3 days of treatment, remove the old medium and replace with 90 μL fresh medium containing 10 μL alamarBlue reagent to microplate wells (see Note 10). 3. Incubate at 37  C for 1–4 h and then terminate experiment (see Note 11). 4. Read absorbance with the excitation/emission in 560/590 nm (see Note 12). 5. Plot a curve of relative fluorescence units vs. drug concentration to generate quantitative results (Fig. 2) (see Note 13).

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Fig. 2 The effects of EGCG on cell viability in cells cultured in 2D and 3D cell cultures. *p < 0.05; **p < 0.01

4

Notes 1. EGCG molecular formula: C22H18O11 458.37 g/mol, exact mass: 458.084911).

(molar

mass:

2. This is an inert, hydrophilic, 3D scaffold disc (9.5 mm diameter) optimized for long-term cell growth. It is suitable for cell culture and drug testing, amenable to extracellular matrices, and compatible with all cell types, cell culture reagents, stains, coatings, extracellular matrices, and hydrogels used in cell culture applications. This format is suitable for in-well assays. 3. HN12 cells are part of the OPC-22 oral and pharyngeal cancer cell line panel. HN6 cells are derived from squamous cell carcinoma of the oral tongue. 4. HN12 and HN6 cells should also be seeded in traditional 48-well plates for comparison. 5. The scaffold will turn gray under these conditions. 6. Adding PDL hydrobromide to SeedEZ facilitates cells to start adhering. 7. Cell numbers seeded into the SeedEZ may be of various origins and sources, and the incubation time may be varied for the different cell types and different research purposes. During the period of long-term culture, feed the cells every 2–3 days by exchanging half of the medium. 8. HN12 and HN6 cells seeded in traditional 24-well microplate plates received the same treatment of EGCG for comparison with 3D culture methods. 9. EGCG is diluted into fresh medium, and each dosage should have eight replicates. 10. alamarBlue cell viability reagents are ready-to-use, nontoxic, resazurin-based solutions that function as cell health indicators by using the reducing power of living cells to quantitatively measure viability. Moreover, alamarBlue reduction is regularly

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measured using absorbance, which gives good levels of accuracy for most experiments. 11. Plates can be refrigerated in the dark and read within 1–3 days if it is not possible to read plates on the day that an experiment is performed. 12. The presence of phenol red in the growth medium does not affect the measurements for alamarBlue. 13. This revealed that EGCG dose-dependently suppressed head and neck cancer cell viability in the SeedEZ scaffold. However, EGCG had less anticancer activity in head and neck cancer cells in the SeedEZ scaffold compared with 2D culture (Fig. 2).

Acknowledgments This work was supported in part by NIH grants R01DE028351 and R03DE028387. References 1. Cheung MK, Yue GGL, Chiu PWY, Lau CBS (2020) A review of the effects of natural compounds, medicinal plants, and mushrooms on the gut microbiota in colitis and cancer. Front Pharmacol 11:744. https://doi.org/10. 3389/fphar.2020.00744 2. Wu Q, Wong JPC, Kwok HF (2020) Putting the brakes on tumorigenesis with natural products of plant origin: insights into the molecular mechanisms of actions and immune targets for bladder cancer treatment. Cell 9(5):E1213. https://doi.org/10.3390/cells9051213 3. Zubair H, Khan MA, Anand S, Srivastava SK, Singh S, Singh AP (2020) Modulation of the tumor microenvironment by natural agents: implications for cancer prevention and therapy. Semin Cancer Biol:S1044-579X(20)30105-X. https://doi.org/10.1016/j.semcancer.2020. 05.009. Online ahead of print 4. Bimonte S, Albino V, Piccirillo M, Nasto A, Molino C, Palaia R et al (2019) Epigallocatechin-3-gallate in the prevention and treatment of hepatocellular carcinoma: experimental findings and translational perspectives. Drug Des Devel Ther 13:611–621 5. Aggarwal V, Tuli HS, Tania M, Srivastava S, Ritzer EE, Pandey A et al (2020) Molecular mechanisms of action of epigallocatechin gallate in cancer: Recent trends and advancement. Semin Cancer Biol:S1044-579X(20)30107-3. https://doi.org/10.1016/j.semcancer.2020. 05.011. Online ahead of print

6. Sharifi-Rad M, Pezzani R, Redaelli M, Zorzan M, Imran M, Ahmed Khalil A et al (2020) Preclinical pharmacological activities of Epigallocatechin-3-gallate in signaling pathways: an update on cancer. Molecules 25 (3):467. https://doi.org/10.3390/ molecules25030467 7. Jensen C, Teng Y (2020) Is it time to start transitioning from 2D to 3D cell culture? Front Mol Biosci 7:33. https://doi.org/10. 3389/fmolb.2020.00033 8. Lang L, Lam T, Chen A, Jensen C, Duncan L, Kong FC et al (2020) Circumventing AKT-associated Radioresistance in Oral cancer by novel nanoparticle-encapsulated Capivasertib. Cell 9(3):533. https://doi.org/10.3390/ cells9030533 9. Vo-Hoang Y, Paiva S, He L, Estaran S, Teng Y (2020) Design and synthesis of Arf1-targeting γ-dipeptides as potential agents against head and neck squamous cell carcinoma. Cell 9 (2):286. https://doi.org/10.3390/ cells9020286 10. Lang L, Shay C, Zhao X, Xiong Y, Wang X, Teng Y (2019) Simultaneously inactivating Src and AKT by saracatinib/capivasertib co-delivery nanoparticles to improve the efficacy of anti-Src therapy in head and neck squamous cell carcinoma. J Hematol Oncol 12 (1):132. https://doi.org/10.1186/s13045019-0827-1

Chapter 10 Evaluation of Antidiabetic Properties of Adenosma Bracteosum Bonati Extracts in Mice with Streptozotocin-Induced Diabetes Giau Van Vo, Paul C. Guest, and Ngoc Hong Nguyen Abstract Diabetes mellitus is a chronic metabolic disorder characterized by persistent hyperglycemia. Traditional medicinal plants with antidiabetic properties can be used as drugs or dietary adjuvants to existing therapies. This chapter presents the preparation of aqueous and ethanol extracts of Adenosma bracteosum Bonati (A. bracteosum) and evaluation of these for antioxidant and α-glucosidase inhibition activities in vitro. In addition, we tested the extracts and the purified A. bracteosum compound (isoscutellarein 8-O-β-Dglucopyranoside) for antihyperglycemic effects in glucose-loaded hyperglycemic and streptozotocin (STZ)-induced diabetic mice. Keywords α-glucosidase inhibition, Antidiabetic, Extract, Isolated compound, Streptozotocin, STZ

1

Introduction Diabetes mellitus is a metabolic disease characterized by high blood glucose levels that result from a deficiency in the production or use of insulin by the body. About 422 million people worldwide have diabetes, particularly in low- and middle-income countries, making it one of the leading causes of death [1–3]. The chronic hyperglycemia during diabetes can cause a number of damaging complications in blood vessels, eyes, heart, kidneys, and nerves [4]. Hyperglycemia tips the metabolic balance towards excess generation of reactive oxygen species (ROS), which has been considered as the “dangerous metabolic route in diabetes” [3, 5, 6]. It has been suggested that ROS are induced by hyperglycemia in diabetes through excess activation mitochondrial respiratory chain enzymes [7–9]. Given the important role of oxidative stress in the pathogenesis of many clinical conditions and aging, antioxidant therapies have

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_10, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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considerable potential in a number of disease areas. In this arena, medicinal plants have contributed significantly to the development of modern prescription drugs. In the case of diabetes, the antioxidant and hypoglycemic activities of a number of plant extracts have been evaluated and confirmed in animal models [10–12]. Many studies have revealed that plant-based formulations contain certain phytochemicals with potential antioxidant, anti-inflammatory, and glucose-lowering properties [12–15]. Vietnam is home to more than 3000 plants with known medicinal properties. One of these is the Adenosma bracteosum Bonati species in the Plantaginaceae family, which has been used as a traditional treatment of liver diseases [16–18]. In two recent studies, we found that a leaf extract of A. bracteosum has antioxidant and antihyperglycemic properties that may make it useful as an alternative or adjunct treatment in diabetes [17, 18]. The following chapter presents a protocol for preparation of the Adenosma bracteosum plant extracts and assessment of the biological activities using both in vitro and in vivo assays. The in vivo testing was carried out using the streptozotocin (STZ)induced mouse model of diabetes.

2

Materials

2.1 Chemicals and Reagents

1. Ethanol fraction elution buffer—ethyl acetate:methanol (10:1). 2. 2,20 -azino-bis-(3-ethylbenozothiazonline-6-sulfonic (ABTS). 3. 2,2-diphenyl-1-picrylhydrazyl (DPPH). 4. p-Nitrophenyl-α-D-glucopyranoside (pNPG). 5. Folin–ciocalteu reagent (Merck, Darmstadt, Germany). 6. Acarbose. 7. Gallic acid. 8. Rutin (Merck, Darmstadt, Germany). 9. Silica gel. 10. 0.2 M Na2CO3. 11. Glibenclamide (see Note 1). 12. Streptozotocin in citrate buffer (pH 4.5) (see Note 1). 13. Ascorbic acid. 14. Glucose.

acid

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Analytical Tests

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1. Alkaloids: Mayer, Dragendorff, and Bouchardat’s reagent (see Note 2). 2. Phenolics and tannin: Folin–Ciocalteu reagent (2% FeCl2, 1% gelatin, 10% NaCl) and 7.5% aqueous Na2CO3 (see Note 3). 3. Flavonoids: Shinoda test and alkaline reagent (2% AlCl3 in ethanol) (see Note 4). 4. Triterpenoids: Liebermann–Burchard assay (see Note 5). 5. Steroids: Salkowski test (see Note 6). 6. Saponins: Foam test with distilled water (see Note 7). 7. Free radical scavenging assay (DPPH· radical methanol solution): 6  105 M 2,2-diphenyl-1-picrylhydrazyl in 80% methanol. 8. ABTS radical scavenging assay: 7 mM ABTS solution with 2.45 mM K2S2O8. 9. α-glucosidase inhibition assay: (a) 0.1 M phosphate buffer, pH 6.8. (b) 0.2 U/mL α-glucosidase solution. (c) Substrate: 5 mM p-nitrophenyl-α-D-glucopyranoside (pNPG) in 0.1 M phosphate (pH 6.8). (d) Stop solution: 0.2 M Na2CO3. 10. Toxicity determination: Extracts and distilled water in 1% dimethyl sulfoxide (DMSO).

2.3

Equipment

1. 1-mm-diameter mesh sieve. 2. Whatman 3 MM paper. 3. Rotary evaporator. 4. Buchi water bath B-480. 5. Chemical hood. 6. UV/VIS/IR spectrophotometer. 7. Micro-plate reader. 8. Beckman Avanti™ J-25I centrifuge. 9. Beckman JA 25-25 rotor. 10. SAS 9.4 software (Medmenham, Marlow, UK).

2.4 Experimental Animals and Biological Materials

1. Swiss albino mice weighing 20–25 g (6–8 weeks old, average body weight of 25 g) (Ho Chi Minh Pasteur Institute in Vietnam) (see Note 8). 2. A. bracteosum plants (see Note 9).

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A)

B)

120 100 80 -

% 60 40 20 0 430

440

m/z

450

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Fig. 1 (a) Expanded spectrum of ESI-MS analysis and (b) structure of isoscutellarein 8-O-β-D-glucopyranoside (IG) (from [18])

3

Methods

3.1 Preparation of Plant Extracts and Isolation

1. Shade dry the aerial parts of A. bracteosum plants. 2. Pulverize the plants to a medium-size powder with a mortar and pestle and pass through a 1-mm-diameter mesh sieve. 3. Macerate further in 90% ethanol and leave for 48 h at room temperature. 4. Filter through 3MM Whatman paper. 5. Remove the solvent under reduced pressure at 35  C to obtain a crude ethanol extract. 6. Subject the ethanol to silica gel column vacuum chromatography and elute with hexane:chloroform linear gradient (100:0 to 0:100) to give nine fractions. 7. Test these fractions for antioxidant effects (see Note 10). 8. Purify the fraction with the highest antioxidant activity (fraction VII) by column chromatography and elution with ethyl acetate and methanol (10:1) to give a yellow powder compound. 9. To identify the isolated compound, determine the molecular weight and structure by electrospray ionization mass spectrometry (ESI-MS), 1H-nuclear magnetic resonance spectroscopy (NMR), 13C-NMR, heteronuclear multiple-bond correlation (HMBC), and heteronuclear single quantum coherence (HSQC) spectroscopy as described (Fig. 1) [18] (see Note 11).

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10. Prepare an aqueous extract from the dried and coarsely powdered material by boiling in a flask fitted with a reflux condenser for 30 min. 11. Filter this extract and concentrate, as described above. 3.2 Preliminary Phytochemical Investigation (See Note 12)

1. Test for the presence of alkaloids using the Mayer, Dragendorff, and Bouchardat’s reagent. 2. Test for phenolics and tannin with 2% FeCl2, 1% gelatine in 10% NaCl. 3. Test for flavonoids with a Shinoda test and alkaline reagent. 4. Test for triterpenoids with the Liebermann–Burchard assay. 5. Analyze steroids with the Salkowski test. 6. Determine saponins by a foam test with distilled water.

3.3 Determination of Total Phenolic Content (See Note 13)

1. Mix 1 mL extract (1 mg/mL) with the 5 mL Folin–Ciocalteu reagent and 4 mL 7.5% aqueous Na2CO3. 2. Incubate 30 min at 40  C and determine the absorbance of the samples by colorimetry at 765 nm in a spectrophotometer. 3. Base the amount of total phenols based on mg gallic acid equivalent/g extract (Fig. 2).

3.4 Determination of Total Flavonoid Content (See Note 14)

1. Add 2 mL extract to 2 mL 2% AlCl3 in ethanol. 2. Incubate 1 h at 25  C. 3. Read the absorbance at 420 nm. 4. Express the total flavonoid content as mg rutin equivalents/ gram extract using a rutin calibration curve (Fig. 2).

3.5 Free Radical Scavenging Activity Assay (See Note 15)

1. Mix 50 μL samples at different concentrations with 2 mL DPPH· radical methanol solution. 2. Read the absorbance at 515 nm in a spectrophotometer after 16 min. 3. Determine the percentage of inhibition of the DPPH· radical according to the following equation [19]: 

% Inhibition ¼ A Cð0Þ  A Sðt Þ =A Cð0Þ   100 where AC(0) is the absorbance of the control (t ¼ 0 min) and AS(t) is the absorbance of the sample (t ¼ 16 min). 4. Calculate the sample 50% inhibition (IC50) values from a graph against the concentration of the samples, using ascorbic acid as a reference (Fig. 3).

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Fig. 2 Total phenolic and flavonoid contents of A. bracteosum aqueous and ethanol extracts. Results are the mean  SD of three experiments

Fig. 3 Antioxidant activity of A. bracteosum aqueous and ethanol extracts, and IG determined by DPPH and ABTS assays in comparison to ascorbic acid standard. Results are the mean  SD of three experiments 3.6 ABTS Radical Scavenging Assay (See Note 16)

1. Generate an ABTS radical by reaction of the ABTS solution with 2.45 mM K2S2O8. 2. Allow the mixture to stand in the dark for 12 h at room temperature. 3. Dilute the resulting solution with ethanol and equilibrate at 30  C. 4. After the addition of 1.0 mL diluted ABTS solution to 10 mL samples and incubation for after 6 min at 30  C, read the absorbance at 734 nm. 5. Calculate the IC50 from the graph using ascorbic acid as the reference (Fig. 3). 1. Combine 60 μL sample with 50 μL 0.1 M phosphate buffer and 0.2 U/mL α-glucosidase solution in 96-well microplates. 2. Incubate 20 min at 37  C.

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Fig. 4 Concentration curve showing α-glucosidase inhibition by aqueous and ethanol extracts compared to acarbose. Results are the mean  SD of three experiments 3.7 In Vitro α-Glucosidase Inhibition Assay (See Note 17)

3. Add 50 μL 5 mM pNPG solution to each well and incubate at 37  C for 20 min. 4. Stop the reactions by addition of 160 μL 0.2 M Na2CO3. 5. Read the absorbance using a micro-plate reader at 405 nm. 6. Compare the absorbance to a blank control containing 60 μL phosphate buffer in place of the extract. 7. Calculate the α-glucosidase inhibitory activity as follows:
Inhibition ð%Þ ¼ A control  A sample  100=A control 8. Determine the concentration of the sample and the reference required to inhibit 50% of the α-glucosidase activity using a graph plot of the percentage of inhibition (Fig. 4).

3.8 Toxicity Determination of Extracts

1. Treat six groups of ten mice with 1, 2, and 3 g/kg each extract. 2. Treat a control group of ten mice in parallel with distilled water containing 1% DMSO. 3. Observe the animals for any toxic effect for 1 h after the treatment period.

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4. Reexamine the animals after 6 h and 24 h for any toxic effects (see Note 18). 3.9 Evaluation of Extracts in StreptozotocinInduced Diabetic Mice

1. Induce experimental diabetes in mice by a single intraperitoneal injection of 150 mg/kg body weight of STZ in citrate buffer. 2. For control animals, inject citrate buffer alone. 3. Determine blood glucose level after 72 h post STZ injection (see Note 19). 4. Divide the mice into five groups of six, with group I comprising the control mice and groups II–V being the diabetic mice. 5. Set up the group treatments as follows: I. Nondiabetic control mice to be administered water. II. Diabetic mice to receive distilled water. III. Diabetic mice to be given 10 mg/kg glibenclamide. IV. Diabetic mice to be given 50 mg/kg ethanol extract. V. Diabetic mice to be given 50 mg/kg aqueous extract. 6. Prepare the above solutions fresh and administer orally once per day for 21 days. 7. Test tail vein blood glucose levels on days 1, 7, 14, and 21 using overnight fasted animals (Fig. 5) (see Note 20).

3.10 Antihyperglycemic Assay on Glucose-Loaded Mice

1. Divide albino mice of either sex randomly into five groups of six animals as follows: I. Control mice to receive distilled water. II. Mice designated to receive 10 mg/kg glibenclamide. III. Mice to be treated with 50 mg/kg A. bracteosum aqueous extract. IV. Mice to be treated with 50 mg/kg A. bracteosum ethanol extract. V. Mice to be treated with isolated compound IG at 10 mg/ kg dose. 2. Administer all treatments orally. 3. After 1 h, treat all of the mice orally with 2 g/kg glucose. 4. Collect blood samples 2 h after the glucose administration. 5. Prepare serum and estimate blood glucose levels (Fig. 6) (see Note 21).

3.11 Statistical Analysis

1. Perform all assessments in triplicate. 2. Perform one-way analysis of variance (ANOVA) with a Fisher’s Least Significant Difference to determine significant differences between groups using the SAS software. 3. Calculate means and standard deviations.

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Fig. 5 Effects of glibenclamide and the aqueous and ethanol extracts from A. bracteosum on blood glucose levels (mM) in streptozotocin (STZ)-induced diabetic mice after 21 days treatment (the data from days 1, 7, and 14 are not shown). Data were mean  SD of values from six mice

4. Determine differences among the mean values of the various parameters by the least significant difference test, with p < 0.05 set to indicate statistical significance for all of the experimental data (see Note 22).

4

Notes 1. This should be prepared fresh on the day of use. Glibenclamide is a drug used commonly to treat type 2 diabetes. The drug works via blockade of ATP-sensitive K+ channels in the β-cell plasma membrane which leads to an increase in insulin secretion [20]. Streptozotocin is used to induce diabetes in rodents by selectively destroying the insulin-producing pancreatic β-cells [21].

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Fig. 6 Effects of glibenclamide (10 mg/kg), aqueous extract, ethanol extract (50 mg/kg), and purified IG (10 mg/kg) on blood glucose in mice receiving 2 g/kg glucose. Data were mean  SD of values from six mice

2. These reagents were prepared as described in previous studies [22, 23]. 3. This reagent was prepared as described [24]. 4. This reagent was prepared as described [25]. 5. This reagent was prepared as described [26]. 6. This reagent was prepared as described [27]. 7. This test was carried out as described [28]. 8. Before beginning experiments, ensure that the appropriate approvals are in place for work with animals. Maintain animals at 24–28  C and 60–70% relative humidity, with a 12:12 h dark:light cycle and pellet food and water available ad libitum. 9. A. bracteosum plants were collected at Ba Den Mountain, Tay Ninh province, Vietnam, in December 2017. The sample was identified by Associate Professor Tran Hop, Ho Chi Minh City University of Natural Science, Vietnam. 10. Fraction VII showed the strongest antioxidant activity. 11. We previously identified the compound by ESI-MS with an m/ z ¼ 447.08 [MH] (Fig. 1). In addition, 1H-nuclear magnetic resonance spectroscopy (NMR), 13C-NMR, heteronuclear multiple-bond correlation (HMBC), and heteronuclear single quantum coherence (HSQC) spectroscopy was used to

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determine the structure [18]. These results are consistent with those of other studies [19]. 12. The extracts were tested for presence of active substances such as flavonoid, tannin, essential oils, triterpenoids, steroids, and saponins. Carry out phytochemical analysis of samples to identify the constituents using procedures previously described [9]. 13. Assess the total phenolic content using the Folin–Ciocalteu method [29]. As shown in Fig. 2, A. bracteosum contained high levels of total phenols which play an important role in the biological activity of the plant. The presence of total phenols was approximately equivalent in both aqueous and ethanol extracts. 14. Estimate the total flavonoid content using the previously reported method [30]. As shown in Fig. 2, A. bracteosum contained high levels of flavonoids, which have strong antioxidant activities. The flavonoids were more enriched in the ethanol extract. 15. Perform triplicate DPPH assays of the samples as described (Fig. 3) [12]. The DPPH assay is commonly used to monitor chemical reactions involving radicals and as an antioxidant assay. 16. Determine the radical scavenging activity of the samples using the ABTS assay according to a previously described procedure with slight modifications (Fig. 3) [31]. ABTS is frequently used by the food and agricultural industries to measure antioxidant capacities in foods and food products. 17. Measure α-glucosidase inhibitory activity as described previously [32], with slight modifications. α-glucosidase inhibitors such as acarbose are oral antidiabetic drugs that work by preventing carbohydrate digestion. Here, the analysis showed that both extracts were more effective than acarbose in inhibiting α-glucosidase activity. The IC50 values of the aqueous extract, ethanol extract, and acarbose were 42.6, 26.6, and 87.9 μg/ mL, respectively. This showed that both extracts contained a higher antihyperglycemic effect compared to acarbose (Fig. 4). The inhibitory activity of purified IG was even greater (IC50 ¼ 1.4 μg/mL; data not shown). This is consistent with other studies which showed that A. bracteosum is a potential source of antidiabetic compounds [10]. Studies have shown that phenolic compounds or enriched extracts from several plants also contain antidiabetic activities [33, 34]. In addition, the A. bracteosum compounds have been shown to interact synergistically with other physiological compounds [35]. 18. We determined the oral acute toxicity of the ethanolic and aqueous extracts of A. bracteosum according to previous studies [36, 37] using a limit test dose of 3000 mg/kg. This

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showed that the animals had no observable changes in their behaviors, and their body weights and food consumption were not different compared to the control group. Although, these findings suggested that the A. bracteosum extracts may be safe for experimental animals at the tested concentrations, further work should be carried out to test this more thoroughly. 19. Mice with serum glucose levels >11.1 mM were considered diabetic and used for the study [38, 39]. 20. Both plant extracts and glibenclamide showed similar hypoglycemic effects in the STZ-treated diabetic mice (Fig. 5). The maximum glucose lowering effect was found on day 21 (days 1, 7, and 14 are not shown). 21. A glucose tolerance test was administered as described previously [40], with slight modifications. The analysis showed that the ethanol and aqueous extracts and IG compound of A. bracteosum lowered the serum glucose levels significantly when compared to the control group, similar to the standard antidiabetic drug, glibenclamide (Fig. 6). 22. Together, these findings show that the extracts and the bioactive compound isolated from A. bracteosum demonstrated valuable pharmacological properties and could be used in the development of new antidiabetic drugs, as found for other plant products [41–43]. References 1. Magliano DJ, Islam RM, Barr ELM, Gregg EW, Pavkov ME, Harding JL et al (2019) Trends in incidence of total or type 2 diabetes: systematic review. BMJ 366:l5003. https:// doi.org/10.1136/bmj.l5003 2. Cho NH, Shaw JE, Karuranga S, Huang Y, da Rocha Fernandes JD, Ohlrogge AW et al (2018) IDF diabetes atlas: global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Res Clin Pract 138:271–281 3. Nguyen TT, Ta QTH, Nguyen TTD, Le TT, Vo VG (2020) Role of Insulin Resistance in the Alzheimer’s Disease Progression. Neurochem Res 45(7):1481–1491. https://doi.org/10. 1007/s11064-020-03031-0. Online ahead of print 4. Foretz M, Guigas B, Viollet B (2019) Understanding the glucoregulatory mechanisms of metformin in type 2 diabetes mellitus. Nat Rev Endocrinol 15(10):569–589 5. Nogueira-Machado JA, Chaves MM (2008) From hyperglycemia to AGE-RAGE interaction on the cell surface: a dangerous metabolic

route for diabetic patients. Expert Opin Ther Targets 12(7):871–882 6. Nguyen TT, Ta QTH, Nguyen TKO, Nguyen TTD, Giau VV (2020) Type 3 diabetes and its role implications in Alzheimer’s disease. Int J Mol Sci 21(9). https://doi.org/10.3390/ ijms21093165 7. Balaban RS, Nemoto S, Finkel T (2005) Mitochondria, oxidants, and aging. Cell 120 (4):483–495 8. Shiba T, Inoguchi T, Sportsman JR, Heath WF, Bursell S, King GL (1993) Correlation of diacylglycerol level and protein kinase C activity in rat retina to retinal circulation. Am J Phys 265(5 Pt 1):E783–E793 9. Van Giau V, An SSA, Hulme JP (2018) Mitochondrial therapeutic interventions in Alzheimer’s disease. J Neurol Sci 395:62–70 10. Sabu MC, Kuttan R (2002) Anti-diabetic activity of medicinal plants and its relationship with their antioxidant property. J Ethnopharmacol 81(2):155–160 11. Lankatillake C, Huynh T, Dias DA (2019) Understanding glycaemic control and current

Anti-diabetic actions of A. bracteosum approaches for screening antidiabetic natural products from evidence-based medicinal plants. Plant Methods 15(1):105. https://doi. org/10.1186/s13007-019-0487-8 12. Ungurianu A, S¸eremet O, Gagniuc E, Olaru OT, Gut¸u C, Grǎdinaru D et al (2019) Preclinical and clinical results regarding the effects of a plant-based antidiabetic formulation versus well established antidiabetic molecules. Pharmacol Res 150:104522. https://doi.org/10. 1016/j.phrs.2019.104522 13. Taghizadeh M, Rashidi AA, Taherian AA, Vakili Z, Sajad Sajadian M, Ghardashi M (2016) Antidiabetic and Antihyperlipidemic effects of ethanol extract of Rosa canina L. fruit on diabetic rats: An experimental study with histopathological evaluations. J Evid Based Complementary Altern Med 21 (4):Np25-30 14. Zhang W, Zhao J, Wang J, Pang X, Zhuang X, Zhu X et al (2010) Hypoglycemic effect of aqueous extract of seabuckthorn (Hippophae rhamnoides L.) seed residues in streptozotocin-induced diabetic rats. Phytother Res 24(2):228–232 15. Tundis R, Loizzo MR, Menichini F, Bonesi M, Conforti F, Statti G et al (2011) Comparative study on the chemical composition, antioxidant properties and hypoglycaemic activities of two Capsicum annuum L. cultivars (Acuminatum small and Cerasiferum). Plant Foods Hum Nutr 66(3):261–269 16. Tsankova ET, Kuleva LV, Thanh LT (1994) Composition of the essential oil of Adenosma bracteosum Bonati. J Essent Oil Res 6 (3):305–306 17. Hong NN, Han LTN, Thang PQ (2018) Antioxidant activity and anti-hyperglycemic effect from Adenosma bracteosum Bonati. Acad J Biol 40(2se). https://doi.org/10.15625/26159023/v40n2se.1286 18. Nguyen NH, Pham QT, Luong TNH, Le HK, Vo VG (2020) Potential antidiabetic activity of extracts and isolated compound from Adenosma bracteosum (Bonati). Biomol Ther 10 (2):201. https://doi.org/10.3390/ biom10020201 19. Yen GC, Duh PD (1994) Scavenging effect of Methanolic extracts of Peanut hulls on freeradical and active-oxygen species. J Agric Food Chem 42(3):629–632 20. Skillman TG, Feldman JM (1981) The pharmacology of sulfonylureas. Am J Med 70 (2):361–372 21. Lenzen S (2008) The mechanisms of alloxanand streptozotocin-induced diabetes. Diabetologia 51(2):216–226

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22. Al-Shamma A, Mitscher LA (1979) Comprehensive survey of indigenous Iraqi plants for potential economic value. 1. Screening results of 327 species for alkaloids and antimicrobial agents. J Nat Prod 42(6):633–642 23. Sinaga SM, Nainggolan M, Iksen I (2019) Isolation and identification of alkaloids extracted from dayak onion (Eleutherinae palmifolia (L.) Merr). Rasayan J Chem 12(03):1298–1303 24. Amarowicz R, Pegg RB, Rahimi-MoghaddamP, Barl B, Weil JA (2004) Free-radical scavenging capacity and antioxidant activity of selected plant species from the Canadian prairies. Food Chem 84:551–562 25. Usman H, Fi A, Usman A (2009) Qualitative phytochemical screening and in vitro antimicrobial effects of methanol stem bark extract of Ficus Thonningii (Moraceae). Afr J Tradit Complement Altern Med 6(3):289–295 26. Pham HL, Ross BP, McGeary RP, Shaw PN, Hewavitharana AK, Davies NM (2006) Saponins from Quillaja saponaria Molina: isolation, characterization and ability to form immuno stimulatory complexes (ISCOMs). Curr Drug Deliv 3(4):389–397 27. Mannan A, Ahmad K (1978) Preliminary study of sex hormones of medical importance in Bangladeshi plants. Bangladesh Med Res Counc Bull 4(2):78–85 28. Soltani M, Parivar K, Baharara J, Kerachian MA, Asili J (2014) Hemolytic and cytotoxic properties of Saponin purified from Holothuria Leucospilota Sea cucumber. Rep Biochem Mol Biol 3(1):43–50 29. Singleton VL, Rossi JA (1965) Colorimetry of Total Phenolics with PhosphomolybdicPhosphotungstic acid reagents. Am J Enol Vitic 16(3):144–158 30. Formagio ASN, Volobuff CRF, Santiago M, Cardoso CAL, Vieira MC, Valdevina Pereira Z (2014) Evaluation of antioxidant activity, Total flavonoids, tannins and phenolic compounds in Psychotria leaf extracts. Antioxidants (Basel) 3 (4):745–757 31. Re R, Pellegrini N, Proteggente A, Pannala A, Yang M, Rice-Evans C (1999) Antioxidant activity applying an improved ABTS radical cation decolorization assay. Free Radic Biol Med 26(9-10):1231–1237 32. Dong HQ, Li M, Zhu F, Liu FL, Huang JB (2012) Inhibitory potential of trilobatin from Lithocarpus polystachyus Rehd against α-glucosidase and α-amylase linked to type 2 diabetes. Food Chem 130(2):261–266 33. Joy KL, Kuttan R (1999) Anti-diabetic activity of Picrorrhiza kurroa extract. J Ethnopharmacol 67(2):143–148

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38. Furman BL (2015) Streptozotocin-induced diabetic models in mice and rats. Curr Protoc Pharmacol 70:5.47.41–45.47.20 39. Hayashi K, Kojima R, Ito M (2006) Strain differences in the diabetogenic activity of streptozotocin in mice. Biol Pharm Bull 29 (6):1110–1119 40. Croft KD (1998) The chemistry and biological effects of flavonoids and phenolic acids. Ann N Y Acad Sci 854:435–442 41. Giugliano D, Ceriello A, Paolisso G (1996) Oxidative stress and diabetic vascular complications. Diabetes Care 19(3):257–267 42. Gonzalez-Burgos E, Gomez-Serranillos MP (2012) Terpene compounds in nature: a review of their potential antioxidant activity. Curr Med Chem 19(31):5319–5341 43. Maritim AC, Sanders RA, Watkins JB 3rd (2003) Diabetes, oxidative stress, and antioxidants: a review. J Biochem Mol Toxicol 17 (1):24–38

Chapter 11 Testing the Effects of Cinnamon Extract Supplementation on Inflammation and Oxidative Stress Induced by Acrylamide Fatemeh Haidari, Majid Mohammadshahi, Behnaz Abiri, Paul C. Guest, Mehdi Zarei, and Mojdeh Fathi Abstract We investigated the effects of cinnamon water extract supplementation on inflammation and oxidative stress induced by acrylamide in rats. This revealed acrylamide-intoxicated control group had significant higher levels of malondialdehyde, tumor necrosis factor-alpha (TNF-α), high-sensitive C-reactive protein (hs-CRP), leptin and alanine transaminase, and lower levels of total antioxidant capacity compared to the negative control group. In contrast, cinnamon extract administration remedied the levels of total antioxidant capacity, malondialdehyde, TNF-α, hs-CRP, and leptin in the treatment groups. However, there was no significant effect on adiponectin or liver enzymes. This chapter presents a protocol involving production of the acrylamide-induced oxidative stress model, the aqueous extraction of cinnamon powder, and measurement of inflammatory and oxidative stress markers. Keywords Cinnamon extract, Acrylamide, Oxidative stress, Liver enzyme, Inflammation

1

Introduction The liver is an essential organ for detoxification of xenobiotics, including toxins, drugs, alcohol, and foods [1]. One component that has a toxic effect on the liver is acrylamide [2]. Although acrylamide has industrial applications, it is also formed when foods are cooked at high temperatures (above 120
C), as in baked, fried, grilled, toasted, or roasted foods. This is known as the Millard reaction which can also confer a desirable flavor and color to the food product (Fig. 1) [3]. This includes foods such as roasted potatoes and root vegetables, chips, crisps, toast, cakes, biscuits, cereals, and coffee. Another common source of acrylamide formation is in tobacco-related products like cigarettes [4]. Acrylamide is a reactive component metabolized in the liver, where it is converted to glycidamide [5]. Both acrylamide and

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_11, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Fig. 1 Formation of acrylamide via the Millard reaction in baked and fried foods

glycidamide are destructive to cells by causing oxidative damage [6]. Oxidative stress is a result of an imbalance between the production of free radicals and the antioxidant defense system. Detoxification of acrylamide in the liver can cause depletion of the reduced form of glutathione and decreased levels of the antioxidant enzymes [7]. The acrylamide-induced oxidative stress can lead to destruction of liver tissue and can be visualized at the molecular level by release of certain aminotransferase enzymes into the bloodstream [8]. On the other hand, previous studies have demonstrated that oxidative stress stimulates inflammatory pathways and results in increased levels of cytokines and adipocytokines such as leptin and adiponectin [9, 10], which can lead to neuro-, geno-, and reproductive toxicities [11–13]. Following the growth of fast foods and the smoking industry in the world, the global concern regarding the intake of acrylamide has increased [14].The Tobacco Atlas in 2013 reported that Eastern and South-Eastern Asia, and Eastern Europe had the highest male smoker prevalence [15]. Thus, there is a critical need for new therapeutic approaches to combat this problem.

Testing the Effects of Cinnamon Extract Supplementation on Inflammation. . .

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Fig. 2 (a) Cinnamon zeylanicumis tree, sticks, and powder. (b) Three main components of cinnamon: transcinnamaldehyde;,eugenol, and linalool

Cinnamon zeylanicum is used as spice and tea in many cultures. It has also been widely used in folk medicine as an effective therapy for various diseases due to its antioxidant and protective properties. It is derived from the inner bark of cinnamon trees and has many bioactive components such as flavonoids, tannins, terpenoids, glycosides, and alkaloids [16]. The essential oils of the bark of the cinnamon tree contain three main components including transcinnamaldehyde, eugenol, and linalool (Fig. 2) [17]. A number of modern studies have shown that these can have anti-inflammatory, antioxidant, anticancer, and hepatoprotective effects [18–21]. Here, we present a protocol for production of the acrylamideinduced oxidative stress model in rats, the aqueous extraction of cinnamon powder, and measurement of inflammatory and oxidative stress markers as a readout of efficacy.

2

Materials 1. Wistar rats aged 6–8 weeks old (150–200 g) (see Note 1). 2. Cinnamon bark (see Note 2).

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3. Filter paper. 4. Acrylamide (Merck, Darmstadt, Germany) (see Note 3). 5. Distilled water. 6. Gavage tubes (see Note 4). 7. Diethyl ether (see Note 5). 8. Blood serum tubes. 9. Benchtop centrifuge. 10. Ice-cold saline (0.9%). 11. Chilled 1.15% KCl containing 0.1 mM ethylenediaminetetraacetic acid (EDTA) (see Note 6). 12. 50 mM phosphate buffer. 13. Mechanical homogenizer. 14. Total antioxidant status (TAS) colorimetric assay kit (Randox Laboratories Ltd., London, UK). 15. TNF-α enzyme-linked immunosorbent assay (ELISA) kit (Orgenium Laboratories, Helsinki, Finland). 16. hs-CRP ELISA kit (Labor Diagnostika Nord, Nordhorn, Germany). 17. Leptin and adiponectin ELISA kits (Boster Biological Technology, Ltd., Wuhan, China) (see Note 7). 18. Thiobarbituric acid (see Note 8). 19. Aspartate transaminase (AST), alanine transaminase (ALT), and alkaline phosphatase (ALP) assay kits (Pars Azmoon, Tehran, Iran) (see Note 9).

3

Methods

3.1 Acrylamide Toxicity Model and Preparation of Cinnamon Extract

1. Allow rats to acclimatize for 2 weeks in a quite controlled animal room (see Notes 10 and 11). 2. Randomly allocate animals into four groups: (a) Normal control rats (sham) (n ¼ 8). (b) Acrylamide-intoxicated control rats (n ¼ 8). (c) Acrylamide-intoxicated rats treated with cinnamon extract (250 mg/kg/day; n ¼ 8). (d) Acrylamide-intoxicated rats treated with cinnamon extract (500 mg/kg/day; n ¼ 8). 3. Dissolve acrylamide in distilled water. 4. For groups b, c, and d, administer acrylamide solution to rats at 35 mg/kg/day by oral gavage for 2 weeks. 5. Administer the same volume of water to the control group.

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Fig. 3 Flowchart showing cinnamon water extraction protocol

6. Wash dried cinnamon barks in distilled water, dry and grind to powder (Fig. 3). 7. Dissolve 10 g fine powder in 100 mL distilled water in a covered Erlenmeyer flask with incubation at 60
C for 1 h. 8. Centrifuge the extract at 1000  g for 5 min at 4
C. 9. Transfer the supernatant to a clean bottle and store at 20
C prior to use [22, 24] (see Note 12). 10. Administer the extract orally by gavage tubes over 4 weeks beginning on the final day of acrylamide intoxication. 11. Twenty-four hours after the final cinnamon extract exposure, anesthetize overnight-fasted rats using diethyl ether. 12. Cull and collect blood by cardiac puncture into serum tubes. 13. After leaving the tubes for 90 min at room temperature, centrifuge at 4000  g for 10 min and store the serum supernatants at 70
C until ready for biochemical analysis. 14. At the same time excise, weigh, and perfuse livers with the cold saline solution and place in chilled KCL/EDTA solution. 15. Chop the livers in 4–5 volumes of 50 mM phosphate buffer and disrupt the tissue using the mechanical homogenizer ([23]). 16. Centrifuge the homogenate at 3000  g for 10 min and then gently remove the top lipid layer and discard.

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17. Collect the remaining supernatant fraction being careful not to disturb the lower cellular layer. 18. Centrifuge the supernatant at 12,000  g for 60 min at 4
C to remove any remaining debris [23]. 19. Store the final supernatant at 70 analysis [23]. 3.2

TAS Assay




C until ready for

1. Add 10 mL buffer to each vial of chromogen in the kit. 2. Dilute each vial of substrate needed for the assay by adding 7.5 mL buffer. 3. Add 1 mL distilled water to each vial of standard. 4. Zero the spectrophotometer at 600 nm against air at 37
C. 5. Equilibrate the diluted substrate and chromogen for 5 min at 37
C. 6. Add 20 μL of the blank, standard, or sample to a cuvette with 1 mL chromogen. 7. Mix and read the initial absorbance (A0). 8. Add 200 μL substrate to each cuvette and mix. 9. Allow the reaction to run for 3 min and read the final absorbance (A). 10. Determine the change in absorbance (ΔA) for each sample using the formula: ΔA ¼ A  A 0 11. Calculate the antioxidant concentration using the following formula: ½standard ðΔA blank  ΔA sampleÞ=ΔA blank  ΔA sample

3.3 Malonaldehyde (MDA) Assay

1. Solubilize thiobarbituric acid and prepare a 4–20 nmol/well standard curve. 2. Dilute samples by trial and error to lie within range of standard curve readings. 3. Add 600 μL thiobarbituric acid to 200 μL samples. 4. Incubate at 95
C for 60 min. 5. Cool to room temperature on ice and leave for 10 min. 6. Pipette 200 μL of each 800 μL sample into the wells of a 96-well microplate. 7. Measure immediately at 532 nm in a spectrophotometer. 8. Determine MDA concentration by comparison with standard curve.

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3.4 ELISA and Activity Assays

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1. Carry out ELISA of serum samples for TNF-α, hs-CRP, leptin, and adiponectin using the kits listed above, according to the manufacturers’ instructions. 2. Perform AST, ALT, and ALP enzyme activity assays using the kits listed above, according to the manufacturers’ instructions. 3. Carry out statistical analysis using the SPSS software and present the descriptive statistics as mean  standard deviation. 4. Examine normality of data with Kolmogorov-Smirnov test and subject the data to one-way Analysis of Variance (ANOVA) followed by the Tukey test (see Note 13). 5. Examine the effect of cinnamon extract administration on oxidative stress biomarkers (TAS and MDA) after 4 weeks with analysis of variance (ANOVA) followed by the Tukey test (P < 0.05 considered significant) (Table 1) (see Note 14). 6. Examine the effect of cinnamon extract administration on serum levels of leptin, adiponectin, and inflammatory biomarkers (TNF-α and hs-CRP) after 4 weeks with ANOVA followed by the Tukey test (P < 0.05 considered significant) (Table 2) [23] (see Note 15). 7. Examine the effect of cinnamon extract administration on liver enzymes activities after 4 weeks with ANOVA followed by the Tukey test (P < 0.05 considered significant) (Table 3) (see Note 16). 8. Discuss and give the main conclusions of the study (see Note 17).

Table 1 Effect of cinnamon extract administration on serum and liver oxidative stress biomarkers

Groups

Serum TAS (nM)

Liver TAS (U/g)

Normal control

9.46  0.58

9.73  0.81

Acrylamide control

7.88  1.17

7.86  1.00

##

Acrylamide + CE (250 mg/kg/ 9.35  1.07* day)

Serum MDA (μM) ##

7.86  1.18

Acrylamide + CE (500 mg/kg/ 9.64  0.42** 9.07  0.37* day) All values are expressed as mean  SD (n ¼ 8) ANOVA followed by Tukey test was used for statistical analysis *p < 0.05 and **p < 0.01 versus acrylamide control group # p < 0.05 and ##p < 0.01 versus normal control group TAS total antioxidant status, MDA malondialdehyde, CE cinnamon extract

Liver MDA (nmol/ mg)

5.24  2.29

4.95  2.45

8.72  3.24

9.28  4.13#

4.36  0.31**

3.68  0.87**

3.53  0.99**

4.05  0.88**

#

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Table 2 Effect of cinnamon extract administration on serum levels of leptin, adiponectin, and inflammatory biomarkers

Groups Normal control Acrylamide control

TNF-α (pg/mL)

Leptin (ng/mL)

hs-CRP (mg/L)

31.13  13.72 631.37  111.64 56.13  18.61

#

895.25  82.90

##

Adiponectin (μg/ mL)

4.41  0.48 15.24  3.65 6.41  1.28## 11.30  6.04

Acrylamide + CE (250 mg/ kg/day)

22.00  10.24** 697.00  245.98 4.03  1.07** 16.89  3.51

Acrylamide + CE (500 mg/ kg/day)

32.70  17.19* 664.50  89.06** 4.60  0.74** 15.05  6.25

All values are expressed as mean  SD (n ¼ 8) ANOVA followed by Tukey test was used for statistical analysis * p < 0.05 and **p < 0.01 versus acrylamide control group # p < 0.05 and ##p < 0.01 versus normal control group TNF-α tumor necrosis factor-α, hs-CRP high-sensitive C-reactive protein, CE cinnamon extract

Table 3 Effect of CE administration on liver enzymes activities Groups

ALT (U/dL)

AST (U/dL)

ALP (U/dL)

63.00  17.22

218.42  23.45

632.71  188.09

81.12  13.76#

204.37  80.93

645.50  244.28

Acrylamide + CE (250 mg/kg/day)

65.62  40.18

143.00  66.15

647.00  266.07

Acrylamide + CE (500 mg/kg/day)

76.50  22.69

153.12  62.75

781.25  155.04

Normal control Acrylamide control

All values are expressed as mean  SD (n ¼ 8) ANOVA followed by Tukey test was used for statistical analysis # p < 0.05 ALT alanine transaminase, AST aspartate transaminase, ALP alkaline phosphatase, CE cinnamon extract

4

Notes 1. Thirty-two male Wistar rats, aged 6–8 weeks, with a body weight of 150–200 g, were purchased from the Physiology Research Center of Ahvaz University of Medical Sciences. 2. Cinnamon barks were purchased from local market and identified and authenticated by an expert from Ahvaz Chamran University. 3. For inducing acrylamide toxicity in rats [24, 25]. 4. For administration of the cinnamon aqueous extract. 5. For anesthesia of the rats.

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6. For perfusion of the liver. 7. All assays used were for the determination of antioxidant status in the rats. 8. For determining the concentration of malondialdehyde (MDA). 9. These kits were used for determining the levels of released enzymes as markers of liver damage. 10. Before beginning experiments, obtain the appropriate ethics committee approval. In this study, the animals were acclimatized in a quite controlled animal room set at 22  3
C and 55  5% humidity, using a 12:12 h light:dark cycle, with free access to a standard pellet diet and water. 11. The study was approved by and performed under the guidelines of the Research Ethics Committee of Ahvaz Jundishapur University of Medical Sciences, Iran (NRC-9414). 12. The protocol of extract preparation based on a study by Gaique et al. [22]. 13. All data were found to be normally distributed. 14. The results showed that the acrylamide toxicity-induced control group had significant lower serum and liver TAS levels compared to the normal control group (P ¼ 0.005 and P ¼ 0.002, respectively). Also, the acrylamide toxicity-induced control group had significant higher serum and liver MDA levels in comparison to the normal control group (P ¼ 0.05 and P ¼ 0.021, respectively). The administration of cinnamon at both dosages led to an increase in serum and liver TAS levels (P < 0.05) and decreased serum and liver MDA levels compared to the acrylamide toxicity-induced control group (P < 0.05). This was consistent with the findings of a previous study showing the antioxidant capacity of cinnamon [17, 19, 24–26]. 15. The results showed increased levels of TNFα, hs-CRP, and leptin in the acrylamide-treated control group compared to the normal control group (P ¼ 0.021, P ¼ 0.002 and P ¼ 0.005, respectively). The administration of both dosages of cinnamon led to a significant decrease in the serum levels of TNFα and hs-CRP and leptin compared to the acrylamidetreated controls (P < 0.05). However, this effect did not reach significance for hs-CRP in the group treated with 250 mg/kg cinnamon (P ¼ 0.055). In addition, the adiponectin levels in the acrylamide-treated control group were not significantly different from those in the normal control group (P ¼ 0.145), and therefore, the cinnamon administration had no significant effect. This study suggests improvement in the levels of inflammatory markers via the antioxidant components

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of cinnamon, consistent with previous studies indicating the presence of flavonoids, anthraquinone, glycosides, alkaloids, steroids, tannins, and terpenoids in cinnamon bark [27]. Some of these phytochemicals, such as flavonoids, triterpenoids, saponins, and alkaloids, have shown hepatoprotective activity [28–31]. 16. The results showed a significant increase in ALT activity (P ¼ 0.041) in the acrylamide-treated group compared to the normal control group with no effect on AST and ALP activities. These findings are consistent with previous studies with regard to ALT but not for AST and ALP activities following acrylamide treatment [2, 7, 10]. In addition, we found no effect of either dosage of cinnamon on the ALT activity levels compared to the nontreated group, consistent with previous studies [32–34]. However other studies have suggested beneficial effects of cinnamon on aminotransferase enzymes [35– 37]. These discrepancies may due to differences in dosage and duration of the cinnamon treatment. 17. The present study provides evidence that oral administration of cinnamon partially improved liver injury in acrylamide-treated rats by decreasing inflammatory factors. It is proposed that the mechanism of cinnamon extract action is via scavenging of free radicals and reduction in the levels of inflammatory biomarkers.

Acknowledgments This work was financially supported by a grant from Nutrition and Metabolic Disease Research Center, Ahvaz Jundishapur University of Medical Sciences (Grant Number: NRC-9414). References 1. Mroueh M, Saab Y, Rizkallah R (2004) Hepatoprotective activity of Centaurium erythraea on acetaminophen-induced hepatotoxicity in rats. Phytother Res 18(5):431–433 2. Ansar S, Siddiqi NJ, Zargar S, Ganaie MA, Abudawood M (2016) Hepatoprotective effect of quercetin supplementation against acrylamide-induced DNA damage in wistar rats. BMC Complement Altern Med 16 (1):327. https://doi.org/10.1186/s12906016-1322-7 3. Lasekan O, Abbas K (2010) Analysis of volatile flavour compounds and acrylamide in roasted Malaysian tropical almond (Terminalia catappa) nuts using supercritical fluid extraction. Food Chem Toxicol 48(8):2212–2216

4. Papousˇek R, Pataj Z, Nova´kova´ P, Lemr K, Barta´k P (2014) Determination of acrylamide and acrolein in smoke from tobacco and E-cigarettes. Chromatographia 77 (17–18):1145–1151 5. Taubert D, Glo¨ckner R, Mu¨ller D, Scho¨mig E (2006) The garlic ingredient diallyl sulfide inhibits cytochrome P450 2E1 dependent bioactivation of acrylamide to glycidamide. Toxicol Lett 164(1):1–5 6. Hansen SH, Olsen AK, Søderlund EJ, Brunborg G (2010) In vitro investigations of glycidamide-induced DNA lesions in mouse male germ cells and in mouse and human lymphocytes. Mutat Res 696(1):55–61

Testing the Effects of Cinnamon Extract Supplementation on Inflammation. . . 7. Watzek N, Scherbl D, Schug M, Hengstler JG, Baum M, Habermeyer M et al (2013) Toxicokinetics of acrylamide in primary rat hepatocytes: coupling to glutathione is faster than conversion to glycidamide. Arch Toxicol 87 (8):1545–1556 8. Zhao M, Wang P, Zhu Y, Liu X, Hu X, Chen F (2015) Blueberry anthocyanins extract inhibits acrylamide-induced diverse toxicity in mice by preventing oxidative stress and cytochrome P450 2E1 activation. J Funct Foods 14:95–101 9. Septembre-Malaterre A, Le Sage F, Hatia S, Catan A, Janci L, Gonthier MP (2016) Curcuma longa polyphenols improve insulinmediated lipid accumulation and attenuate proinflammatory response of 3T3-L1 adipose cells during oxidative stress through regulation of key adipokines and antioxidant enzymes. Biofactors 42(4):418–430 ¨, 10. Alturfan AA, Tozan-Beceren A, S¸ehirli AO Demiralp E, S¸ener G, Omurtag GZ (2012) Resveratrol ameliorates oxidative DNA damage and protects against acrylamide-induced oxidative stress in rats. Mol Biol Rep 39 (4):4589–4596 11. Liu S, Jiang L, Zhong T, Kong S, Zheng R, Kong F et al (2015) Effect of acrylamide on oocyte nuclear maturation and cumulus cells apoptosis in mouse in vitro. PLoS One 10(8): e0135818. https://doi.org/10.1371/journal. pone.0135818 12. Jiang L, Cao J, An Y, Geng C, Qu S, Jiang L et al (2007) Genotoxicity of acrylamide in human hepatoma G2 (HepG2) cells. Toxicol In Vitro 21(8):1486–1492 13. Goffeng LO, Kjuus H, Heier MS, Alvestrand M, Ulvestad B, Skaug V (2008) Colour vision and light sensitivity in tunnel workers previously exposed to acrylamide and N-methylolacrylamide containing grouting agents. Neurotoxicology 29(1):31–39 14. Braithwaite I, Stewart AW, Hancox RJ, Beasley R, Murphy R, Mitchell EA et al (2014) Fast-food consumption and body mass index in children and adolescents: an international cross-sectional study. BMJ Open 4(12): e005813. https://doi.org/10.1136/ bmjopen-2014-005813 15. Einstein A, Podolsky B, Rosen N (1935) Can quantum-mechanical description of physical reality be considered complete? Phys Rev 47 (10):777–780. http://inters.org/files/ einsteinetal1935.pdf 16. Mohamed Sham Shihabudeen H, Hansi Priscilla D, Thirumurugan K (2011) Cinnamon extract inhibits α-glucosidase activity and dampens postprandial glucose excursion in

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diabetic rats. Nutr Metab (Lond) 8(1):46. https://doi.org/10.1186/1743-7075-8-46 17. El-Baroty GS, El-Baky HA, Farag R, Saleh MA (2010) Characterization of antioxidant and antimicrobial compounds of cinnamon and ginger essential oils. Afr J Biochem Res 4 (6):167–174 18. Hagenlocher Y, Ho¨sel A, Bischoff SC, Lorentz A (2016) Cinnamon extract reduces symptoms, inflammatory mediators and mast cell markers in murine IL-10/ colitis. J Nutr Biochem 30:85–92 19. Roussel AM, Hininger I, Benaraba R, Ziegenfuss TN, Anderson RA (2009) Antioxidant effects of a cinnamon extract in people with impaired fasting glucose that are overweight or obese. J Am Coll Nutr 28(1):16–21 20. Zhang K, Han ES, Dellinger TH, Lu J, Nam S, Anderson RA et al (2016) Cinnamon extract reduces VEGF expression via suppressing HIF-1α gene expression and inhibits tumor growth in mice. Mol Carcinog 56(2):436–446 21. Eidi A, Mortazavi P, Bazargan M, Zaringhalam J (2012) Hepatoprotective activity of cinnamon ethanolic extract against CCL 4-induced liver injury in rats. EXCLI J 11:495–507 22. Gaique TG, Lopes BP, Souza LL, Paula GS, Pazos-Moura CC, Oliveira KJ (2015) Cinnamon intake reduces serum T3 level and modulates tissue-specific expression of thyroid hormone receptor and target genes in rats. J Sci Food Agric 96(8):2889–2895 23. Haidari F, Omidian K, Rafiei H, Zarei M, MohamadShahi M (2013) Green tea (Camellia sinensis) supplementation to diabetic rats improves serum and hepatic oxidative stress markers. Iran J Pharm Res 12(1):109–114 24. Gunawardena D, Karunaweera N, Lee S, van Der Kooy F, Harman DG, Raju R et al (2015) Anti-inflammatory activity of cinnamon (C. zeylanicum and C. cassia) extracts–identification of E-cinnamaldehyde and o-methoxycinnamaldehyde as the most potent bioactive compounds. Food Funct 6 (3):910–919 25. Dehghan G, Shaghaghi M, Jafari A, Mohammadi M, Badalzadeh R (2014) Effect of endurance training and cinnamon supplementation on post-exercise oxidative responses in rats. Mol Biol Res Commun 3(4):269–281 26. Wang F, Pu C, Zhou P, Wang P, Liang D, Wang Q et al (2015) Cinnamaldehyde prevents endothelial dysfunction induced by high glucose by activating nrf2. Cell Physiol Biochem 36(1):315–324 27. Shihabudeen HMS, Priscilla DH, Thirumurugan K (2011) Cinnamon extract inhibits

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α-glucosidase activity and dampens postprandial glucose excursion in diabetic rats. Nutr Metab (Lond) 8(1):46. https://doi.org/10. 1186/1743-7075-8-46 28. Kokanova-Nedialkova Z, Nedialkov P, Kondeva-Burdina M, Simenova R, Tsankova V, Nikolov S (2016) Good kingHenry (Chenopodium bonus-henricus L.)—a source of hepatoprotective flavonoids. Planta Med 81(S 01):S1–S381. https://doi.org/10. 1055/s-0036-1596856 29. Wang GW, Deng LQ, Luo YP, Liao ZH, Chen M (2016) Hepatoprotective triterpenoids and lignans from the stems of Schisandra pubescens. Nat Prod Res 31(16):1855–1860 30. Zheng YF, Wei JH, Fang SQ, Tang YP, Cheng HB, Wang TL et al (2015) Hepatoprotectivetriterpenesaponins from the roots of Glycyrrhizainflata. Molecules 20(4):6273–6283 31. Raj VP, Chandrasekhar RH, Vijayan P, Dhanaraj S, Rao MC, Rao VJ et al (2010) In vitro and in vivo hepatoprotective effects of the total alkaloid fraction of Hygrophilaauriculata leaves. Indian J Pharmacol 42(2):99–104 32. Koochaksaraie R, Irani M, Gharavysi S (2011) The effects of cinnamon powder feeding on some blood metabolites in broiler chicks. Rev Bras Cieˆnc Avı´c 13(3):197–202

33. Wickenberg J, Lindstedt S, Nilsson J, Hlebowicz J (2014) Cassia cinnamon does not change the insulin sensitivity or the liver enzymes in subjects with impaired glucose tolerance. Nutr J 13(1):1. https://doi.org/10.1186/14752891-13-96 34. Lu T, Sheng H, Wu J, Cheng Y, Zhu J, Chen Y (2012) Cinnamon extract improves fasting blood glucose and glycosylated hemoglobin level in Chinese patients with type 2 diabetes. Nutr Res 32(6):408–412 35. Askari F, Rashidkhani B, Hekmatdoost A (2014) Cinnamon may have therapeutic benefits on lipid profile, liver enzymes, insulin resistance, and high-sensitivity C-reactive protein in nonalcoholic fatty liver disease patients. Nutr Res 34(2):143–148 36. Amin KA, El-Twab A (2009) Oxidative markers, nitric oxide and homocysteine alteration in hypercholesterolimic rats: role of atorvastatine and cinnamon. Int J Clin Exp Med 2 (3):254–265 37. Moselhy SS, Ali HK (2009) Hepatoprotective effect of cinnamon extracts against carbon tetrachloride induced oxidative stress and liver injury in rats. Biol Res 42(1):93–98

Chapter 12 Proteomic Mapping of the Human Myelin Proteome Paul C. Guest Abstract Alzheimer’s disease (AD) is a degenerative cognitive condition that affects individuals with an increasing prevalence in older age groups. There are currently five drugs on the market for AD but no new effective ones have been discovered for decades. There has been increasing interest in the use of natural remedies such as special diets and plant extracts but these require further study. Based on the known effects on white matter and neuronal conductance in Alzheimer’s disease, we present a protocol for proteomic analysis of myelin-enriched brain fractions as a way of identifying potential biomarkers of efficacy. This fingerprint could be used in screening assays for novel compounds for treatment of AD. Keywords Oligodendrocytes, Myelin, Proteome, Pathway, Biomarker, Drug target

1

Introduction There have been many theories about the pathological processes involved in Alzheimer’s disease (AD), although most of these involve accumulation of neuronal amyloid beta plaques and neurofibrillary tangles which disrupt neuronal functioning and synaptic connectivity [1]. Previous studies have shown these effects also lead to alterations in the insulating myelin sheath around neuronal axons which are essential components involved in the conduction of neuronal signals [2]. Other effects include alterations in oligodendrocytes and expression of genes involved in myelin function [3]. Emerging evidence suggests that inflammation and damaging oxidative processes may be involved in the pathophysiology of AD. For this reason, a number of anti-inflammatory drugs have been tested in attempts to improve symptoms [4]. However, most of these have demonstrated little efficacy with some adverse effects [5]. For this reason, natural substances have also been tested. For example, the turmeric rhizome compound curcumin has been found to have neuroprotective functions such as inhibition of Ab

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_12, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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plaque and tau tangle formation [6, 7]. In addition, several studies have shown that coffee consumption is associated with a lower risk of developing Alzheimer disease [8]. This effect may be “J-shaped” with lower risk for cognitive dysfunction occurring with consumption of 1–2 cups of coffee per day [9]. Increasing evidence has also shown that healthy eating and increased physical exercise may help to delay the onset or prevent AD [10–12]. In the case of nutritional effects, administration of a medicinal food called CerefolinNAC® for 18 months led to significant reductions in brain atrophy rates in patients with AD or vascular dementia [13]. Another study showed that consumption of the triglyceride-based medicinal food Axona® appeared to be effective in mild AD cases [14]. Also, the traditional Mediterranean diet may reduce the risk of AD and reverse the Aβ deposition and neurodegeneration process [15]. Physical exercise is well known to have beneficial effects in a variety of diseases [11, 12] and can lead to improvement is some features of AD, such as a reduction in oxidative stress [16] and improved insulin signaling [17]. Exercise may also increase the process of neurogenesis in the hippocampus, which is a major factor involved in synaptic connectivity [18]. Furthermore, it has been shown to enhance functioning in elderly persons with mild cognitive impairment [19, 20]. A number of studies have also shown that exercises such as running can protect against myelin sheath loss in animal models of AD [21, 22] and depression [23]. Myelin is composed of lipids with a well-characterized composition consisting mainly of galactolipids and cholesterol [24]. A number of proteins have also been detected in association with the oligodendrocytes and the myelin sheath, mainly through gel-based proteome analyses [25, 26]. The most prominent of these include myelin basic protein (MBP) and proteolipid protein (PLP). However, the myelin sheath proteome contains at least 200 additional proteins which are likely to be critical in oligodendrocyte and myelin function [25, 26]. Here, we present a protocol for comprehensive characterization of myelin proteins via homogenization of postmortem brain tissue, enrichment of a myelin fraction using density gradient centrifugation, and proteomic profiling using liquid chromatography tandem mass spectrometry (LC-MS/MS). Further studies of these proteins may help in the development of new biomarkers for use as molecular readouts in studies testing new compounds in models of AD.

2

Materials

2.1 Density Gradient Centrifugation

1. Human brain samples collected postmortem from 12 chronic schizophrenia patients and 8 healthy controls (see Note 1).

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2. Homogenization buffer: 0.32 M sucrose, 1 mM EDTA, 5 mM Tris, pH 7.4). 3. 3, 10, 15, and 23% Percoll solutions in 0.32 M sucrose, 1 mM EDTA, 0.25 mM dithiothreitol (DTT), and 5 mM Tris (pH 7.4) (see Note 2). 4. 12 mL capacity polycarbonate centrifuge tubes. 5. Benchtop micro-centrifuge and ultra-centrifuge. 6. Sample buffer: 6% sodium dodecyl sulphate (SDS), 100 mM Tris pH 6.8, 30% glycerol, 100 mM dithiothreitol (DTT), and 0.001% w/v bromophenol blue. 7. Bradford protein assay kit. 2.2

Electrophoresis

1. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) sample buffer: 6% SDS, 100 mM Tris (pH 6.8), 30% glycerol, 100 mM DTT, and 0.001% bromophenol blue. 2. 12% bis-tris polyacrylamide gels polymerized using a standard protocol [27]. 3. Electrophoresis power supply. 4. Scalpel.

2.3

LC-MS/MS

1. 0.1% formic acid. 2. Nano-high-performance CA, USA).

LC

system

(Eksigent,

Dublin,

3. LTQ XL-Orbitrap mass spectrometer (Thermo Scientific, Bremen, Germany). 4. Solvent A: 94.9% water, 5% acetonitrile, and 0.1% formic acid. 5. Solvent B: 99.9% acetonitrile and 0.1% formic acid. 6. MASCOT Distiller (Matrix Sciences, London, UK). 7. Metascape. 8. Search Tool for the Retrieval of Interacting Genes/Proteins (STRING).

3

Methods

3.1 Percoll Density Gradient Centrifugation

1. Prepare Percoll gradients by adding 2 mL of 23% Percoll to the bottom of each centrifuge tube and carefully layer 2 mL of 15, 10, and 3% Percoll on top of this (see Note 3). 2. Mechanically disrupt 1 g freshly thawed and chopped brain tissue in 9 mL ice-cold homogenization buffer (see Note 4). 3. Centrifuge at 100
g for 10 min at 4  C. 4. Recover the supernatant and dilute to 10 mL in homogenization buffer.

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Brain homogenate Centrifuge 1000 x g, 10 min

Supernatant

Pellet

centrifuge 31000 x g, 5 min

Percoll

0% 3% Myelin 10% 15% 23%

Fig. 1 Percoll density gradient centrifugation protocol for enrichment of the myelinome from postmortem brain tissue

5. Determine the protein concentration using the Bradford assay (see Note 5). 6. Carefully layer 2 mL supernatant containing 8–10 mg total protein on the top of the 3% Percoll layer in the centrifuge tube. 7. Centrifuge 5 min at 31,000
g at 4  C. 8. Recover a fraction enriched in myelin biomarkers from the 3/10% interface as described by Dunkley et al. [28] (Fig. 1). 3.2 Electrophoresis (See Note 6)

1. Dilute samples 10
and estimate the protein content using the Bradford assay. 2. Add sample loading buffer and heat samples for 5 min at 95  C. 3. Centrifuge briefly to collect liquid in the bottom of the tube and separate the proteins by electrophoresis on the 12% SDS-PAGE gels. 4. Electrophorese for 5 min after the bromophenol blue dye front reaches the separating gel. 5. Cut each well with the scalpel from the top of the gel down to the dye front.

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195

6. Mince each gel piece and digest with trypsin in situ as described previously [29]. 7. Lyophilize the resulting peptides and freeze at 80  C before LC-MS/MS analysis. 3.3

LC-MS/MS

1. Suspend lyophilized peptides in 0.1% formic acid (see Note 7). 2. Inject into the high-performance LC system coupled to the LTQ XL-Orbitrap mass spectrometer (see Note 8). 3. Separate the peptides using a discontinuous linear gradient from 98% solvent A and 2% solvent B to 40% solvent A and 60% solvent B (see Note 9). 4. Carry out data acquisition as described [30] using the following fragmentation parameters: repeat duration time, 30 s; isolation width, 2 mm; activation time, 30 ms; normalized collision energy, 35 V; and activation, Q ¼ 0.250. 5. Use MASCOT Distiller for protein identification as previously described [31] using the criteria outlined in Table 1. 6. Identify proteins for quantitation using criteria in Table 2. 7. Submitted altered proteins to in silico systems biology analyses using Metascape to identify the top 10 pathways, cellular compartments, and diseases associated with the dataset (see Notes 10 and 11). 8. Determine the most enriched pathways and hub proteins using STRING [32] (see Notes 10 and 12).

Table 1 Criteria for peptide identification using MASCOT Distiller Criteria

Value

Peptide mass accuracy

10 ppm

Fragment ion mass accuracy

0.5 Da

Peptide false discovery rate (FDR)

1%

Protein FDR

1%

Maximum missed cleavages

2

Enzyme

Trypsin

Fixed modification

Carbamidomethylation

Variable modification

Methionine oxidation

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Table 2 Criteria for protein identification for quantitative analysis

4

Criteria

Value

Number nonredundant peptides

>2

Minimum fold change

1.5

Standard deviation

10

Analysis of variance

P  0.05

Notes 1. Samples from schizophrenia patients were from the Nordbaden Psychiatric Center (Wiesloch, Germany), and the control samples were from the Institute of Neuropathology, Heidelberg University (Heidelberg, Germany). All subjects were Caucasian Germans, with no history of alcohol or drug abuse, and free from somatic and neurodegenerative diseases by neuropathological characterization (Braak staging lower than II) [33]. Samples were collected postmortem from mentally healthy individuals with no history of antidepressant or antipsychotic during usage. The study was approved by the Ethics Committee of the Medical School of Heidelberg University, and all subjects had given written consent for the use of their tissues for medical research. 2. Percoll is composed of colloidal silica particles 15–30 nm in diameter coated with polyvinylpyrrolidone. It is used commonly for density gradient purification of cells and subcellular compartments as it has low viscosity and low osmolarity, with no toxicities. 3. This can be achieved with a peristaltic pump or handheld pipette, taking care not to disturb the layers. One trick is to load from the bottom up such that the less-dense layers are applied first and underlayered with successively layers of increasing density. 4. This can be performed using a number of instruments such as a glass tube homogenizer, sonicator, polytron, or other cell disrupters. 5. This should result in 4–5 mg protein/mL buffer. If too high, dilute accordingly. If too low, redo the extraction using a greater tissue:buffer ratio. 6. Electrophoresis is performed as a cleanup step to remove the percoll and other reagents prior to mass spectrometry.

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7. Formic acid is used because it provides protons for LC-MS/ MS analysis in positive ionization mode in the form of [M + H]+ ions. 8. This is the basic instrumentation used in this study. Although other instruments and components can be used, these must be optimized for the specific experimental design and targeted outcomes. 9. There are many advantages for the use of gradient LC in MS experiments including peptide separation, mitigation of ion suppression, and the resulting higher peak capacity. 10. These analytical software are freely available. Other such tools can be used for similar purposes, such as the Ingenuity Pathways Knowledgebase (available for purchase from Qiagen). 11. This study resulted in the most comprehensive characterization of the human myelinome with the identification of 480 distinct proteins, and 172 of these proteins were present at different levels in the schizophrenia patients compared to the controls (Table 3) [34]. Most of these altered proteins had roles in glial cell differentiation, metabolism/energy, synaptic vesicle function, and neurodegeneration. 12. The STRING analysis showed that the hub proteins with the highest degree of connectivity in the network consistent of kinases and synaptic vesicle transport proteins which may represent drug targets. In addition, the findings suggested that disruptive effects on synaptic activity occur in schizophrenia, and this supports the disconnectivity hypothesis of this neuropsychiatric disease.

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Table 3 List of proteins present at different levels in the myelinome fraction from schizophrenia patients (SZ) compared to controls (CT). Proteins in red font were increased and those in green were decreased in SZ compared to controls Gene LSAMP PRNP OPCML PDE2A PFN2 CAMKV PPP3R1 CDC42 SIRT2 DNAJC5 VAMP2 CAP2 CRMP1 NAPB GNAQ NIPSNAP2 ENDOD1 CPLX2 CBR1 PRDX1 QDPR HPRT1 MDH1 FLOT1 GAP43 TPM1 TPM2 PKM RTN1 HRAS CAPZA2 GDI1 ATP1B1 PPIB BCAN CDK5 NDRG2 MAPRE2 NCAN DPYSL2 TOMM70 GPM6A LDHB ATP2A2 ATP6V1D SEPTIN7 MARCKS SYN2 CALM1 ENO2 NRGN MOG

SZ/CT 22.92 14.69 9.50 9.35 8.08 4.33 4.17 4.00 3.82 3.77 3.49 3.47 3.39 3.38 3.38 3.36 3.36 3.32 3.22 3.20 3.15 3.11 2.92 2.89 2.89 2.89 2.89 2.80 2.71 2.65 2.57 2.53 2.52 2.51 2.51 2.46 2.41 2.34 2.33 2.32 2.27 2.26 2.25 2.20 2.14 2.09 2.09 2.06 2.04 2.04 2.04 2.03

Protein Name Limbic system-associated membrane protein Major prion protein Opioid-binding protein/cell adhesion molecule cGMP-dependent 3',5'-cyclic phosphodiesterase Profilin-2 CaM kinase-like vesicle-associated protein Calcineurin subunit B type 1 Cell division control protein 42 homolog NAD-dependent deacetylase sirtuin-2 DnaJ homolog subfamily C member 5 Vesicle-associated membrane protein 2 Adenylyl cyclase-associated protein 2 Dihydropyrimidinase-related protein 1 Beta-soluble NSF attachment protein Guanine nucleotide-binding protein G(q) subunit alpha Protein NipSnap homolog 2 Endonuclease domain-containing 1 protein Complexin-2 Carbonyl reductase [NADPH] 1 Peroxiredoxin-1 Dihydropteridine reductase Hypoxanthine-guanine phosphoribosyltransferase Malate dehydrogenase, cytoplasmic Flotillin-1 Neuromodulin Tropomyosin alpha-1 chain Tropomyosin beta chain Pyruvate kinase isozymes M1/M2 Reticulon-1 GTPase HRas F-actin-capping protein subunit alpha-2 Rab GDP dissociation inhibitor alpha Sodium/potassium-transporting ATPase subunit beta-1 Peptidyl-prolyl cis-trans isomerase B Brevican core protein Cell division protein kinase 5 Protein NDRG2 Microtubule-associated protein RP/EB family member 2 Neurocan core protein Dihydropyrimidinase-related protein 2 Mitochondrial import receptor subunit TOM70 Neuronal membrane glycoprotein M6-a L-lactate dehydrogenase B chain Sarcoplasmic/endoplasmic reticulum calcium ATPase 2 V-type proton ATPase subunit D Septin-7 Myristoylated alanine-rich C-kinase substrate Synapsin-2 Calmodulin Gamma-enolase Neurogranin Myelin-oligodendrocyte glycoprotein

(continued)

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Table 3 (continued) SNAP91 TPM3 SLC25A18 TMOD2 SNCB SV2A HPCAL4 GDI2 AK1 DYNLL1 CNP PPP3CA EHD3 HSPA2 COX6C SNCA SEPTIN2 PGK1 CANX CLTA HSPA1A HSPA8 CAND1 HSPA6 SH3GL2 SFXN3 HSP90B1 PFKL VSNL1 CD9 CRYM ALDH2 TAGLN3 GSTP1 STMN1 ACTN3 MAPK1 SLC17A7 GOT1 MIF GNAO1 GDAP1 CCT4 ATP6V1H ATL1 CCT6A TAGLN SLC2A1 LGALS1 TUBA8 MAP2K1 SLC12A5 BIN1 TUBA4A

2.02 2.01 2.00 1.99 1.98 1.93 1.92 1.91 1.91 1.91 1.89 1.86 1.86 1.85 1.85 1.82 1.80 1.80 1.79 1.79 1.78 1.78 1.75 1.72 1.71 1.69 1.65 1.64 1.63 1.63 1.59 1.59 1.59 1.59 1.58 1.58 1.57 1.57 1.57 1.56 1.52 1.51 1.51 1.50 0.66 0.66 0.66 0.64 0.63 0.63 0.62 0.62 0.61 0.60

Clathrin coat assembly protein AP180 Tropomyosin alpha-3 chain Mitochondrial glutamate carrier 2 Tropomodulin-2 Beta-synuclein Synaptic vesicle glycoprotein 2A Hippocalcin-like protein 4 Rab GDP dissociation inhibitor beta Adenylate kinase isoenzyme 1 Dynein light chain 1, cytoplasmic 2',3'-cyclic-nucleotide 3'-phosphodiesterase Serine/threonine-protein phosphatase 2B catalytic subunit alpha isoform EH domain-containing protein 3 Heat shock-related 70 kDa protein 2 Cytochrome c oxidase subunit 6C Alpha-synuclein Septin-2 Phosphoglycerate kinase 1 Calnexin Clathrin light chain A Heat shock 70 kDa protein 1 Heat shock cognate 71 kDa protein Cullin-associated NEDD8-dissociated protein 1 Heat shock 70 kDa protein 6 Endophilin-A1 Sideroflexin-3 Endoplasmin 6-phosphofructokinase, liver type Visinin-like protein 1 CD9 antigen Mu-crystallin homolog Aldehyde dehydrogenase, mitochondrial Transgelin-3 Glutathione S-transferase P Stathmin Alpha-actinin-3 Mitogen-activated protein kinase 1 Vesicular glutamate transporter 1 Aspartate aminotransferase, cytoplasmic Macrophage migration inhibitory factor Guanine nucleotide-binding protein G(o) subunit alpha Ganglioside-induced differentiation-associated protein 1 T-complex protein 1 subunit delta V-type proton ATPase subunit H Atlastin-1 T-complex protein 1 subunit zeta Transgelin Solute carrier family 2, facilitated glucose transporter member 1 Galectin-1 Tubulin alpha-8 chain Dual specificity mitogen-activated protein kinase kinase 1 Solute carrier family 12 member 5 Myc box-dependent-interacting protein 1 Tubulin alpha-4A chain

(continued)

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Table 3 (continued) MT-CO2 TUBB8 NCALD CLU EEF1A1 MGST3 ACAT1 CKB CADM2 EPB41L3 PLP1 SEPTIN5 BASP1 GFAP CSRP1 PTPRZ1 CTNNB1 PRKAR2B ANXA2 DNM1L CLTB PSMA4 CADM1 NCDN GJA1 NPTN PDHB NCAM2 CYCS DDAH1 PURA MAG ANXA5 PRKACB MYL6 MATR3 FLNA OLFM1 MAP1A CLDN11 SFRS3 VIM CALR PGAM1 ATP6V1G2 ATP1B2 VAPA IDH3A MYH9 SLC1A3 PC NONO BSN GLUL

0.60 0.60 0.59 0.59 0.56 0.55 0.55 0.55 0.54 0.54 0.51 0.50 0.50 0.47 0.47 0.47 0.47 0.45 0.44 0.44 0.43 0.43 0.42 0.42 0.42 0.41 0.41 0.41 0.41 0.40 0.40 0.38 0.38 0.37 0.36 0.35 0.35 0.35 0.34 0.34 0.34 0.34 0.30 0.30 0.27 0.26 0.26 0.25 0.22 0.22 0.20 0.20 0.19 0.19

Cytochrome c oxidase subunit 2 Tubulin beta-8 chain Neurocalcin-delta Clusterin Elongation factor 1-alpha 1 Microsomal glutathione S-transferase 3 Acetyl-CoA acetyltransferase, mitochondrial Creatine kinase B-type Cell adhesion molecule 2 Band 4.1-like protein 3 Myelin proteolipid protein Septin-5 Brain acid soluble protein 1 Glial fibrillary acidic protein Cysteine and glycine-rich protein 1 Receptor-type tyrosine-protein phosphatase zeta Catenin beta-1 cAMP-dependent protein kinase type II-beta regulatory subunit Annexin A2 Dynamin-1-like protein Clathrin light chain B Proteasome subunit alpha type-4 Cell adhesion molecule 1 Neurochondrin Gap junction alpha-1 protein Neuroplastin Pyruvate dehydrogenase E1 component subunit beta, mitochondrial Neural cell adhesion molecule 2 Cytochrome c N(G),N(G)-dimethylarginine dimethylaminohydrolase 1 Transcriptional activator protein Pur-alpha Myelin-associated glycoprotein Annexin A5 cAMP-dependent protein kinase catalytic subunit beta Myosin light polypeptide 6 Matrin-3 Filamin-A Noelin Microtubule-associated protein 1A Claudin-11 Splicing factor, arginine/serine-rich 3 Vimentin Calreticulin Phosphoglycerate mutase 1 V-type proton ATPase subunit G 2 Sodium/potassium-transporting ATPase subunit beta-2 Vesicle-associated membrane protein-associated protein A Isocitrate dehydrogenase [NAD] subunit alpha, mitochondrial Myosin-9 Excitatory amino acid transporter 1 Pyruvate carboxylase, mitochondrial Non-POU domain-containing octamer-binding protein Protein bassoon Glutamine synthetase

(continued)

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Table 3 (continued)

LMNB2 NEFH SUCLG1 HAPLN2 LMNA FGB ACTR1A HSPG2 FGA PKP2 FGG GNG3

0.17 0.16 0.15 0.13 0.11 0.07 0.07 0.06 0.06 0.05 0.04 0.02

Lamin-B2 Neurofilament heavy polypeptide Succinyl-CoA ligase [GDP-forming] subunit alpha, mitochondrial Hyaluronan and proteoglycan link protein 2 Lamin-A/C Fibrinogen beta chain Alpha-centractin Basement membrane-specific heparan sulfate proteoglycan core protein Fibrinogen alpha chain Plakophilin-2 Fibrinogen gamma chain Guanine nucleotide-binding protein G(I)/G(S)/G(O) subunit gamma-3

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Chapter 13 Testing for Thyroid Peroxidase and Antineuronal Antibodies in Depression and Schizophrenia Johann Steiner, Winfried Stoecker, Bianca Teegen, Henrik Dobrowolny, Gabriela Meyer-Lotz, Katrin Borucki, Paul C. Guest, and Hans-Gert Bernstein Abstract Dietary interventions and physical exercise may improve some symptoms in mental illnesses such as major depression and schizophrenia. Hashimoto’s thyroiditis is a known risk factor for these conditions and is marked by the presence of circulating antibodies to thyroid peroxidase (TPO) and thyroglobulin (TG). This chapter presents a protocol to determine if patients with major depression or schizophrenia contain high circulating levels of these antibodies relative to healthy controls. We also describe a procedure testing for the presence of other circulating biomarkers related to brain function, including antibodies directly related to neuronal function. This analysis was performed by screening biochip mosaics of frozen tissue sections and transfected HEK293 cells expressing target antigens using patient and control sera. Finally, we describe a correlation analysis of these markers with symptom scores at baseline and after 6 weeks treatment of the patients using antipsychotics or antidepressants as appropriate. Keywords Hashimoto thyroiditis, Mental disorder, Depression, Schizophrenia, Neuronal antibodies, Psychiatric symptom scores

1

Introduction Mental illnesses such as depressive disorders and schizophrenia are major contributors to the global burden of disease and associated healthcare costs [1]. Although the primary line of therapy for these disorders involves pharmacological and psychological interventions, not all people respond favorably. Thus, alternative approaches such as dietary and exercise-based interventions should be considered for prevention and treatment. The results of a preliminary study conducted in 2017 suggested the potential benefits of exercise for impaired cognition in major depression [2]. A study in 2018 found that chronic schizophrenia patients may experience

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_13, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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hippocampal plasticity in response to exercise [3]. A review from a research group in India found a positive impact of exercise in severe and common mental disorders [4]. In addition, a meta-analysis of randomized controlled trials showed that dietary interventions significantly reduced depressive symptoms [5]. Another review of nine clinical studies found an overall significant effect of the turmeric-derived natural compound curcumin on reduction of depressive and anxiety symptoms, with a large effect size [6]. This compound is thought to work through its anti-inflammatory and antioxidant properties. Epidemiological studies have led to the suggestion that autoimmune diseases such as type 1 diabetes mellitus and Hashimoto’s thyroiditis can lead to increased risk of psychiatric disorders such as depression and schizophrenia [7–9]. In the case of Hashimoto’s thyroiditis, an encephalopathy form can occur (HE) in which the molecular diagnostic features include serum autoantibodies against thyroid peroxidase and thyroglobulin, which are present in most of the affected cases [10]. The symptoms can sometimes include psychiatric manifestations such as memory deficits, disorientation, epileptic seizures, psychosis, and depression or anxiety [11, 12]. However, these findings have remained controversial due to poor evidence for causation of the psychiatric manifestations through interactions between thyroid antibodies and neurons [13, 14]. For this reason, it has been proposed that HE should be considered as a diagnosis for autoimmune-based psychiatric symptoms combined with positive tests for antibodies against neuronal proteins [12, 14]. In addition, we have proposed that thyroid antibody carriers may show increased levels of specific neuronal antibodies as a risk factor for psychiatric diseases [15]. Consistent with this idea, case reports have shown that suspected HE patients were found to be positive for N-methyl-D-aspartate receptor (NMDAR) antibodies [16–18]. This chapter presents a protocol for measurement of thyroid and brain-related antibodies in serum from acutely ill major depression and schizophrenia patients in comparison to healthy control participants. We also summarize procedures for measurement of serum C-reactive protein as a measure of inflammatory status and symptom severity using the Hamilton 21 (HAMD-21) questionnaire for major depression [19] and the positive and negative syndrome scale (PANSS) for schizophrenia [20]. Finally, we present an analysis aimed at determining whether or not any significant correlations exist between these parameters in patients at baseline and after 6 weeks of treatment.

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Materials 1. Biobanked serum samples from 99 acute major depression and 182 acute schizophrenia patients (taken at baseline and after 6 weeks treatment), and 357 controls (Table 1) (see Notes 1 and 2).

2.1 Samples and Reagents

2. Sterile blood-draw needles (14–20 gauge) with single draw or butterfly system. 3. Tourniquet. 4. Alcohol wipes (70% isopropyl alcohol). 5. BD Serum Vacutainer™ tubes (Becton Dickinson, Heidelberg, Germany). 6. Phosphate-buffered saline (PBS). 7. Fluorescein-labeled goat antibodies against human IgAGM. 8. IgA, IgG, and IgM immunoglobulins. 9. Benchtop centrifuge. 2.2 Equipment and Analytical Tools

1. Polyendocrinopathy Biochip Mosaic (FA 1010-1005-2, Euroimmun, Luebeck, Germany), containing frozen tissue sections of monkey thyroid gland, endocrine pancreas, adrenal cortex, ovary, testis (Leydig cells), and stomach parietal cells from monkey [21].

Table 1 Demographic details associated with serum samples from major depression, schizophrenia, and control groups with respect to thyroid antibody status Thyroid antibody status (TPO, TG) Variables

TPO+/TG+ (n ¼ 53)

TPO/TG (n ¼ 585)

p-Value

Age (years)

34.0 (24.5, 45.0)

34.0 (26.0, 46.0)

0.875

BMI (kg/m2)

22.7 (21.1, 26.2)

23.8 (21.6, 27.2)

0.222

Waist: hip

0.85 (0.82, 0.90)

0.87 (0.82, 0.91)

0.302

1.0 (0.6, 4.0)

1.5 (0.6, 4.0)

0.359

Neutrophil (10 /L)

3.60 (2.84, 4.63)

3.72 (2.87, 4.97)

0.440

Eosinophil (109/L)

0.13 (0.09, 0.23)

0.15 (0.09, 0.23)

0.690

0.05 (0.00, 0.06)

0.04 (0.00, 0.63)

0.325

2.01 (1.56, 2.48)

2.02 (1.63, 2.48)

0.769

0.35 (0.26, 0.48)

0.41 (0.32, 0.52)

0.025

CRP (mg/L) 9

9

Basophil (10 /L) 9

Lymphocytes (10 /L) 9

Monocytes (10 /L)

TPO thyroid peroxidase, TG thyroglobulin, BMI body mass index

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2. Neurology-Mosaic-6 and Neurology-Validation-Mosaic, consisting of recombinant cell substrates expressing neuronal cell surface, synaptic proteins, and other neuronal and glial proteins (Euroimmun) (Table 2).

Table 2 List of neuronal cell surface, synaptic proteins, other neuronal and glial proteins expressed on the Neurology-Mosaic-6 and Neurology-Validation-Mosaic Neuronal cell surface or synaptic proteins 1. AMPA glutamate receptor subunits GluR1 and GluR2 2. Aquaporin-4 3. Contactin-associated protein 2 (CASPR2) 4. Dipeptidyl peptidase like 6 (DPPX) 5. Translation initiation factor 1/2 (IF1/IF2) 6. Dopamine receptors D1/2/3/4/5 7. GABA receptors B1/B2 8. Glycine receptor A1β 9. Metabotropic glutamate receptors GRM1/GRM5 10. Leucine-rich glioma-inactivated 1 (LGI1) 11. NMDA glutamate receptor subunits NR1a and NR2a/b Other neuronal or glial proteins 1. Amphiphysin 2. CV2 3. Delta/notch like EGF repeat containing (DNER) 4. Glutamic acid decarboxylase 2 (GAD65) 5. Hu 6. Ma1 7. Ma2/Ta 8. Myelin oligodendrocyte glycoprotein (MOG) 9. Recoverin 10. Rho-GTPase 11. Ri 12. SRY-box transcription factor 1 (Sox-1) 13. Yo 14. Zic

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3. Frozen tissue sections of rat hippocampus and rhesus monkey cerebellum (used as positive control for the NeurologyMosaic-6 and Neurology-Validation-Mosaic). 4. Cobas 8000 e601 modular analyzer (Roche Diagnostics, Basel, Switzerland). 5. Cobas 8000 c701 modular analyzer (Roche Diagnostics). 6. XN-3000 automated counter (Sysmex Corporation, Kobe, Japan). 7. HAMD-21 [19] and PANSS [20] scoring systems for depression and schizophrenia, respectively (see Note 3). 8. Statistical software package R (http://www.r-project.org). 9. Shapiro-Wilk tests for data normality. 10. Nonparametric Mann-Whitney U tests for data with non-normal distribution. 11. Fisher’s exact tests for group differences.

3 3.1

Methods Samples

1. Record demographic details associated with samples at the time of blood draw (baseline and after 6 weeks treatment). 2. If carrying out a new study, collect up to 8 mL of whole blood in serum tubes around 8:00 a.m. from fasting subjects. 3. Immediately after collection, invert the tube 8–10 times. 4. Allow blood to clot 90 min at room temperature. 5. Centrifuge at 1100  g for 15 min at 4  C. 6. Transfer 0.5 mL aliquots of the top serum layer to pre-labeled 1.5 mL-capacity Eppendorf LoBind tubes on ice. 7. Record and discard samples which are hemolyzed (red or pink tinge) or those that show lipemia (milky white appearance). 8. Place aliquots immediately on dry ice and transfer to a 80  C freezer until analysis (see Note 4). 9. Document the daily applied names and dosages of antidepressant, antipsychotic, and benzodiazepine drugs for the 6-week treatment period. 10. Divide the sum dosages of these drugs for the 6-week treatment period by 42 to get the daily dose. 11. Use conversion tables as described previously [22–25] (see Note 5) and add up the result for the respective medication type to determine mean daily amitriptyline, chlorpromazine, and diazepam equivalent dosages over the 6-week treatment period.

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3.2 Immunological Analyses

1. Test samples for the presence of autoimmune antibodies using multiplex indirect immunoassays on biochips under blinded conditions. 2. Detect thyroid and polyendocrine syndrome autoantibodies using the Polyendocrinopathy Biochip Mosaic with frozen tissue sections. 3. Detect brain antibodies using the Neurology-Mosaic-6 and Neurology-Validation-Mosaic. 4. Confirm the presence of the brain antibodies using frozen tissue sections of rat hippocampus and rhesus monkey cerebellum for confirmatory tests. 5. For each assay, incubate microscopic slides 30 min in PBS-diluted patient sera using a 1:10 starting dilution of the serum with PBS. 6. Wash with PBS for 5 min and incubate 30 min with fluoresceinlabeled goat antibodies against human IgAGM for endocrinerelated antibodies or IgA, IgG, and IgM immunoglobulins for brain-related antibodies. 7. Wash samples again for 5 min in PBS. 8. Embed in PBS-buffered glycerol and examine visually by fluorescence microscopy [26]. 9. Classify samples as positive or negative based on fluorescence intensity of the transfected cells compared with non-transfected cells and control samples (see Note 6).

3.3 Thyroid Hormones and Other Biomarkers (See Note 7)

1. Determine serum concentrations of thyroid stimulating hormone (TSH), free tri-iodothyronine (FT3), and free thyroxine (FT4) by electro-chemiluminescence immunoassay on the Cobas 8000 e601 modular analyzer. 2. Determine CRP by immunoturbidimetry on the Cobas 8000 c701 modular analyzer. 3. Determine differential blood counts using the XN-3000 automated counter. 4. Intra- and inter-assay coefficients of variation should be 40

>40

3.5 Analysis of DNA Fragmentation (See Note 8)

1. Expose HepG2 and Huh7 cells to camptothecin, β-S, and β-SG at their IC50 doses for 24 h at 37  C under a humidified atmosphere of 5% CO2. 2. Isolate total DNA using a DNA purification kit according to the manufacturer’s instructions. 3. Subject 2 μg each DNA sample to electrophoresis on 1.5% agarose gels and post-stain with 10 μg/mL ethidium bromide using standard procedures (see Note 9). 4. Photograph the gels under ultraviolet illumination (Fig. 2) (see Note 10).

3.6 Optical Microscopy Analysis of Cell Apoptosis (See Note 11)

1. Seed 1  106 cells in 6-well plates and incubate for 24 h as above. 2. Expose HepG2 and Huh7 cells to β-S and β-SG at 10 μg/mL (approximately two times their IC50 concentrations) for 48 h at 37  C under a humidified atmosphere of 5% CO2. 3. Visualize the cells at an appropriate magnification using a light microscope (Fig. 3) (see Note 12).

3.7 Fluorescent Assays for Measuring Caspases Activity (See Note 13)

1. Culture HepG2 and Huh7 cells in 96-well plates at a density of 2  104 cells/well and treat with β-S or β-SG at their IC50 concentration for 24 h, as above. 2. Add 100 μL caspase reagent to each well (from the caspase activity kit) and carry out the assay according to the manufacturer’s instructions. 3. Measure the fluorescence intensity of each well at 535/620 (excitation/emission), 490/525, and 370/450 nm for caspase 3, 8, and 9, respectively, using the plate reader (Fig. 4a) (see Note 14).

3.8 Western Blot Analysis

1. Treat cells as above with β-S or β-SG at their IC50 values for 24 h. 2. Harvest as above and extract the total proteins by homogenizing with a cell disrupter in cell extraction buffer, followed by centrifugation at 16,000  g for 20 min at 4  C.

Evaluation of Anti-Hepatocellular-Cancer Properties of β-Sitosterol. . .

20001000500100-

Control

b -SG (6 mg/mL)

b -S (6 m g/mL)

Camptothecin (4 m g/mL)

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b -SG (6 m g/mL)

3000-

Base pairs

Base pairs

b-S (6 m g/mL)

B) Camptothecin (4 m g/mL)

A)

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Fig. 2 Apoptosis induced in HepG2 (a) and Huh7 (b) cells by camptothecin, β-S, β-SG at their IC50 concentrations, compared to control buffer. Samples were loaded onto agarose gels and the effects on DNA degradation visualized by ethidium bromide staining, followed by ultraviolet imaging A)

Control

10 m g/mL

B)

b -S

b -S

b-SG

b-SG

Control

10 m g/mL

Fig. 3 Optical microscopy analysis showing apoptosis effect of β-S and β-SG on (a) HepG2 and (b) Huh7 cancer cells. The concentration of each compound (10μg/mL) approximated two times the IC50 concentrations

3. Load the total proteins onto 12% SDS-PAGE gels, electrophoresis and transfer onto PVDF membranes according to standard procedures [9]. 4. Block the nonspecific sites on the membranes using 5% BSA in TBS buffer and probe the membranes with caspase-3 (1:1000),

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A) 60

RFU (x 103)

50

40 Control b -S b-SG

30 20 10 0

HepG2

Huh7

HepG2

Caspase-3

Huh7

HepG2

Caspase-8

HepG2

B) Control

b -S b-SG

Huh7

Caspase-9

Huh7 Control

b -S b-SG

Caspase-3 Cleaved caspase-3 GAPDH Caspase-8 GAPDH Caspase-9 Cleaved caspase-9 GAPDH -

Fig. 4 β-S and β-SG induced liver cancer cells death through caspase-dependent pathways. (a) Measurement of caspase activities in HepG2 and Huh7 cells using the caspase-3, caspase-8, and caspase-9 multiplex activity assay kit. RFU¼relative fluorescence units. (b) Western blot analysis of full length and cleaved caspase-3, 8, and 9 proteins in HepG2 and Huh7 cells. GAPDH was used as a loading control. GAPDH¼glyceraldehyde 3-phosphate dehydrogenase

8 (1:1000), and 9 (1:1000) antisera, in addition to GAPDH antisera (1:5000) in TBST at 4  C overnight.

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5. After washing three times with TBST buffer, add the corresponding HRP-conjugated secondary antibodies in TBST and incubate for 1 h at room temperature. 6. Visualize the immunoreactive bands by ECL detection following the manufacturer’s protocol and quantify by densitometry using the Image J software (see Note 15). 7. Estimate the proteolytic activation by comparing the ratios of the high and low molecular weight bands of each caspase enzyme. 3.9 Statistical Analysis

1. Perform all assessments in triplicate. 2. Perform one-way analysis of variance (ANOVA) with a Fisher’s least significant difference to determine significant differences between groups using the SAS software. 3. Calculate means and standard deviations. 4. Determine differences among the mean values of the various parameters by the least significant difference test, with p < 0.05 set to indicate significance for all experimental data (see Note 16).

4

Notes 1. Camptothecin was originally isolated from the bark and stem of Camptotheca acuminata, a tree native to China and used as a cancer treatment in traditional Chinese medicine. 2. The plants were collected from Hai Duong province, Vietnam, in 2018 and taxonomically authenticated by Professor Vo, Hanoi Medical University (specimen voucher no. V571). 3. All cells were obtained from the American Type Culture Collection. 4. We identified the isolated compounds by 13 C-NMR as described previously [8].

1

H- NMR and

5. The DPPH assay is commonly used to monitor chemical reactions involving radicals and as an antioxidant assay. 6. Determine the radical scavenging activity of the samples using the ABTS assay according to a previously described procedure with slight modifications. ABTS is frequently used by the food and agricultural industries to measure antioxidant capacities in these products. 7. Survival of HepG2 and Huh7 liver cancer cells was assessed by cell viability assays following exposure to increasing doses of β-S, β-SG, and camptothecin for 48 h. This revealed IC50 values ranging from 3.8 to 8.7 mg/mL (Table 2), with

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camptothecin showing the greatest potency, followed by β-SG and then β-S. According to National Cancer Institute criteria, natural extracts with IC50 value 20 μg/mL should be considered as highly cytotoxic to cancer cells [10–12]. Interestingly, no cytotoxic effect was observed using normal human primary fibroblasts, with minimal effect seen at even the highest dosage (40 μg/mL; data not shown). Therefore, both β-S and β-SG compounds appear to have strong in vitro cytotoxic activities against HepG2 and Huh7 cells with little or no toxic effect against normal cells. 8. To confirm the apoptosis, DNA fragmentation was also tested by agarose gel electrophoresis. 9. Proper care should be taken wearing appropriate personal protective equipment as ethidium bromide is a mutagen. 10. This showed no fragmentation in the control group, while significant fragmentation was found with the camptothecin treatment, and lower fragmentation was achieved by the β-S and β-SG treatments. 11. This is a simple imaging protocol used for visualizing the cells. It is not quantitative. Should quantitation be desired, this could be achieved via fluorescence-activated cell sorting [13] or using an immunohistochemical approach [14]. 12. This revealed significant apoptosis of both HepG2 and Huh7 cells. 13. To determine the potential mechanisms underlying the cytotoxic effects mediated by β-S and β-SG, the activities of caspase3, -8 and -9 in HepG2 and Huh7 cells were measured using the fluorometric multiplex assay. 14. This analysis showed that β-S and β-SG treatment enhanced caspase-3 and 9 activities, while caspase-8 activity was not altered significantly, compared to untreated controls. 15. This findings indicated supported the findings of increased caspase-3 and 9 activities due to treatment with the compounds as shown by increased cleavage of inactive procaspase3 and procaspase-9 into the corresponding active forms. The increased activity of the caspase enzymes was confirmed by increased conversion of the higher molecular forms of these enzymes to the lower molecular weight active forms. These results are consistent with the findings of increased apoptosis of HepG2 and Huh7 cells due to treatment with β-S and β-SG. Other studies have confirmed the antiproliferative activity of β-S in studies of breast cancer [15, 16], colon cancer [17– 19], and HeLa cells [20], due to in caspase-induced apoptosis. In addition, β-SG isolated from Castanopsis indica leaves was

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found to induce apoptosis through upregulating caspase-9 and caspase-3 activities [21]. 16. Together, these findings show that the bioactive compounds β-S and β-SG isolated from I. zollingeriana demonstrated pharmacological properties that may have potential as anticancer agents. References 1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 68 (6):394–424 2. Akinyemiju T, Abera S, Ahmed M, Alam N, Alemayohu MA, Allen C et al (2017) The Burden of Primary Liver Cancer and Underlying Etiologies From 1990 to 2015 at the Global, Regional, and National Level: Results From the Global Burden of Disease Study 2015. JAMA Oncol 3(12):1683–1691 3. Mansoori B, Mohammadi A, Davudian S, Shirjang S, Baradaran B (2017) The different mechanisms of cancer drug resistance: a brief review. Adv Pharm Bull 7(3):339–348 4. Angiolella L, Sacchetti G, Efferth T (2018) Antimicrobial and antioxidant activities of natural compounds. Evid Based Complement Alternat Med 2018:1945179. https://doi. org/10.1155/2018/1945179 5. Hisaeda A, Matsunami K, Otsuka H, Takeda Y (2011) Flavonol glycosides from the leaves of Indigofera zollingeriana. J Nat Med 65 (2):360–363 6. Ali A, Shyum Naqvi SB, Gauhar S, Saeed R (2011) Anti-inflammatory and analgesic activities of ethanolic extract of Sphaeranthus indicus Linn. Pak J Pharm Sci 24(3):405–409 7. Nisar M, Tariq SA, Marwat IK, Shah MR, Khan IA (2009) Antibacterial, antifungal, insecticidal, cytotoxicity and phytotoxicity studies on Indigofera gerardiana. J Enzyme Inhib Med Chem 24(1):224–229 8. Vo TK, Ta QTH, Chu QT, Nguyen TT, Vo VG (2020) Anti-hepatocellular-cancer activity exerted by β-Sitosterol and β-Sitosterol-glucoside from Indigofera zollingeriana Miq. Molecules 25:3021. (in press) 9. Guest PC (2020) Brain proteomic analysis on the effects of the antidepressant fluoxetine. Methods Mol Biol 2138:419–430 10. Grever MR, Schepartz SA, Chabner BA (1992) The National Cancer Institute: cancer drug

discovery and development program. Semin Oncol 19(6):622–638 11. Goldin A, Venditti JM, Macdonald JS, Muggia FM, Henney JE, Devita VT Jr (1981) Current results of the screening program at the division of cancer treatment, National Cancer Institute. Eur J Cancer 17(2):129–142 12. Protocols for screening chemical agents and natural products against animal tumors and other biological systems. Cancer Chemotherapy Reports 25. 1962. Drug Evaluation Branch, Bethesda, MD, USA; Nat. Cancer Institute 13. Chen S, Li D, Ren Z, Yu D, Ning B, Mei N et al (2020) Using a lentivirus-based inducible RNAi vector to silence a gene. Methods Mol Biol 2102:195–210 14. Mansfield JR, Guest PC, Burks J (2017) Phenotyping multiple subsets of immune cells in situ in formalin-fixed, paraffin-embedded tissue sections. Adv Exp Med Biol 974:327–338 15. Awad AB, Roy R, Fink CS (2003) Betasitosterol, a plant sterol, induces apoptosis and activates key caspases in MDA-MB-231 human breast cancer cells. Oncol Rep 10(2):497–500 16. Awad AB, Chinnam M, Fink CS, Bradford PG (2007) Beta-Sitosterol activates Fas signaling in human breast cancer cells. Phytomedicine 14(11):747–754 17. Awad AB, Chen YC, Fink CS, Hennessey T (1996) Beta-Sitosterol inhibits HT-29 human colon cancer cell growth and alters membrane lipids. Anticancer Res 16(5a):2797–2804 18. Choi YH, Kong KR, Kim YA, Jung KO, Kil JH, Rhee SH et al (2003) Induction of Bax and activation of caspases during beta-sitosterolmediated apoptosis in human colon cancer cells. Int J Oncol 23(6):1657–1662 19. Montserrat-de la Paz S, Ferna´ndez-Arche MA, Bermu´dez B, Garcı´a-Gime´nez MD (2015) The sterols isolated from evening primrose oil inhibit human colon adenocarcinoma cell proliferation and induce cell cycle arrest through upregulation of LXR. J Funct Foods 12:64–69 20. Cheng D, Guo Z, Zhang S (2015) Effect of β-sitosterol on the expression of HPV E6 and

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p53 in cervical carcinoma cells. Contemp Oncol (Pozn) 19(1):36–42 21. Dolai N, Kumar A, Islam A, Haldar PK (2016) Apoptogenic effects of beta-sitosterol

glucoside from Castanopsis indica leaves. Nat Prod Res 30(4):482–485

Chapter 16 Label-Free Electrochemical Biosensors to Evaluate the Antioxidant Effect of Tocopherol in Ultraviolet Radiation Lixia Gao and Yong Teng Abstract Electrochemical biosensors offer a sensitive, specific, and rapid detection platform for in situ real-time monitoring of intracellular and extracellular metabolites. These sensors have been widely used to evaluate the efficacy of preclinical drugs, especially for natural products with antioxidant potency. Ultraviolet (UV) radiation causes oxidative stress in cells and induces cells to release reactive oxygen species. Tocopherol is a fat-soluble vitamin found in vegetable oils as well as in grains, seeds, and nuts, which plays an important protective role as an antioxidant in resisting oxidative stress caused by UV radiation. Here, we describe a protocol using a glass carbon electrode functionalized with nanotube@DNA-Mn3(PO4)2 composite to monitor and quantify the production of superoxide ions in UV-irradiated melanoma cells in the presence or absence of tocopherol. This study demonstrates the advantages and potential application of label-free electrochemical sensors in the measurement of natural antioxidants from plant materials. Keywords Electrochemical biosensors, UV, Tocopherol, Superoxide, Antioxidant, Natural products

1

Introduction Electrochemical biosensors combine biological activity recognition materials with electrochemical detection devices and are widely used in clinical medicine, drug and food analysis, and environmental monitoring. Electrochemical detection platforms can transform the changes of the body after the treatment of diseases into electrical signals, and thereby monitor the effects of diseases and drug treatments through the analysis of electrical signals [1]. In addition, electrochemical biosensors have the advantages of high efficiency, convenience, and low cost. The electrochemical detection platform usually adopts a three-electrode configuration, including working, counter, and reference electrodes (Fig. 1). Electrochemical biosensors can also detect cell metabolites and small molecules released by cells, providing a new research strategy for studying cell stress caused by changes in the external environment.

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_16, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Fig. 1 Schematic diagram of classic three-electrode electrochemical biosensor detection system

Ultraviolet (UV) light represents one of the most important environmental impacts for human skin diseases [2, 3]. Recently, due to the destruction of the atmospheric ozone (O3) layer, people are paying increasing attention to UV radiation. Based on different wavelengths, sunlight UV rays are divided into UVA, UVB, and UVC. UVC rays (100–290 nm) are absorbed by the O3 layer in the upper atmosphere, but UVB and UVA rays reach the Earth’s surface, and are the major fractions linked to skin diseases. UVB rays (290–320 nm) are absorbed mostly by the epidermis and keratinocyte DNA, while UVA rays (320–400 nm) are primarily oxidative in nature and penetrate more deeply into the dermal layers of the skin [4]. Related research has shown that UV radiation (UVR) can stimulate the production of a series of reactive oxygen species (ROS) resulting in cellular oxidative stress, which is a proven cause of basal cell carcinoma, squamous cell carcinoma, and melanoma skin cancers [5]. Naturally occurring vitamin E exists in eight chemical forms of tocotrienol, with varying levels of biological activity. Alpha-(α-) tocopherol is the only form which has been shown to meet human nutritional requirements. This can be found in vegetable oils, grains, seeds, and nuts. Tocopherol has been widely reported as an antioxidant and plays a critical role in UV resistance. The traditional methods for detecting ROS are mainly biological in nature. In our previous work [2], we successfully constructed an electrochemical biosensor to detect the levels of ROS released by cells [6]. Here, we establish a new protocol to quantitatively measure the production of superoxide ions in UV-irradiated melanoma A375 cells, in the presence or absence of tocopherol (Fig. 2). Our study highlights the potential of the electrochemical method for evaluation of the antioxidant effects of natural products and their related mechanisms.

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Fig. 2 The process of electrochemical biosensors in detection of the antioxidant effect of tocopherol following UV radiation

2

Materials

2.1 Preparation Method of Tocopherol Working Solution

2.2 Synthesis of O2
Electrochemical Biosensor l

1. Anhydrous methanol solution. 2. 1 M tocopherol stock in ethanol (see Note 1). 3. Complete growth medium: 90% RPMI 1640, 10% fetal bovine serum (FBS) (see Note 2). 1. Deoxyribonucleic acid (DNA), low molecular weight from salmon sperm (see Note 3). 2. 0.1 M MnSO4. 3. 0.1 M K3PO4. 4. Superoxide dismutase (SOD). 5. 0.5 mg/mL multi-walled carbon nanotube (CNT) (see Note 3). 6. 5% Nafion® 117 solution. 7. 0.01 M phosphate-buffered saline (PBS). 8. 15 mg/mL graphene oxide. 9. 0.1 M KO2.

2.3 Polishing of Glassy Carbon Electrode

1. 0.3 mm and 0.05 mm alumina powder. 2. 0.1 M KCl. 3. 5 mM potassium ferricyanide (K3Fe (CN)6). 4. 5 mM potassium ferrocyanide (K4 [Fe(CN)6]l3H2O).

2.4 Cells and Other Reagents

1. A375 human melanoma cells (ATCC, Rockville, MD, USA). 2. 0.25% trypsin-ethylenediaminetetraacetic EDTA).

acid

(trypsin-

3. Dimethyl sulfoxide (DMSO). 2.5 Equipment (See Note 4)

1. Broad-spectrum MUA-165 UV lamp. 2. UV radiometer. 3. CHI760E electrochemical detector, glassy carbon electrode (d ¼ 3 mm). 4. Hg/HgCl2/KCl reference electrode.

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5. A platinum wire counter electrode. 6. Deionized (DI) water apparatus.

3 3.1

Methods 1. Remove the A375 cryotube from the liquid nitrogen tank.

Cell Culture

2. Quickly thaw A375 cells (< 1 min) by gently swirling the vial in the 37  C water bath until there is only a small amount of ice left in the vial. 3. Transfer the desired amount of pre-warmed complete growth medium dropwise into the centrifuge tube containing the thawed cells. 4. Centrifuge the cell suspension at approximately 200  g for 5 min. 5. After the centrifugation, aseptically decant the supernatant without disturbing the cell pellet. 6. Gently resuspend the cells in complete growth medium and let them grow to reach a confluency of 90–100% at 37  C. 1. Add 2.1 mg DNA into 1 mL 0.1 M MnSO4 with constant stirring at 60  C (see Note 5).

3.2 Preparation of O2
Electrochemical Biosensor l

2. After 10 min, add 9 mL 0.1 M K3PO4 with stirring until the mixture becomes transparent (see Note 6). 3. Collect pellets of DNA@Mn3(PO4)2 composites by centrifugation at 9000  g for 10 min at 4  C (see Note 7). 4. Dilute DNA@Mn3(PO4)2 nanocomposite with 2 mL DI water for subsequent experiments. 5. Maintain in a 4  C refrigerator (see Note 8). 6. Drip 5 μL 0.5 mg/mL CNT solution and drip on a polished glassy carbon electrode to dry under room temperature. 7. Drop-cast 5 μL DNA@Mn3(PO4)2 mixture on the above electrode. 8. Calibrate O2
electrochemical sensors and detect the O2
level from cell release (see Note 9). l

3.3 Detection of Intracellular O2
Levels in UV-Irradiated Human Melanoma Cells l

l

1. Use the cyclic voltammetry curve to monitor intracellular O2
generation on the electrochemical station. l

2. Scan over a potential range of 0.25–0.85 V at 50 mV/s for O2
electrochemical sensors (see Note 10). l

3. Detect concentration changes of O2
at 0.7 V by the amperometric response of the DNA@Mn3(PO4)2/CNT electrode (see Note 10). l

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4. Detect O2
levels in A375 cells with or without UV irradiation, in the presence of 25 μM tocopherol using the electrochemical biosensor (see Note 11). l

5. Record peak current at 0.7 V. 6. Monitor and quantitatively measure the current change by superoxide anions of O2
(see Note 12). l

3.4 Detection of Tocopherol Effects Against UV Radiation

1. Autoclave the 2 cm2 cell-culture slices and put them into 24-well plates (see Note 5). 2. Seed A375 cells at a density of 1  105 per well in 24-well plates and incubate overnight at 37  C (see Note 13). 3. Incubate A375 cells in the presence or absence of 25 μM tocopherol for 12 h. 4. Incubate cells in the absence of tocopherol under the same conditions as a control. 5. Transfer the cell-containing cell-culture slices to the electrochemical detection pool and add 2.5 mL serum-free medium. 6. Record the electrochemical signal from the cells exposed to UVR using the electrochemical detection platform (see Note 14).

4

Notes 1. The protocol has been optimized for use with this drug. The same drug from other suppliers will work, but optimization may be required. 2. The protocol has been optimized for this medium, and this product yields the best performance. 3. The protocol has been optimized for DNA and CNT, and this product yields the best performance. 4. There are no strict restrictions on the instruments used in this experiment, and similar products from other companies can be used if they have the appropriate functions. 5. This protocol has been optimized for these experimental conditions. Other experimental methods need to be optimized. 6. We have optimized the reaction time and synthesis of the nanocomposites, and this requires approximately 1 h. Therefore, when the reaction has been underway for this time, attention should be paid as to whether or not the reactant solution becomes transparent. The reaction beaker should be placed in a water bath for heating and stirring. 7. This protocol has been optimized for centrifugation time, g force, and temperature.

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8. Electrochemical sensor calibration is the only method to detect sensitivity and detection limit, and it is also a mark of successful sensor preparation. Therefore, this step is important in the process of constructing the electrochemical sensor. 9. We have optimized the stirring time and found that 30 min gives optimal results. 10. DNA@Mn3(PO4)2/CNT nanocomposites have a characteristic current peak over the range of 0.25–0.85 V. This has been optimized from our previous work. 11. This concentration of tocopherol was derived from the relevant literature. Optimization studies showed that 25 μM tocopherol yields the best performance [6]. 12. Calculate the current change value of O2
from cells with UVR with reference to the current value of cells without UVR. l

13. We have optimized the cell density and found that 1  105/ well gives optimal results. 14. We have optimized the irradiation time and UV dose. Different cells and drugs in other experiments need to be optimized. References 1. Gao L, Teng Y (2016) Exploiting plug-and-play electrochemistry for drug discovery. Future Med Chem 8(5):567–577 2. Gao L, Wang X, Tang Y, Huang S, Hu CA, Teng Y (2017) FGF19/FGFR4 signaling contributes to the resistance of hepatocellular carcinoma to sorafenib. J Exp Clin Cancer Res 36(1):8. https://doi.org/10.1186/s13046-016-0478-9 3. Berwick M, Lachiewicz A, Pestak C, Thomas N (2008) Solar UV exposure and mortality from skin tumors. Adv Exp Med Biol 624:117–124 4. Duthie MS, Kimber I, Dearman RJ, Norval M (2000) Differential effects of UVA1 and UVB

radiation on Langerhans cell migration in mice. J Photochem Photobiol B 57(2-3):123–131 5. Dizdaroglu M, Jaruga P, Birincioglu M, Rodriguez H (2002) Free radical-induced damage to DNA: mechanisms and measurement. Free Radic Biol Med 32(11):1102–1115 6. Gao LX, Bian C, Wu Y, Nisar MF, Chen S, Li CM et al (2018) Label-free electrochemical sensor to investigate the effect of tocopherol on generation of superoxide ions following UV irradiation. J Biol Eng 12:17. https://doi.org/10. 1186/s13036-018-0099-2

Chapter 17 qRT-PCR Analysis of GLUT-4 and Assessment of Trolox as an Effective Antioxidant in Diabetic Cardiomyoblasts S. Asha Devi, Ravichandra Shivalingappa Davargaon, and M. V. V. Subramanyam Abstract A high global prevalence of diabetes and its implications on the heart in vivo and in vitro tools have been pursued to alleviate the complications of high glucose. This chapter oulines the methods used for maintaining H9C2 cardiomyoblasts in vitro and for stimulating hyperglycemic situation. In addition, we present a method to assess cellular GLUT-4 expression using qRT-PCR. This cellular model also allows us to examine the therapeutic approach of an antioxidant, Trolox, for upregulating GLUT-4 and uptake of glucose under hyperglycemic condition. Keywords Apoptosis, Cardiomyoblast, Diabetes, GLUT-4, Trolox

1

Introduction High glucose (HG) toxicity is an important initiator of cardiovascular diseases, and a contributing factor to the development of cardiomyocyte death and diabetes complications [1]. Type 2 diabetes is due to hyperlycemia, which alters the regulation of several metabolic pathways [2]. There is a shift in energy source in diabetic hearts, with cardiomyocytes possessing high levels of ketone bodies that will inhibit glucose influx and utilization. Apoptotic cell death is more pronounced in the hearts of diabetic patients [3, 4] and animal models [5]. Glucose translocators 4 (GLUT-4) belongs to a family of GLUTs that have a role in glucose uptake in the cardiomyocytes [6]. Insulin aids in the uptake of glucose in the heart by activating phosphotidyl-3 kinase (P13K) and Akt, thereby increasing the translocation of GLUT-4 and other molecules such as 50 -adenosine monophosphate-activated protein kinase (AMPK) to the plasma membrane [7, 8]. High glucose-induced stress inhibits glucose

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entry into cardiomyocytes by downregulating GLUT-4 coupled with changes in ATP and mitochondrial-dependent apoptosis [9]. Notably, in the human heart, GLUT-4 is the major isoform that represents approximately 70% of the total GLUTs [10]. Furthermore, clinical utility of GLUT-4 expression in cancer has been recognized, and evidence regarding the use of GLUTs as prognostic or predictive biomarkers is under investigation [11]. The H9c2 cell line has its origins from embryonic rat ventricular tissue [12], and although these cells are no longer able to contract, many similarities to primary cardiomyocytes have been observed. This includes membrane morphology, G-protein signaling, and electrophysiological properties [13, 14]. Hence, the H9c2 cell line can be used as in vitro model to study the metabolic capacity of the heart [15]. This chapter presents a protocol used for assessing GLUT-4 during hyperglycemia employing an in vitro model of rat cardiomyoblast cells [12]. Further, it is possible to utilize the technique to study the suitability of a water-soluble analog of vitamin E, Trolox, for upregulation of GLUT-4 expression.

2 2.1

Materials Cell Culture

1. H9c2 cardiomyoblast cell lines (National Centre for Cell Science, Pune, India). 2. Cell culture medium: Dulbecco’s modified eagle’s medium (DMEM) with low-glucose (5.5 mM), L-glutamine, sodium bicarbonate, and sodium pyruvate. 3. 10% fetal bovine serum (FBS). 4. 1% antibiotic solution (100 U/mL penicillin, 100 μg/mL streptomycin). 5. 5% CO2 incubator. 6. D-Glucose. 7. 100 μM 6-hydroxy-2,5,7,8-tetramethyl chromane-2-carboxylic acid (Trolox) dissolved in water 24 h before use. 8. Phosphate-buffered saline (PBS; pH 7.4): 10 mM Na2HPO4, 1.8 mM KH2PO4, 2.7 mM KCl, 137 mM NaCl. 9. Trypsin-EDTA solution: 0.25% trypsin and 0.02% EDTA in Dulbecco-PBS. 10. 25 cm2 cell culture flasks, 6-well culture plates.

2.2 GLUT-4 mRNA Expression

1. Cell scraper. 2. Commercially available cDNA synthesis kit. 3. Chloroform:isoamyl alcohol 24:1 (v:v) mixture.

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4. Commercially available first-strand synthesis kit. 5. RNase-free water. 6. Deoxyribonucleotide triphosphates (dNTPs). 7. Diethyl pyrocarbonate (DEPC). 8. Isopropanol. 9. Poly-A (to purify mRNA from mammalian cells/tissues). 10. Oligo dT primer mix (2.5 mM each). 11. Reverse transcriptase buffer (10). 12. RNase inhibitor (40 U/μL). 13. 0.1 M dithiothreitol (DTT). 14. RNase H. 15. Moloney murine leukemia virus (MMuLV; 20 U/μL) reverse transcriptase. 16. DNAse-free water. 17. Q-PCR kit (Chromous Biotech Pvt. Ltd.) or commercially available Q-PCR kit. 18. TRIzol RNA isolation kit (Sigma Aldrich, MO, US) or commercially available total RNA extraction kit. 19. Phenol:chloroform (1:1 v/v). 20. 2-propanol. 21. 3 U/μL SYBR green master mix (2). 22. Forward and reverse primers for GLUT-4 and β-actin (Table 1). 23. Horizontal electrophoresis unit with power pack. 24. Microcentrifuge. 25. 1.5 and 2 mL microcentrifuge tubes. 26. 96-well microplates. Table 1 Sequence of the primers for mRNA of GLUT-4 receptor and β-actin for qRT-PCR (From [9] with permission) Gene

Primer sequence

Product size (BP)

Accession code

GLUT 4

Forward primer: 50 -AGTGATTGAACAGAGCTACAATGC-30 Reverse primer: 50 -CTTCCCAACCATTGAGAAATGATGC-30

242

D28561.1

β-actin

Forward primer: 50 -AGTGATTGAACAGAGCTACAATGC-30 Reverse primer: 50 -CTTCCCAACCATTGAGAAATGATGC-30

174

NM_031144.3

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27. PCR tubes. 28. PCR thermocycler. 29. UV-Vis NanoDrop One microvolume spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). 30. 1% agarose gel in tris-acetate-EDTA (TAE) buffer. 31. Electrophoresis power supply. 32. 1 GreenView dye. 33. Geldoc system (Chromus Biotech India Pvt. Ltd.; Bengaluru, Karnataka, India). 34. Microwave. 35. ABI Step-one Real-Time PCR System (Thermo Fisher Scientific) or any Real-Time PCR System. 36. Analytical and HPLC grade common chemicals and solvents.

3 3.1

Methods Cell Culture

1. Remove the vial containing cryopreserved H9c2 cells from the liquid nitrogen cylinder (see Notes 1–4). 2. Keep the vial in 37  C water bath till the medium becomes liquid and immediately centrifuge the cells at 1200  g for 4 min (see Note 5). 3. Discard the supernatant and resuspend the cells in fresh 1 mL cell culture medium (see Notes 6 and 7). 4. Transfer the suspended cells into a 25 cm2 flask. 5. Incubate cells at 37  C in a 95% air/5% CO2 incubator, and allow them to adhere and grow. 6. Change the media after 2 days with fresh media and grow cells until they reach 80–90% confluence. 7. Wash cells with 0.1 M PBS and add 3–5 mL trypsin-EDTA solution and incubate for 3 min at 37  C as above. 8. Collect the cells using a cell scraper into a fresh 5 mL centrifuge tube containing media. 9. Centrifuge the cells at 1200  g for 5 min. 10. Discard the supernatant, resuspend cells in media. 11. Count the cells using a hemocytometer, seed into 6-well plates (5  105/well). 12. Grow H9c2 cells as described above until they reach 50–60% confluency.

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1. At 50–60% cell confluence, induce the hyperglycemic condition experimentally by adding 15, 24, and 33 mM D-glucose to the DMEM media [5] and designate as HG (see Notes 8–12). 2. Similarly, maintain three similar HG-exposed groups and add 100 μM Trolox 24 h before the glucose exposure and designate this with the T + HG acronym (see Note 13). 3. In parallel, maintain control cells and Trolox pretreated control (T-C) cells. 4. Maintain the HG and T + HG cells for 24, 48, and 72 h as described above (see Note 8). 5. On completion of the treatments, discard the media and wash cells with 0.1 M PBS.

3.3

RNA Extraction

1. After the completion of the treatment, wash cells with 0.1 M PBS. 2. Add 3–5 μL trypsin-EDTA solution to the cells and incubate for 5 min at 37  C as above. 3. Scrape the cells using a cell scraper and collect them into a centrifuge tube with media. 4. Centrifuge at 300  g for 5 min at 4  C and suspend the cells in 0.1 M PBS (see Note 14). 5. Add TRI Reagent (1 mL/10 cm2 surface of culture plate, 5  105 cells). 6. Pipette the cells up and down 5–10 times vigorously so that the lysate forms a homogenous sample (see Note 15). 7. Incubate the homogenate for 5–10 min at room temperature. 8. Add 0.2 mL phenol:chloroform and mix vigorously 3–5 times for 20 s and incubate on ice for 15–20 min. 9. Centrifuge the solution at 12,000  g for 15 min at 2–8  C, resulting in formation of three layers (see Notes 16 and 17): (a) At the bottom of the tube red organic layer (containing protein). (b) At the middle of the tube interphase (containing DNA). (c) At the top of the tube colorless aqueous layer (containing RNA). 10. Carefully pipette out the top aqueous layer and add to a new tube (see Note 17). 11. Add 500 μL of 2-propanol/mL and mix properly. 12. Incubate the sample on ice for 10 min to precipitate the RNA. 13. Following incubation, centrifuge the sample at 12,000  g for 10 min at 2–8  C. 14. Discard the supernatant (see Note 18).

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15. To the RNA pellet, add 0.5 mL of ethanol and 80 μL of 3 M sodium acetate and incubate for 2 min at room temperature. 16. Centrifuge the tubes at 7500  g for 10 min at 2–8  C. 17. Wash the RNA pellet with 1 mL 75% ethanol Tap tube or Vortex and subject to centrifugation for 10 min at 7500  g at 2–8  C. 18. Carefully discard the supernatant and air dry the pellet (see Notes 19–22). 19. Store the RNA pellets if needed in 75% ethanol at 2–8  C for 1 week and up to 1 year by storing at 20  C for further study (see Notes 23–25). 20. Dissolve the RNA pellet in an appropriate volume of Rnasefree water. 21. Determine the purity using the Nano Drop spectrophotometer (a 260/280 ratio of approximately 2:1 is considered to be pure RNA) (see Note 26). 22. Evaluate RNA integrity and concentration on a denaturing gel and by comparing the brightness of the 28S and 18S RNA bands (A ratio of 2:1 of 28S:18S represents good intact RNA). 3.4 Procedure for cDNA Synthesis

1. Synthesize cDNA using RNA with oligo(dT) or even with random primers involving denaturation, annealing, cDNA synthesis, and termination of reaction including removal of RNA. 2. Transfer 5 μg of the above extracted total RNA to a fresh PCR tube (see Note 27). 3. Add 0.5 μg poly-A and 0.5 μL oligo (dT)-primer, gently mix and incubate at 65  C for 15 min. 4. Add a reaction mixture containing 5 μL 10 RT-buffer, 0.25 μL RNase inhibitor (40 U/μL), 2 μL dNTP mix, 5 μL DTT, 2 μL MMuLV reverse transcriptase, and 15.75 μL DEPC-treated water to make the total reaction volume to 30 μL (see Note 28). 5. Immediately place the tube on ice for 5 min to cool. 6. Add 10 μL RNA (1–5 μg) to the above reaction mixture, gently mix and place the tube in the PCR machine, and set the temperature to 42  C for 1 h. 7. Incubate 5 min at 94  C to stop the reverse transcriptase reaction and place the tube on ice to instantly cool the sample. 8. Remove traceable RNA by adding 1 μL of RNase H and incubate at 37  C for 20 min. 9. Use 20 μL DNAse-free water to dissolve the cDNA and store at 20  C until analysis (see Note 24).

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10. Determine the purity of obtained cDNA by absorbance ratios at 260/280 using NanoDrop spectrophotometer as above (an approximate ratio of 1.8 is considered as pure DNA). 3.5

qRT-PCR

1. Take 2 μL of the first-strand cDNA obtained from the previous reaction step (see Note 29). 2. Add 2 μL of each forward and reverse primer for GLUT-4 and β-actin (Table 1) (see Note 30). 3. Add 25 μL of 2 SYBR green master mix. 4. Add 20 μL Rnase-free water to make a final reaction mix volume to 50 μL. 5. Preset the program of the PCR min with the following steps: (a) 94  C for 5 s initial denaturation. (b) 55  C for 10 s for annealing reaction. (c) 72  C for 10 s for elongation reaction. (d) After 40 cycles of I–III, 72  C for 5 min. 6. Analyze GlUT-4 and the β-actin transcript using the formula 2ΔΔCt, where ΔCt represents the difference in Ct values between the target gene and actin (see Notes 31–33). 7. Normalize the PCR data with β-actin mRNA levels and express relative mRNA levels as GLUT-4/β-actin ratio using 2ΔΔCt values (Fig. 1a). 8. Load 200–500 ng of PCR-amplified product in the 2% of agarose gel with 1 GreenView dye and apply 100 V to run the electrophoresis unit for 1 h. 9. Once the electrophoresis is complete, remove the gel carefully and place on the Geldoc system for capturing the gel images (Fig. 1b) (see Note 34).

4

Notes 1. Wear the cryoprotective gloves while taking the vial from liquid nitrogen. 2. Users should take care that pipettes tips, tubes, and other laboratory consumables are sterilized as appropriate before starting an experiment. 3. Handle carefully while thawing vials and centrifugation of cryopreserved cells during their recovery given their sensitivity. 4. Wipe the vial with ethanol after centrifugation and before and after use in the biosafety cabinet.

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Glut4/β-actin ratio (2^ΔΔct)

4

High glucose

Trolox + High glucose

3

2

1

0 Control

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Glucose concentration (mM)

Fig. 1 Alterations in GLUT-4 expression after exposing H9c2 cells to different high glucose concentrations for 24, 48, and 72 h with or without Trolox pretreatment. The upper panel (a) represents relative levels of mRNA expressed by qRT-PCR as the GLUT4/β-actin ratio (2ΔΔct), and values are mean  SEM of three replicates. Two-way ANOVA with Tukey’s HSD test revealed a significant difference in mean as ****P < 0.0001 with respective HG-treated subgroup, ####P < 0.0001 with control. Lower panel (b) represents agarose gel bands of GLUT-4 and β-actin mRNA at different glucose concentrations with a standard ladder in the center

5. Cryopreserved cell recovery should be done under sterile conditions; the researcher should wear sterile gloves and take care to maintain sterile conditions. 6. One should make sure that post-trypsinization, cells should be uniform with no clumping. 7. If cells form clumps, the user should gently purge/pipette out cells several times so that they detach from each other and are uniformly distributed. This will make it easier to count and seed the cells. 8. Users should wear apron, gloves, and eye-protective goggles to handle the samples and chemicals carefully. Label the tubes properly and cover with cello pin tape to avoid accidental

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erasure of the writing due to ethanol exposure and chances of cross contamination. 9. Users should check the reagents and buffers used in the experiments for precipitation and allow previously frozen samples for 10–15 min to come to working temperature. 10. Keep the working solutions at 4  C and avoid repeated freezing and thawing steps. 11. Dissolve D-glucose in DMEM and pass through a sterile syringe filter. This is aimed to simulate diabetes at three different levels: stage 3 or early decompensation (~16–20 mM), stage 5 or severe decompensation (>22 mM), and hyperglycemic hyperosmotic syndrome (>33 mM) as reported earlier [16, 17]. 12. Keep the number of purgings/pipettings consistent for all the samples of the experimental groups during processing of the cells. 13. Dissolve Trolox in DMEM and pass through a sterile syringe filter. 14. Care must be taken while taking out the tubes from the centrifuge and while separating out/aliquoting the layers formed during the centrifugation. 15. After adding TRIzol reagent, pipetting cells in and out will make a uniform mixture for better results. 16. Care must be taken while discarding the supernatant. Immediately remove the supernatant by inverting tube. Do not vigorously tap or disturb the centrifuge tubes while removing supernatant because this may disrupt the pellet. 17. Aspirate the upper aqueous layer carefully and avoid taking the below layer that may increase the chances of impure RNA. Disturbance during pipetting the layers may create contamination and affect the purity of the RNA. 18. While discarding supernatant, do not disturb the tube as this may lead to detachment of loss of the pellet. 19. Do not let the pellet dry completely or do not use a vacuum centrifugation method to dry the RNA pellet since this may affect the solubility of obtained RNA. 20. It is recommended to use PCR plates while performing cDNA synthesis. It is better to prepare extra volumes of reagents as a backup in case of loss. 21. It is recommended to use the multichannel pipette for pipetting reagents so that one can reduce the chances of potential human error while adding reagents directly into the wells of the PCR plate.

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22. RNA has to be added to individual wells in the PCR plate and incubated in the PCR machine for the formation of cDNA. 23. Repeated freezing and thawing procedure should be avoided because this may affect the PCR signal. 24. To avoid repeated freezing-thawing, one can make aliquots of the obtained cDNA. For making the working solution, dilute the cDNA to 1:25 by using nuclease-free molecular grade water, and another half can be stored at 20  C for longterm storage. 25. For use within 1–7 days, one can store the cDNA at 4  C. 26. For pure RNA, which is free from reverse transcriptase or DNA polymerase inhibitors, samples should have an approximate ratio of 2:1. 27. The PCR signal may be affected by repeated freezing and thawing of the RNA sample. 28. One should obtain the primers and PCR reaction reagents and kits from an authentic quality provider, and working reagents must be prepared using nuclease-free molecular grade water and should be prepared freshly. 29. The housekeeping gene is just as important as the gene of interest. There are different types of housekeeping or normalizing genes available, such as β-actin, Gapdh, phosphoglycerate kinase 1 (pgk1), ATP synthase, H+ transporting, mitochondrial F0 complex, subunit B1 (atp5f1), β-tubulin, ubiquitin (ubq), RNA ribosomal 18 s-(rnar18 s), phosphoglycerate kinase (pgk), and ribosomal protein. Choosing the right one for the study is important. β-actin and Gapdh are the most extensively used, but researchers should choose the best one based on the type of tissue or cells used for the study, and whether or not the pathways involving these genes are likely to be affected by the experimental conditions. 30. Guidelines for designing and construction of standard primer: (a) Avoid runs of four or more identical nucleotides. (b) Melting temperature (Tm) should be 58–60  C. (c) The guanine-cytosine (GC) content should be less than 65%. (d) The last five nucleotides at the 30 end of each primer should contain no more than two G or C residues. 31. During the process of qRT PCR, one may not able to see the amplification curve for the samples used. This may be due an error in the master mix preparation. Sometimes, one may see a short or improper amplification curve. In this case, one has to redo the RNA extraction process.

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32. The user should make sure the PCR reagents, and buffer expiration dates are good. Also, the composition, concentration supplied, and working concentrations should all be checked before proceeding with the experiment. 33. The user should wear safety gloves, mask, and goggles while weighing, melting/handling agarose. Precautions should be taken to avoid inhaling agar dust and contact with skin or eyes while handling agar. In case of contact with eyes, rinse immediately with plenty of water. For contact with skin, wash with soap and water. If mouth contact occurs, rinse mouth with water. Precautions should be taken by providing ventilation if agar dust is formed, and keep the container lid tight. 34. Use of GreenView dye has an advantage over ethidium bromide (EtBr), as green view is nontoxic, non-mutagenic, and inexpensive compared to EtBr.

Acknowledgments This work was supported by financial assistance granted under the Promotion of University Research and Scientific Excellence (PURSE)-Department of Science and Technology (DST) program (SR/59/Z-23/2010/38) dt. 27.06.2011), New Delhi and University Grants Commission-Centre with Potential for Excellence in a Particular Area (UGC-CPEPA, F.No.8-2/2008 (NA/PE) dt. 21.12.2011), New Delhi, India. References 1. Song YH, Geng Y, Lin Q, Shan Z, Lin S, Li Y (2008) Glucose induces apoptosis of cardiomyocytes via microRNA-1 and IGF-1. Biochem Biophys Res Commun 376(3):548–552 2. Stefano GB, Challenger S, Kream RM (2016) Hyperglycemia-associated alterations in cellular signaling and dysregulated mitochondrial bioenergetics in human metabolic disorders. Eur J Nutr 55(8):2339–2345 ˜ anes M 3. Chowdhry MF, Vohra HA, Galin (2007) Diabetes increases apoptosis and necrosis in both ischemic and nonischemic human myocardium: role of caspases and polyadenosine diphosphate-ribose polymerase. J Thorac Cardiovasc Surg 134(1):124–131 4. Kuethe F, Sigusch HH, Bornstein SR, Hilbig K, Kamvissi V, Figulla HR (2007) Apoptosis in patients with dilated cardiomyopathy and diabetes: a feature of diabetic cardiomyopathy? Horm Metab Res 39(9):672–676

5. Cai L, Li W, Wang G, Jiang Y, Kang YJ (2002) Hyperglycemia-induced apoptosis in mouse myocardium. Diabetes 51(6):1938–1948 6. Abel ED (2004) Glucose transport in the heart. Front Biosci 9(1):201–215 7. Saltiel AR, Kahn RC (2001) Insulin signalling and the regulation of glucose and lipid metabolism. Nature 414:799–806 8. Towler MC, Hardie DG (2007) AMP-activated protein kinase in metabolic control and insulin signalling. Circ Res 100 (3):328–341 9. Ravichandra SD, Asha Devi S, Subramanyam MVV (2019) Trolox prevents high glucoseinduced apoptosis in rat myocardial H9c2 cells by regulating GLUT-4 and antioxidant defense mechanism. IUBMB Life 71 (12):1876–1895 10. Szablewski L (2017) Glucose transporters in healthy heart and in cardiac disease. Int J Cardio 230(3):70–75

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11. Barron CC, Bilan PJ, Tsakiridis T, Tsiani E (2016) Facilitative glucose transporters: implications for cancer detection, prognosis and treatment. Metabolism 65(2):124–139 12. Kimes BW, Brandt BL (1976) Properties of a clonal muscle cell line from rat heart. Exp Cell Res 98(2):367–381 13. Hescheler J, Meyer R, Plant S, Krautwurst D, Rosenthal W, Schultz G (1991) Morphological, biochemical, and electrophysiological characterization of a clonal cell (H9c2) line from rat heart. Circ Res 69(6):1476–1486 14. Sipido KR, Marban E (1991) L-type calcium channels, potassium channels, and novel

nonspecific cation channels in a clonal muscle cell line derived from embryonic rat ventricle. Circ Res 69(6):1487–1499 15. Zordoky BNM, EL-Kadi AOS (2007) H9c2 cell line is a valuable in vitro model to study the drug metabolizing enzymes in the heart. J Pharmacol Toxicol Methods 56(3):317–322 16. Umpierrez GE, Murphy MB, Kitabchi AE (2002) Diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome. Diabetes Spectrum 15(1):28–36 17. Weir GC, Bonner-weir S (2004) Five stages of evolving β-cell dysfunction during progression to diabetes. Diabetes 53(suppl 3):S16–S21

Chapter 18 Flow Cytometric Analysis of Hyperglycemia-Induced Cell Death Pathways in Cardiomyoblasts Ravichandra Shivalingappa Davargaon, M. V. V. Subramanyam, and S. Asha Devi Abstract Type-2 diabetes, characterized by hyperglycemia causing various symptoms of metabolic disorders in the heart, kidneys, and brain, has many underlying molecular mechanisms leading to functional insufficiency of these organs. We describe protocols wherein we have optimized conditions for maintenance of hyperglycemic H9c2 cell lines and design to assess the effect of a water-soluble vitamin, Trolox, on the apoptotic pathway. Primarily, the design provides researchers to analyze apoptosis by flow cytometry. Keywords Annexin, Apoptosis, Cardiomyoblast, Flow cytometer, Hyperglycemia, Trolox

1

Introduction Research studies have proven that hyperglycemia as risk factor per se directly causing cardiac damage, leading to diabetic cardiomyopathy (DCM) [1–3]. Hyperglycemia-induced apoptosis of cardiomyocytes in diabetic animal models and patients is due to increased production of ROS, loss of contractile tissue, and eventually dysfunction [4, 5]. Caspases are cysteine-protease enzymes and play an important role in apoptosis. The caspases are synthesized and exist as inactive zymogen form, made-up of a large and small subunit. These subunits become separated as a result of proteolytic cleavage, which also results in activation of the enzyme [6]. These activate a series of reactions which finally results in apoptosis. Based on function, caspases are classified into: (1) proapoptotic (caspase-2, 3, 6, 7, 8, 9, 10) involved in signal transduction leads to cell death and (2) pro-inflammatory (caspase-1, 4, 5, 11, 12) caspases involved in control of cytokine maturation at the time of inflammation. The activation of caspase-3 through the release of cytochrome c is a

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_18, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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pivotal step in the initiation of apoptosis [7]. Further, the reactive oxygen species (ROS) as one of the stimuli for the release of cytochrome c is an equally important step toward apoptosis [8– 10]. The delivery of glucose from the blood to cardiac cells occurs by glucose transporter (GLUT)-4. Interestingly, the toxicity of high glucose is regulated, and oxidative stress (OS) induction in DCM is preventable through trolox, a water-soluble vitamin E in H9c2 cells, wherein GLUT-4 mRNA is significantly enhanced [11]. Programmed cell death involves transport of phosphatidylserine (PS) from the inner surface to the outer side of the plasma membrane. Even though PS externalization has various consequences in the cell, apoptosis recognition is among these. Apoptosis is an unavoidable mechanism that plays a vital role in health and disease, in embryonic development and in monitoring cell homeostasis. To estimate the percentage of cells in different stages of apoptosis, fluorescein isothiocyanate (FITC)-conjugated annexin V is used, which is a calcium-dependent positively charged sensitive phospholipid-binding protein probe that specifically binds to externalized PS when it is translocated to the outer surface of the plasma membrane during apoptosis. Flow cytometry (FC) is a technologically sophisticated tool having vast applications in cell and molecular biology besides bacteriology, virology, cancer biology, and infectious disease monitoring [12, 13]. The use of H9c2 cells as an in vitro model of rat cardiomyoblasts was established by Kimes and Brandt [14]. Studies have shown that DCM can be initiated in vitro in rat embryonic heartderived H9c2 cells, neonatal cardiomyocytes or cardiac fibroblasts with high glucose (HG), or advance glycation end product (AGE) stimulation [15, 16]. This chapter presents a flow cytometric protocol for evaluating apoptotic signaling pathways in hyperglycemic H9c2 cells and the impact of Trolox as an effective intervention in the mitochondrial-dependent apoptotic pathway.

2 2.1

Materials Cell Culture

1. H9c2 rat cardiomyoblast cell lines (National Centre for Cell Science (NCCS, Pune, India). 2. Cell culture medium: Dulbecco’s modified eagle’s medium (DMEM) with low glucose (5.5 mM), L-glutamine, sodium bicarbonate, and sodium pyruvate. 3. 1% antibiotics solution (100 U/mL penicillin, 100 μg/mL streptomycin). 4. 10% fetal bovine serum (FBS). 5. 5% preset CO2 incubator.

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6. 25 cm2 cell culture flasks, 6-well culture plates. 7. 1.5 and 2 mL click lock microcentrifuge tubes. 8. D-glucose. 9. 1 μM doxorubicin hydrochloride. 10. 5 μM camptothecin. 11. 100 μM 6-hydroxy-2,5,7,8-tetramethyl chromane-2-carboxylic acid (Trolox) dissolved in water 24 h before use. 12. Phosphate-buffered saline (PBS; pH 7.4): 10 mM Na2HPO4, 1.8 mM KH2PO4, 2.7 mM KCl, 137 mM NaCl. 13. Trypsin-ethylenediaminetetraacetic acid (EDTA) solution: 0.25% trypsin and 0.02% EDTA in Dulbecco’s phosphatebuffered saline. 14. 5 mL-capacity flow cytometer tubes. 15. Microcentrifuge. 2.2

Caspase-9 Assay

1. Caspase FITC staining kit (Abcam; Cambridge, MA, USA). 2. Caspase-9 inhibitor, Leu-Glu-His-Asp-fluoromethyl ketone (LEHD-FMK), conjugated to FITC (FITC-LEHD-FMK) solution (Caspase FITC staining kit). 3. Wash buffer (Caspase FITC staining kit). 4. Benzyloxycarbonyl-Val-Ala-Asp (OMe) fluoromethylketone (Z-VAD-FMK) (Caspase FITC staining kit).

2.3

Caspase 3 Assay

1. Caspase 3 FITC staining kit (Biovision; Milpitas, CA, USA). 2. Caspase-3 inhibitor, Asp-Glu-Val-Asp (OMe) fluoromethylketone DEVD-FMK, conjugated to FITC (FITC-DEVD-FMK) (Caspase 3 FITC staining kit).

2.4 Annexin V/ PI Assay

1. FITC—Annexin V. 2. Propidium iodide (PI). 3. 10
binding buffer: 0.1 M Heps/NaoH (pH 7.4), 1.4 M NaCl, 25 mM CaCl2.

2.5 Equipment and Software

1. FACSAria™ III Cell Sorter (BD-Biosciences; San Jose, CA, USA). 2. FACSDiva™ (v 7.0) software (BD-Biosciences).

3

Methods

3.1 Cryorecovery of Cells and Culture

1. Remove cryopreserved H9c2 cells vial from the liquid nitrogen cylinder.

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2. Thaw the vial, keep in 37  C water bath until the medium becomes liquid, and immediately centrifuge the cells at 1200
g for 4 min (see Notes 1–4). 3. Carefully discard the supernatant and resuspend the cells in 1 mL freshly made cell culture medium (see Note 5). 4. Transfer the suspended cells into a 25 cm2 flask and incubate cells in a CO2 incubator at 37  C, 5% CO2, 95% humidity, and allow them to adhere and grow. 5. Replace with fresh media after 2 days and allow the cells to grow until they reach 80–90% confluency. 6. Wash cells with 0.1 M PBS and add 3–5 mL of trypsin-EDTA solution and incubate 3 min in a preset CO2 incubator. 7. Collect the cells using a cell scraper into a new 5 mL centrifuge tube with media. 8. Centrifuge the cells at 1000
g for 5 min. 9. Discard the supernatant, resuspend cells in media, and count the cells using a hemocytometer. 10. Seed cells in 6-well plates (5
105/well) and grow as above until they reach 50–60% confluency. 3.2 Grouping and Treatment

1. Upon reaching 50–60% cell confluency, induce a hyperglycemic condition experimentally by adding 33 mM D-glucose to the media and designate as HG [4] (see Notes 6–8). 2. Maintain the 33 mM HG-exposed group and add 100 μM Trolox 24 h prior to HG exposure and designate this group as T + HG (see Note 9). 3. Maintain the HG and T + HG cells for 24 h under the same conditions described above. 4. Wash both sets of cells (~1
106/mL each) with 0.1 M PBS following completion of the treatment. 5. Harvest the cells by adding 3–5 μL trypsin-EDTA solution onto cells and incubate 5 min in a CO2 incubator as above. 6. Remove the cells using a cell scraper and collect into a centrifuge tube with media. 7. Centrifuge the cells at 1000
g for 5 min at 4  C (see Note 10). 8. Following centrifugation, discard the supernatant carefully and suspend the cells in 0.1 M PBS. 9. Wash the cells with ice-cold PBS for the assays (see Note 11). 1. Label tube as positive control where cells are treated with apoptosis-inducing agents like 1 μM doxorubicin hydrochloride or 5 μM camptothecin.

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Fig. 1 Percent-activated caspase-9 positive cells after exposing H9c2 cells to high glucose concentrations and Trolox pretreated HG-exposed H9c2 cells 3.3 Caspase-9 Estimation Using Flow Cytometry (See Note 12)

2. Label tube as negative control where cells are treated with 1 μL caspase inhibitor Z-VAD-FMK from the kit to induce cells to inhibit activation of caspase-9 (see Note 13). 3. Label tubes as per the abovementioned HG and T + HG treatments, and use untreated cells as controls. 4. Remove the needed caspase-9 kit reagents from the 20  C freezer and place on ice (see Note 14). 5. Pipette 300 μL of cell suspension into a labeled 1.5 mL tube. 6. Add 1 μL FITC-LEHD-FMK from the caspase-9 kit to each tube, mix well, and incubate at 37  C with 5% CO2 for 30–60 min (see Notes 15–17). 7. Centrifuge the cells at 1000
g for 5 min. 8. Discard the supernatant carefully and suspend the cell pellet in 0.5 mL wash buffer. 9. Centrifuge the cells at 1000
g for 5 min. 10. Carefully remove the tube from the centrifuge and discard the supernatant. 11. Resuspend the cell pellet in 300 μL wash buffer and analyze the samples in the flow cytometer using the FL-1 channel (485/535 nm; Ex/Em), following the manufacturer’s instructions (Fig. 1) (see Notes 18–23).

3.4 Caspase 3 Estimation Using Flow Cytometry (See Note 24)

1. Label positive control tubes where cells are treated with apoptosis-inducing agents like 1 μM doxorubicin hydrochloride or 5 μM camptothecin. 2. Label a negative control tube where induced cell samples are treated with caspase inhibitor Z-VAD-FMK (1 μL/mL) to inhibit activation of caspase-9 (see Note 13).

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Count

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Fig. 2 Percent-activated caspase-3 positive cells after exposing H9c2 cells to high glucose concentrations and Trolox pretreated HG-exposed H9c2 cells

3. Label the tubes as above for the HG and HG + T samples (see Note 18). 4. Remove reagents and buffers from 20  C and place on ice (see Note 14). 5. Induce apoptosis using the desired experimental method in cells and use uninduced cells as a control. 6. Pipette 300 μL cell suspension into appropriately labeled 1.5 mL tubes. 7. Add 1 μL FITC-DEVD-FMK to each tube, mix well, and incubate at 37  C with 5% CO2 for 30–60 min (see Note 15). 8. Centrifuge cells at 1000
g for 5 min. 9. Discard the supernatant carefully and suspend the pellet in 0.5 mL wash buffer. 10. Centrifuge cells at 1000
g for 5 min. 11. Remove the tubes carefully and discard the supernatant. 12. Resuspend the cell pellet in 500 μL wash buffer and analyze the samples with the flow using the FL-1 channel (485/535 nm; Ex/Em) as above (Fig. 2) (see Notes 18–23). 3.5 Analysis of Apoptosis Using Annexin-V/PI in the Flow Cytometer (See Note 25)

1. After the aforementioned grouping and treatment, wash the hyperglycemic and Trolox pretreated hyperglycemia-exposed cardiomyoblast H9c2 cells (~1
106/mL) with 0.1 M PBS (see Notes 1 and 2). 2. In parallel, maintain the untreated cells and positive control cells tube (see Note 26). 3. Add 3–5 μL trypsin-EDTA solution to cells and incubate for 5 min in the incubator with 5% CO2, 37  C and 95% humidity (see Note 5). 4. Scrape the cells and collect in a centrifuge tube with media.

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Fig. 3 Annexin-V and PI double-stained cells with various stages of apoptosis after high glucose exposed and high glucose with Trolox pretreatment. Quadrate 1 (Q1) represents cells in the late apoptosis stage, Q2 cells undergoing apoptosis, Q3 healthy cells, and Q4 pre-apoptotic cells. Data represented as % cells in each quadrate

5. Centrifuge at 1000
g for 5 min at 4  C. 6. Discard the supernatant carefully and wash cells twice using ice-cold 0.1 M PBS (see Note 15). 7. Resuspend ~1
106/mL concentration cells in 1
binding buffer. 8. Take 100 μL of cell suspension (1
105) in a 5 mL flow cytometer tube and add 5 μL of Annexin V and 5 μL of PI (see Notes 6 and 7). 9. Vortex cells in medium speed and incubate the tubes in dark for 15 min at room temperature (25  C) (see Note 16). 10. Post-incubation, add 400 μL of 1
binding buffer to each tube. 11. Analyze cells in flow cytometer within 1 h at 485/535 nm (Ex/Em) as above (see Notes 17–23). 12. Record the intensity of 10,000 fluorescence events and analyze the data using the FACSDiva software according to the manufacturer’s instructions. 13. Plot the cells on four quadrants (Q1 ¼ late apoptotic cells sage; Q2 ¼ apoptotic cells; Q3 ¼ healthy or non-apoptotic cells stage; and Q4 ¼ early apoptotic cells stage (Figs. 3 and 4) (see Notes 27 and 28).

4

Notes 1. Wear the protective gloves (to withstand the freezing temperature) while taking the vial from liquid nitrogen.

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Fig. 4 Schematic representation of the workflow of cell death analysis using flow cytometer upon exposure of H9c2 cardiomyoblasts to hyperglycemic conditions (the image was created on biorender platform)

2. Users should take care of the consumables like pipettes tips, tubes, and other laboratory consumables before starting the experiment. 3. Cryopreserved vial recovery should be done carefully while thawing and centrifuging as cryopreserved cells are sensitive and fragile. 4. Recovery of cryopreserved cells should be performed under sterile conditions, the user should wear sterile gloves, wipe the vials with ethanol after centrifugation and while transfering into the biosafety cabinet. 5. Post trypsinization, cells should be uniformly distributed with no cell clumps. Users should gently purge cells so that cells detach from each other so that it will be easy to count and seed them. 6. Users should wear an apron, gloves, and eye-protective goggles while handling the samples and chemicals carefully. Label the

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tubes properly and cover with cello pin tape to avoid ink remove from the label due to ethanol exposure and chances of cross contamination. 7. Users should check the expiration date, precipitation of reagents, and buffers used in the experiments and remove from the freezer 10–15 min prior to use so that these come to working temperature. Keep the working solutions at 4  C, avoid repeated freezing and thawing steps. 8. Dissolve D-glucose in DMEM filter using a sterile syringe filter. The 33 mM concentration represents hyperglycemic hyperosmotic syndrome (>33 mM) stages of diabetes as reported earlier [17, 18]. 9. Dissolve Trolox in DMEM and filter using a sterile syringe filter. 10. While processing cells, keep the number of purgings uniform for all samples of the experimental groups. 11. Care must be taken while taking out the tubes from centrifuge and while discarding the supernatant after centrifugation. 12. Caspase-9 being an initiator caspase of the apoptotic pathway, gets activated as a result of cytochrome c release from the inner mitochondrial space as a consequence of a disturbance in mitochondrial permeability transition. Active caspase-9 in turn converts caspase 3 to an active form and that leads to an apoptotic mode of cell death. The caspase-9 inhibitor LEHD-FMK conjugated to FITC (FITC-LEHD-FMK) as a fluorescent marker is used in this assay. FITC-LEHD-FMK is cell-permeable, nontoxic, and irreversibly binds to activated caspase-9 in apoptotic cells. As a cautionary note, carefully label tubes and seal with cello tape to prevent cross contamination and erasing of label due to handling. Factors to be considered while using caspase activity assays: (a) Different types of cells show a difference in caspase expression. (b) Caspase substrate used in the assay may not be specific for particular caspase, to avoid overlapping specificities, one should use other methods like western blot or fluorescence substrates assay like FRET that can be employed in combination with a caspase activity assay. (c) Caspase cascade cleavage is duration-dependent, therefore, one should note at what time the highest concentration of caspase cascade is taking place. 13. The user should maintain a positive and negative control along with the designed experimental groups, which helps to get a working confirmation of reagents used in the assay.

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14. Aliquot the reagent and fluorochrome into vials and label as a working solution. Minimize thawing freezing cycles and exposure of fluorochrome to light. 15. In between the incubation period, mix tubes once. 16. Do not vortex at high speed as this may damage cells. Vortex tubes before loading the tube into flow cytometer for analysis to minimize formation of cells clumps. If cells form clumps, then the user faces clogging problems in the flow cytometer. 17. Do not expose the sample to light during incubation and before loading into the flow cytometer. This may result in the loss of fluorescence as fluorescence probes are light-sensitive. 18. Check all connections are proper and all three components are working properly: fluidics; optics; and electronics. 19. For good results, it’s important to use the recommended amount of cells and reagents while analyzing in the flow cytometer. 20. Factors for the high background are due to use of a higher number of cells, an increased volume of reagents, improper washing of cells, highly confluent cells, contamination of cells, and using a longer duration of incubation than suggested. 21. Factors that result in lower background include the use of fewer cells, low volume of reagents, delay in apoptosis in cells, and an improper setting of the flow cytometer. 22. Do not over or under incubate the cells with fluorochrome as this may affect the result of the experiment. 23. Inconsistent results during analysis may be due to the use of an uneven number of cells for analysis, use of an inappropriate volume of reagents, uneven incubation time, dislodging, and inadvertant washing away of adherent cells during the experiment prior to analysis. 24. Caspase-3 inhibitor, DEVD-FMK conjugated to FITC (FITCDEVD-FMK), is used in this assay as a marker. FITC-DEVDFMK is cell-permeable, nontoxic, and irreversibly binds to activated caspase-3 in apoptotic cells. 25. The PS exposure serves as a sensitive marker for early stages of apoptosis using FITC-annexin V and PI combinations as a double-staining method to quantitatively determine the percentage of cells actively undergoing apoptosis. PI is used to differentiate live and dead cells. Cells with an undamaged phospholipid membrane will not be stained by PI, while damaged cells will take up the PI stain. Apoptotic cells show positive for annexin V and negative for PI, whereas cells which show positive for annexin V and PI are in the late apoptotic, necrotic, or already dead stage. Cells which are negative for both annexin

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V and PI are alive and do not show quantifiable apoptosis. Double-staining using annexin-V and PI was done by following the manufacturer’s instructions. 26. Controls for compensation and setup of the instrument for annexin V/PI staining: (a) Unstained cells. (b) FITC-annexin V alone stained cells (no PI). (c) PI alone stained cells (no Annexin V). 27. To determine the basal level of apoptotic and dead cells, an untreated cell population is used. The percentage of cells that have undergone apoptosis is then determined by substracting the percentage of apoptotic cells in the untreated cell population from that in the treated population. 28. Cell death is the eventual outcome of cells undergoing apoptosis, cells in the late stage of apoptosis will have a damaged cell membrane and so will stain positive for Annexin V and PI. Therefore, the assay does not distinguish between cells that have already undergone an apoptotic cell death and cells that have died as a result of the necrotic pathway (in either case, the dead cells will stain with both FITC Annexin V and PI).

Acknowledgments This work was supported by financial assistance granted under the University Grants Commission-Centre with Potential for Excellence in a Particular Area (UGC-CPEPA, F.No.8-2/2008 (NA/PE) dt.21.12.2011), New Delhi, India. References 1. Devereux RB, Roman MJ, Paranicas M, O’Grady MJ, Lee ET, Welty TK et al (2000) Impact of diabetes on cardiac structure and function: the strong heart study. Circulation 101(19):2271–2276 2. Singh JP, Larson MG, O’Donnell CJ, Wilson PF, Tsuji H, Lloyd-Jones DM et al (2000) Association of hyperglycemia with reduced heart rate variability (The Framingham Heart Study). Am J Cardiol 86(3):309–312 3. Johnston MT, Veves A (2001) Diabetes and cardiovascular diseases. Humana Press, Totowa, NJ. ISBN-10: 089603755X 4. Cai L, Li W, Wang G, Guo L, Jiang Y, Kang YJ (2002) Hyperglycemia-induced apoptosis in mouse myocardium: mitochondrial cytochrome C-mediated caspase-3 activation pathway. Diabetes 51(6):1938–1948

5. Cai L, Wang Y, Zhu G, Chen T, Song Y, Li XKang YJ (2006) Attenuation by metallothionein of early cardiac cell death via suppression of mitochondrial oxidative stress results in a prevention of diabetic cardiomyopathy. J Am Coll Cardiol 48(8):1688–1697 6. Huang ML, Chiang S, Kalinowski DS, Bae DH, Sahni S, Richardson DR (2019) The role of the antioxidant response in mitochondrial dysfunction in degenerative diseases: crosstalk between antioxidant defense, autophagy, and apoptosis. Oxidative Med Cell Longev 2019:6392763 7. Roy S (2000) Caspase at the heart of the apoptotic cell death pathway. Chem Res Toxicol 13 (10):961–962 8. Feuerstein GZ, Young PR (2000) Apoptosis in cardiac diseases: stress- and mitogen-activated

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signaling pathways. Cardiovasc Res 45 (3):560–569 9. Wang GW, Klein JB, Kang YJ (2001) Metallothionein inhibits doxorubicin-induced mitochondrial cytochrome c release and caspase-3 activation in cardiomyocytes. J Pharmacol Exp Ther 298(2):461–468 10. Davargaon RS, Asha Devi S, Subramanyam MVV (2018) Toxic effect of high glucose on cardiomyocytes, H9c2 cells: Induction of oxidative stress and ameliorative effect of trolox. J Biochem Mol Toxicol 33(4):e22272. https:// doi.org/10.1002/jbt.22272 11. Davargaon RS, Asha Devi S, Subramanyam MVV (2019) Trolox prevents high glucoseinduced apoptosis in rat myocardial H9c2 cells by regulating GLUT-4 and antioxidant defense mechanism. IUBMB Life 71 (12):1876–1895 12. Boeck G (2000) Current status of flow cytometry in cell and molecular biology. Int Rev Cytol 204:239–298

13. McKinnon KM (2018) Flow cytometry: an overview. Curr Protoc Immunol 120:5.1.1–5.1.11 14. Kimes BW, Brand BL (1976) Properties of a clonal muscle cell line from rat heart. Exp Cell Res 98(2):367–381 15. Sun Q, Wu X, Wang H, Chen W, Zhao X, Yang Y, Chen W (2019) Protective effects of astragalus polysaccharides on oxidative stress in high glucose-induced Or SOD2-Silenced H9C2 cells based on PCR array analysis. Diabetes Metab Syndr Obes 12:2209–2220 16. Tang D, Kang R, Berghe TV, Vandenabeele P, Kroemer G (2019) The molecular machinery of regulated cell death. Cell Res 29 (3):347–364 17. Umpierrez GE, Murphy MB, Kitabchi AE (2002) Diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome. Diabetes Spectrum 15(1):28–36 18. Weir GC, Bonner-weir S (2004) Five stages of evolving β-cell dysfunction during progression to diabetes. Diabetes 53(suppl 3):S16–S21

Chapter 19 Vietnamese Medicinal Plants as Potential Resources to Explore New Anticancer and Anti-inflammation: Established Assays for Pharmacological Tests Trang Thi Phuong Nguyen, Dieu Thi Xuan Nguyen, and Triet Thanh Nguyen Abstract Cancer is one of the most serious health problems in the world, which annually increases in incidence and mortality rates. Among therapies for cancer, chemical treatments are widespread. However, the benefit of these compounds remains limited due to high cytotoxicity, resistances, and non-selectivity. In addition to cancer, inflammation is also a common symptom and usually relates to other diseases such as infection and cancer. Therefore, investigation of new agents for anticancer and anti-inflammation is of high interest. The tropical climate of Vietnam makes it one of the most biodiversity-rich countries in the world, with a wide availability of traditional medicines and herbs for primary healthcare. However, most of utilization of Vietnamese medicinal plants is not evidence-based as few systematic studies of these have been performed. In this chapter, we present established anticancer and anti-inflammation assays for natural extract and compounds from a Vietnamese medicinal plant. In addition, the procedures of extraction, separation, and isolation of this plant are described. Key words Anticancer, Anti-inflammation, Natural product, Medicinal plants, XTT assay, Extraction, Cyclooxygenase (COX) inhibition

1

Introduction Natural product research is still a potential approach concerning the investigation of promising novel compounds for anticancer remedies despite the rapid development of pharmaceutically synthetic chemistry [1]. Plants have been proven to be an important source of accepted substances for the treatment of cancers. Nine anticancer compounds originating from plants have been approved for various types of cancer since 1961, including vinblastine, vincristine, etoposide, teniposide, taxol (paclitaxel), navelbine, taxotere

Trang Thi Phuong Nguyen and Dieu Thi Xuan Nguyen contributed equally with all other contributors. Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_19, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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(docetaxel), camptothecin, topotecan, and irinotecan. They are classified in different groups according to chemical structures, such as alkaloids, isoprenoids, polyketides, naphthoquinones, flavonoids, other polyphenol-type derivatives, and carotenoids. Because of the structural complexity, plant-derived compounds present a wide range of diverse mechanisms for targeting different types of cancer cells [1, 2]. Natural products have also been used as a source for discovery of anti-inflammatory agents since ancient times. Inflammation was described by Celsius with four typical signs (redness, heat, pain, and swelling), and he used willow extracts to alleviate these. The consumption of plants containing salicylate led to the development and manufacture of aspirin-derived anti-inflammatory drugs. Despite the development of synthetic drugs, plant-derived drugs still play a significant role in remedies. According to the British Nutrition Foundation report on phytochemicals, plant natural products for anti-inflammatory property can be classified in several major groups: terpenoids, flavonoids, allied phenolic, polyphenolic compounds, and sulfur-containing substances. Some of these have been studied for their clinical efficacy [3]. Increasing numbers of studies have been performed to prove the connection between inflammation and cancer. Inflammation can contribute to many stages of cancer progression, including initiation, promotion, angiogenesis, and metastasis, through two main pathways. The extrinsic pathway shows the effects of inflammatory conditions on the increase of cancer risk in organs such as the liver, pancreas, stomach, colon, and prostate gland. The intrinsic pathway shows the connection between genetic factors, such as oncogenes, and the inflammatory milieu. For instance, Helicobacter pylori infection has been linked to gastric cancer, infection with hepatitis viruses, such as hepatitis B or C (HBV or HCV), and can increase the risk of hepatocellular carcinoma. Instead of infection, immunodeficiency and autoimmunity-induced chronic inflammation can also promote tumor development, which has been observed in colorectal cancer-related inflammatory bowel disease. Conversely, application of microbial preparations for induction of acute inflammation has been applied as a successful cancer treatment, via a currently unknown mechanism [4, 5]. Vietnam is one of the most biodiversity-rich countries in the world as it possesses around 20,000–30,000 vascular plant species. The most up-to-date data have shown that there are about 11,458 animal species and 21,017 plant species in Vietnam. Among the described plants, only 6000 are used currently for medical, food, materials, and other purposes. As is the case for several other Asian countries, Vietnam is also rich in traditional medicine knowledge, with 80% of the population using such treatments in the primary healthcare system [6]. To promote the potential of Vietnamese medicinal resources, many studies have been performing recently

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for screening the anticancer and anti-inflammatory activities. In 2002, Tran Le Quan et al. screened 77 Vietnamese medicinal plants for antiproliferative activity against several cancer cell lines, using the colorimetric MTT assay for metabolic activity [7]. In a continuing effort to boost the knowledge about bioactivities and phytochemicals of the medicinal plants growing in Vietnam, we present a protocol with a special focus on assessing anticancer and anti-inflammatory activities. Specifically, we present the bioactivity-guided isolation of potential natural products with these properties from Vietnamese medicinal plant resources, as well as the XTT cell proliferation and cyclooxygenase (COX) inhibition assays, using several common cancer cell lines, such as the CCRF-CEM (a T lymphoblastoid cell line obtained from a 4-yearold Caucasian female with acute lymphoblastoid leukemia), HCT116 (a malignant cell line isolated from a male with colonic carcinoma), MDA-MB-231 (a cell line isolated from a Caucasian female breast adenocarcinoma), U251 (derived from a malignant glioblastoma tumor), and MRC-5 (derived from human fetal lung by SV40 transformation) cell lines. It is hoped that such investigations of the phytochemical constituents of medicinal plants can be applied to seek and develop promising anticancer, antiinflammatory compounds from herbal plants growing in Vietnam.

2

Materials

2.1 Plant Material, Extraction, and Isolation of Compounds

1. Aerial parts of Enhydra fluctuans Lour (Fig. 1) (see Note 1). 2. n-Hexane. 3. Petroleum ether. 4. Dichloromethane. 5. Chloroform. 6. Diethyl ether. 7. Acetone. 8. Ethyl acetate. 9. n-Butanol. 10. Ethanol. 11. Methanol. 12. Formic acid. 13. Thin layer chromatography (TLC) plates. 14. Vanillin-sulfuric acid. 15. High-performance instrument.

liquid

chromatography

(HPLC)

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Fig. 1 Enhydra fluctuans Lour

16. Stationary phases: silica gel, aluminum oxide, Sephadex, cellulose, and polyamide. 17. Rotary evaporator. 18. Ultrasonic bath. 19. Glass column. 20. Flash chromatography system. 21. Fast centrifugal partition chromatography (FCPC) system. 22. Spectrophotometer with ultraviolet and visible (UV/VIS) light capability. 2.2 Structure Identification of Isolated Compounds

1. NMR solvents. 2. HPLC grade solvents. 3. NMR tubes. 4. NMR spectrometer. 5. Liquid chromatography-mass spectrometry system (LC-MS). 6. Polarimeter. 7. X-ray apparatus. 8. ECD/VCD instrument.

2.3

Cell Culture

(electronic/vibrational

circular

dichroism)

1. Human T-lymphoblastic leukemia CCRF-CEM cells. 2. Breast cancer MDA-MB-231 cells. 3. Human glioblastoma U251 cells. 4. Human colorectal carcinoma HCT116 cells. 5. Medium for CCRF-CEM and MDA-MB-231 cells: RPMI 1640 (Gibco®, Invitrogen, Darmstadt, Germany), containing 2 mM L-glutamine, 10% heat-inactivated fetal bovine serum

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(FBS; PAA Laboratories, Pasching, Austria), and 1% penicillinstreptomycin. 6. Medium for U251 and HCT116 cells: Dulbecco’s Modified Eagle medium (DMEM; Gibco®), containing 4 mM L-glutamine, 10% heat-inactivated FBS, 1% penicillin-streptomycin. 7. Heraeus HERA cell 240 breeder (Thermo Fisher Scientific Inc.; Vienna, Austria). 8. Neubauer hemocytometer. 9. CASY® cell counter (Innovatis; Reutlingen, Germany). 10. Olympus CKX41 microscope (Hamburg, Germany). 2.4 Viability Assay (XTT Assay)

1. Cell proliferation kit II (XTT; Roche Diagnostics, Mannheim, Germany). 2. Vinblastine. 3. Dimethyl sulfoxide (DMSO). 4. Hidex Sense microplate reader (Turku, Finland).

2.5 Cyclooxygenase (COX) Inhibition Assays

1. Ovine COX-1 and human recombinant COX-2 enzymes (Cayman Chemicals; Ann Arbor, MI, USA). 2. PEG2 KIA kit (Enzo Life Sciences; Farmingdale, NY, USA). 3. 1.25 μM indomethacin. 4. 8.8 μM celecoxib (see Note 2). 5. 5 μM N-[2-(cyclohexyloxy)-4-nitrophenyl]-methanesulfonamide (NS 398) (Cayman Chemicals). 6. 5 μM arachidonic acid (AA). 7. Assay buffer: 0.1 M Tris/HCl (pH 8.0). 8. 50 μM ethylenediaminetetraacetic acid (EDTA). 9. 10% formic acid.

3

Methods

3.1 Plant Material, TLC, and HPLC Fingerprints

1. Dry aerial parts of plants. 2. Pulverize to a powder for extraction. 3. Extract material powder with different solvents such as n-hexane, dichloromethane, ethyl acetate, and methanol (see Note 3). 4. Evaporate solvent and dry extracts under nitrogen. 5. Store at 4  C for further chemical analysis, pharmacological studies, and isolation of active components.

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6. Screen all extracts for phytochemical composition by applying 10 μL of a 5 mg/mL stock solution of every extract on TLC plates. 7. Develop the TLC plates with different mobile phases to optimize the conditions for separation, such as n-hexane-ethyl acetate (5:5), chloroform-methanol-formic acid (80:20:1), and ethyl acetate-acetone (9:1). 8. Observe the TLC plates under UV at 254 nm and 366 nm. 9. Spray the plates with vanillin-sulfuric acid to detect terpenoidtype compounds as blue to purple spots and flavonoids as yellow spots (nonspecific). 3.2 Extraction, Separation, and Isolation of Compounds from Plant Materials

1. Extract the powdered plant material from step 2 Subheading 3.1, with methanol or ethanol using a method such as cold maceration, percolation, reflux extraction, or ultrasonicassisted extraction to obtain the total extract (see Note 4). 2. Remove the organic solvent by vacuum to yield the crude extract. 3. Suspend the extract in water and sequentially fractionate with petroleum ether, diethyl ether, ethyl acetate, and n-butanol (see Note 5). 4. Evaporate organic layers and the final aqueous layer under reduced pressure to yield the petroleum ether, diethyl ether, ethyl acetate, n-butanol, and water fractions. 5. Subject the fractions of interest to column chromatography (open column or flash chromatography) to separate them into subfractions. 6. Monitor the separation by TLC and HPLC analysis (Fig. 2). 7. Further fractionate the subfractions of interest, isolate and purify the compounds using different preparative techniques, such as column chromatography (with silica gel, Sephadex LH-20, aluminum oxide, cellulose, or polyamide as the stationary phase), FCPC, recrystallization, preparative TLC or preparative HPLC (see Note 4).

3.3

Recrystallization

1. Select the fraction in which the compound of interest is dominant (see Note 6). 2. Completely dissolve the mixture in a minimum amount of solvent or mixture of solvents in which the desired compound has moderate solubility to create a saturated solution. 3. Cool down the solution or evaporate the solvent(s) slowly to crystallize the compound of interest.

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mAU 300

250 200 150 100 50 0 0

10

20

30

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50

min

Fig. 2 HPLC-PDA analysis of n-hexane extract of Enhydra fluctuans aerial parts, detected at 230 nm

Fig. 3 Classical silica gel column chromatography 3.4 Silica Gel Column Chromatography (Fig. 3) (See Note 7)

1. Choose the suitable mobile phase by TLC. 2. Stabilize the stationary phase in the column with the initial concentration of the mobile phase. 3. Apply the sample onto the column as a solution or as a homogeneous mixture with silica gel.

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4. Elute by the mobile phase. 5. Monitor by TLC, collect, and combine the fractions containing similar composition. 6. Evaporate the obtained fractions to dryness. 3.5 Sephadex Column Chromatography (Fig. 4)

1. Swell Sephadex fully in the suitable solvent or mixture of solvents (mobile phase) and fill in the glass column. 2. Stabilize the stationary phase in the column. 3. Dissolve the sample in a minimum amount of mobile phase, filter if necessary. 4. Load sample on top of the bed. 5. Isocratically elute using the mobile phase. 6. Monitor by TLC, collect, and combine the fractions containing similar composition. 7. Evaporate the obtained fractions to dryness.

3.6

FCPC

1. Select a suitable two-phase solvent system. 2. Saturate the solvents in a separatory funnel, separate, and degas in an ultrasonic bath prior to use. 3. Fill the tube system by the mobile phase with low rotation. 4. Increase the rotation and pump in the mobile phase. 5. Equilibrate the system. 6. Inject the sample solution. 7. Perform the separation. 8. Monitor by TLC, collect, and combine the fractions containing similar composition. 9. Evaporate the obtained fractions to dryness.

3.7 Preparative TLC (See Note 8)

1. Develop a suitable mobile phase on analytical TLC plates. 2. Apply sample on a preparative TLC plate as a long streak. 3. Detect the compounds of interest without destroying them by UV or using reagents on a small part of the plate vertically (see Note 9). 4. Scrape off the silica containing the target compounds. 5. Extract the compounds of interest by a suitable solvent (see Note 10).

3.8 Preparative HPLC (See Note 11)

1. Develop a suitable mobile phase using analytical HPLC with the respective analytical column. 2. Adjust and optimize the conditions on a preparative HPLC system.

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Fig. 4 Sephadex column chromatography

3. Inject the sample solution. 4. Collect the target compound(s) based on the HPLC signal (s) detected by detector.

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Fig. 5 Structure identification of enhydrin 3.9 Structure Identification of Isolated Compounds (Fig. 5)

1. Perform the LC-MS analysis of isolated compounds to determine their molecular weights. 2. Record one-dimensional and two-dimensional NMR spectra of isolated compounds. 3. Elucidate the structure of the compounds based on NMR data and their molecular weights in comparison with data published in literatures as available. 4. Identify the absolute configuration of the compounds if necessary, using X-ray diffraction analysis, ECD, VCD, Raman optical activity, or optical rotation measurements.

3.10

Cell Culture

1. Grow cells with appropriate medium, incubated at 5% humidified CO2 at 37  C (see Note 12). 2. Split cells when the confluence reached 90% at the ratio of 1:5 every 2 days or 1:10 every 3 days (see Note 13).

3.11 Cell Number Counting

1. Count the cells with Neubauer hemocytometer. 2. Mix at the ratio of 1:1 with medium. 3. Fill ca 7–10 μL of this suspension in the chamber. 4. Observe at 100 magnification with an Olympus CKX41 microscope. 5. Count cells in four squares. 6. Calculate number of cells as a mean value of four squares (see Note 14). 7. For counting using the CASY® counter, dilute 25 μL (for CCRF-CEM, U251, HCT116) or 50 μL (MDA-MB-231) of a cell suspension with 10 mL CASYton solution and analyze.

3.12 Viability Assay (XTT Assay) (See Notes 15 and 16)

1. Seed 5000 cells of MDA-MB-231, HCT116 in 100 μL suspension into every well of 96-well plates 24 h before adding the test compounds.

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2. Seed 10,000 cells of CCRF-CEM into every well of 96-well plates and add the compounds immediately. 3. Prepare a fresh solution consisting of XTT labeling reagent and an electron-coupling reagent in a ratio of 50:1. 4. Incubate cells with the substances for 72 h before adding 50 μL of XTT solution administered to each well. 5. Use vinblastine as a positive control (see Note 17). 6. Dissolve all compounds in 10% DMSO (see Note 18). 7. Incubate 1.5 h for the four cell lines: CCRF-CEM, HCT116, MDA-MB-231, U251 (see Note 19). 8. Read the absorbances in the spectrophotometer. 3.13 Cyclooxygenase (COX) Inhibition Assays (See Note 20)

1. Thaw AA at room temperature. 2. Add 10 μL of assay buffer and 10 μL samples in each well of a 96-well plate. 3. Preincubate enzymes and samples for 5 min at room temperature. 4. Add 10 μL AA in each well. 5. Add 10 μL EDTA in each well assessing COX-2 (do not add for COX-1). 6. Prepare a standard curve of prostaglandin E2 (PGE2) according to the kit instructions. 7. Incubate by shaking for 20 min in a water bath at 37  C. 8. Add 10 μL 10% formic acid. 9. Perform the enzyme assay according to the kit instructions (see Note 21). 10. After a simultaneous incubation at room temperature, wash away excess reagents and add substrate. 11. After a 45-min incubation at room temperature, add 50 μL of stop solution from the kit to stop the reaction. 12. Read the optical density for the yellow color generated at 405 nm on a microplate reader immediately (see Note 22).

4

Notes 1. These should be collected by trained botanist. 2. Celecoxib is a cyclooxygenase 2 (COX2) inhibitor and nonsteroidal anti-inflammatory drug (NSAID) sold under the brand name Celebrex, among others. 3. Dried powder was successively extracted with solvents of increasing polarities in a Soxhlet apparatus for 24 h with every

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solvent, to give four dried extracts: n-hexane, dichloromethane, ethyl acetate, and methanol extracts. 4. All of these techniques will work but may be material- and use-dependent. 5. The volume of each solvents used depends on the composition and amount of each fractions. Each step of the liquid-liquid extraction is considered complete when the final organic layer after removal of solvent leaves an insignificant residue. 6. This can be determined using standards. 7. 3 kg of plant powder was extracted with 96% ethanol by percolation at room temperature. The total volume of 96% ethanol used was 60 L. The crude extract (600 g) was obtained after removal of solvent. 8. Enhydrin was purified from the enriched fraction as fine needles by recrystallization in ethanol [8]. 9. Detection usually occurs at the border of the plate. 10. Ethyl acetate fraction of E. fluctuans (7.5 g) was applied to column chromatography with silica gel as the stationary phase (300 g), eluted by petroleum ether and ethyl acetate mixture with step gradient of ethyl acetate. The separation was monitored by TLC, the similar subfractions were combined, resulting in 16 subfractions. The further purification of subfractions 12 and 13 by preparative TLC using petroleum:ethyl acetate (3:1) as mobile phase led to the isolation of baicalein-7-Oglucoside and baicalein-7-O-diglucoside [9]. 11. 19-hydroxy-15-desoxy orientalide, a melampolide-type sesquiterpene lactone, was isolated from an Enhydra species by preparative HPLC using a Phenomenex Ultremex C18 column (5 μm, 10 mm i.d.  250 mm), with methanol water (6:5) as the mobile phase [10]. 12. Human T-lymphoblastic leukemia CCRF-CEM cells and breast cancer MDA-MB-231 cells were cultured in RPMI 1640 medium (Gibco®), supplied with 2 mM L-glutamine, 10% heat-inactivated fetal bovine serum, and 1% Pen/Strep. Human glioblastoma U251 and human colorectal carcinoma HCT116 were grown in DMEM, 4 mM L-glutamine, 10% FBS, and 1% penicillin/streptomycin [11]. 13. The cells were cultured to grow at least 1 week before performing the experiments and kept for a maximum of 2 months to prevent development of old and mutated cells. 14. In this method, all cells were calculated, and Trypan Blue or dye in appropriate time could be used to determine whether the cells were alive or dead.

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15. The cells were only used for cytotoxic assays when the vitality reached over 90%. 16. Vinblastine is a chemotherapy medication. 17. In the XXT assay [11, 12], tetrazolium salt is widely used in histochemical localization studies and cell biology assays as a detection reagent. XTT (sodium 3-[1-(phenylaminocarbonyl)3,4 tetrazolium]-bis (4-methoxy-6-nitro) benzene sulfonic acid hydrate), a second generation of tetrazolium salt derivative, is a colorless or pale yellow compound that turns into brightly orange when it is reduced to form a water-soluble formazan derivative by mitochondrial oxidoreductases, released by viable cells (see Fig. 6 for the formation of formazan derivative from XTT). However, the results of XTT assays are not optimal when used alone, which are improved by an electron-coupling reagent (N-methyl dibenzopyrazine methyl sulfate, PMS). This assay was first established in 1988 by Scudiero et al. [13] and is popularly used to determine cellular proliferation and viability. 18. The final concentration of DMSO in the wells was kept at 0.5%, which exhibited no toxicity for the cells. 19. IC50 values of positive control (vinblastine) used for the cancer cell lines are shown in Table 1 [14]. 20. COX inhibition assay: COX enzymes are bifunctional enzymes, responsible for converting AA to bioactive prostaglandins such as PGE2, prostacyclin (PGI2), prostaglandin D2 (PGD2), prostaglandin F2α, and thromboxane by a peroxidase function. There are two well-known isoforms of COX being COX-1 and COX-2. Whereas COX-1 is responsible for physiological functions of normal tissues, involved in cellular homeostasis, COX-2 induces biosynthesis of PG-related acute inflammatory conditions. Chronic use of NSAIDs leads to the considerable risks of gastrointestinal hemorrhage due to COX-1 inhibition. On the other hand, the new selective COX-2 inhibitors seem to prevent the gastrointestinal side effects, but they have been found to cause cardiovascular problems [15]. Hence, the application of herbal extracts for the treatment of inflammation should be considered in both anti-COX-1 and anti-COX2 enzyme activities. 21. The principle of this assay is based on the quantitative determination of PGE2 using the PGE2-EIA kit. The kit uses a monoclonal antibody to PGE2 to bind, in a competitive manner, PGE2 in the samples and standard. PGE2 is formed from AA via the reaction catalyzed by ovine COX-1 and human recombinant COX-2 enzymes [16]. Refer to the PGE2-EIA kit protocol (or other PGE2-EIA/ELISA protocol) for complete instructions.

Fig. 6 Formation of formazan derivative from XTT

Oxireductases

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Table 1 IC50 values of positive control (vinblastine) used for the cancer cell lines IC50 values of positive control (vinblastine) (nM)

Cell line CCRF-CEM

9.4  0.2

HCT116

8.7  0.5 31.1  4.6

MDA-MB-231

8.1  1.0

U251

22. The intensity of the bound yellow color is inversely proportional to the concentration of PGE2 in either standards or samples. The measured optical density is used to calculate the concentration of PGE2. The inhibition of COX-1 and COX-2 by the samples is calculated based on the produced PGE2.

Acknowledgments Trang Thi Phuong Nguyen and Dieu Thi Xuan Nguyen contributed equally to this work. References 1. Demain AL, Vaishnav P (2011) Natural products for cancer chemotherapy. Microb Biotechnol 4(6):687–699 2. Cragg GM, Pezzuto JM (2016) Natural products as a vital source for the discovery of cancer chemotherapeutic and chemopreventive agents. Med Princ Pract 25(2):41–59 3. Yuan G, Wahlqvist ML, He G, Yang M, Li D (2006) Natural products and antiinflammatory activity. Asia Pac J Clin Nutr 15 (2):143–152 4. Grivennikov SI, Greten FR, Karin M (2011) Immunity, Inflammation, and Cancer. Cell 140 (6):883–899 5. Allavena P, Garlanda C, Borrello MG, Sica A, Mantovani A (2008) Pathways connecting inflammation and cancer. Curr Opin Genet Dev 18(1):3–10 6. Nguyen DNV, Nguyen T (2008) An overview of the use of plants and animals in traditional medicine systems in Viet Nam. Traffic Southeast Asia. Greater Mekong Programme, Hanoi, Vietnam. http://www.trafficj.org/publica tion/08_medical_plants_Viet_Num.pdf 7. Ueda JY, Tezuka Y, Banskota AH, Le Tran Q, Tran QK, Harimaya Y et al (2002)

Antiproliferative activity of Vietnamese medicinal plants. Biol Pharm Bull 25(6):753–760 8. Ali E, Ghosh Dastidar PP, Pakrashi SC, DurhamL J, Duffield AM (1972) Studies on Indian medicinal plants—XXVIII: sesquiterpene lactones of Enhydra fluctuans Lour. Structures of enhydrin, fluctuanin and fluctuadin. Tetrahedron 28(8):2285–2298 9. Santanu S, Upal KM, Arijit M, Dilipkumar P, Silpi LM, Souvik R (2010) Flavonoids of Enhydra fluctuans exhibit anticancer activity against Ehrlich’s ascites carcinoma in mice. Nat Prod Commun 5(8):1239–1242 10. Bardo´n A, Cardona L, Cartagena E, Catala´n CAN, Pedro JR (2001) Melampolides from Enydra anagallis. Phytochemistry 57 (1):125–130 11. Nguyen TT, Kretschmer N, Pferschy-Wenzig EM, Kunert O, Bauer R (2019) Triterpenoidal and phenolic compounds isolated from the aerial parts of Helicteres hirsuta and their cytotoxicity on several cancer cell lines. Nat Prod Commun 14(1):7–10 12. Kretschmer N, Rinner B, Deutsch AJ, Lohberger B, Knausz H, Kunert O et al (2012) Naphthoquinones from Onosma

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paniculata induce cell-cycle arrest and apoptosis in melanoma cells. J Nat Prod 75 (5):865–869 13. Scudiero DA, Shoemaker RH, Paull KD, Monks A, Tierney S, Nofziger TH (1988) Evaluation of a soluble tetrazolium/formazan assay for cell growth and drug sensitivity in culture using human and other tumor cell lines. Cancer Res 48:4827–4833 14. Kretschmer N (2011) Phytochemical and pharmacological investigations on constituents of medicinal plants with potential anti-cancer activity. Dissertation (PhD); University of Graz, Austria; urn: nbn:at:at-ubg:1-28906

15. Alberto MR, Zampini IC, Isla MI (2009) Inhibition of cyclooxygenase activity by standardized hydroalcoholic extracts of four Asteraceae species from the Argentine Puna. Braz J Med Biol Res 42(9):787–790 16. Lajter I, Pan SP, Nikles S, Ortmann S, Vasas A, Csupor-Lo¨ffler B et al (2015) Inhibition of COX-2 and NF-κB1 gene expression, NO production, 5-LOX, and COX-1 and COX-2 enzymes by extracts and constituents of Onopordum acanthium. Planta Med 81 (14):1270–1276

Chapter 20 Testing the Effect of Curcumin on Proliferative Capacity of Colorectal Cancer Cells Tannaz Jamialahmadi, Paul C. Guest, Amir R. Afshari, Muhammed Majeed, and Amirhossein Sahebkar Abstract This chapter presents a protocol for studying the effects of curcumin in a colorectal cell line and a mouse model of colitis-associated colon carcinogenesis. The protocol using the CT26 cell line incorporates cell proliferation, migration, invasion, spheroid formation, cell cycle, polymerase chain reaction (PCR), and western blot analyses. For the mouse model, this involved a macroscopic and histological examination of the colon and assays for oxidative damage markers. Keywords Colorectal cancer, CRC, Curcumin, Light microscopy, Histology, Activity assays, Western blot analysis

1

Introduction According to World Health Organization reports, colorectal cancer (CRC) was the second leading cause of cancer-related deaths in 2018, at 862,000 [1]. The incidence of CRC has increased steadily worldwide, especially in developing countries that have adopted a “Western” lifestyle [2]. This has been linked with a sedentary lifestyle, red meat consumption, alcohol, and tobacco, and increased obesity. Therefore, the risk of developing CRC can be reduced by reducing these factors and increased consumption of fiber and whole foods, along with specific vitamins and minerals. Polyphenols are naturally occurring bioactive compounds that have been tested with mixed results as potential therapeutics in various cancer models [3]. Curcumin is a polyphenolic compound in the turmeric plant (Curcuma longa L.). It has a long history of use in traditional medicines and has received considerable research interest in recent years due to discoveries showing that it has numerous pharmacological properties [4–10] (Fig. 1). Besides,

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_20, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Fig. 1 Structure of curcumin

curcumin is known to have anticancer and antitumor activities [11– 16]. Curcumin appears to cause cancer cell death by modulating multiple signaling networks involving membrane receptor pathways, kinases, cytokines, transcription factors, epigenetic changes, and cell cycle regulation [17–19]. This chapter presents a protocol for studying the effects of curcumin in a CRC cell line and a mouse model of colitis-associated colon carcinogenesis [20]. The protocol using the cell line incorporates cell proliferation, migration, invasion, spheroid formation, cell cycle, polymerase chain reaction (PCR), and western blot analyses. For the mouse model, this involves a macroscopic and histological examination of the colon and assays for oxidative damage markers.

2

Materials

2.1 Samples and Reagents

1. CT26 cells (American Type Culture Collection; Manassas, VA, USA) (see Note 1). 2. Eight-week-old female C57BL/6 mice (n ¼ 24) (Pasteur Institute; Tehran, Iran) (see Note 2). 3. Azoxymethane (AOM) (see Note 3). 4. 1% dextran sodium sulfate (DSS). 5. Curcumin (Sami Labs Ltd.; Bangalore, India) in phosphatebuffered saline. 6. Roswell Park Memorial Institute (RPMI)-1640 medium, containing 10% fetal bovine serum (FBS) and 1% penicillin. 7. 0.25% trypsin-ethylenediaminetetraacetic solution.

acid

(EDTA)

8. Propidium iodide (PI). 9. 70% ice-cold ethanol. 10. RNase. 11. PCR primers for cyclin D1, E-cadherin, and beclin (Macrogen Co, Seoul, South Korea).

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12. RPMI/F12 supplemented 1:1 with GlutaMAX-I. 13. Phosphate-buffered saline (PBS). 14. 10% formalin solution. 15. Hematoxylin-eosin (HE). 16. 0.2% methylene blue solution. 17. Malondialdehyde (MDA) assay buffer: 0.5% thiobarbituric acid (TBA)/15% trichloroacetic acid (TCA). 5,50 -dithiobis(2-nitrobenzoic acid (DTNB). 18. 100 mM Tris-EDTA buffer (pH 8.6) (TE). 2.2

Assay Kits

1. 3-(4,5-dimethyl-2-thiazolyl)-2, 5-diphenyl-2H-tetrazolium bromide (MTT) cell metabolism assay kit (see Note 4). 2. RNX-PLUS RNA extraction system (SinaClon; Tehran, Iran). 3. SYBR Premix Ex Taq DNA polymerase (TaKaRa Bio; Shiga, Japan). 4. Oligonucleotide primers for cyclin D1, E-cadherin, and beclin genes (Macrogene Co; Seoul, South Korea). 5. Superoxide Dismutase colorimetric assay kit (Randox Laboratories Ltd.; London, UK) [21] (see Note 5).

2.3 Western Blot Analysis

1. Tissue-lysis buffer: 50 mM Tris (pH 8.0), 150 mM NaCl, 1% Triton X-100. 2. Sample buffer: 0.2 M Tris (pH 6.8), 10% sodium dodecyl sulfate (SDS), 10 mM dithiothreitol (DTT), 20% glycerol, and 0.05% bromophenol blue. 3. Transfer buffer: 25 mM Tris/190 mM glycine (pH 8.3), 20% methanol. 4. Blocking buffer: 20 mM Tris (pH 7.4), 150 mM NaCl, 5% skimmed milk powder. 5. Antibody incubation buffer: 20 mM Tris (pH 7.4), 150 mM NaCl, 0.1% Tween-20. 6. Wash buffer: 20 mM Tris (pH 7.4), 150 mM NaCl. 7. Antibodies: rabbit antihuman cyclin D1 and mouse antihuman β-actin (Cell Signaling Technology; Danvers, MA, USA). 8. Peroxidase-conjugated sheep anti-mouse serum. 9. Enhanced chemiluminescence (ECL) detection reagents 1 and 2 (GE Healthcare; Little Chalfont, UK).

2.4 Equipment and Software

1. 6-well microtiter plates. 2. 24-well plates. 3. Plate reader. 4. FACSCalibur flow cytometer and FlowJo software.

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5. DMI300B microscope (Leica; Wetzlar, Germany). 6. ABI-PRISM StepOne instrument (Applied Biosystems; Foster City, CA, USA). 7. Optical microscope and digital camera. 8. Slab gels polymerized from 10% acrylamide and 0.1% N,N0 -methylenebisacrylamide in Tris/glycine/SDS buffer (see Note 6). 9. Electrophoresis power supply. 10. Gel tanks and SDS polyacrylamide gel electrophoresis (SDS-PAGE) gels. 11. Nitrocellulose membranes (see Note 7). 12. Semidry electrophoretic transfer device (see Note 8). 13. SPSS statistical software (v.20; IBM; Chicago, IL, USA) (see Note 9).

3

Methods

3.1 Cell Viability Assay

1. Culture CT26 cells in F12 or RPMI-1640/FBS/streptomycin media at 37  C. 2. Harvest cells with trypsin-EDTA when they are in the exponential log phase. 3. Treat cells for 24, 48, and 72 h with 0–1000 μM curcumin. 4. Processed the plates for the MTT assay as described previously [22]. 5. Add 15 μL of MTT to each well and incubate 4 h at 37  C. 6. Add stop solution and leave overnight at room temperature. 7. Measure the optical density in a plate reader at 540 nm. 8. Normalize cell viability results in the medium control group and express as mean  SEM. Calculate cell viability using the following formula: Cell viability ð%of controlÞ ¼ 1  ðOD test sampleÞ=ðOD of control sampleÞ  100

3.2 Cell Cycle Analysis

1. To analyze the cell cycle distribution, seed CT-26 cells in a 6-well plate overnight in normal growth media. 2. Treat with curcumin for an additional 24 h. 3. Centrifuge at 1000  g, aspirate, and discard the medium. 4. Fix the cell pellets in 70% ice-cold ethanol for 2 h at 4  C.

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5. Incubate with RNase at 37  C for 30 min. 6. Stain cell nuclei with PI for 30 min. 7. Examine cell cycle distribution in the FACSCalibur flow cytometer using FlowJo software (see Note 10). 3.3 Analysis of Spheroids

1. Seed 105 cells per mL in RPMI/F12 supplemented with GlutaMAX-I (1:1) in agarose-coated 96-well plates to form spheroids. 2. After 15 days of culture, assess spheroid formation using an inverted phase contrast with the Leica-DMI300B microscope (see Note 11). 3. Calculate the spheroid volume (V) from the geometric mean of the perpendicular diameters D ¼ (Dmax + Dmin)/2, as follows [23]: V ¼ ð4=3Þ  π ðD=2Þ3

3.4

Migration Assay

1. Seed 2  105 cells in a 24-well plate and incubate overnight in a complete culture medium. 2. The next day, create a scratch in the center of each well. 3. Treat the cells with different curcumin concentrations (IC50, 2  IC50, and 0.5  IC50). 4. Investigate the time for the cells to fill the scratch and record by photography (see Note 12).

3.5

Real-Time PCR

1. Extract total RNA from the cells after treatment with 5-FU and curcumin at 1  IC50 and 5  IC50 concentrations using the RNX-PLUS system, according to the manufacturer’s protocol. 2. Synthesize cDNA from 100 μg of the resulting total RNA. 3. Carry out quantitative real-time reverse transcription-PCR using specific primers for cyclin D1, E-cadherin, and beclin in the StepOne instrument using the SYBR Premix Ex Taq DNA polymerase. 4. Normalize expression levels of the target genes to GAPDH gene expression levels, as described [24, 25] (see Note 13).

3.6 Western Blot Analysis

1. Harvest cells and lyse with ice-cold lysis buffer. 2. Heat the lysates in loading buffer for 5 min at 95  C and centrifuge at 700  g for 10 s (see Note 14). 3. Subject samples to SDS-PAGE at approximately 120 V/h until the dye front reaches the bottom of the gel (see Note 15).

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4. Disassemble the plates encasing the gel and subject the electrophoresed proteins in the gel to semidry electrophoretic transfer onto the nitrocellulose membranes (see Note 16). 5. After transfer, immerse the membranes in a blocking buffer and mix gently on a rocker for 2 h (see Note 17). 6. Remove the blocking solution and rinse 2 in antibody incubation buffer. 7. Incubate membranes with either cyclin D1 (1:000) or β-actin (1:5000) in antibody incubation buffer overnight at 4  C (see Note 18). 8. Remove the solutions and wash 3 for 5 min in antibody incubation buffer. 9. Add peroxidase-conjugated anti-rabbit or anti-mouse serum (both at 1:1000) to both membranes and incubate 2 h at room temperature. 10. Rinse 3 for 5 min in wash buffer and 2 in water. 11. Drain excess water from the membranes and place protein side up on smoothed cling film. 12. Mix equal volumes of ECL detection solutions 1 and 2 and add this to both membranes, so the entire surface is covered, and incubate 1 min at room temperature. 13. Remove excess detection reagent by holding an edge with forceps and touching a corner to filter paper. 14. Place the membrane protein side down on cling film and wrap so the cover is smooth with no wrinkles or air bubbles. 15. Insert membranes protein side up in a suitably sized film cassette. 16. Place one ECL Hyperfilm on top, seal the cassette, and expose for detection of the immunoreactive bands (see Notes 19 and 20). 3.7 Animal Model of Colitis-Associated Colon Carcinogenesis

1. Divide mice into four groups (n ¼ 6 each): designated control, 5-FU, curcumin, and 5-FU/curcumin-treated. 2. Perform intraperitoneal injections of mice with 10 mg/ kg AOM. 3. Provide three cycles of 1% DSS in drinking water for 1 week, followed by normal drinking water for 2 weeks. 4. Starting 1 week after the second DSS exposure, give curcumin (25 mg/kg/day, oral gavage), 5-FU (35 mg/kg 1/week), and curcumin +5-FU, as appropriate. 5. Evaluate the disease activity index at the end of the experiment using the criteria in Table 1.

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Table 1 Disease activity index criteria Score Criteria

0

1

2

3

Loss of body weight

Less than 5%

5–10%

10–15%

More than 15%

Prolapse of rectum

No sign

Sign

Clear

Extensive

Stool consistency

Normal

Soft

Very soft

Diarrhea

Rectal bleeding

None

Red

Dark red

Gross bleeding

Table 2 Scoring of inflammation in the colon Description

Grade

Normal appearance

0

Shortening/loss of basal 1/3 of crypts with mild mucosal inflammation

1

Loss of basal 2/3 of crypts and moderate mucosal inflammation

2

Loss of all crypts with severe inflammation mucosal but surface epithelium retained

3

Mucosal ulcer presentation with severe and extensive mucosal inflammation

4

6. For macroscopic and histological examination of tumors, isolate colons, wash using PBS, and open longitudinally to evaluate tumor number and size (see Note 21). 7. Fix the tissues in 10% formalin solution and embed them into paraffin blocks for sectioning (5 μm) and staining using HE. 8. Observe and record images using the optical microscope and digital camera (see Note 22). 9. Score inflammation in the HE-stained sections according to the criteria in Table 2 [26]. 10. Report as a mean score/mouse and assess as described previously [27]. 3.8 Determination of Oxidative Damage

1. Weigh target tissue and homogenize with PBS. 2. Centrifuge at 12,000  g for 10 min and recover the supernatant. 3. For MDA determination, dilute homogenate tenfold in PBS and combine 1 mL of this with 2 mL MDA assay buffer. 4. Heat 20 min in a boiling water bath. 5. Centrifuge at 4000  g and read the supernatant’s absorbance at 535 nm to calculate MDA as described [28].

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6. Use a standard curve of 100, 50, 25, 12.5, and 6.25 μM MDA in PBS to determine MDA concentration. 7. For estimating thiol concentration, add 1 mL TE to the tissue homogenate and read the absorbance in a spectrophotometer at 412 nm compared to Tris-EDTA buffer alone (A1). 8. Add 20 μL DTNB to this solution and leave at room temperature for 15 min. 9. After 15 min, rerecord the sample absorbance (A2) compared to a DTNB blank (DTNB). 10. Estimate the total thiol concentration (mM) using the formula [29]: Total thiol concentration ½mM ¼ ½A 2  A 1  DTNB  1:07=0:05  13:6

11. Measure SOD activity using the RANSOD kit according to the manufacturer’s instructions. 12. Measure catalase (CAT) activity as described by Aebi (1984) [30], based on the conversion of H2O2 to H2O and O2 by the sample in PBS and following a reduction in absorbance at 240 nm in 1 min. 13. Repeat all experiments at least twice. 14. Express data as mean  SE and analyze by Student’s t-test or ANOVA, followed by Tukey’s multiple comparison tests. 15. Carry out data analysis using the SPSS software and consider differences statistically significant with P < 0.05 (see Note 23).

4

Notes 1. This is an N-nitroso-N-methylurethane-(NNMU)-induced, undifferentiated colon carcinoma cell line. 2. Researchers must ensure that the experiments are approved by the local ethical agency. The current procedures were approved by the Ethical Committee of Mashhad University of Medical Science. 3. AOM is a gene mutation agent that can be used with dextran sulfate sodium (DSS) to create cancer models in laboratory animals. These are mostly used to study mechanisms of cancer progression and chemoprevention.

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4. The MTT is a colorimetric assay used for spectrophotometric quantification of cell proliferation and viability. The assay analyzes the number of viable cells by cleavage of tetrazolium salts. 5. This is an enzymatic method and based on a procedure described by McCord et al. [21]. 6. Such gels can be purchased ready-made from a supplier such as Novex (San Diego, CA, USA) or prepared by the user according to standard procedure, as described by Garcia et al. [31]. 7. Immobilon® P membranes composed of polyvinylidene fluoride (PVDF) can also be used if lower background staining is required. 8. Wet transfer devices can also be used. 9. Other statistical packages, such as GraphPad Prism (La Jolla, CA, USA), can also be used. 10. This analysis revealed that curcumin inhibited the cell cycle in the CRC cells as the percentage of the sub-G1 population increased to 30.2%, compared with this population in control (3.49%) [20]. Also, curcumin significantly increased cell numbers in the G0/G1 phase and led to a corresponding decrease in the G2/M phase compared to the control. 11. These results showed tumor shrinkage in spheroids treated with curcumin for 10 days, compared with untreated spheroids [20]. 12. This showed that 24 h treatment with curcumin led to a decreased invasion of the cells. 13. Curcumin significantly increased the expression of E-cadherin as a biomarker for invasion suppression [32]. This analysis also showed that cyclin D1 mRNA (a marker of uncontrolled cell growth [33]) was decreased, and beclin mRNA increased (a marker of autophagosome formation [34]). See [20] for data. 14. The heating denatures proteins for more efficient separation by SDS-PAGE. The brief centrifugation step collects the heated solution at the bottom of the tube to fully recover the original volume. 15. We used a 10% acrylamide gel to resolve protein bands in the region of 20–120 kDa to detect cyclin D1 and b-actin with fair resolution. For resolving higher molecular weight proteins, lower acrylamide concentrations should be used, and vice versa. 16. The use of 20% methanol in the transfer buffer aids transfer of membrane and hydrophobic proteins. Transfer at a power according to the manufacturer’s instructions. Generally, transfer at a constant current, and if transferring at a constant

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voltage, do not let the current exceed 0.4 A. A suitable starting voltage would be approximately 100 V, but reduce this if the current climbs too high. 17. This step is performed to block nonspecific sites on the membrane for improving the signal to noise ratio. 18. This step can also be carried out at room temperature for 1–2 h. 19. Exposure times should be varied depending on the quality of the antibodies and the native abundance of the target proteins. It may be necessary to perform a time course to determine each new experiment’s optimum exposure times. However, the intensity of the signal will fade with time. 20. This analysis revealed that cyclin D1 expression was significantly decreased in the curcumin-treated cells, with the most substantial changes seen with the curcumin +5-FU treatment. Over-expression of cyclin D1 can shorten the G1 phase of the cell cycle and force them through the G0/S checkpoint, leading to uncontrolled growth, as in cancer [33]. 21. We showed previously that curcumin tumor numbers and area were significantly reduced in treated groups, with the most remarkable effects seen in the curcumin/5-FU group [20]. 22. We previously showed that curcumin ameliorated inflammation as visualized in H & E stained colons [20]. 23. These analyses showed that the level of thiol was decreased in the AOM group compared to the control group, and increased in Cur and Cur + 5-FU groups compared to the AOM group. Also, in contrast with the control group, the activity of SOD and CAT were significantly decreased in the AOM group but were ameliorated by curcumin treatment [20].

Conflict of Interest Muhammed Majeed is the founder of Sabinsa-Sami Ltd. References 1. https://www.who.int/news-room/factsheets/detail/cancer 2. Rawla P, Sunkara T, Barsouk A (2019) Epidemiology of colorectal cancer: incidence, mortality, survival, and risk factors. Prz Gastroenterol 14(2):89–103 3. Alam MN, Almoyad M, Huq F (2018) Polyphenols in colorectal cancer: current state of knowledge including clinical trials and molecular mechanism of action. Biomed Res Int

2018:4154185. https://doi.org/10.1155/ 2018/4154185 4. Prasad S, Aggarwal BB (2011) Turmeric, the Golden spice: from traditional medicine to modern medicine. In: IFF B, Wachtel-Galor S (eds) Herbal medicine: biomolecular and herbal medicine: biomolecular and clinical aspects, 2nd edn. CRC Press, Boca Raton, FL, pp 263–288. ISBN-13: 978-1-43980819-1

Testing the Effect of Curcumin on Proliferative Capacity of Colorectal. . . 5. Mahmood K, Zia KM, Zuber M, Salman M, Anjum MN (2015) Recent developments in curcumin and curcumin based polymeric materials for biomedical applications: a review. Int J Biol Macromol 81:877–890 6. Mandal M, Jaiswal P, Mishra A (2020) Role of curcumin and its nanoformulations in neurotherapeutics: a comprehensive review. J Biochem Mol Toxicol 34(6):e22478. https://doi. org/10.1002/jbt.22478 7. Mollazadeh H, Cicero AF, Blesso CN, Pirro M, Majeed M, Sahebkar A (2019) Immune modulation by curcumin: the role of interleukin-10. Crit Rev Food Sci Nutr 59(1):89–101 8. Momtazi AA, Derosa G, Maffioli P, Banach M, Sahebkar A (2016) Role of microRNAs in the therapeutic effects of curcumin in non-cancer diseases. Mol Diagn Ther 20(4):335–345 9. Panahi Y, Ahmadi Y, Teymouri M, Johnston TP, Sahebkar A (2018) Curcumin as a potential candidate for treating hyperlipidemia: a review of cellular and metabolic mechanisms. J Cell Physiol 233(1):141–152 10. Panahi Y, Khalili N, Sahebi E, Namazi S, Simental-Mendı´a LE, Majeed M, et al (2018) Effects of Curcuminoids Plus Piperine on Glycemic, Hepatic and Inflammatory Biomarkers in Patients with Type 2 Diabetes Mellitus: A Randomized Double-Blind Placebo-Controlled Trial. Drug Res 68(7):403–409 11. Abbas Momtazi A, Sahebkar A (2016) Difluorinated curcumin: a promising curcumin analogue with improved antitumor activity and pharmacokinetic profile. Curr Pharm Des 22 (28):4386–4397 12. Iranshahi M, Sahebkar A, Takasaki M, Konoshima T, Tokuda H (2009) Cancer chemopreventive activity of the prenylated coumarin, umbelliprenin, in vivo. Eur J Cancer Prev 18(5):412–415 13. Teymouri M, Pirro M, Johnston TP, Sahebkar A (2017) Curcumin as a multifaceted compound against human papilloma virus infection and cervical cancers: a review of chemistry, cellular, molecular, and preclinical features. Biofactors 43(3):331–346 14. Ghasemi F, Shafiee M, Banikazemi Z, Pourhanifeh MH, Khanbabaei H, Shamshirian A, et al (2019) Curcumin inhibits NF-kB and Wnt/β-catenin pathways in cervical cancer cells. Pathology Research and Practice, 215(10):152556. https://doi.org/10.1016/ j.prp.2019.152556 15. Xiang DB, Zhang KQ, Zeng YL, Yan QZ, Shi Z, Tuo QH et al (2019) Curcumin: from a controversial “panacea” to effective antineoplastic products. Medicine (Baltimore) 99(2):

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Chapter 21 Assessment of Topical and Transdermal Penetration of Curcuma heyneana Rhizome Extract in Rat Skin: Histological Analysis Idha Kusumawati, Rohmania, Mega Ferdina Warsito, and Eka Pramyrtha Hestianah Abstract Currently, there are increasing numbers of dermal and transdermal dosage forms of both natural and synthetic compounds on the market. Therefore, it is necessary to have a method that can measure the release and penetration of the compound into the skin. This chapter presents a current method for evaluating the skin penetration of a Curcuma heyneana rhizome extract in vivo using histological parameters. We also evaluate a liposome delivery system of the same extract to determine any differences in penetration due to changes in the drug delivery system. Keywords Skin penetration, Skin permeation, Curcuma heyneana rhizome extract, Liposomes, Histological analysis

1

Introduction Recently, research into the development of transdermal and dermal dosage forms of natural therapeutic agents has increased. This skinapplied dosage form can deliver a minimal or noninvasive therapeutic agent into the body, which has an advantage over other delivery routes. This is in line with the increasing development of new drug delivery systems [1, 2]. The development of topical and transdermal drug delivery systems shows a significant advantage in effectively hitting drug targets in the body, thereby reducing systemic side effects. Also, such approaches can be an alternative to overcome the problem of oral drugs with low absorption and the occurrence of first-pass metabolic effects [1, 3]. For dermal and transdermal dosage forms, studies on drug penetration into the skin is a concern to determine the ability of drugs to reach their therapeutic targets. The penetration ability of a

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therapeutic agent is influenced by several factors such as the release of the agent from the carrier, the penetration of the agent through the stratum corneum and other skin layers, and the activity of the agent at the target point [1, 4]. In both dermal and transdermal dosage forms, the skin is a challenging barrier for efficient penetration of the therapeutic agent. The skin consists of three main layers, namely the epidermis, dermis, and hypodermis, and its thickness is influenced by body area, age, and gender [1, 2, 5, 6]. The factors affecting the release and penetration of the drug are the interactions between the drug, the skin, and the carrier. The release and penetration of the drug from the dermal and transdermal dosage forms to the systemic circulation is a series of multistep processes which includes: (a) release from the preparation; (b) partition into the stratum corneum; (c) diffusion into the stratum corneum; (d) partition of the stratum corneum into the epidermal layer; (e) diffusion across the epidermal layer into the dermis; (f) absorption by blood vessels; and (g) reaching the systemic circulation [1]. In previous research, we have shown that the ethanol extract of Curcuma heyneana rhizome has an antioxidant and antiaging activity that protects the skin from the damaging effects of excessive UV exposure [7–9]. This study used a histomorphometric method of rats exposed to UV light [10]. The development of a drug delivery system is needed to bring drugs into the skin, subcutaneous tissue, and even to the systemic body. Herbal extracts contain a variety of complex chemical constituents that have properties from lipophilic to hydrophilic and have small to large chemical structures. This will affect the ability of these chemical substances to penetrate into the skin [7, 9]. To increase penetration, an ethanol extract of Curcuma heyneana can be made in the form of a liposome. In this chapter, we use a rat skin tissue layer model and describe an in vivo bioassay protocol for enabling the penetration of the ethanol extract of Curcuma heyneana rhizome labeled with fluorescent rhodamine.

2

Materials

2.1 Animals, Solutions, and Reagents

1. 200–300 g healthy adult male rats (2–3 months old) (see Note 1). 2. 1% rhodamine. 3. Standard rat chow. 4. 70% ethanol. 5. Water. 6. Ethanolic extract of Curcuma heyneana rhizome [7] (see Note 2). 7. Gel base (see Note 3).

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8. Propylene glycol. 9. Phospholipon 90. 10. 100 mM phosphate buffer (pH 6.4) (see Note 4). 2.2 Equipment and Software

1. Electric razor. 2. Scissors. 3. Microdissection forceps. 4. Dissecting boards and pins. 5. Cryotome (Leica). 6. Microwave oven. 7. ULTRA-TURRAX® high-performance dispersing instrument (IKA; Staufen, Germany). 8. Rotary evaporator. 9. Inverted system microscope IX71-IX2 series optical microscope (Olympus; Shinjuku-ku, Tokyo, Japan) (see Note 5). 10. DP71 camera (Olympus). 11. Cell D software (Olympus). 12. Statistical analysis package (see Note 6).

3 3.1

Methods Animals

1. Acclimatize rats for at least 5 days before use (see Note 7). 2. Set the temperature of the animal room at 22
C (3
C) and the relative humidity at 30–70%. 3. Set the lighting cycle at 12 h light and 12 h dark. 4. Provide a conventional diet with access to water ad libitum. 5. Shave the back of each rat using the electric razor to expose a 3  3 cm area (Fig. 1).

3.2 Preparation of Curcuma heyneana Rhizome Extract

1. Wash the Curcuma heyneana rhizome, cut, and dry in an oven set at 40
C for 3 days. 2. Grind the dried material (100 g) into powder. 3. Extract using 10 volumes of 70% ethanol by heating in a microwave at 30% power for 1 min. 4. Combine the extract with the 1% rhodamine solution. 5. Dry by evaporating the ethanol under reduced pressure to obtain a crude extract.

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Fig. 1 Shaved back of the rat

Fig. 2 Sample application on skin back of the rat 3.3 Preparation of Liposomes of Curcuma heyneana Rhizome Extract

1. Dissolve the Phospholipon 90 using 6 mL propylene glycol. 2. Mix the extract of Curcuma heyneana rhizome (containing 3 mg curcuminoids) into the Phospholipon 90 solution. 3. Stir the mixture using the ULTRA-TURRAX at a speed of 8600 rpm for 5 min. 4. Add 4 mL of the phosphate buffer slowly during stirring.

3.4

Treatment

1. Assign the rats randomly into three groups: vehicle (gel base), Curcuma heyneana rhizome extract in gel base, liposome of Curcuma heyneana rhizome extract in gel base. 2. Apply the sample (50 mg) topically to the shaved area.

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Fig. 3 Skin biopsy from the back of the rat 3.5 Biopsy and Histology Analysis

1. After 60 min, cull rats by cervical dislocation. 2. Remove the skin wounds from the shaved area using the dissection tools (Fig. 3) (see Note 8). 3. Freeze the skin biopsies using liquid nitrogen for fresh sectioning (2 μm) using a cryotome (Fig. 4) (see Note 9). 4. Observe and record images using the fluorescence microscope and digital camera (Fig. 5 and Table 1) (see Note 10).

3.6 Statistical Analysis

1. Present the results as mean  standard error of the mean (SEM) and estimate statistical differences between groups using one-way analysis of variance (ANOVA) with Duncan’s test, considering p < 0.05 as statistically significant. 2. Determine the ratio data of the scoring of the sample penetration into the rat skin layer (Table 1 and Fig. 6) (see Note 11).

4

Notes 1. Before starting the research, researchers should ensure that all procedures adhere to ethical standards for animal use and are approved by the appropriate institutional authority. This study was approved by the Animal Experiment Ethics Committee of Airlangga University (protocol number 1146/10) [7]. 2. The ethanol extract of Curcuma heyneana rhizome used in this study was derived from previous research. Curcuma heyneana is a Zingiberaceous plant native to Java Island, Indonesia, known locally as Temu Giring, and is used for beauty treatments in Javanese and Balinese traditions [7].

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Fig. 4 Histology slide showing fresh biopsy rat skin

Fig. 5 (a) Diagram showing the basic layers of skin. (b) Experimental image showing scoring of the rat skin layers: (1) upper epidermis to stratum granulosum; (2) stratum spinosum to basal stratum; (3) upper dermis; and (4) lower dermis

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Table 1 Criteria for scoring histological specimens Score

Description

1

The sample penetration reaches the stratum corneum and the stratum granulosum layer

2

The sample penetration reaches the stratum spinosum and the stratum basal layer

3

The sample penetration reaches the papillary dermis

4

The sample penetration reaches the reticular dermis

4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 vehicle

a

extract

b

liposome of extract

c

Fig. 6 Scoring of histologic analysis of drug penetration through rat skin. Values are expressed as mean  SEM (n ¼ 6). Means associated with each set of data are significantly different at p < 0.05 (Duncan’s test) from either (a) vehicle (gel base) group, (b) Curcuma heyneana rhizome extract in gel base or (c) liposome of Curcuma heyneana rhizome extract in gel base

3. The vehicle used should be semisolid (cream- or gel-based) instead of liquid using a gel base. Attempts should be made so that this is similar to the Curcuma heyneana and retinoic acid samples. Both Curcuma heyneana extract and its liposomes are mixed into the gel base [7]. 4. Many buffers can be used. Here, we use phosphate buffer pH 6.8 for liposome preparation. 5. In this study, we used an Olympus fluorescence microscope, camera, and analysis package. Other similar systems can be used although the user should ensure compatibility with the experimental procedures. 6. Several statistical software packages can be used such as Microsoft Excel (Redmond, WA, USA) and SPSS (SPSS Inc., Chicago, IL, USA). 7. Acclimatizing the rats and ensuring conditions are constant and otherwise comfortable can reduce stress for more reproducible results.

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8. The rat skin biopsy should be immediately placed on filter paper to prevent it from creasing. 9. Histological slides should be analyzed immediately to prevent rhodamine fluorescence from fading. 10. The evaluation of liposome delivery system of the extract and its liposome can determine using the differences in penetration due to changes in the drug delivery system. The penetration of the sample was analyzed using rhodamine as an indicator [11– 13]. The skin penetration level of the sample was determined semiquantitatively based on scoring system (Table 1 and Fig. 5). 11. According to the penetration test results, the extract could penetrate the upper dermis and the basal stratum. The presence of phospholipids in liposomes that mimic the skin membrane explains this.

Acknowledgments This work was supported by an International Research Collaboration and Scientific Publication grant from the Ministries of Research, Technology, and Higher Education, Republic of Indonesia (Grant no. 597/UN3.14/LT/2017). Also, thanks to all my students for the nice pictures. References ˝cs M, 1. Zsiko´ S, Csa´nyi E, Kova´cs A, Budai-Szu Ga´csi A, Berko´ S (2019) Methods to evaluate skin penetration in vitro. Sci Pharm 87(3):19. https://doi.org/10.3390/ scipharm87030019 2. Roohnikan M, Laszlo E, Babity S, Brambilla D (2019) A snapshot of transdermal and topical drug delivery research in Canada. Pharmaceutics 11(6):256. https://doi.org/10.3390/ pharmaceutics11060256 3. Luı´s A, Ruela M, Perissinato AG, Esselin M, Lino DS (2016) Evaluation of skin absorption of drugs from topical and transdermal formulations. Brazilian J Pharm Sci 52(3):527–544 4. Shah VP, Yacobi A, Rədulescu FS, Miron DS, Lane ME (2015) A science based approach to topical drug classification system (TCS). Int J Pharm 491(1–2):21–25 5. Menon GK, Cleary GW, Lane ME (2012) The structure and function of the stratum corneum. Int J Pharm 435(1):3–9

6. Schaefer H, Redelmeier TE (2001) Chapter 11; skin penetration. In: Rycroft RJG, Menne´ T, Frosch PJ, Lepoittevin JP (eds) Textbook of contact dermatitis. Springer, Berlin, pp 209–225. ISBN: 978-3-662-103043 7. Kusumawati I, Kurniawan KO, Rullyansyah S, Prijo TA, Widyowati R, Ekowati J (2018) Antiaging properties of Curcuma heyneana Valeton & Zipj: a scientific approach to its use in Javanese tradition. J Ethnopharmacol 225:64–70 8. Kusumawati I, Indrayanto G (2013) Natural antioxidants in cosmetics. Stud Nat Prod Chem 40:485–505 9. Warsito MF, Kusumawati I (2019) The impact of herbal products in the prevention, regeneration and delay of skin aging. Adv Exp Med Biol 1178:155–174 10. Kusumawati I, Kurniawan KO, Rullyansyah S, Hestianah EP (2020) Histomorphometric analysis of anti-aging properties on rat skin. Methods Mol Biol 2138:313–321

Transdermal Penetration of Curcuma heyneana 11. Reichman J (1998) Handbook of optical filters for fluorescence microscopy. Chroma Technology Corp, Brattleboro, VT. https://www. chroma.com/sites/default/files/ HandbookofOpticalFilters.pdf USA 12. Weber GF, Menko AS (2005) Color image acquisition using a monochrome camera and standard fluorescence filter cubes.

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Biotechniques 38(1):52, 54, 56. https://doi. org/10.2144/05381BM06 13. Kolmakov K, Belov VN, Bierwagen J, Ringemann C, Mu¨ller V, Eggeling C et al (2010) Red-emitting rhodamine dyes for fluorescence microscopy and nanoscopy. Chemistry 16(1):158–166

Chapter 22 Measuring the Effects of Berberine on Serum Prooxidant–Antioxidant Balance in Metabolic Syndrome Tannaz Jamialahmadi, Paul C. Guest, Aida Tasbandi, Khalid Al-Rasadi, and Amirhossein Sahebkar Abstract Disturbances in the prooxidant–antioxidant balance can occur in metabolic syndrome. Here, we present a protocol for the setup of a clinical trial of metabolic syndrome patients treated with berberine, a dietary phytochemical of the Berberis vulgaris plant, or placebo. The main aim is to obtain a quick and real-time assessment on the overall redox state based on measurement of the prooxidant–antioxidant balance. Keywords Metabolic syndrome, Prooxidant–antioxidant balance, Reactive oxygen species, Natural products, Barberry

1

Introduction Disturbances in the prooxidant–antioxidant balance occur via increased oxidative stress in the pathogenesis of disorders such as metabolic disease, neurodegenerative conditions, and cancer [1]. Oxidants can be generated as an outcome of metabolism or from the effects of environmental factors. Reactive oxygen species (ROS) are the most prevalent causes of oxidative damages in patients suffering from metabolic syndrome. A number of studies have also demonstrated oxidative damage can result from increased prooxidants as well as a reduction in protective antioxidants or both [2–5]. This has been shown as increased levels of lipid peroxidation combined with reduced activity of antioxidant enzymes such as superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPX) [6, 7]. The metabolic syndrome describes a collection of risk factors for type 2 diabetes mellitus (T2DM) and cardiovascular disease, consisting of obesity, high cholesterol levels, high blood pressure, raised fasting plasma glucose, and T2DM [8]. The International

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_22, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Diabetes Federation produced a definition in 2007 for greater applications in clinical practice, which states that metabolic syndrome is characterized by three or more of the following: (1) fasting glucose
110 mg/dL; waist circumference (WC)
the 90th percentile (age- and sex-specific); triglycerides
110 mg/dL (age-specific), high-density-lipoprotein cholesterol (HDL-C)  40 mg/dL; and blood pressure
90th percentile (age-, sex-, and height-specific) [9]. The incidence of metabolic syndrome is approximately parallel to that of obesity and T2DM. In 2015, a global survey of 95 countries found that 604 million adults and 108 million children were obese, defined as having a body mass index (BMI) over 30 kg/m2, which accounted for almost 10% of the world population at that time [10]. In addition, approximately 422 million people worldwide have diabetes, which comprised around 5.8% of the population in the world in that year [11]. Such chronic diseases are placing an ever-increasing economic burden on the healthcare systems worldwide. In addition, metabolic syndrome places at greater risk of worse outcome or death from SARS-CoV-2 infection in the current global pandemic [12–14]. Identifying factors involved in development of metabolic syndrome as well as new treatment approaches is of paramount importance, not only for the affected individual but also to ease the increasing burdens on the healthcare systems. The prooxidant– antioxidant balance technique is a useful and economical method for determining the prooxidant burden and antioxidant capacity [15–18]. A shift in this balance towards increased ROS production can lead to oxidative stress and increased disease (Fig. 1). Phytochemicals with antioxidant properties can be used as a complementary treatment for some diseases such as metabolic disorders [19]. In traditional medicine, Berberis vulgaris (common name, barberry) has been used in the treatment of hypertension and cardiovascular disorders [20]. It is native to Europe, Africa, and Asia and has been naturalized in North America, and cultivated in New Zealand [21]. It is cultivated for its fruits in many countries. It is a bushy plant with yellow timber and ovoid-shaped leaves with a pointy end, yellow flowers, and red oblong fruits (Fig. 2). The fruits contain active ingredients such as berberine, berbamine, palmatine, oxyacanthine, malic acid, and berberrubin [22]. Many studies have shown that the berries have multiple medicinal properties such as antipyretic, antihyperglycemic, hypolipidemic, antimicrobial, anticancer, and antioxidant activities [22–24]. It has also been reported that the isoquinoline alkaloid berberine from the barberry berries has positive medicinal effects in diseases like hyperlipidemia, diabetes, obesity, coronary artery disease, and metabolic syndrome. This has been linked to antioxidant effects [25–31]. Here we present a protocol for a clinical study of metabolic syndrome patients to assess the potential efficacy of berberine as an

Measuring the Effects of Berberine on Serum Prooxidant–Antioxidant. . .

Metabolic stress

Equilibrium ROS Elimination

311

ROS Production

ROS Elimination

ROS Production

Fig. 1 Prooxidant–antioxidant balance

Fig. 2 (a) Berberis vulgaris (barberry) plant. (b) Berberine molecule

antioxidant. The main endpoint was an assay to assess the prooxidant–antioxidant balance in serum taken from the patients treated with or without berberine, as described previously [24].

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Materials

2.1 Materials and Participants

1. Subjects (18–65 years old) with metabolic syndrome and no consumption of nutritional supplements in past 3 months preceding the trial (see Note 1). 2. Serum blood collection tubes (see Note 2). 3. Glucose strips and meter (see Note 3). 4. Benchtop centrifuge. 5. Standard lipid analysis platform (see Note 3). 6. Enzyme-linked immunosorbent assay (ELISA) plate reader. 7. 200 mg capsules containing dried barberry juice (Khoosheh Sorkhe Shargh Agro Industrial Co, Tehran, Iran). 8. 200 mg capsules placebo (Khoosheh Sorkhe Shargh Agro Industrial Co) (see Note 4). 9. NUTRITIONIST 4 software (First Databank, San Bruno, CA, USA). 10. Sphygmomanometer for determination of blood pressure (see Note 3). 11. Stadiometer for measurement of height. 12. Scales for determination of bodyweight. 13. Tape measure for determining waist circumference.

2.2 Prooxidant– Antioxidant Balance Assay

1. 0–100% 250 μL hydrogen peroxide (H2O2). 2. 3 mM uric acid. 3. 10 mM NaOH. 4. 3,30 ,5,50 -tetramethylbenzidine/dimethyl sulfoxide (TMB/DMSO) solution: 60 mg TMB in 10 mL DMSO. 5. 50 mM acetate (pH 4.5). 6. 50 mM acetate (pH 5.8). 7. 100 mM chloramine T. 8. 250 U/mg peroxidase enzyme solution. 9. SPSS (version 16.0, SPSS Inc., Chicago, IL, USA) (see Note 5).

3

Methods

3.1 Participants and Trial Protocol

1. Exclude subjects with systemic disease and lactating or pregnant women. 2. Provide subjects with written sheets and an oral description about the study.

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3. Obtain all demographic, medical, and drug history, family history, smoking status, and occupation via the use of questionnaires. 4. Design study as a 6-week double-blind, randomized, placebocontrolled trial (see Note 6). 5. Divide participants randomly into two groups (n ¼ 53 each) using a computer-generated code: (a) Group 1: to receive three capsules containing 500 mg berberine juice per day (see Note 7). (b) Group 2: to receive three capsules containing 200 mg placebo per day. 6. Exclude subjects with a history of systemic diseases or existing conditions such as: (a) Lupus. (b) Cholestatic problems and gallstone. (c) Rheumatoid arthritis. (d) Kidney disease. (e) Pregnancy and lactation. (f) Use of antithrombotic or antiplatelet medications such as warfarin, heparin, clopidogrel, and aspirin. (g) Consumption of antidyslipidemic, antihypertensive, and antidiabetic drugs. (h) Use of antioxidant supplements (see Note 8). 7. Determine baseline age, weight, body mass index (BMI; kg/m2), waist circumference, body fat (%), and systolic (SBP) and diastolic (DBP) blood pressure (see Note 9). 8. Carry out trial for 6 weeks (Fig. 3). 9. Determine adherence of patients to the study by counting capsules and exclude those participants who fall off the schedule (see Note 10).

T0

Week

0

Assessment of baseline parameters including PAB

T6

Barberry treatment 1

2

3

4

5

6

Assessment of end parameters including PAB

Fig. 3 Study protocol design. PAB prooxidant–antioxidant balance, T0 time 0 (baseline), T6 week 6

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3.2 Blood Collection for Laboratory Analysis

1. Collect 8 mL blood samples into serum tubes at baseline and at the end of the 6-week protocol. 2. Leave at room temperature for 90 min to allow clotting. 3. Centrifuge at 10,000  g for 15 min at 4  C. 4. Collect serum supernatant and transfer to fresh tubes in 1 mL aliquots. 5. Exclude samples showing hemolysis and store remaining aliquots at 80  C until time for analysis (see Note 11). 6. Determine glucose and lipid levels using standard clinical laboratory techniques (see Note 12).

3.3 Prooxidant– Antioxidant Balance Assay

1. Prepare a fresh TMB cation solution by combining 400 μL TMB/DMS0 solution, 20 mL 50 mM acetate (pH 4.5), and 70 μL 100 mM chloramine T. 2. Mix well and incubate 2 h in the dark at room temperature. 3. Add 25 U peroxidase enzyme solution to 20 mL of the above solution (see Note 13). 4. Prepare the TMB working solution by combining 200 μL TMB/DMSO in 10 mL 50 mM acetate (pH 5.8) with 1 mL TMB cation solution. 5. Incubate 2 min in the dark at room temperature (see Note 14). 6. Add 10 μL each sample, standard or distilled water blank and 200 μL freshly prepared TMB working solution to each well of a 96-well plate. 7. Incubate 12 min in the dark at 37  C. 8. Add 100 μL 2 N HCl to each well and measure the optical density at 450 nm using an ELISA reader with a 570 or 620 nm reference wavelength. 9. Plot a curve using the standard solutions. 10. Express prooxidant–antioxidant balance in arbitrary units as % hydrogen peroxide in the standard solution [32]. 11. Determine the values of the unknown samples based on those obtained from the standard curve (Fig. 4) (see Note 15).

3.4 Statistical Analyses

1. Carry out statistical analyses using SPSS or equivalent software. 2. Assess normality of data using Kolmogorov–Smirnov tests. 3. Report data as mean  standard deviation or median and interquartile range. 4. Compare between groups using independent samples t-tests (for normal variables) or Mann-Whitney U tests (for non-normal variables).

Measuring the Effects of Berberine on Serum Prooxidant–Antioxidant. . .

D AU – proxidant-antioxidant balance

20

315

P=0.01

15

10 5 0 -5 -10 -15 -20

Berberine

Control

Fig. 4 Changes in prooxidant–antioxidant balance (PAB) in the barberry and placebo groups. The change (Δ) is given as arbitrary absorbance units (AUs) from baseline (time ¼ 0) to the end of the 6-week treatment protocol [25]

5. Use paired samples t-tests and Wilcoxon signed ranks tests for normal and non-normal variables, respectively. 6. Set statistical significance at a two-sided p-value of p < 0.05.

4

Notes 1. Metabolic syndrome can be defined according to International Diabetic Federation criterion (2005) [8]. All subjects must sign an informed consent document, and the local ethics committee must approve the procedure and the study registered with an appropriate clinical trials authority. The study must be approved by the Institutional Ethics Committee. 2. It is possible to also use plasma tubes containing anticoagulants. However, the user should ensure that the anticoagulant used does not interfere with subsequent assays. 3. These measurements were not analyzed in this study as we focused on changes in that of the prooxidant–antioxidant balance over a 6-week treatment period. However, such molecular and physical parameters should be assessed over longer treatment periods as these might be expected to show beneficial changes with antioxidant treatments. 4. The berberine and placebo capsules should be identical in appearance and texture to maintain blindness of the study. 5. Other statistical packages can be used such as GraphPad Prism (La Jolla, CA, USA). 6. In this study, we used a 6-week trial.

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7. The daily dosage of berberine can vary in the range of 300–1500 mg. 8. Nutritional recommendations based on the American Heart Association guidelines were provided for all participants and dietary compositions assessed using the NUTRITIONIST 4 software. 9. All measurements should also be taken at the end of the study to determine if the treatments have had a significant positive effect on these. However, it is likely that a longer study format may be needed to observe changes in these parameters. 10. Checks can also be made with biweekly visitation. 11. Hemolysis occurs due to breakage of the red blood cells, visualized by a pink to red tinge (depending on the degree of hemolysis). 12. These were not determined in this study but should be analyzed in longer study formats. Multiple parameters involved in metabolic syndrome have shown improvements with some dietary phytochemicals [33–37]. These measures include blood glucose, the homoeostasis model assessment for insulin resistance (HOMA-IR), lipid parameters, and atherosclerosis indicators, as well as pro-inflammatory cytokines and the reductive–oxidative (redox) status. 13. This can be stored at 20  C or used immediately. 14. This must be prepared fresh by incubating 2 min in the dark at room temperature, followed by immediate use. 15. A previous study showed that the barberry treatment had a significant effect on the prooxidant–antioxidant balance in favor of reducing prooxidants and/or increasing antioxidants (see ref. 25 for complete details). References 1. Rahal A, Kumar A, Singh V, Yadav B, Tiwari R, Chakraborty S et al (2014) Oxidative stress, prooxidants, and antioxidants: the interplay. Biomed Res Int 2014:761264. https://doi. org/10.1155/2014/761264 2. Valko M, Leibfritz D, Moncol J, Cronin MT, Mazur M, Telser J (2007) Free radicals and antioxidants in normal physiological functions and human disease. Int J Biochem Cell Biol 39 (1):44–84 3. Rani V, Deep G, Singh RK, Palle K, Yadav UC (2016) Oxidative stress and metabolic disorders: pathogenesis and therapeutic strategies. Life Sci 148:183–193 4. Prasad K (2019) AGE-RAGE stress: a changing landscape in pathology and treatment of

Alzheimer’s disease. Mol Cell Biochem 459 (1–2):95–112 5. Kohan R, Collin A, Guizzardi S, Tolosa de Talamoni N, Picotto G (2020) Reactive oxygen species in cancer: a paradox between proand anti-tumour activities. Cancer Chemother Pharmacol 86(1):1–13 6. Nazirog˘lu M, Butterworth PJ (2005) Protective effects of moderate exercise with dietary vitamin C and E on blood antioxidative defense mechanism in rats with streptozotocin-induced diabetes. Can J Appl Physiol 30:172–185 7. Darroudi S, Fereydouni N, Tayefi M, Ahmadnezhad M, Zamani P, Tayefi B et al (2019) Oxidative stress and inflammation, two features associated with a high percentage

Measuring the Effects of Berberine on Serum Prooxidant–Antioxidant. . . body fat, and that may lead to diabetes mellitus and metabolic syndrome. Biofactors 45 (1):35–42 8. Alberti KGMM, Zimmet PZ, Shaw JE (2005) The metabolic syndrome—a new world-wide definition from the International Diabetes Federation Consensus. Lancet 366 (9491):1059–1062 9. (2007) The IDF consensus definition of the metabolic syndrome in children and adults. file:///C:/Users/Lenovo%20User/Downloads/Mets_definition_children%20(1).pdf 10. GBD 2015 Obesity Collaborators; Afshin A, Forouzanfar MH, Reitsma MB, Sur P, Estep K et al (2015) Health effects of overweight and obesity in 195 countries over 25 years. N Engl J Med 377(1):13–27 11. https://www.who.int/news-room/factsheets/detail/diabetes 12. Cooper ID, Crofts CAP, DiNicolantonio JJ, Malhotra A, Elliott B, Kyriakidou Y et al (2020) Relationships between hyperinsulinaemia, magnesium, vitamin D, thrombosis and COVID-19: rationale for clinical management. Open Heart 7(2):e001356. https://doi.org/ 10.1136/openhrt-2020-001356 13. Cornejo-Pareja IM, Go´mez-Pe´rez AM, Ferna´ndez-Garcı´a JC, Barahona San Millan R, Aguilera Luque A, de Hollanda A et al (2020) Coronavirus disease 2019 (COVID-19) and obesity. Impact of obesity and its main comorbidities in the evolution of the disease. Eur Eat Disord Rev 28(6):799–815. https://doi.org/ 10.1002/erv.2770 14. Huang Y, Lu Y, Huang YM, Wang M, Ling W, Sui Y et al (2020) Obesity in patients with COVID-19: a systematic review and metaanalysis. Metabolism 113:154378. https:// doi.org/10.1016/j.metabol.2020.154378 15. Ahmadnezhad M, Arefhosseini SR, Parizadeh MR, Tavallaie S, Tayefi M, Darroudi S et al (2018) Association between serum uric acid, high sensitive C-reactive protein and prooxidant-antioxidant balance in patients with metabolic syndrome. Biofactors 44(3):263–271 16. Timar A, Saberi-Karimian M, Ghazizadeh H, Reza Parizadeh SM, Sabbaghzadeh R, Emadzadeh M et al (2019) Evaluation of the serum prooxidant-antioxidant balance before and after vitamin D supplementation in adolescent Iranian girls. Adv Med Sci 64(1):174–180 17. Nobakht Motlagh Ghoochani BF, Ghafourpour M, Abdollahi F, Tavallaie S (2019) Pro-oxidant antioxidant balance in patients with non-alcoholic fatty liver disease. Gastroenterol Hepatol Bed Bench 12 (2):124–130

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18. Ghazizadeh H, Kathryn Bohn M, Ghaffarian Zirak R, Kamel Khodabandeh A, ZareFeyzabadi R, Saberi-Karimian M et al (2020) Comprehensive laboratory reference intervals for routine biochemical markers and prooxidant-antioxidant balance (PAB) in male adults. J Clin Lab Anal 28:e23470. https:// doi.org/10.1002/jcla.23470 19. Taghipour YD, Hajialyani M, Naseri R, Hesari M, Mohammadi P, Stefanucci A et al (2019) Nanoformulations of natural products for management of metabolic syndrome. Int J Nanomedicine 14:5303–5321 20. Gundogdu M (2013) Determination of antioxidant capacities and biochemical compounds of Berberis vulgaris L. fruits. Adv Environ Biol 7(2):344–348 21. Arayne MS, Sultana N, Bahadur SS (2007) The berberis story: Berberis vulgaris in therapeutics. Pak J Pharm Sci 20(1):83–92 22. Hajzadeh M, Rajaei Z, Shafiee S, Alavinejhad A, Samarghandian S, Ahmadi M (2011) Effect of barberry fruit (Berberis vulgaris) on serum glucose and lipids in streptozotocin-diabetic rats. Clin Biochem 44 (13). https://doi.org/10.1016/j. clinbiochem.2011.08.825 23. Potdar D, Hirwani RR, Dhulap S (2012) Phyto-chemical and pharmacological applications of Berberis aristata. Fitoterapia 83 (5):817–830 24. Yang H, Tian T, Wu D, Guo D, Lu J (2019) Prevention and treatment effects of edible berries for three deadly diseases: cardiovascular disease, cancer and diabetes. Crit Rev Food Sci Nutr 59(12):1903–1912 25. Mohammadi A, Sahebkar A, Kermani T, Zhilaee M, Tavallaie S, Mobarhan MG (2014) Barberry administration and pro-oxidant-antioxidant balance in patients with metabolic syndrome. Iran Red Crescent Med J 16(12): e16786. https://doi.org/10.5812/ircmj. 16786 26. Yao J, Kong W, Jiang J (2015) Learning from berberine: treating chronic diseases through multiple targets. Sci China Life Sci 58 (9):854–859 27. Yin J, Zhang H, Ye J (2008) Traditional Chinese medicine in treatment of metabolic syndrome. Endocr Metab Immune Disord Drug Targets 8(2):99–111 28. Wang Y, Huang Y, Lam KS, Li Y, Wong WT, Ye H et al (2009) Berberine prevents hyperglycemia-induced endothelial injury and enhances vasodilatation via adenosine monophosphate-activated protein kinase and

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endothelial nitric oxide synthase. Cardiovasc Res 82(3):484–492 29. Xia X, Weng J (2010) Targeting metabolic syndrome: candidate natural agents. J Diabetes 2 (4):243–249 30. Zarei A, Changizi-Ashtiyani S, Taheri S, Ramezani M (2015) A quick overview on some aspects of endocrinological and therapeutic effects of Berberis vulgaris L. Avicenna. J Phytomed 5(6):485–497 31. Habtemariam S (2020) The quest to enhance the efficacy of berberine for type-2 diabetes and associated diseases: physicochemical modification approaches. Biomedicine 8(4):90. https://doi.org/10.3390/ biomedicines8040090 32. Alamdari DH, Paletas K, Pegiou T, Sarigianni M, Befani C, Koliakos G (2007) A novel assay for the evaluation of the prooxidant-antioxidant balance, before and after antioxidant vitamin administration in type II diabetes patients. Clin Biochem 40 (3–4):248–254 33. Firouzi S, Malekahmadi M, GhayourMobarhan M, Ferns G, Rahimi HR (2018)

Barberry in the treatment of obesity and metabolic syndrome: possible mechanisms of action. Diabetes Metab Syndr Obes 11:699–705 34. Sharma H, Kumar P, Deshmukh RR, Bishayee A, Kumar S (2018) Pentacyclic triterpenes: new tools to fight metabolic syndrome. Phytomedicine 50:166–177 35. Hedayati N, Bemani Naeini M, Mohammadinejad A, Mohajeri SA (2019) Beneficial effects of celery (Apium graveolens) on metabolic syndrome: a review of the existing evidences. Phytother Res 33(12):3040–3053 36. Calvano A, Izuora K, Oh EC, Ebersole JL, Lyons TJ, Basu A (2019) Dietary berries, insulin resistance and type 2 diabetes: an overview of human feeding trials. Food Funct 10 (10):6227–6243 37. Huang J, Qin S, Huang L, Tang Y, Ren H, Hu H (2019) Efficacy and safety of Rhizoma curcumea longae with respect to improving the glucose metabolism of patients at risk for cardiovascular disease: a meta-analysis of randomised controlled trials. J Hum Nutr Diet 32 (5):591–606

Chapter 23 Testing the Anti-inflammatory Effects of Curcuminoids in Patients with Colorectal Cancer Tannaz Jamialahmadi, Paul C. Guest, Aida Tasbandi, Muhammed Majeed, and Amirhossein Sahebkar Abstract Colorectal cancer is the third most common cancer and accounts for the second highest number of cancerrelated deaths worldwide. Natural products such as the turmeric-derived curcuminoids are known to have protective effects against several kinds of cancers by acting as antioxidant and anti-inflammatory agents. Here, we present a protocol for assessing the effects of curcuminoids on serum cytokine profiles in a doubleblind placebo-controlled trial of patients with stage 3 colorectal cancer undergoing chemotherapy. The protocol could also be applied to other cancer types. Keywords Colorectal cancer, Inflammation, Cytokines, Turmeric, Curcuminoids, Curcumin

1

Introduction Colorectal cancer is the third most common cancer after lung and breast cancer and accounts for the second highest number of cancer deaths worldwide (Table 1 and Fig. 1) [1]. The prognosis for patients with colorectal cancer is low with a five-year survival of approximately 64% and this is even lower for the metastatic colorectal cancer with an approximate 12% 5-year survival [2, 3]. The incidence of colorectal cancer has increased steadily with the largest increases seen in developing countries that have adopted the “Western diet” [4]. In line with this, the greatest risk factors are obesity, consumption of red meat, alcohol, and tobacco use, and sedentary lifestyle [5–7]. In addition, approximately 5% of colon cancers arise due to inherited conditions, such as Lynch syndrome and familial adenomatous polyposis, and around 30% are likely to be due to other inherited conditions or mutations in susceptibility genes [8]. Colorectal cancer normally begins as a benign tumor that ultimately progresses to malignancy [9].

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_23, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Table 1 WHO rankings of cancer types resulting in the highest number of global deaths Cancer type

Number of deaths (in 2018)

Lung

1,760,000

Colorectal

862,000

Stomach

783,000

Liver

782,000

Breast

637,000

Fig. 1 World map showing the geographical incidence age-standardized colorectal cancer deaths in 2018. The map was derived from Rawla et al. [4]

The standard treatments for colorectal cancer are surgery, chemotherapy, and radiotherapy, which can be used in combination depending on localization and stage of the disease [10–12]. Total mesorectal excision can be the best approach for localized tumors, depending on ease of access [13, 14]. Since complete removal of malignant cells is often not possible, most stage 2 and stage 3 patients undergo additional treatments with adjuvant chemotherapy and/or radiotherapy [15, 16]. Both of these treatments are likely to have many side effects due to nonspecific cytotoxicity of any growing or dividing normal cells [17, 18]. Furthermore, many patients relapse even after such combination treatments. Therefore, there is an urgent need for alternative and effective treatments for patients with colorectal cancer. Curcumin is a phytochemical extracted from turmeric (Curcuma longa L.) rhizomes. Many studies have now demonstrated

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Fig. 2 The curcuminoids found in turmeric

that curcumin and the other turmeric-derived curcuminoids are safe and have protective effects in different diseases [19–21], such as several kinds of cancers [22–24], through its action on multiple targets and via different molecular mechanisms (Fig. 2) [25]. The anticancer effects appear to target apoptosis, cell cycle regulation, oncogene expression, tumorigenesis, and metastasis, and it has been used as an adjunctive therapy to ameliorate the effects of chemotherapy and radiotherapy [26]. In addition to the positive effects mentioned above, this tempering effect of curcumin appears to be mediated by a reduction of the systemic inflammation that occurs in response to chemotherapy and radiotherapy, through positive effects on cytokines and growth factors [27–30]. In this study, we describe the establishment of a double-blind placebo-controlled trial in patients with stage 3 colorectal cancer who received surgery followed by chemotherapy in the Baqiyatallah Oncology Clinic, Tehran, Iran. The patients received either curcuminoid or placebo capsules for 8 weeks and were assessed for serum levels of C-reactive protein (CRP) by a multiplex immunoassay allowing simultaneous analysis of 12 pro- and anti-inflammatory cytokines and growth factors at baseline and at the end of intervention (Fig. 3). Traditional immunoassays normally target a single antigen and rely on reactions associated with covalently linked reporter

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Tannaz Jamialahmadi et al. Specific antibodies coupled to microspheres Anti-TNF- a

Anti-IL-1a

Anti-IL-2

Antibody conjugated microspheres containing red to infrared dyes at different ratios. This results in fluorescence at distinct l s following excitement with a laser

Anti-IFN-g

TNF-a

Add biotinylated antibody

Identity

Quantity

TNF-a is detected by anti-TNF– a microspheres only

Fig. 3 Multiplex immunoassay flowchart. In the example, a multiplex assay is created targeting 4 inflammation-related molecules: tumor necrosis factor-alpha (TNF-α), interleukin 1-alpha (IL-1α), IL-2, and interferon gamma (IFN-γ)

enzymes. However, technological advancements over the past 20 years or so have paved the way for detection of multiple antigens in a single assay. This maximizes the amount of information that can be gained from the sample and simultaneously reduces sample volumes, laboratory analysis times, and costs. However, multiplexed assays have potential problems not seen with single assays [31]. These include the potential of false positives caused by

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antibody interactions and cross-reactions, which can cause misleading results [32–37]. Thus, validation studies are required as followup.

2

Materials

2.1 Participants and Reagents

1. 500 mg curcuminoid capsules (C3 Complex® containing 5 mg piperine, Sami Labs Ltd., Bangalore, India) (see Note 1). 2. Placebo capsules (Sami Labs Ltd) (see Note 2). 3. 8 mL capacity blood serum collection tubes. 4. Benchtop centrifuge. 5. Human CRP immunoturbidimetric latex assay kit (Biosystems S.A., Barcelona, Spain).

2.2 Microsphere Conjugation

1. Magnetic separator (see Note 3). 2. 4 mL 12.5
106 magnetic microspheres per mL. 3. 125 μg/mL monoclonal antibodies (see Note 4). 4. Cross-linking reagent: N-hydroxysulfosuccinimide (sulfoNHS) (see Note 5). 5. Carboxyl-activating reagent: N-(3-dimethylaminopropyl)N0 -ethylcarbodiimide (EDCI) (see Note 6). 6. Activation buffer: 100 mM sodium phosphate (pH 6.0). 7. Coupling reagent: 0.05 M 2-morpholino-ethane-sulfonic acid mono-hydrate (MES) (pH 5.0). 8. Blocking buffer: 10 mM sodium phosphate (pH 7.4), 150 mM NaCl, 0.02% Tween-20, 0.1% bovine serum albumin (BSA), and 0.05% sodium azide. 9. Sonicator.

2.3 Detection Antibody

1. Antibodies against the same proteins as above but different epitopes (see Note 4). 2. Sulfo-NHS biotin (Thermo Fisher Scientific) (see Note 7). 3. Dialysis solution: Phosphate-buffered saline (PBS, pH 7.4).

2.4 Multiplex Development

1. Assay buffer: PBS, 1% BSA. 2. Wash buffer: PBS, 0.02% Tween-20. 3. 100 μg/mL streptavidin R-phycoerythrin (SPE). 4. 96-well microtiter plates. 5. Recombinant or whole protein standards (see Note 8). 6. Blocking buffer (see Note 9). 7. Luminex 100 Analyzer.

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8. Double-deionized H2O and 70% ethanol. 9. Hemocytometer.

3 3.1

Methods Treatment

1. Set up the study as a double-blind placebo-controlled trial (see Note 10). 2. Recruit 20 years-old patients with stage 3 colorectal cancer aged on chemotherapy following their referral to the clinic. 3. Complete a checklist of patient demographic and clinical history information at the baseline. 4. Assign patients using randomization into the following two treatment groups (see Note 11). (a) One 500 mg curcuminoids capsule per day. (b) One placebo capsule per day. 5. Collect fasting blood samples into serum tubes during the morning before the intervention. 6. Leave at room temperature for 90 min to allow clotting. 7. Centrifuge at 10,000
g for 15 min and collect the upper serum layer. 8. Store each sample in 0.5 mL aliquots at 20  C until ready for analysis. 9. Administer capsules for 8 weeks. 10. After the 8 weeks, collect fasting blood samples into serum tubes during the next morning, prepare serum as above and store 0.5 mL aliquots at 20  C until ready for analysis.

3.2 Creation of Antibody-Microsphere Conjugates (See Note 12)

1. Place vials containing microspheres on the magnetic separator for 2 min to ensure complete collection (see Note 3). 2. Remove the solution taking care not to disturb the microspheres. 3. Add 0.5 mL activation buffer, vortex and sonicate to create a suspension. 4. Place vials in the magnetic separator for 1 min to collect the microspheres. 5. Carefully remove supernatant and resuspend the microspheres as above in 0.4 mL activation buffer. 6. Add activation buffer to the cross-linking reagent so the final concentration is 50 mg/mL. 7. Add 50 μL of this activated cross-linking reagent to the microspheres and suspend by vortexing.

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8. Add activation buffer to the coupling reagent so the final concentration is 10 mg/mL. 9. Add 50 μL of the activated coupling reagent to the microspheres and vortex to suspend. 10. Incubate 20 min at room temperature in the dark (see Note 13). 11. Place the tube in the magnetic separator for 1 min. 12. Carefully remove the supernatant and wash twice by addition of 0.5 mL coupling reagent. 13. Leave the beads suspended in 0.45 mL coupling reagent and add 0.2 mL antibodies individually to separate batches of microspheres (see Note 14). 14. Incubate with gentle rotation for 2 h in the dark at room temperature. 15. Place the vials in the magnetic separator for 1 min. 16. Gently remove supernatant and resuspend in 1 mL blocking buffer. 17. Incubate 30 min as above. 18. Place tube in magnetic separator for 1 min. 19. Gently remove the supernatant and wash twice in 0.25 mL blocking buffer. 20. Count the microspheres using a hemocytometer or similar device. 21. Bring the concentration of the microsphere-antibody conjugates to 50
106 per mL and store at 4  C until ready for use. 3.3 Biotinylation of Sandwich Antibodies

1. Add 10 mM sulfo-NHS biotin to antibody solutions using a 20:1 molar ratio). 2. Incubate for 2 h on ice (see Note 15). 3. Remove surplus sulfo-NHS biotin through dialysis with PBS. 4. Add 1% BSA (final concentration).

3.4

Assay

1. Combine 5 μL of each microsphere solution into one tube for the desired different antibody assays to make up to 1.4 mL in assay buffer (Table 2) (see Note 16). 2. Create seven tenfold serial dilutions of 1 μg/mL each recombinant protein to generate an 8-point standard curve. 3. Create 5 μg multiplex (all antibodies combined) biotinylated antibody solution in 5 mL assay buffer (see Note 17). 4. Dilute serum 1:5 in assay buffer (see Note 18). 5. Add 30 μL diluted sample (or standard solutions) to designated wells of the microtiter plate.

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Table 2 Analytes assayed in multiplex immunoassay Analyte

Abbreviation

Tumor necrosis factor-alpha

TNF-α

Interleukin-1-alpha

IL-1a

Interleukin-1-beta

IL-1β

Interleukin-2

IL-2

Interleukin-4

IL-4

Interleukin-6

IL-6

Interleukin-8

IL-8

Interleukin-10

IL-10

Monocyte chemo attractant protein-1

MCP-1

Interferon-gamma

IFN-γ

Epidermal growth factor

EGF

Vascular endothelial growth factor

VEGF

6. Add 10 μL blocking buffer. 7. Add 10 μL multiplex microspheres. 8. Incubate 1 h at room temperature (see Note 19). 9. Wash three times with 100 μL wash buffer. 10. Add 40 μL multiplex biotinylated antibody solution to each well and incubate as above. 11. Turn on the Luminex 100 Analyzer to allow a warm up time of 30–40 min. 12. Add 20 μL SPE to each sample and incubate 30 min as above (see Note 20). 13. Wash three times with 100 μL wash buffer and leave in 100 μL assay buffer for 5 min. 14. Open xPonent® software on the Luminex instrument. 15. Adjust the probe height to 96-well plate. 16. Go to Maintenance > Probe & Heater and use two discs in 96-well plate. 17. Run the enhanced startup routine (see Note 21). 18. Fill the 96-well plate with appropriate reagents H2O and 70% ethanol. 19. Go to Maintenance > Auto Maint > System Initialization. 20. Follow instrument instructions for setting the assay protocol to account for sample volume, microsphere type, and gating.

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21. Enter the volume/well to be aspirated. 22. Enter the analysis type as Quantitative Protocol. 23. Enter the number of standards not including a blank. 24. Select microsphere regions with the name of the analytes, count number (50), and units (pg/mL). 25. Select Apply All. 26. Select the replicate count. 27. Enter the background and standards. 28. Create standard curve for protocol following the prompts. 29. Create batch, select protocol, associate standard curve, and assign unknown analyte wells. 30. Add sample dilution factor and run analysis. 3.5

Data Analysis

1. Carry out data analyses and determine the levels of each analyte in each sample (see Notes 22). 2. Identify significant differences (two-sided p < 0.05) between experimental and control samples using Student’s t-test for each analyte measurement.

4

Notes 1. In this formulation, the curcuminoids are enhanced with piperine black pepper tree extract, which increases absorption by more than tenfold. 2. These were identical in shape and texture to maintain blindness of the study to both patients and administrators. 3. Other instruments such as a plate washer can also be used here to collect the beads in between reagent and buffer changes. 4. One antibody is used for capture and another for detection of each analyte. In this case, pairs of antibodies are used against TNF-α, IL-1α, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, MCP-1, IFN-γ, EGF, and VEGF to assess the inflammation response. Each antibody pair should recognize a distinct epitope on the analyte of interest to avoid steric hindrance effects and to allow maximum selectivity. 5. Sulfo-NHS is used to convert carboxyl groups to aminereactive NHS esters for cross-linking methods. 6. EDCI is used as a carboxyl-activating agent for formation of bonds with primary amine groups. 7. This should be prepared fresh before use. 8. These are for determining absolute levels of the various cytokines and growth factors.

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9. Many blocking buffers can be used here to reduce nonspecific binding. We used Meridian Life Sciences Tru-Block. 10. This trial was approved by the Ethics Committee at the Baqiyatallah University of Medical Sciences (ID: IR.BMSU. REC.1396.1870). 11. A total of 36 volunteers were enrolled in this study in each group due to a probability of a 10% dropout. 12. We actually submitted our samples for analysis using the EV 3513 Cytokine Biochip Array (Randox Laboratories, Crumlin, UK) by sandwich and competitive chemiluminescence immunoassays (Randox Laboratories, Crumlin, UK). However, we also provide a standard protocol for building and carrying the assay in this section. 13. This can be done with gentle mixing, such as on a rotator at low speed. 14. Remember that each set of beads will be encoded with different ratios of red and infrared dyes to allow them to be distinguished in the analyzer. 15. This incubation can also be carried out at room temperature for 30 min. 16. This is a multiplex pool of the antibody-microsphere conjugates targeting the different inflammatory analytes. 17. This is multiplex detection pool of antibodies targeting the different inflammatory analytes (the epitopes are distinct from those targeted by the capture antibodies). 18. The low dilution factor is based on the low abundance of the target analytes in serum. More abundant targets such as the apolipoproteins would need larger dilutions. 19. This is dependent on antibody affinity. The incubation here can also be carried out overnight at 4  C. 20. The amount of SPE added is proportionate to the number of analytes in the assay. 21. This takes approximately 10 min. 22. The readings can be optimized by varying the sample dilutions if needed. More accurate readings will be obtained if sample readings are localized to the linear region of standard curves.

Conflict of Interest Muhammed Majeed is the founder of Sabinsa Corp. and Sami Labs Ltd. The other authors declare no competing interests.

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Chapter 24 Analytical Methods and Bioassays for Cytotoxicity and Antidiabetic Properties of Aquilaria crassna Leaf Extracts in HepG2 Cells Pinnara Rojvirat, Netiya Karaket, Phanupol Mongkolsiri, and Sarawut Jitrapakdee Abstract Aquilaria crassna is a herbal plant that has recently been reported to possess several biological activities. A. crassna leaf extracts have been demonstrated to have a glucose-lowering effect in animal models. However, it is unclear what phytochemical compounds mediate this antidiabetic property. Here, we describe analytical methods for identifying such compounds from dried leaves by differential extractions with ethanol, butanol, ethyl acetate, and water, respectively. The phytochemical compounds in each fraction were further identified by gas chromatography-mass spectrometry. The cytotoxicity of these fractions was tested against a HepG2 cell line, while the rate of glucose utilization was determined using glucose oxidase assay. Lastly, the inhibitory effect on suppression of hepatic glucose production in HepG2 cells was determined by quantitative real-time PCR of genes encoding pyruvate carboxylase, phosphoenolpyruvate carboxykinase, fructose-1,6-bisphosphatase, glucose-6-phosphatase, and liver glycogen synthase. Keywords Aquilaria crassna, Diabetes, Gas chromatography-mass spectrometry, Glucose metabolism, Gluconeogenesis, Glycogen synthesis

1

Introduction Diabetes is a chronic metabolic disorder characterized by hyperglycemia as a result of insulin resistance combined with lowered insulin production and secretion. Chronic hyperglycemia can result in further complications such as cardiovascular disease, renal failure, and retinopathy [1]. Diabetes can be found into two types. Type 1 diabetes, or insulin-dependent diabetes, is caused by an autoimmune reaction that results in destruction of pancreatic beta cells and an absolute absence of insulin production. Unlike type 1 diabetes, type 2 diabetes, or non-insulin-dependent diabetes, is caused by insulin resistance of the insulin-responsive tissues and/or

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_24, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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lowered insulin secretion from pancreatic β-cells. Liver plays a central role in maintaining systemic glucose homeostasis through regulation of insulin action. Insulin stimulates glucose uptake and glycogen synthesis while it inhibits glycogen breakdown and gluconeogenesis [2]. Therefore, failure of insulin secretion and action can lead to increased hepatic glucose production, resulting in overt hyperglycemia. Metformin is the most prescribed oral antidiabetic drug which lowers glucose production by inhibiting hepatic gluconeogenesis [3]. However, high dosages of metformin of up to 0.5–2 g are required to exhibit this action. Furthermore, this drug can produce some side effects such as lactic acidosis and weight gain [4]. For these reasons, alternative medications such as medicinal plants are being explored as an alternative choice for diabetic treatment. Several attempts have been made to search for bioactive compounds from several plant species that exhibit antidiabetic properties, such as glucose lowering or enhanced hepatic glucose utilization effects [5]. Aquilaria crassna, a medicinal plant which can grow in many tropical areas including South East Asia and India, has received much attention because it contains several bioactive compounds. Leaf extracts of A. crassna have been reported to show antimicrobial [6], anti-glycation, anti-inflammatory [7], anti-pyretic, analgesic, and anti-oxidant [8] activities. Manok et al. recently reported that A. crassna leaf extract can lower plasma glucose levels in streptozotocin-induced diabetic mouse model [9]. However, the identity of the bioactive compound(s) and the exact mechanism on reducing plasma glucose are unclear. Here, we present a protocol for extraction of A.crassna leaves, and a means of identifying the phytochemical compounds in each fraction by gas chromatography-mass spectrometry (GC-MS). In addition, we describe a bioassay for determining cytotoxicity of the extracts and quantitative gene expression of gluconeogenic [fructose-1,6-bisphosphatase (FBP), glucose 6-phosphatase (G6P), phosphoenolpyruvate carboxykinase (PEPCK), and pyruvate carboxylase (PC)], and glycogen synthase 2 (GYS-2) enzymes in the human hepatocyte HepG2 cell line. A schematic diagram of A. crassna extraction process and bioassays is shown in Fig. 1.

2

Materials

2.1 Collection of A. crassna Leaves for Chemical Component Analysis

1. A. crassna leaves (see Note 1). 2. Paper bag or envelope. 3. Distilled water. 4. Paper towels.

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Dry powder of A. crassna (100 g) Solid-liquid extraction by Sonicate with 500 mL ethanol, repeat twice Evaporate to dryness

Ethanol extract Evaporate to dryness

Add 200 mL distilled water, Then add 200 mL butanol, repeat twice

Residue (water phase)

Butanol extract

Evaporate to dryness

Liquid-liquid extraction by Add 200 mL ethyl acetate, repeat twice Evaporate to dryness

Residue (water phase)

Ethyl acetate extract

GC-MS Analysis

In vitro cytotoxicity assay glucose utilization assay qPCR assay

Fig. 1 Schematic diagram showing A. crassna extraction process and bioassays 2.2 Preparation of A. crassna Leaf Extract

1. Aluminum foil. 2. Hot air oven. 3. Grinding device or machine such as a mortar and pestle. 4. 20 cm diameter sieve mesh (0.79 mm opening size). 5. Ethanol (liquid chromatography grade). 6. Butanol (analytical grade). 7. Hexane [high performance liquid chromatography (HPLC) grade]. 8. Ethyl acetate (HPLC grade). 9. 125 mm-diameter Whatman® qualitative filter paper, grade 1. 10. Laboratory glassware including 500 mL funnels. 11. V-805 rotary vacuum evaporator with vacuum controller.

2.3

GC-MS Analysis

1. Heptadecanoic acid, methyl ester (analytical grade). 2. Methanol (analytical HPLC grade). 3. 0.45 μm syringe nylon filter membrane (13 mm diameter). 4. 3.0 mL-capacity syringe. 5. 2.0 mL-capacity clear glass (9 mm screw vial) with polytetrafluoroethylene (PTFE)-silicone septa.

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6. Ultrasonic water bath. 7. 10 mL-capacity screw cap vials. 8. GC-MS Agilent® 7890A GC system coupled with 5975C inert XL MSD with triple-axis detector and autosampler (see Note 2). 9. GC column HP-5 ms (J&W, Agilent®) 30 m
50 μm
0.25 μm (see Note 2). 10. Helium (He) carrier gas. 11. GC/MSD Chem Station data analysis software. 12. NIST08 MS library (see Note 3). 2.4 In Vitro Cytotoxicity Assay

1. HepG2 cell line: ATCC® HB-8065™ (American Type Culture Collection). 2. Low glucose medium: Dulbecco’s Modified Eagle Medium (DMEM) containing 5.6 mM glucose, 10% (v/v) fetal bovine serum (FBS), and 1% (v/v) penicillin/streptomycin (10,000 U/mL). 3. High glucose medium: DMEM containing 25 mM glucose, 10% FBS, and 1% penicillin/streptomycin. 4. Phosphate-buffered saline (PBS): 10 mM Na2HPO4, 18 mM KH2PO4, 2.7 mM KCl, 137 mM NaCl (pH 7.4). 5. 0.5% (w/v) trypsin-ethylenediaminetetraacetic acid (EDTA). 6. Dimethyl sulfoxide (DMSO). 7. 0.2 μM membrane filter. 8. 1 mL syringe. 9. MTT medium: 0.5 mg/mL 3-(4,5-dimethylthiazol-2-yl)-2,5diphenyltetrazolium bromide (MTT) in low glucose medium (see Note 4). 10. 96-well plates.

2.5 Hepatic Glucose Utilization

1. Glucose GAGO-20 assay kit (see Note 5). 2. 12 N sulfuric acid (H2SO4). 3. Bradford protein assay reagents (see Note 6). 4. Glucose production assay medium: DMEM glucose-free medium supplemented with 1 mM sodium pyruvate, 20 mM sodium lactate, 15 mM HEPES (pH 7.4), and 1% penicillin– streptomycin.

2.6 Quantitative PCR of Gluconeogenesis Enzymes and GYS-2 Gene Expression

1. Commercial total RNA extraction kit. 2. NanoDrop 2000c spectrophotometer. 3. Diethylpyrocarbonate (DEPC)-treated water. 4. Random hexamers. 5. 25 mM MgCl2 solution.

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6. 10 mM dNTPs. 7. ImProm-II™ reverse transcriptase (Promega) (see Note 7). 8. KAPA SYBR FAST qPCR Master Mix (2
) Universal (Kapa Biosystems). 9. KAPA PROBEFAST qPCR Master Mix (2
) Universal (Kapa Biosystems). 10. Primers and Taqman probes (Tables 1 and 2). 11. 0.2 mL-capacity thin-walled microtube strips with lids.

Table 1 Primers sequences used for SYBR Green qPCR system Target gene

Primer

Nucleotide sequences

FBP

Forward primer

50 -AGCCTTCTGAGAAGGATGCTC-30

Reverse primer

50 -GTCCAGCATGAAGCAGTTGAC-30

Forward primer

50 -GGGAAAGATAAAGCCGACCTAC-30

Reverse primer

50 -CAGCAAGGTAGATTCGTGACAG-30

Forward primer

50 -CGGCTACCACATCCAAGGAA-30

Reverse primer

50 -GCTGGAATTACCGCGGCT-30

G6P

18s rRNA

Table 2 Primer and probe sequences used for Taqman qPCR system Target gene

Primer/probe

Nucleotide sequences

PC

Forward primer

50 -GATGACTTCACAGCCCAG-30

Reverse primer

50 -GGGCACCTCTGTGTCCAG-30

Probea

50 -CCCTGGTGGCCTGTACCAAAGGG-30

Forward primer

50 -CCACAGCGGCTGCAGAACAT-30

Reverse primer

50 -GAAGGGCCGCATGGCAAA-30

Probea

50 -AAGGCAAAATCATCATGCATGACC-30

Forward primer

50 -TGCGTATTATGACCCGACTG-30

Reverse primer

50 -TCAGGGTTTTCTCTGGGTTG-30

Probea

50 -AAGGCAAAATCATCATGCATGACCC-30

Forward primer

50 -CGGCTACCACATCCAAGGAA-30

Reverse primer

50 -GCTGGAATTACCGCGGCT-30

PEPCK-C

GYS-2

18s rRNA

50 -TGCTGGCACCAGACTTGCCCTC-30

Probea a

0

0

Labeled at the 5 with 6-carboxyfluorescein (FAM) and the 3 with 6-carboxytetramethylrhodamine (TAMRA)

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Fig. 2 Collect part of plant material (leaf and petiole)

12. Mx3000P Q-PCR system (Agilent Technologies) or equivalent qPCR system.

3

Methods

3.1 Collection of A. crassna Leaves Sample for Chemical Component Analysis

1. Detach fully mature leaves from an A. crassna tree. 2. Remove the petioles from the leaf and place in a paper bag (Fig. 2). 3. Put the paper bag on ice. 4. Immediately wash the leaves with distilled water. 5. Remove excess water with paper towels. 6. Store leaves at 4  C.

3.2 Preparation of A. crassna Leaves Extract

1. Place A. crassna leaves on aluminum foil. 2. Place in hot air oven at 50  C for 18–24 h until dry. 3. Determine total dry weight. 4. Grind dried leaves to powder with grinding implement (see Note 8). 5. Determine weight of the dry sample powder. 6. Add 100 g powder to 1 L canonical flask for solid-liquid extraction. 7. Add 500 mL of ethanol, place the beaker in the ultrasonic water bath, and adjust the frequency to 90 Hz for 2
30 min. 8. Pour leaf lysate through the Whatman filter paper, collect the flowthrough, and label as “ethanol extract.” 9. Re-extract the residue with ethanol as above and pool the extracts. 10. Evaporate the ethanol in rotary evaporator to produce an “ethanol extract.” 11. Determine the dry weight of the crude ethanol extract.

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12. Divide the crude ethanol extract into three parts for further extraction, GC-MS analysis, and bioassays (below). 13. Add 200 mL water to 1–2 g of ethanol extract from above. 14. Sonicate as above. 15. Pour water extract in a glass separation funnel and add 200 mL of butanol. 16. Extract solution by vigorous shaking. 17. Allow separation between butanol and water phases by leaving the mixture at room temperature for 30–60 min. 18. Collect the upper butanol layer. 19. Re-extract the water phase with butanol by repeating the steps above twice. 20. Pour all butanol fractions in a 1 L round-bottom flask. 21. Evaporate the butanol phase using the rotatory evaporator to produce a “butanol fraction.” 22. Pour the remaining water phase into a separation funnel. 23. Add 200 mL of ethyl acetate and extract by vigorous shaking. 24. Allow separation of ethyl acetate and water phases by leaving the solution at room temperature for 30–60 min. 25. Collect the upper ethyl acetate fraction. 26. Repeat the ethyl acetate extraction of the residual water phase twice. 27. Combine all ethyl acetate fractions and evaporate as above to produce the “ethyl acetate fraction.” 28. Evaporate the remaining water phase using the rotary evaporator to produce the “water fraction.” 3.3

GC-MS Analysis

1. Weigh 10 mg of each fraction. 2. Redissolve each fraction in 1 mL methanol and sonicate as above for 5 min. 3. Add 9 mL of methanol to each sample in the 10 mL volumetric flask to obtain a final concentration of 1 mg/mL. 4. Invert approximately seven times and pass 1.0 mL of each fraction through the syringe filter. 5. Pipette 490 μL of each fraction into 2.0 mL-capacity vials with PTFE-silicone septa. 6. Prepare the internal standard (10 mg/mL heptadecanoic acid) in 10 mL methanol. 7. Invert the internal standard solution in volumetric flask seven times. 8. Add 10 μL of internal standard to each sample and mix well.

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9. Proceed to GC-MS analysis. 10. Apply samples prepared above to the autosampler of the GC system coupled with the inert XL MSD and triple-axis detector. 11. Set flow rate of He carrier at 1 mL/min, with inlet temperature 250  C. 12. Program the oven temperature to 50  C, with a hold for 3 min and a linear increase to 250  C at 5  C/min. 13. Set mass detection at 55–550 mass/charge (m/z) with a solvent delay of 3 min. 14. Run the GC-MS according to this method. 15. Analyze the resulting data with the GC/MSD Chem Station software and compare the results with the NIST08 MS library to identify compounds. 3.4 In Vitro Cytotoxicity Studies

1. Plate 1
104 HepG2 cells per well in 100 μL of the plating medium in 96-well plates. 2. Incubate at 37  C for 24 h. 3. Discard the medium. 4. Prepare a DMSO-based A. crassna leaf extracts by adding 1 mL DMSO to 0.2 g of each extract prepared above in 1.5 mLcapacity microtubes to produce 200 mg/mL final concentrations. 5. Mix vigorously and centrifuge at 3000
g. 6. Filter through the 0.2 μm membrane. 7. Transfer the filtrates to new 1.5 mL-capacity microtubes. 8. Dilute by mixing 500 μL of sample with an equal volume of DMSO in a new microtube to obtain a 100 mg/mL extract. 9. Prepare two-fold serial dilutions of each extract with DMSO to produce concentrations of 50, 25, 12.5, and 6.25 mg/mL. 10. Dispense samples as 20 μL-aliquots for storage at 80  C or proceed immediately to the following step. 11. Prepare extract solutions by adding 2 μL of each concentration to 998 μL of the low glucose medium and mix well. 12. For a control sample (containing no extract), mix 2 μL of DMSO with 998 μL of low glucose medium. 13. Add 100 μL of each concentration of extract solution to each well of the culture plate (each in triplicate). 14. Incubate at 37  C for 24 h. 15. Discard medium. 16. Add 100 μL of MTT medium to each well containing cells and one empty well as a control (see Note 9).

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17. Incubate plates at 37  C for 1 h. 18. Discard MTT medium from each well. 19. Add 200 μL of DMSO to each well to dissolve the formazan precipitates. 20. Mix by pipetting. 21. Measure the absorbance at 540 nm. 22. Average the A540 readouts from triplicate samples. 23. Calculate the percentage of cytotoxicity: %cytotoxicity ¼ ðA540 blank controlA 540 of extracttreated cellsÞ
100 3.5 Hepatic Glucose Utilization Assay

1. Plate 2
105 HepG2 cells in 500 μL of low glucose medium in 24-well plates at 37  C for 24 h. 2. Remove the medium. 3. Add 500 μL of low glucose medium without FBS. 4. Incubate at 37  C for 24 h. 5. Prepare A. crassna leaf extracts for treating cells by adding 2 μL of each concentration of each extract above to 998 μL high glucose medium. 6. Add 500 μL of each concentration of each extract solution to each well. 7. Incubate at 37  C for 24 h. 8. Transfer 10 μL of conditioned medium from the 24-well cultured plates to 96-well plates. 9. Dilute 10 μL of conditioned medium with 90 μL of distilled water. 10. Prepare 100 μL of 0.1, 0.2, 0.3, 0.4, 0.5 mM of glucose standard solutions in distilled water. 11. Reconstitute the assay reagent by adding 0.8 mL of the o-dianisidine reagent to the amber bottle containing the 39.2 mL of glucose oxidase/peroxidase reagent (see Note 10). 12. Add 100 μL of assay reagent to each well of 96-well plates and incubate at room temperature for 30 min. 13. Terminate the reactions by adding 100 μL of 12 N H2SO4. 14. Measure the absorbance of each sample at 540 nm (see Note 11). 15. Determine the glucose concentration in each sample from a standard curve plotted between different known concentrations of glucose read in the spectrophotometer at A540. 16. Determine the protein concentration using the Bradford reagents following manufacturer’s instructions [10].

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17. Calculate hepatic glucose utilization: Net glucose utilization ¼ ½initial glucose concentration ðμMÞ remaining glucose concentration ðμMÞ=total protein ðμgÞ Relative glucose utilization ¼ net glucose consumption ðinterestÞ= net glucose consumption ðcontrolÞ 3.6 qPCR Analysis of Gluconeogenic Enzymes and GYS-2 Expression

1. Add 2 mL of plating medium/well in two sets of 6-well plates (see Note 12). 2. Seed 1
106 HepG2 cells in each well of 6-well plates. 3. Incubate both plates at 37  C for 24 h. 4. Discard the plating medium from both cultured plates. 5. Add 2 mL of DMEM glucose-high glucose without serum to the first plate. 6. Add 2 mL of DMEM low glucose without serum to the second plate. 7. Incubate at 37  C for 24 h. 8. Discard the medium from both plates. 9. Add 2 mL of each A. crassna extract to one set of plates labeled “A.” 10. Add 2 mL of each A. crassna extract to one set of plates labeled “B.” 11. Incubate both cultured plates at 37  C for 24 h. 12. Discard the medium from both plates. 13. For the plates labeled A, proceed to Subheading 3.6, step 17. 14. For the plates labeled B, add 2 mL glucose production assay medium to each well. 15. Incubate at 37  C for 4 h. 16. Discard the medium and proceed to the next step. 17. Wash cells in both plates with 1 mL cold PBS. 18. Extract total RNA from cells in step 1 using commercial RNA extraction kit. 19. Determine the concentration spectrophotometer.

of

RNA

with

20. Add 200 ng of random hexamers with 2 μg of total RNA in 10 μL DEPC-treated water in 50 μL-capacity tubes. 21. Incubate the reaction at 70  C for 5 min. 22. Place tube on ice for 5 min.

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Table 3 Components of reverse transcription master mix Component

Volume (μL)

5
ImProm-II reaction buffer

4

25 mM MgCl2

2.4

10 mM dNTPs

1

ImProm-II reverse transcriptase

1

DEPC-treated water

1.6

Total volume

10

Table 4 Components of SYBR green-based qPCR mix Component

Volume (μL)

2
KAPA SYBR FAST qPCR master mix

6

10 μM forward primer

0.24

10 μM reverse primer

0.24

Distilled water

3.5

cDNA

2

Total volume

12

23. Prepare 10 μL of reverse transcription master mix as shown in Table 3. 24. Add 10 μL of reverse transcription master mix to step 6. 25. Gently mix and briefly centrifuge at 3000
g for 1 min. 26. Place samples in PCR machine and run using the following thermal profiles: 25  C for 5 min, 42  C for 60 min, 70  C for 15 min, and final holding at 16  C. 27. Store the resulting cDNA at 20  C until use. 28. For determination of the expression of FBP and G6P using SYBR Green qPCR system, prepare for qPCR by assembling the indicated components in 0.2 mL thin wall PCR tube as shown in Table 4. 29. Place the tubes in the PCR machine with thermal profiles setting as follows: 95  C for 5 min, 40 cycles at 95  C for 40 s, 58  C for 90 s, and 72  C for 30 s. 30. For determination of the expression of PEPCK, PC, and GYS-2, prepare qPCR by assembling the components shown in Table 5 in 0.2 mL thin wall PCR tubes.

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Table 5 Components of TaqMan-based qPCR mix Component

Volume (μL)

2
KAPA PROBE FAST qPCR master mix

6

10 μM forward primer

0.24

10 μM reverse primer

0.24

10 μM probe

0.12

Distilled water

3.38

cDNA

2

Total volume

12

31. Put the tubes in the PCR machine with settings as follows: 95  C for 5 min, 40 cycles at 95  C for 40 s, and 58  C for 90 s. 32. Calculate expression data from the cycle threshold (Ct) value using the ΔCt method of quantification. 33. Normalize the mRNA expression of each gene with that of 18s ribosomal RNA (18s rRNA) and report as relative gene expression. 34. Calculate the fold change of each gene expression for the treated conditions compared to the control using the comparative CT method (ΔΔCT method) [11].

4

Notes 1. The plant should be identified by a qualified botanist. 2. Other systems can be used although the user will have to adapt operating protocols to their own purposes. 3. This is used for comparison with user data to identify unknown compounds from GC/MS and MS/MS spectra, using library searching. 4. MTT is used in a colorimetric assay for determining cell metabolic activity, usually as a readout of viability. NAD(P)Hdependent cellular oxidoreductase enzymes in cells reduce the MTT to an insoluble purple-colored formazan. We use the dye in this study to assess cytotoxicity. It is important to perform MTT assays in the dark due to light sensitivity. 5. This kit is used for determination of glucose in levels. The glucose in samples is oxidized to gluconic acid and hydrogen peroxide (H2O2) by glucose oxidase, and H2O2 reacts with o-dianisidine via peroxidase to form a colored product. Sulfuric

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acid can be used to form a more stable pink product, and the intensity of this can be measured at 540 nm (proportional to the sample glucose concentration). 6. This is a colorimetric protein assay based on a shift in absorbance of the protein-binding dye Coomassie Brilliant Blue G-250. 7. Other reverse transcriptases can be used, but the user may have to modify conditions. 8. An electric stainless grinder or food blender machine with adjustable speed can be used. 9. Option: add 15 μL of 5 mg/mL MTT solution to the existing media in the culture and add 35 μL low glucose medium to each well. Ensure that each well contains the same volume of the medium. 10. These are contents of the GAGO-20 assay kit. 11. The color of the sample should change from orange to pink. 12. The first set of plates are used for qPCR of GYS-2 expression, and the second set of plates are used for that of the gluconeogenic enzymes.

Acknowledgments This work was supported by National Research Council of Thailand (NRCT) and Plant Genetic Conservation Project Under the Royal Initiation of Her Royal Highness Princess Maha Chakri Sirindhorn (RSPG), 2019 (9/2562) to P.R. and N.K. References 1. American Diabetes Association (2009) Diagnosis and classification of diabetes mellitus. Diabetes Care 32:S62–S67 2. Dimitriadis G, Mitrou P, Lambadiari V, Maratou E, Raptis AS (2011) Insulin effects in muscle and adipose tissue. Diabetes Res Clin Pract 93:S52–S59 3. Wollen N, Bailey CJ (1988) Inhibition of hepatic gluconeogenesis by metformin. Synergism with insulin. Biochem Pharmacol 37 (22):4353–4358 4. Cameron AR, Logie L, Patel K, Erhardt S, Bacon S, Middleton P et al (2018) Metformin selectively targets redox control of complex I energy transduction. Redox Biol 14:187–197 5. Salehi B, Ata A, V Anil Kumar N, Sharopov F, Ramı´rez-Alarco´n K, Ruiz-Ortega A et al (2019) Antidiabetic potential of medicinal plants and their active components. Biomol

Ther 9(10):551. https://doi.org/10.3390/ biom9100551 6. Kamonwannasit S, Nantapong N, Kumkrai P, Luecha P, Kupittayanant S, Chudapongse N (2013) Antibacterial activity of Aquilaria crassna leaf extract against Staphylococcus epidermidis by disruption of cell wall. Ann Clin Microbiol Antimicrob 12:20. https://doi.org/ 10.1186/1476-0711-12-20 7. Wongwad E, Pingyod C, Saesong T, Waranuch N, Wisuitiprot W, Sritularak B et al (2019) Assessment of the bioactive components, antioxidant, antiglycation and antiinflammatory properties of Aquilaria crassna Pierre ex Lecomte leaves. Ind Crops Prod 138:111448. https://doi.org/10.1016/j. indcrop.2019.06.011 8. Sattayasai J, Bantadkit J, Aromdee C, Lattmann E, Airarat W (2012) Antipyretic,

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analgesic and anti-oxidative activities of Aquilaria crassna leaves extract in rodents. J Ayurveda Integr Med 3(4):175–179 9. Manoka S, Sungthong B, Sato H, Sugiyama E, Sato VH (2016) Hypoglycemic and antioxidant activities of the water extract of Aquilaria crassna leaves in Streptozotocin- nicotinamideinduced Type-2 diabetic mice. Nat Prod Commun 11(6):757–761

10. Bradford MM (1976) A rapid and sensitive method for the quantification of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72:248–254 11. Rao X, Huang X, Zhou Z, Lin X (2013) An improvement of the 2^(delta delta CT) method for quantitative real-time polymerase chain reaction data analysis. Biostat Bioinforma Biomath 3(3):71–85

Chapter 25 Testing the Physical and Molecular Effects of Nutritional Supplements and Resistance Exercise in Middle-Aged Females Behnaz Abiri, Paul C. Guest, Parvin Sarbakhsh, and Mohammadreza Vafa Abstract Aging results in loss of muscle mass and strength, which are linked to development of metabolic disorders such as insulin resistance, obesity, and type 2 diabetes mellitus. A number of studies have now shown that these effects can be ameliorated by dietary supplementation with natural products such as vitamins, omega3 fatty acids, and protein and by physical activities such as aerobic and resistance exercise. Here, we present a protocol for setting up a trial to test the effects of vitamin D and omega-3 fatty acid supplementation and resistance exercise on various anthropometric and molecular measurements in middle-aged females. Keywords Overweight, Obesity, Vitamin D, Omega-3 fatty acids, Resistance exercise, Metabolism

1

Introduction Aging results in the progressive loss of muscle strength, which has been linked to increasing disability and metabolic disorders [1, 2]. This can negatively impact physical health and thereby increase the burden on the healthcare systems and society. Such age-related effects on muscle strength can be delayed or accelerated by modifiable factors including nutrition and physical activity levels. In addition, the muscles appear to be the master regulator of metabolism in healthy people with increasing evidence showing that muscle mass and body composition are important factors in overall health [3]. It follows that metabolic processes can be more impaired in individuals who are overweight or obese due to greater amounts of adipose tissue [4, 5]. A number of studies have now shown that body composition can be shifted toward the balance of increased muscle mass through the use of natural products such as vitamin D [6–8] and omega-3 fatty acids [9–11]. In addition, physical exercise, particularly resistance training, can have beneficial

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_25, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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A)

B)

25-hydroxyvitamin D3

Eicosapantaenoic acid (EPA)

Docosahexaenoic acid DHA)

Fig. 1 Chemical structures of (a) 25-hydroxyvitamin D3 and (b) the omega-3 fatty acids EPA and DHA

effects on body composition by shifting the body composition balance to increased muscle mass [12–14]. The main circulating form of vitamin D in the body is 25-hydroxyvitamin D3 (Fig. 1a), which is involved in calcium homeostasis and bone metabolism [15]. This vitamin is also important in the function of organs such as pancreatic β-cells, neurons, immune cells, and myocytes, and vitamin D deficiency is associated with the loss of skeletal muscle mass and function [16, 17]. The elderly are susceptible to vitamin D deficiency due to reduced dietary intake, lower sun exposure, and other physiological effects [18–21]. There are also increasing studies which have shown a protective impact of omega-3 polyunsaturated fatty acids, such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) (Fig. 1b), against the loss of muscle mass that occurs during aging [22] as well as protective anti-inflammatory effects in skeletal muscle aiding maintenance of good muscle performance [23]. For example, a study showed that supplementation of omega-3 fatty

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Aging

Poor nutrition Protein Vitamin D

Body composition Muscle mass Fat mass

Poor lifestyle

Physical activity Obesity Smoking and alcohol

Insulin resistance Inflammation Muscle mass and function Risk of disease Risk of death

Fig. 2 Diagram showing the effects of aging, poor nutrition, and poor lifestyle on body composition, with the associated effects on inflammation and insulin signaling and health risks

acids triggered anti-inflammatory responses and growth in muscle tissues in combination with resistance training in active older women [24]. The effect of resistance exercise either alone or in combination with nutritional supplementation has also been demonstrated in multiple studies [14, 25]. In addition to the effects on reduction of inflammation, these nutritional and exercised-based approaches appear to work through the activation of mTOR signaling and reduction of insulin resistance in the muscle tissue [14, 26, 27]. Thus, all of these approaches could also be useful in minimizing poor outcomes from COVID-19 infection, which is currently overrunning most countries in the world as a severe pandemic. This is due to the fact that the greatest risk factors are advanced age and the presence of metabolic diseases like obesity and type 2 diabetes which are marked by insulin resistance (Fig. 2) [28, 29]. Here, we present a general protocol for determining the effects of vitamin D and omega-3 fatty acid supplementation as well as resistance exercise in middle-aged females over 12 weeks using outcomes of: (1) anthropometric changes in body mass index (BMI), waist circumference and body composition; (2) changes in physical measurements such as handgrip and isometric knee extension strength; and (3) alterations in molecular readouts of inflammation and insulin resistance.

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Fig. 3 Instruments for determining (a) body composition (BF54 monitor), (b) grip strength (dynamometer), and (c) static muscle strength (Manual Muscle Tester)

2

Materials

2.1 Subjects and Treatments

1. Female volunteers aged 40–55 years (see Note 1). 2. 1000 IU vitamin D tablet of 1000 IU (Jalinous Pharmaceutical Co.; Tehran, Iran) (see Note 2). 3. Vitamin D placebo tablet (containing maltodextrin) (see Note 3). 4. Omega-3 fatty acid capsules (330 mg; MorDHA VISION, Minami Nutrition; Antwerp, Belgium) (see Note 4). 5. Omega-3 fatty acid placebo capsules (Zahravi Pharmaceutical Company; Tabriz, Iran) (see Note 5).

2.2 Equipment and Analytical Tools

1. 9-mL capacity blood serum tubes. 2. Bench-top centrifuge with capacity to hold serum tubes. 3. MPR4 Plus microplate reader (Hiperion; Medizintecchnik Gmbh & C.KG; Roedermark, Germany) (see Note 6). 4. BF54 body composition monitor (Beurer GmbH; Ulm, Germany) (see Note 6) (Fig. 3a). 5. Stadiometer for assessing height. 6. Nutritionist 4 software for determining dietary composition (https://nutrium.io/) (see Note 6). 7. Barbell with weight discs allowing a maximum of 44 kg (100 lbs) (see Note 7). 8. Two dumbbells, each allowing a maximum of 11 kg (25 lbs) (see Note 7). 9. Squat rack and bench press combination (see Notes 7 and 8). 10. Handheld dynamometer (DIGI-II; Saehan Corporation; Masan, Gyeongsangnam-do, Republic of Korea) (Fig. 3b) (see Note 5).

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11. Nicholas Manual Muscle Tester (Lafayette Inc.) (Fig. 3c) (see Note 6). 2.3 Blood Glucose Determination

1. Glucose test strips. 2. Single-use blood sampling device such as a finger prick lancet cartridge. 3. Blood glucose meter (see Notes 6 and 9).

2.4

Insulin Assay

1. Insulin Human Simple Step ELISA® Kit contents (Abcam, Cambridge, UK) (see Note 10). (a) Wash buffer. (b) Antibody cocktail: mixture of capture and detection antibodies. (c) 6 nM insulin stock standard solution. (d) 96-well assay plate strips. (e) 3,30 ,5,50 -tetramethylbenzidine solution.

(TMB)

development

2. Microplate reader. 3. Method for determining protein concentration such as the bicinchoninic acid (BCA) or Bradford dye-binding assay. 4. Deionized water. 5. Phosphate-buffered saline (PBS): 1.4 mM KH2PO4, 8 mM Na2HPO4, 140 mM NaCl, 2.7 mM KCl (pH 7.4). 6. Plate shaker. 7. Protease inhibitors. 2.5 25(OH) Vitamin D Assay

1. 25(OH)-D3 enzyme-linked immunosorbent assay (ELISA) kit (EUROIMMUN AG; Luebeck, Germany) (see Note 11). (a) Dissociation buffer. (b) 25(OH) vitamin D standards (0.5–1010 ng/mL). (c) Diluent. (d) 25(OH) vitamin D conjugate. (e) Anti-sheep-coated well strips for 96-well plate. (f) Sheep 25(OH) vitamin D antibody. (g) Diluent for 25(OH) vitamin D3 conjugate. (h) Wash buffer. (i) Para-nitrophenylphosphate substrate. (j) Stop solution.

(PNPP)

chromogenic

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Other Assays

1. ELISA kit for tumor necrosis factor alpha (TNF-α). 2. ELISA kit for interleukin-6 (IL-6). 3. ELISA kit for C-reactive protein.

3 3.1

Methods Trial Setup

1. Set up study as a randomized, double-blinded, and placebocontrolled trial with the following inclusion/exclusion criteria: Inclusion (a) Female (40–55 years old). (b) Serum 25(OH)-D3less than 25 ng/mL. (c) Nonobese body 29.9 kg/m2.

mass

index

(BMI;

18.5

to

(d) No chronic diseases. (e) Nonsmoking. (f) Not in pregnancy, lactation, or menopause. (g) Not taking vitamin D or omega-3 fatty acid supplements. (h) Not taking laxative or hormone medications. Exclusion (a) Not signing the informed consent document. (b) Less than 80% compliance. (c) Currently in a weight loss program. (d) Taking any other nutritional supplements which could affect the study outcome. 2. Calculate the required number of participants for each group at 80% power with an α ¼ 0.05 to detect a difference in handgrip strength of 4 kg with a standard deviation of 5.6 kg [21] (see Note 12). 3. Randomly allocate participants in to four groups for the 12 week trial of nutritional supplements under blinded conditions (see Note 13). (a) Control (n ¼ 37): placebo capsules for weekly vitamin D and daily omega-3 fatty acids. (b) Vitamin D (n ¼ 37): weekly vitamin D capsules and daily placebo capsules for omega-3 fatty acids. (c) Omega-3 fatty acids (n ¼ 37): Daily omega-3 fatty acid capsules and weekly placebo capsules for vitamin D. (d) Combined intervention (n ¼ 37): daily omega-3 fatty acid and weekly vitamin D capsules.

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4. To test the effects of resistance exercise for 12 weeks, set up two more groups as follows: (a) Control (n ¼ 37): nonresistance exercise group. (b) Resistance exercise group (n ¼ 37): resistance exercise for 40 min three times per week. 5. Instruct participants in the supplements trial to take their allocations with their lunch as outlined above. 6. Conduct the study for 12 weeks using bottles containing a 4-week supply (28 tablets each) and ask the participants not to change their routine dietary intake or physical activity over this time. 7. Ask all participants to return their containers at the end of each 4-week period. 8. Monitor compliance by capsule counting. 9. For the exercise trial, instruct participants to complete this as follows (see Note 14): Barbell Squat (Fig. 4a) (see Note 15) (a) Instruct the participant to remove the barbell from the rack by dipping underneath it and placing the bar across the shoulders just below the back of the neck. (b) Have them stand with their feet slightly wider than hip width, with toes facing marginally outward. (c) Instruct them to perform a natural squat by simultaneously bending their knees and driving their hips backward while inhaling deeply. (d) Have them sit into a squat position with thighs parallel to the ground while keeping their heels and toes on the ground, with chest up and shoulders back. (e) Finally, tell them to press into their heels and straighten their legs to return to the starting position while breathing outward. (f) Instruct the participant to perform 10–15 repetitions with repeated sets according to the schedule shown in Table 1. Bench Press (Fig. 4b) (see Note 16) (a) Have the participant lie down on the bench in a supine position so that their head is beneath the barbell and feet are planted on the floor to the sides of the bench. (b) Instruct them to place both hands on the barbell using an overhand grip (with palms facing away from them), slightly wider than their shoulders. (c) Ask them to push the bar away upward and forward to unrack the barbell and keeping it positioned above their chest (starting position).

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Fig. 4 Pictorial chart showing how to perform (a) the squat, (b) bench press, (c) one-armed row and (d) handgrip exercise

(d) Ask them to inhale, bend their elbows to lower the barbell until middle part of the bar just touches their chest. (e) Instruct them to exhale while extending their elbows and pushing the barbell away from their chest to return to the starting position. (f) Have them perform 8–12 repetitions like this before returning the barbell securely on the rack. (g) Have them perform sets according to the schedule shown in Table 1. One-Armed Dumbbell Row (Fig. 4c) (see Note 17) (a) Instruct the participant to place a dumbbell on the left side of the flat bench with their right knee on the end of the bench and torso bent at the waist so the upper body is

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Table 1 Schedule for resistance training over the 12-week trial (reps should only be increased if the resistance still lies in the comfortable range) Week

Squat

Bench press

One-armed row

Handgrips

1

1 set

1 set

1 set

1 set

2

1 set

1 set

1 set

1 set

3

1 set-increased reps

1 set-increased reps

1 set-increased reps

1 set-increased reps

4

2 sets

2 sets

2 sets

1 set-increased reps

5

2 sets

2 sets

2 sets

1 set-increased reps

6

2 sets-increased reps

2 sets-increased reps

2 sets-increased reps

1 set-increased-reps

7

2 sets-increased reps

2 sets-increased reps

2 sets-increased reps

2 sets

8

3 sets

3 sets

3 sets

2 sets

9

3 sets

3 sets

3 sets

2 sets-increased reps

10

3 sets-increased reps

3 sets-increased reps

3 sets-increased reps

2 sets-increased reps

11

3 sets-increased reps

3 sets-increased reps

3 sets-increased reps

2 sets-increased reps

12

3 sets-increased reps

3 sets-increased reps

3 sets-increased reps

2 sets-increased reps

parallel to the floor, and the right hand placed on the bench for support. (b) Ask them to inhale and pick up the dumbbell with their left hand using an overhand grip (palm facing them). (c) Instruct them to perform the lift using their back muscles and pulling the dumbbell straight up to the side of their chest while exhaling. (d) Ask them to hold the dumbbell at the top of the movement for a count of one. (e) Then instruct them to return the dumbbell to the start position while inhaling. (f) Have them perform 10–15 repetitions with repeated sets according to the schedule in Table 1 and switching sides. (g) For the handgrip exercise, have them grip this as shown in Fig. 4d. (h) Ask them to squeeze by tightening their fingers so that the bottom of the handles is just touching. (i) Instruct them to perform this for 20–50 repetitions according to the schedule shown in Table 1 (see Note 18). 1. Measure height using the stadiometer to the nearest 0.5 cm in standing position without shoes.

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3.2 Anthropomorphic Measurements (See Note 19)

2. Asses body weight using the BF4 monitor or standard scales to the nearest 0.1 kg while participants are minimally clothed and without shoes. 3. Calculate BMI: body weight (kg) divided by height squared (m2). 4. Measure waist circumference with the tape measure in cm at the narrowing point above the hips. 5. Measure hip circumference with the tape measure in cm at the widest point. 6. Calculate the weight/hip ratio. 7. Evaluate dietary intakes with a 24 h food recall for 2 days (one week day and one weekend day). 8. Determine body composition of each participant using the BF54 monitor (Fig. 3a). 9. Determine nutrient intake levels using the Nutritionist 4 software.

3.3 Strength Assessments

1. Assess handgrip strength in kg units in each participant’s dominant hand using the dynamometer (Fig. 3b) [24] (see Note 20). 2. Assess isometric knee extension strength of each participant using Manual Muscle Tester in kg units in the dominant leg [25] (Fig. 3c) (see Note 21): (a) Participants should be seated on straight-back standard chair. 

(b) Their hips and knees should be bent at 90 with thighs parallel to the floor. (c) The dynamometer should be placed proximal to the ankle joint. (d) The subjects should be asking to raise their leg hinging from the knee (Fig. 2c). (e) Perform statistical analysis with SPSS version 20 or similar. 3. Express descriptive as mean  standard deviation. 3.4 Serum Preparation for Laboratory Analysis

1. Draw approximately 8 mL blood from each participant after an overnight fast into serum tubes and let stand for 90 min at room temperature to allow clotting (see Note 22). 2. Centrifuge at 1000  g for 10 min to allow separation of the serum from the clotted matter. 3. Carefully collect the top serum layer, aliquot, and freeze at 80  C until ready for analysis. 4. Remove all samples which show evidence of hemolysis (see Note 23).

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1. After an overnight fast, ask the participants to wash their hands with soap and warm water, followed by thorough drying. 2. Place a glucose test strip into the properly calibrated glucose meter. 3. Use the lancet to prick the edge of the subject’s finger to reveal a small drop of blood (see Note 24). 4. Touch the finger with the blood drop to the appropriate section of the test strip to transfer blood to the strip via capillary action. 5. Record the blood glucose reading on the meter.

3.6 Insulin Immunoassay

1. Prepare an 8-point insulin standard curve of 130, 65, 32, 16, 8, 4, 2, and 0 pM by adding the diluent in a sequential manner to the insulin stock standard. 2. Thaw serum samples and bring slowly to room temperature in a water bath. 3. Add 50 μL sample or standard to each well of the plate strips as required (see Note 25). 4. Add 50 μL antibody cocktail to each well. 5. Seal the plate and leave at room temperature for 1 h on a shaker using a medium rotation speed. 6. Wash all wells three times using 350 μL wash buffer (see Note 26). 7. Invert the plate after the last wash and blot dry against paper towels. 8. Add 100 μL TMB solution to each well and leave in the dark for 10 min on a plate shaker as above. 9. Add 100 μL stop solution to each well and place on the shaker as above for 1 min. 10. Place in the plate reader and record the absorbance at 450 nm in each well. 11. Calculate the final absorbance of each sample by subtracting the blank (0 pM standard) value. 12. Determine the concentration of insulin in each sample by interpolating from the insulin standard curve. 13. Calculate the homeostatic model assessment of insulin resistance (HOMO-IR) index using the formula below (see Note 27): Fasting insulin ðμU=LÞ  fasting glucose ðnmol=LÞ=22:5 1. Add 90 μL dissociation buffer into all wells of interest in a 96-well plate.

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3.7 Serum 25(OH) Vitamin D Measurement

2. Add 10 μL sample diluent into the maximum and nonspecific binding wells. 3. Add 10 μL samples/standards into the appropriate wells. 4. Leave 5 min at room temperature on a plate shaker with gentle shaking. 5. Add 50 μL to each well. 6. Add 50 μL conjugate diluent into the non-specific binding wells. 7. Add 50 μL antibody to all wells except the nonspecific binding ones. 8. Seal the plate and leave 1 h with mixing on a plate shaker as above. 9. Wash all wells three times with 325 μL wash buffer. 10. After the final wash, aspirate the well contents and place on paper towel to remove residual contents. 11. Add 200 μL PNPP solution to each well. 12. Seal the plate and incubate 30 min as above. 13. Add 50 μL stop solution to each well. 14. Read the absorbance of each well in a plate reader at 405 nm. 15. Subtract the blank value from all readings. 16. Determine 25(OH) vitamin D in serum samples by interpolation from the standard curve.

3.8

Statistics

1. Examine normality of all data with Kolmogorov-Smirnov test and use paired t-tests to compare baseline and after 12 weeks values in each group. 2. Compare all values at baseline and after 12 weeks with independent t-tests ( p < 0.05 considered significant).

4

Notes 1. This is the population group we targeted in this study to determine whether or not there are any positive effects of the nutritional interventions on anthropomorphic measures, strength, and biomarker measures. Our participants were recruited from the staff at Iran University of Medical Sciences (IUMS), and all signed inform consent documents. Note that we did not test these subjects for the resistance exercise trial here, but we present the protocol to do so. These procedures are flexible in terms of the subjects tested and could include, for example, other groups including aged, obese, or diabetic individuals.

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2. Other sources of these can be used with an appropriate placebo matching tablets. 3. In this study, the placebo capsules were provided by Roshd Pharmaceutical Incubation Center of Tehran University of Medical Sciences. 4. Each capsule contains 54 mg EPA, 250 mg DHA, and 26 mg other omega-3 fatty acids. 5. These contain corn oil but otherwise identical in appearance and texture to the omega-3 fatty acid capsules. 6. Other similar products can be used if compatible with the study format. 7. This can be provided by many suppliers or through the use of a gym. 8. Before beginning resistance exercises, be sure and consult your physician. Also, ensure that you are using the equipment properly for obtaining the maximum benefit and for safety reasons. Seek guidance from a trainer or receive training and perform the exercises in a gym. Another advantage of using a gym is the fact that all of the exercise movements can be performed with machines with built-in safety features (thereby reducing risk of injury). 9. Ensure meter has quality control (QC) performed daily in studies using multiple patients using appropriate QC solutions. 10. Other insulin immunoassay kits can be used. 11. Other vitamin D immunoassay kits can be used. 12. We calculated the number of required participants as 31 per group. However, we recruited 37 per group to allow for potential attrition. 13. We allocated the participants to groups blindly using a random number table. The randomization list was created by a person not involved in the study. The test and placebo capsules (n ¼ 28 per treatment) were put into containers labeled with participant numbers using the randomized list every 4 weeks for three 4-week intervals. 14. This procedure was not performed in this study, but we recommend the indicated exercises as they act on the largest muscle groups in the body. In addition, increases in strength can easily be observed by an increase repetitions or barbell/ dumbbell weight increase over the 12-week trial (in addition to use of the dynamometer and muscle tester). 15. The squat affects the thighs and buttocks, which are the largest muscles in most individuals. This exercise should be performed at least initially with a “spotter” ready to assist if necessary. Also, repetitions should not be performed to exhaustion as this

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could lead to injury. The weight chosen should be selected to err on the side of being too light to begin with to allow the user to become familiar with the movements and perform the indicated repetitions comfortably. As the weeks go by, most people will require an increase in the weight, which is a good indication that they are getting stronger. 16. The bench press affects the chest (pectorals), shoulders (deltoids), and the back of the arms (triceps), which are also among the largest muscles in the body. As above, this exercise should be performed at least initially with a “spotter” ready to assist if necessary. 17. This exercise affects the large back (latissimus dorsi) and, to some extent, the front smaller arm muscles (biceps and brachioradialis). 18. The resistance of the handgrips determines the number of repetitions that can be performed. Select one for the participant that allows the indicated repetitions to be performed. 19. Assess anthropomorphic measurements at baseline and after the 12-week trial. 20. For consistency, it is best to have all participants seated on an armchair with the elbow bent forward to 90 and the hand grasping the dynamometer as shown in Fig. 2b. 21. During the testing, the subjects were encouraged to raise the force to the greatest height slowly while the tester was opposing. 22. An overnight fast is necessary for all molecular readings, which can be affected by food and drink (e.g., glucose and insulin). 23. This can be seen as samples with a pink or red hue. 24. If no blood appears, the subject’s finger can be “milked” by gentle massaging of the finger as necessary. 25. We recommend performing each analysis in duplicate. 26. Ensure complete removal of liquid at each step by either aspirating or decanting the contents. 27. The HOMO-IR determines the degree of insulin resistance by taking into account the relationship between insulin and glucose. References 1. Lauretani F, Russo C, Bandinelli S, Bartali B, Cavazzini C, Iorio A et al (2003) Age-associated changes in skeletal muscles and their effect on mobility: an operational diagnosis of sarcopenia. J Appl Physiol (1985) 95 (5):1851–1860

2. Greenlund LJS, Nair KS (2003) Sarcopeniaconsequences, mechanisms, and potential therapies. Mech Ageing Dev 124(3):287–299 3. Robinson SM, Reginster JY, Rizzoli R, Shaw SC, Kanis JA, ESCEO working group et al (2018) Does nutrition play a role in the

Combined Physical and Molecular Assessment prevention and management of sarcopenia? Clin Nutr 37(4):1121–1132 4. Kim G, Kim JH (2020) Impact of skeletal muscle mass on metabolic health. Endocrinol Metab (Seoul) 35(1):1–6 5. Tallis J, James RS, Seebacher F (2018) The effects of obesity on skeletal muscle contractile function. J Exp Biol 221(Pt 13):jeb163840. https://doi.org/10.1242/jeb.163840 6. Cereda E, Veronese N, Caccialanza R (2018) The final word on nutritional screening and assessment in older persons. Curr Opin Clin Nutr Metab Care 21(1):24–29 7. Abiri B, Vafa M (2020) Vitamin D and muscle sarcopenia in aging. Methods Mol Biol 2138:29–47 8. Uchitomi R, Oyabu M, Kamei Y (2020) Vitamin D and sarcopenia: potential of vitamin D supplementation in sarcopenia prevention and treatment. Nutrients 12(10):3189. https:// doi.org/10.3390/nu12103189 9. Smith GI, Atherton P, Reeds DN, Mohammed BS, Rankin D, Rennie MJ et al (2011) Dietary omega-3 fatty acid supplementation increases the rate of muscle protein synthesis in older adults: a randomized controlled trial. Am J Clin Nutr 93(2):402–412 10. Smith GI (2016) The effects of dietary omega3s on muscle composition and quality in older adults. Curr Nutr Rep 5(2):99–105 11. Troesch B, Eggersdorfer M, Laviano A, Rolland Y, Smith AD, Warnke I et al (2020) Expert opinion on benefits of long-chain Omega-3 fatty acids (DHA and EPA) in aging and clinical nutrition. Nutrients 12(9):2555. https://doi.org/10.3390/nu12092555 12. Peterson MD, Sen A, Gordon PM (2011) Influence of resistance exercise on lean body mass in aging adults: a meta-analysis. Med Sci Sports Exerc 43(2):249–258 13. Liao CD, Tsauo JY, Wu YT, Cheng CP, Chen HC, Huang YC et al (2017) Effects of protein supplementation combined with resistance exercise on body composition and physical function in older adults: a systematic review and meta-analysis. Am J Clin Nutr 106 (4):1078–1091 14. Marzuca-Nassr GN, SanMartı´n-Calı´sto Y, Guerra-Vega P, Artigas-Arias M, Alegrı´a A, Curi R (2020) Skeletal muscle aging atrophy: assessment and exercise-based treatment. Adv Exp Med Biol 1260:123–158

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15. Park S, Ham JO, Lee BK (2014) A positive association of vitamin D deficiency and sarcopenia in 50 year old women, but not men. Clin Nutr 33(5):900–905 16. Scott D, Blizzard L, Fell J, Ding C, Winzenberg T, Jones G (2010) A prospective study of the associations between 25-hydroxyvitamin D, sarcopenia progression and physical activity in older adults. Clin Endocrinol 73 (5):581–587 17. Haroon M, FitzGerald O (2012) Vitamin D deficiency: subclinical and clinical consequences on musculoskeletal health. Curr Rheumatol Rep 14(3):286–293 18. Omdahl JL, Garry PJ, Hunsaker LA, Hunt WC, Goodwin JS (1982) Nutritional status in a healthy elderly population: vitamin D. Am J Clin Nutr 36(6):1225–1233 19. McKenna MJ (1992) Differences in vitamin D status between countries in young adults and the elderly. Am J Med 93(1):69–77 20. Gloth FMIII, Gundberg CM, Hollis BW, Haddad JG, Tobin JD (1995) Vitamin D deficiency in homebound elderly persons. JAMA 274 (21):1683–1686 21. Holick MF (1995) Environmental factors that influence the cutaneous production of vitamin D. Am J Clin Nutr 61(3 Suppl):638S–645S 22. Smith GI, Julliand S, Reeds DN, Sinacore DR, Klein S, Mittendorfer B (2015) Fish oil-derived n-3 PUFA therapy increases muscle mass and function in healthy older adults. Am J Clin Nutr 102(1):115–122 23. Rondanelli M, Rigon C, Perna S, Gasparri C, Iannello G, Akber R et al (2020) Novel insights on intake of fish and prevention of sarcopenia: all reasons for an adequate consumption. Nutrients 12(2):307. https://doi.org/10. 3390/nu12020307 24. Strandberg E, Ponsot E, Piehl-Aulin K, Falk G, Kadi F (2019) Resistance training alone or combined with N-3 PUFA-rich diet in older women: effects on muscle fiber hypertrophy. J Gerontol A Biol Sci Med Sci 74(4):489–494 ˇ , Lo¨fler S, Hofer C (2020) 25. Sˇarabon N, Kozinc Z Resistance exercise, electrical muscle stimulation, and whole-body vibration in older adults: systematic review and meta-analysis of randomized controlled trials. J Clin Med 9(9):2902. https://doi.org/10.3390/jcm9092902 26. Dupont J, Dedeyne L, Dalle S, Koppo K, Gielen E (2019) The role of omega-3 in the

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prevention and treatment of sarcopenia. Aging Clin Exp Res 31(6):825–836 27. Li G, Lin L, Wang YL, Yang H (2019) 1,25 (OH)2D3 Protects Trophoblasts Against Insulin Resistance and Inflammation Via Suppressing mTOR Signaling. Reprod Sci 26 (2):223–232 28. Stefan N, Birkenfeld AL, Schulze MB, Ludwig DS (2020) Obesity and impaired metabolic

health in patients with COVID-19. Nat Rev Endocrinol 6(7):341–342 29. Rajpal A, Rahimi L, Ismail-Beigi F (2020) Factors leading to high morbidity and mortality of COVID-19 in patients with type 2 diabetes. J Diabetes 12:895–908. https://doi.org/10. 1111/1753-0407.13085

Chapter 26 Analysis of Cytotoxic Effects of Zerumbone in Malignant Glioblastoma Cells Mohammad Jalili-Nik, Amir R. Afshari, Khadijeh Mahboobnia, Paul C. Guest, Tannaz Jamialahmadi, and Amirhossein Sahebkar Abstract Glioblastoma multiforme (GBM) is an aggressive tumor in the central nervous system with a poor prognosis. Currently, the main interventions include surgery, chemotherapy, and radiotherapy. Recently, several natural products have been reported as potentially effective and safer treatment options. Here, we studied the effects of zerumbone, a sesquiterpene compound derived from Zingiber zerumbet Smith rhizomes, on human GBM U-87 MG cells in vitro. To meet this purpose, we used a cytotoxicity assay, as well as a quantitative polymerase chain reaction of apoptosis-related genes and western blot analysis of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), a transcription factor that controls the production of cytokines and molecules involved in cell survival. Keywords Glioblastoma multiforme, Natural products, Zerumbone, Cytotoxicity, qPCR, Western blot

1

Introduction Glioblastoma multiforme (GBM) is the most lethal primary tumor of the central nervous system, with an overall survival rate of approximately 1 year after diagnosis (Fig. 1) [1, 2]. Like most other tumors, GBM is characterized by an increased proliferative capacity and low apoptotic activity. Current GBM therapies, such as surgery, radiation therapy, and/or chemotherapy with temozolomide (TMZ), remain palliative instead of curative. Therefore, the potential options are pursued with novel, more effective, and safer interventions that address impaired signaling pathways in GBM [3– 5]. Several studies have reported that apoptosis pathways are lowered in GBM cells, resulting in disruption of the balance between cell proliferation and cell death, with a net effect of increased cell growth [6, 7]. Besides, the expression of transcription factors such

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_26, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Prefrontal cortex

Glioblastoma

Temporoparietal lobe Cerebellum

Fig. 1 Glioblastoma multiforme lesion in the right temporoparietal lobe as shown by computed tomography (CT) scanning

as nuclear factor kappa B (NF-κB) is disrupted in GBM, which leads to uncontrolled proliferation of the cancerous cells [6, 7]. Over the last few years, a number of natural products have been reported to have excellent efficacy as potential agents to induce cytotoxicity and decrease cell proliferation in GBM, including auraptene, cannabinoids, Ferula latisecta, quercetin, resveratrol, and curcumin [3–9]. In our recent research, the cytotoxic and antiproliferative activities of phytochemical zerumbone have been illustrated in GBM U-87 MG cells [10]. Zerumbone is a natural crystalline cyclic sesquiterpene and the main biologically active component in Zingiber zerumbet Smith rhizomes (Fig. 2). Zerumbone is an effective antiproliferative treatment in different types of malignant cells like colon, breast, cervical, and liver cancer, and these effects appear not to impact healthy cells [11–14]. Here, we test the effects of zerumbone treatment of U-87 MG cells using a cytotoxicity assay. Also, we described a quantitative polymerase chain reaction (qPCR) approach to assess the effects on genes involved in apoptosis regulation and western blot analysis to measure the protein levels of the NF-κB p65 complex.

2 2.1

Materials Cell Culture

1. U-87 MG malignant GBM cell line (National Cell Bank of Iran (NCBI), Pasteur Institute; Tehran, Iran). 2. Primary astrocyte cells (NCBI; Pasteur Institute, Tehran, Iran).

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Fig. 2 Zingiber zerumbet Smith plant, rhizome and extracted zerumbone molecule

3. Culture medium: Dulbecco’s Modified Eagle Medium (DMEM), containing 10% fetal bovine serum (FBS), 100 μg/ mL streptomycin, and 100 U/mL penicillin. 4. Phosphate-buffered saline (PBS; pH 7.4): 10 mM Na2HPO4, 1.8 mM KH2PO4, 2.7 mM KCl, 137 mM NaCl. 5. Zerumbone powder (Abcam, Cambridge, United Kingdom). 6. 3-(4,5-dimethyl-2-thiazolyl)-2, 5-diphenyl-2H-tetrazolium bromide (MTT) cell metabolism assay kit (see Note 1). 7. Lysis buffer: 25 mM Tris–HCl (pH 7.4), containing 75 mM NaCl, 1 mM ethylenediaminetetraacetic acid (EDTA), 0.5 mM ethylene glycol-bis(β-aminoethyl ether)-N,N,N0 ,N0 -tetraacetic acid (EGTA), 1% Triton X-100, 0.1% sodium deoxycholate, and 0.5% sodium dodecyl sulfate (SDS). 8. Sonicator. 9. Microcentrifuge. 10. Bicinchoninic acid (BCA) protein assay kit. 2.2 Quantitative Reverse Transcription(qRT)-PCR

1. RNeasy® mini kit (Qiagen, Valencia, CA, USA). 2. Prime-Script™ RT reagent kit (TaKaRa Holdings Inc.; Kyoto, Japan). 3. Specific primers for glyceraldehyde 3-phosphate dehydrogenase (GAPDH), B cell lymphoma 2 (Bcl-2), Bcl-2-associated X protein (Bax), and tumor suppressor protein (p53) (Table 1). 4. Light Cycler RT-PCR system (Roche Applied Science; Pleasanton, CA, USA).

2.3

Gradient Gel

1. Gel loading buffer: 125 mM Tris/HCl (pH 6.8), containing 2% SDS, 0.25 M sucrose, 5 mM EDTA, 65 mM dithiothreitol (DTT), and 0.005% bromophenol blue. 2. 8–12% SDS-polyacrylamide gels (see Note 2).

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Table 1 Primer sequences used in PCR analysis of apoptosis-related genes Gene

Forward primer (50 !30 )

Reverse primer (50 !30 )

Bcl-2

CTGAGGAGCTTTGTTTCAACCA

TCAAGAAACAAGGTCAAAGGGA

Bax

GGAGCTGCAGAGGATGATTG

CCAGTTGAAGTTGCCGTCAC

P53

ACCCTTGCTTGCAATAGGTG

AACAAAACACCAGTGCAGGC

GAPDH

ACAACTTTGGTATCGTGGAAGG

GCCATCACGCCACAGTTTC

3. Stacking gel: 5% acrylamide containing 0.065% N,N0 methylenebisacrylamide, 0.125 M Tris–HCl (pH 6.8), and 0.2% SDS. 4. 12% acrylamide, containing 0.065% N,N0 methylenebisacrylamide, 0.375 M Tris–HCl (pH 8.8), and 0.2% SDS. 5. 8% acrylamide, containing 0.065% N,N0 methylenebisacrylamide, 0.375 M Tris–HCl (pH 8.8), and 0.2% SDS. 6. 10% ammonium persulfate (APS). 7. Tetramethylethylenediamine (TEMED). 8. 150 mm  150 mm glass plates, with 1.5 mm  150 mm spacers and 1.5 mm thickness 12-well gel comb. 9. Running buffer: 25 mM Tris (pH 8.5), 192 mM glycine, 0.1% SDS. 2.4 Semidry Electrophoresis Transfer

1. 0.45 mm thickness membranes.

polyvinylidene

difluoride

(PVDF)

2. Transfer buffer: 25 mM Tris/190 mM glycine (pH 8.3), 20% methanol. 3. Blocking buffer: 20 mM Tris (pH 7.4), 100 mM NaCl, 5% skimmed milk powder. 4. Antibody incubation buffer: 20 mM Tris (pH 7.4), 100 mM NaCl, 2% skimmed milk powder. 5. Rabbit monoclonal antibodies against human NF-κB p65 and beta-actin (Cell Signaling Technology; Beverly, MA, USA). 6. Anti-rabbit horseradish peroxidase-conjugated secondary antibodies (see Note 3). 7. Wash buffer: 20 mM Tris (pH 7.4), 150 mM NaCl, and 0.1% Tween-20. 8. Semidry electrophoresis device for Western transfer. 9. Cling film or similar.

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10. Enhanced chemiluminescence (ECL) detection reagents 1 and 2. 11. Syngene GBox device (Syngene, UK). 12. ImageJ software.

3

Methods

3.1 Cell Viability Assay

1. Seed 104 U-87 cells/well in culture medium in a 96-well plate and incubate overnight at 37  C. 2. The next day, incubate the cells 0–400 μM zerumbone for 24 and 48 h at 37  C. 3. Add 15 μL 5 mg/mL MTT solution from the kit to each well and incubate 3 h at 37  C. 4. Add stop solution and measure the absorbance at 570 and 620 nm (background). 5. Normalize the results to the medium control group and calculate % viability relative to the 0 μM zerumbone control (see Note 4).

3.2

qRT-PCR

1. Extract total RNA from the cells treated with 37.5 and 75 μM zerumbone (from above) according to the manufacturer’s instructions. 2. Design and synthesize PCR primers for GAPDH, Bax, Bcl-2, and p53 (Table 1). 3. Carry out cDNA amplification using the Light Cycler RT-PCR system according to the manufacturer’s instructions. 4. Use the 2ΔΔCt technique to analyze the expression levels of the Bax, Bcl-2, and p53 target genes. 5. Normalize the above values to the average expression level of GAPDH (see Note 5).

3.3 Preparation of 8–12% Polyacrylamide Gels

1. Set up the gradient gel maker, as shown in Fig. 3. 2. Turn on the mixers under each gel solution and add APS and TEMED, both to a final concentration of 0.05% to initiate the polymerization. 3. Immediately turn on the peristaltic pump to begin transferring the 8% gel solution into the 12% one, and simultaneous transfer of the starting 12% mixture to between the glass plates (see Note 6). 4. Continue pumping to the point where the final mixture is approximately 3 cm from the top of the gel to allow space for the stacking gel (see Note 7).

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Peristalc pump

8%

12%

Mixing chamber

Acrylamide soluons

Add well comb

Add stacking gel Stack 8%

12% 8-12% resolving gel

Fig. 3 Setup of the gradient maker for pouring an 8–12% gradient polyacrylamide gel

5. Wait approximately 30 min for polymerization and then add APS and TEMED to the stacking gel solution both to a final concentration of 0.05% to initiate the polymerization. 6. Layer this on top of the resolving gel and insert the well comb being careful not to introduce air bubbles. 7. Leave the comb in place until the stacking gel has set completely. 3.4 Running of SDS Polyacrylamide Gels

1. Seed cells and incubate overnight as above. 2. Treat with 75 μM zerumbone for 1 h. 3. Wash cells 3 in PBS and resuspend in lysis buffer. 4. Sonicate the samples and centrifuge at 13,000  g at 4  C and collect the supernatant. 5. Quantify the protein concentration using the BCA assay. 6. Heat samples in loading buffer for 3 min at 95  C and centrifuge at 700  g for 10 s (see Note 8). 7. Subject samples to electrophoresis at a constant 120 V until the bromophenol blue dye front just reaches the bottom of the glass plates. 8. Disassemble the glass plates and gently place the gel on top of the immobilon P membrane in the sandwich configuration shown in Fig. 4.

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Transfer direction

Gel Membrane

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Filter paper stack

Fig. 4 Configuration of the gel and membrane within the semidry electrophoretic transfer device 3.5 Western Blot Transfer

1. Subject the proteins in the gel to semidry electrophoretic transfer onto the membrane according to the manufacturer’s instructions. 2. After the transfer has completed, immerse the membrane in blocking buffer and mix gently by rocking for 2 h (see Note 9). 3. Remove the blocking solution and rinse twice in wash buffer. 4. Incubate membranes with primary antibodies against NF-κB p65 (1:1000) and β-actin (1:5000) in antibody incubation buffer overnight at 4  C (see Note 10). 5. Remove the solutions and wash the membrane three times for 5 min in wash buffer. 6. Add the appropriate peroxidase-conjugated secondary antibodies (1:3000) to the membrane and incubate by gentle mixing as above for 1.5 h at room temperature. 7. Rinse three times for 5 min in wash buffer and twice in water. 8. Drain excess water from the membrane and place on smoothed cling film with the protein side (the top of the membrane in Fig. 3) facing upward. 9. Mix an equal volume of ECL detection solution 1 with detection solution 2 and add this to both membranes such that the entire surface is covered. 10. Incubate 1 min at room temperature. 11. Remove excess detection reagent by holding an edge with forceps and touching a corner to a tissue. 12. Place the membranes protein side down on to a fresh piece of cling film and wrap each one so that the cover is smooth with no wrinkles or air bubbles. 13. Obtain the luminescent signal using the Syngene GBox device (Syngene, UK).

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14. Visualize and quantitate the immunoreactive protein bands using the ImageJ software and compare them to β-actin immunoreactivity (see Notes 11 and 12).

4

Notes 1. This is a colorimetric test for assessing cell proliferation and viability. The assay quantifies viable cells number by cleavage of tetrazolium salts, which are read in a spectrophotometer. 2. These gels can be purchased from many suppliers or cast in the lab using separate 8% and 12% acrylamide solutions and a peristaltic pump. Gradient gels are typically better than homogeneous gels as they allow the visualization of a broader molecular weight range and higher resolution of individual bands. 3. The secondary antibodies should recognize the species that the first antibodies were raised in. 4. We showed previously that zerumbone caused significant growth inhibition of the U-87 cells in a concentrationdependent manner [10]. 5. In this analysis, we showed previously that the apoptotic process was triggered as demonstrated by the upregulation of the proapoptotic Bax gene and simultaneously suppression of the antiapoptotic Bcl-2 gene [10]. 6. Thus, the solution in the mixing chamber will be continuously diluted from 12% to 8% acrylamide. 7. This will require trial and error adjusting the starting volumes of each gel solution such that the top should be as close to 8% as possible. For the current gel setup, we calculated that 12.5 mL of each solution is needed to fill the glass plates within 3 cm of the top of the plates. 8. The heating step denatures the proteins, and centrifugation helps to recover the entire sample at the bottom of the tube. 9. This step is meant to achieve a lower background by blocking nonspecific binding sites on the membrane. Some different blocking agents can be used, including milk proteins and bovine serum albumin. 10. This can also be performed for 1–2 h at room temperature if the antibodies have sufficiently high affinity. 11. Since both antibodies can be detected with the same second antibody, this serves as an internal standard in each lane to account for loading and, at the same time, provides a ratiometric means of determining changes in the expression of the target protein.

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12. We found previously that zerumbone activated the NF-κB p65 protein [Jalili-Nik]. Taken together, these findings indicated that zerumbone is a potential natural compound for the treatment of GBM due to its cytotoxic activity. References 1. Hanif F, Muzaffar K, Perveen K, Malhi SM, Simjee SU (2017) Glioblastoma Multiforme: a review of its epidemiology and pathogenesis through clinical presentation and treatment. Asian Pac J Cancer Prev 18(1):3–9 2. Alexander BM, Cloughesy TF (2017) Adult Glioblastoma. J Clin Oncol 35 (21):2402–2409 3. Tavana E, Mollazadeh H, Mohtashami E, Modaresi SMS, Hosseini A, Sabri H et al (2020) Quercetin: a promising phytochemical for the treatment of glioblastoma multiforme. Biofactors 46(3):356–366 4. Jalili-Nik M, Sabri H, Zamiri E, Soukhtanloo M, Roshan MK, Hosseini A et al (2019) Cytotoxic effects of ferula Latisecta on human glioma U87 cells. Drug Res (Stuttg) 69 (12):665–670 5. Afshari AR, Jalili-Nik M, Soukhtanloo M, Ghorbani A, Sadeghnia HR, Mollazadeh H et al (2019) Auraptene-induced cytotoxicity mechanisms in human malignant glioblastoma (U87) cells: role of reactive oxygen species (ROS). EXCLI J 18:576–590 6. Cruickshanks N, Zhang Y, Yuan F, Pahuski M, Gibert M, Abounader R (2017) Role and therapeutic targeting of the HGF/MET pathway in glioblastoma. Cancers (Basel) 9(7):87. https://doi.org/10.3390/cancers9070087 7. Erices JI, Torres A, Niechi I, Bernales I, Quezada C (2018) Current natural therapies in the treatment against glioblastoma. Phytother Res 32(11):2191–2201 8. Soukhtanloo M, Mohtashami E, Maghrouni A, Mollazadeh H, Mousavi SH, Roshan MK et al (2020) Natural products as promising targets in glioblastoma multiforme: a focus on

NF-kappaB signaling pathway. Pharmacol Rep 72(2):285–295 9. Ashrafizadeh M, Mohammadinejad R, Farkhondeh T, Samarghandian S (2020) Protective effect of resveratrol against glioblastoma: a review. Anticancer Agents Med Chem. https://doi.org/10.2174/ 1871520620666200929151139. Online ahead of print 10. Jalili-Nik M, Sadeghi MM, Mohtashami E, Mollazadeh H, Afshari AR, Sahebkar A (2020) Zerumbone promotes cytotoxicity in human malignant glioblastoma cells through reactive oxygen species (ROS) generation. Oxidative Med Cell Longev 2020:3237983. https://doi.org/10.1155/2020/3237983 11. Kim M, Miyamoto S, Yasui Y, Oyama T, Murakami A, Tanaka T (2009) Zerumbone, a tropical ginger sesquiterpene, inhibits colon and lung carcinogenesis in mice. Int J Cancer 124(2):264–271 12. Deorukhkar A, Ahuja N, Mercado AL, Diagaradjane P, Raju U, Patel N et al (2015) Zerumbone increases oxidative stress in a thioldependent ROS-independent manner to increase DNA damage and sensitize colorectal cancer cells to radiation. Cancer Med 4 (2):278–292 13. Yan H, Ren MY, Wang ZX, Feng SJ, Li S, Cheng Y et al (2017) Zerumbone inhibits melanoma cell proliferation and migration by altering mitochondrial functions. Oncol Lett 13 (4):2397–2402 14. Haque MA, Jantan I, Arshad L, Bukhari SNA (2017) Exploring the immunomodulatory and anticancer properties of zerumbone. Food Funct 8(10):3410–3431

Chapter 27 Protocol for Testing the Potential Antioxidant Effects of Curcuminoids on Patients with Type 2 Diabetes Mellitus Tannaz Jamialahmadi, Yunes Panahi, Muhammed Majeed, Paul C. Guest, and Amirhossein Sahebkar Abstract Oxidative stress has a key role in the pathogenesis of type 2 diabetes mellitus. Alternative therapy with antioxidants has been tested as a potential approach to curb the effects of this disorder. Here, we present a protocol to set up a randomized double-blind placebo-controlled trial to assess the impact of treatment with a mixture of curcuminoids on a number of physiological and molecular biomarker measures with the main focus on determining the total antioxidant capacity. Keywords Oxidative stress, Total antioxidant capacity, Diabetes, Type 2 diabetes mellitus, T2DM

1

Introduction According to the World Health Organization (WHO), the prevalence of type 2 diabetes mellitus (T2DM) is almost 400 million worldwide, with higher levels in developing and low-income countries (Fig. 1) [1]. T2DM and prediabetes are also linked with obesity, and both are risk factors for increased coronary heart disease [2]. The complicating factors and associated comorbidities result in a significant strain on the healthcare systems worldwide, in addition to around 1.6 million deaths each year [3]. Several studies have demonstrated increased inflammation and oxidative stress along with reduced antioxidant capacities in individuals with T2DM [4–7]. The perturbed metabolism in T2DM leads to increased production of reactive oxygen species (ROS), which can exert damaging effects that induce and aggravate diabetes via effects on the insulin-producing pancreatic β cells, fragmentation or oxidation of proteins, DNA damage, fatty acid production, as well as effects on vascular permeability, with micro and macrovascular complications [8, 9]. A number of

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_27, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Fig. 1 Prevalence of type 2 diabetes mellitus (T2DM) in developing and low-income countries

pharmacological treatments are available for patients with T2DM, which work via different modes of action [10]. However, these do not necessarily target the perturbations in antioxidant pathways and may limit efficacy. Epidemiological and observational studies have demonstrated an inverse association between antioxidant intake and T2DM [11], though studies involving the use of antioxidants such as vitamin C and vitamin E have had mixed and potentially conflicting results [12–14]. For these reasons, identifying new antioxidant compounds as a treatment for the damaging inflammatory and oxidative effects in T2DM is an important objective in diabetes management and care. Phytochemicals with antioxidant properties such as curcumin can be used as a complementary treatment for T2DM and obesity [15]. Curcumin is a yellow-pigmented compound of Curcuma longa L. rhizomes (turmeric) belonging to the Zingiberaceae family, which has been used as a medication in traditional medicine for hundreds or thousands of years (Fig. 2). Turmeric contains the major curcuminoids (curcumin, demethoxycurcumin, and bisdemethoxycurcumin), which possess similar properties. Among the myriad of health-promoting effects [16– 22], the antioxidant effects of curcuminoids are most prominent, including inhibition of lipid peroxidation, and superoxide and hydroxyl radical scavenging [23–26]. Clinical use of curcuminoids is affected by low oral bioavailability due to their rapid intestinal and hepatic metabolism via glucuronidation [27]. To address this potential problem, we

Protocol for Testing the Potential Antioxidant Effects of Curcuminoids on. . .

Curcuma longa

373

Turmeric rhizome and powder

Demethoxycurcumin

Curcumin

Bisdemethoxycurcumin

Fig. 2 Curcuma longa plant, rhizome, powder, and predominant curcuminoids

coadministered curcuminoids with piperine. This combination has absorption-enhancing by blocking both the intestinal and hepatic glucuronidation pathway, as demonstrated in a number of clinical studies [28–31]. Here, we present a protocol for a clinical study of metabolic syndrome patients to assess the potential efficacy of the curcuminoids as an antioxidant. The primary endpoint was an assay to determine the total antioxidant capacity in serum taken from the patients treated with or without a curcuminoids-piperine complex. The key results of this analysis have been described previously [32].

2

Materials

2.1 Participants, Samples, and Reagents

1. Adult subjects aged 18–65 years with T2DM (n ¼ 118) (see Note 1). 2. Curcumin C3 Complex(R) capsules containing 500 mg curcuminoids and 5 mg piperine (Sabinsa Group Limited, Bangalore, India). 3. Placebo capsules matched in shape, size, color, and texture to the curcumin capsules (see Note 2). 4. Phlebotomy kit and 8 mL capacity blood serum collection tubes. 5. Glucose strips and monitor. 6. Insulin immunoassay kit.

2.2

TAC Analysis

1. TAC kit containing (see Note 3): (a) Assay diluent. (b) 2% Cu2+ reagent prepared fresh in assay diluent.

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(c) Protein mask. (d) 1 mM Trolox standard in 2% dimethyl sulfoxide (DMSO). 2. Phosphate-buffered saline (PBS; pH 7.4): 10 mM Na2HPO4, 1.8 mM KH2PO4, 2.7 mM KCl, 137 mM NaCl. 3. Microplate reader. 4. MilliQ water. 5. Triton X-100. 2.3

Equipment

1. Ion exchange chromatography apparatus. 2. Spectrophotometer. 3. 96-well plate with clear flat bottom. 4. Homogenizer. 5. Microcentrifuge. 6. SPSS Statistics for Windows Version 20.0 (IBM Corp., Armonk, NY, USA).

3 3.1

Methods Treatment

1. Recruit adult subjects aged 18–65 years according to the following criteria: Inclusion criteria (a) Fasting plasma glucose (FPG) 126 mg/dL. (b) Glycated hemoglobin (HbA1C) 6.5%. (c) Use of antidiabetic treatments. Exclusion criteria (a) Pregnancy or breastfeeding. (b) Not giving informed consent. (c) Participation in a concomitant trial. (d) Presence of malignancies. (e) Chronic liver disease. (f) Biliary or cholestatic diseases. (g) Renal failure. (h) Chronic inflammatory diseases. (i) Endocrine diseases other than T2DM. (j) Obsessive compulsive disorder. (k) Hyperglycemia due to secondary causes. (l) Receiving hormone therapy or other herbal medicines. (m) Hypersensitivity to the study medication. (n) Lack of compliance with the study parameters.

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2. Set up study as a randomized double-blind placebo-controlled trial with a parallel-group design. 3. Randomly allocate subjects to the following groups: (a) Curcumin C3 Complex for 3 months. (b) Placebo for 3 months. 4. Administer the capsules to the participants as above under blinded conditions for both the participants and the investigators. 3.2 Blood Sampling and Laboratory Analyses

1. Collect overnight fasting blood samples at baseline and at the end of the study into serum tubes. 2. Allow the blood to clot at room temperature for 60 min and centrifuge at 750  g for 10 min to obtain serum. 2. Aliquot and store the serum at 80  C until required (see Note 4). 3. Determine fasting glucose using glucose strips and monitor according to the manufacturer’s instructions. 4. Determine the serum concentrations of insulin using the immunoassay kit. 5. Calculate homeostatic model assessment for insulin resistance (HOMA-IR) using the formula: Fasting insulin ðlIU=mLÞ  fasting glucose ðmmol=LÞ=22:5Þ 6. Measure hemoglobin A1C (HbA1C) by ion exchange chromatography as described [33]. 7. Determine serum activities of superoxide dismutase (SOD) and malondialdehyde (MDA) spectrophotometrically, as described [34]. 8. Determine weight, height, and systolic and diastolic blood pressures according to standard procedures. 9. Calculate BMI as weight (in kg) divided by height in m2.

3.3

TAC Assay

1. For the standard curve, prepare 100 μL 0, 4, 8, 12, 16, and 20 nmoles Trolox per well using the assay diluent in the 96-well microplate. 2. Add 10 μL each serum sample to the microplate (see Note 5). 3. For the assay, add 100 μL freshly prepared 2% Cu2+ solution to all wells of the plate. 4. Incubate the plate 90 min at room temperature with gentle shaking in the dark. 5. Measure the absorbance in each well on the microplate reader at 570 nm.

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6. Subtract the absorbance of the blank (0 nmoles Trolox) from all readings. 7. Plot the corrected values for the standards. 8. Interpolate the concentrations of Trolox in the samples from the standard curve. 3.4

Statistics

1. Perform statistical analyses using the SPSS statistics package or similar. 2. Express data as mean  SD or number (%). 3. Carryout within-group comparisons using paired samples t-test or Wilcoxon signed-ranks test for normally and non-normally distributed data, respectively. 4. Perform between-group comparisons using independent samples t-test or Mann–Whitney U test for normally and non-normally distributed data, respectively (see Note 6). 5. Compare categorical variables between the groups using the chi-square test. 6. Perform bivariate correlations between changes in serum levels of SOD, MDA, and TAC using Pearson’s and Spearman’s correlation coefficients for normally and non-normally distributed data, respectively. 7. Perform univariate analysis of covariance (ANCOVA) using a general linear model to adjust for effects of potential confounders on associations between curcumin supplementation and changes in SOD, MDA, and TAC.

4

Notes 1. The study protocol was approved by the Ethics Committee at the Baqiyatallah University of Medical Sciences. It was also registered in the Iranian Registry of Clinical Trials, and written informed consent was received from all participants. 2. The curcuminoid and placebo capsules were matched in shape, size, and color, and the color of the placebo (microcrystalline cellulose) was matched to that of the curcuminoid powder. The oral bioavailability of curcuminoids was enhanced in this study by the addition of 5 mg piperine to each 500 mg curcuminoid capsule. The preparation used in this study contained the three major curcuminoids: curcumin; demethoxycurcumin; and bisdemethoxycurcumin. 3. This kit measures small molecule and protein antioxidants in the presence of a proprietary protein mask. The assay works by conversion of Cu2+ to Cu+ by antioxidants in the sample. The protein mask stops the reduction of Cu2+ reduction by protein

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antioxidants, leaving the analysis of only the small molecules (although we did not use that here). Chelation of the produced Cu+ with a colorimetric probe allows reading of the absorbance at 570 nm in proportion to the total antioxidant capacity. The Trolox is used as a standard antioxidant in the assay. 4. Aliquoting is essential as frequent freeze-thaw cycles of samples can lead to loss of some serum analytes due to cryoprecipitation or other factors. 5. Sample volume can differ based on modified versions of the assay and the kit used. Generally, 1–10 μL is sufficient when protein masking is used. 6. In a previous study, we found that the curcuminoid treatment led to significant reductions in body weight and BMI. At the same time, these parameters were both increased in the placebo group. In addition, we found significant elevations in SOD and TAC with a reduction in the MDA levels. These findings indicated that curcuminoid treatment might have decreased body weight by increasing antioxidant capacity. Conflict of Interest: Muhammed Majeed is the CEO of Sabinsa Corporation and Sabinsa Group Limited. References 1. https://www.who.int/news-room/factsheets/detail/diabetes 2. Huang Y, Cai X, Chen P, Mai W, Tang H, Huang Y et al (2014) Associations of prediabetes with all-cause and cardiovascular mortality: a meta-analysis. Ann Med 46(8):684–692 3. Chiang JI, Jani BD, Mair FS, Nicholl BI, Furler J, O’Neal D et al (2018) Associations between multimorbidity, all-cause mortality and glycaemia in people with type 2 diabetes: a systematic review. PLoS One 13(12): e0209585. https://doi.org/10.1371/journal. pone.0209585 4. Luc K, Schramm-Luc A, Guzik TJ, Mikolajczyk TP (2019) Oxidative stress and inflammatory markers in prediabetes and diabetes. J Physiol Pharmacol 70(6). https://doi.org/10. 26402/jpp.2019.6.01 5. Yaribeygi H, Atkin SL, Sahebkar A (2019) A review of the molecular mechanisms of hyperglycemia-induced free radical generation leading to oxidative stress. J Cell Physiol 234 (2):1300–1312 6. Yaribeygi H, Butler AE, Barreto GE, Sahebkar A (2019) Antioxidative potential of antidiabetic agents: a possible protective mechanism

against vascular complications in diabetic patients. J Cell Physiol 234(3):2436–2446 7. Yaribeygi H, Sathyapalan T, Atkin SL, Sahebkar A (2020) Molecular mechanisms linking oxidative stress and diabetes mellitus. Oxidative Med Cell Longev 2020:8609213. https:// doi.org/10.1155/2020/8609213 8. Giacco F, Brownlee M (2010) Oxidative stress and diabetic complications. Circ Res 107 (9):1058–1070 9. Babel RA, Dandekar MP (2020) A review on cellular and molecular mechanisms linked to the development of diabetes complications. Curr Diabetes Rev. https://doi.org/10. 2174/1573399816666201103143818. Online ahead of print 10. Upadhyay J, Polyzos SA, Perakakis N, Thakkar B, Paschou SA, Katsiki N et al (2018) Pharmacotherapy of type 2 diabetes: an update. Metabolism 78:13–42 11. Montonen J, Knekt P, Jarvinen R, Reunanen A (2004) Dietary antioxidant intake and risk of type 2 diabetes. Diabetes Care 27(2):362–366 12. Boaz M, Smetana S, Weinstein T, Matas Z, Gafter U, Iaina A et al (2000) Secondary prevention with antioxidants of cardiovascular

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disease in end-stage renal disease (SPACE): randomised placebo-controlled trial. Lancet 356(9237):1213–1218 13. Lonn E, Yusuf S, Dzavik V, Doris C, Yi Q, Smith S et al (2001) Effects of ramipril and vitamin E on atherosclerosis: the study to evaluate carotid ultrasound changes in patients treated with ramipril and vitamin E (SECURE). Circulation 103(7):919–925 14. Sacco M, Pellegrini F, Roncaglioni MC, Avanzini F, Tognoni G, Nicolucci A (2003) Primary prevention of cardiovascular events with low-dose aspirin and vitamin E in type 2 diabetic patients: results of the primary prevention project (PPP) trial. Diabetes Care 26 (12):3264–3272 15. Shehzad A, Ha T, Subhan F, Lee YS (2011) New mechanisms and the anti-inflammatory role of curcumin in obesity and obesity-related metabolic diseases. Eur J Nutr 50(3):151–161 16. Ghandadi M, Sahebkar A (2017) Curcumin: An effective inhibitor of interleukin-6. Curr Pharm Des 23(6):921–931 17. Iranshahi M, Sahebkar A, Takasaki M, Konoshima T, Tokuda H (2009) Cancer chemopreventive activity of the prenylated coumarin, umbelliprenin, in vivo. Eur J Cancer Prev 18(5):412–415 18. Ghasemi F, Shafiee M, Banikazemi Z, Pourhanifeh MH, Khanbabaei H, Shamshirian A, et al (2019) Curcumin inhibits NF-kB and Wnt/β-catenin pathways in cervical cancer cells. Pathology Research and Practice, 215(10):152556. https://doi.org/10.1016/ j.prp.2019.152556 19. Momtazi AA, Derosa G, Maffioli P, Banach M, Sahebkar A (2016) Role of microRNAs in the therapeutic effects of curcumin in non-cancer diseases. Mol Diagn Ther 20(4):335–345 20. Panahi Y, Ahmadi Y, Teymouri M, Johnston TP, Sahebkar A (2018) Curcumin as a potential candidate for treating hyperlipidemia: a review of cellular and metabolic mechanisms. J Cell Physiol 233(1):141–152 21. Panahi Y, Khalili N, Sahebi E, Namazi S, Simental-Mendı´a LE, Majeed M, et al (2018) Effects of Curcuminoids Plus Piperine on Glycemic, Hepatic and Inflammatory Biomarkers in Patients with Type 2 Diabetes Mellitus: A Randomized Double-Blind PlaceboControlled Trial. Drug Res 68(7):403–409 22. Teymouri M, Pirro M, Johnston TP, Sahebkar A (2017) Curcumin as a multifaceted compound against human papilloma virus infection

and cervical cancers: a review of chemistry, cellular, molecular, and preclinical features. Biofactors 43(3):331–346 23. Ruby A, Kuttan G, Babu KD, Rajasekharan K, Kuttan R (1995) Antitumour and antioxidant activity of natural curcuminoids. Cancer Lett 94(1):79–83 24. Borra SK, Mahendra J, Gurumurthy P, Jayamathi, Iqbal SS, Mahendra L (2014) Effect of curcumin against oxidation of biomolecules by hydroxyl radicals. J Clin Diagn Res 8(10): CC01–CC05. https://doi.org/10.7860/ JCDR/2014/8517.4967 25. Abrahams S, Haylett WL, Johnson G, Carr JA, Bardien S (2019) Antioxidant effects of curcumin in models of neurodegeneration, aging, oxidative and nitrosative stress: a review. Neuroscience 406:1–21 26. Sahebkar A, Serban MC, Ursoniu S, Banach M (2015) Effect of curcuminoids on oxidative stress: a systematic review and meta-analysis of randomized controlled trials. J Funct Foods 18:898–909 27. Anand P, Kunnumakkara AB, Newman RA, Aggarwal BB (2007) Bioavailability of curcumin: problems and promises. Mol Pharm 4 (6):807–818 28. Shoba G, Joy D, Joseph T, Majeed M, Rajendran R, Srinivas PS (1998) Influence of piperine on the pharmacokinetics of curcumin in animals and human volunteers. Planta Med 64(4):353–356 29. Panahi Y, Alishiri GH, Parvin S, Sahebkar A (2016) Mitigation of systemic oxidative stress by curcuminoids in osteoarthritis: results of a randomized controlled trial. J Diet Suppl 13 (2):209–220 30. Panahi Y, Ghanei M, Hajhashemi A, Sahebkar A (2016) Effects of curcuminoids-piperine combination on systemic oxidative stress, clinical symptoms and quality of life in subjects with chronic pulmonary complications due to sulfur mustard: a randomized controlled trial. J Diet Suppl 13(1):93–105 31. Saberi-Karimian M, Keshvari M, GhayourMobarhan M, Salehizadeh L, Rahmani S, Behnam B et al (2020) Effects of curcuminoids on inflammatory status in patients with non-alcoholic fatty liver disease: a randomized controlled trial. Complement Ther Med 49:102322. https://doi.org/10.1016/j.ctim. 2020.102322 32. Panahi Y, Khalili N, Sahebi E, Namazi S, Karimian MS, Majeed M et al (2017) Antioxidant

Protocol for Testing the Potential Antioxidant Effects of Curcuminoids on. . . effects of curcuminoids in patients with type 2 diabetes mellitus: a randomized controlled trial. Inflammopharmacology 25(1):25–31 33. Jalali MT, Bavarsad SS, Hesam S, Afsharmanesh MR, Mohammadtaghvaei N (2020) Assessing agreement between the three

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Chapter 28 The Detection of Toxic Compounds in Extracts of Callilepis laureola (Oxeye Daisy) and Senecio latifolius (Ragwort) by Ultra-Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS/MS) Tracy Snyman and Nigel J. Crowther Abstract Methods used for the detection of toxic components of Callilepis laureola and Senecio latifolius have ranged from the use of thin-layer chromatography, spectrophotometry, and immunoassay to gas chromatography with mass spectrometry. However, each of these techniques has a number of drawbacks. In this chapter, we will describe a solid-phase extraction technique, which allows for the detection and quantitation of the toxins atractyloside and retrorsine in each plant extract using ultra-performance liquid chromatographymass spectrometry (UPLC-MS/MS). This methodology offers high specificity and sensitivity and the ability to identify a broad range of analytes. Keywords Atractyloside, Retrorsine, Callilepis laureola, Senecio latifolius, Solid-phase extraction, Liquid chromatography-mass spectrometry, Multiple reaction monitoring

1

Introduction It is estimated that approximately 70% of the population of South Africa use plant-based traditional remedies [1]. Although most of these remedies are perceived to be safe, there are some that are known to have toxic effects, and this is particularly dangerous in an environment where there is limited control of dosages and little information on the plants being used [2]. Two of the plants known to be commonly used in herbal remedies and which have toxic side effects are Callilepis laureola (C. laureola) and Senecio latifolius DC (S. latifolius). Atractyloside (ATR), a diterpenoid glycoside, is found in C. laureola, and pyrrolizidine alkaloids (PAs), such as retrorsine, are present in S. latifolius. These compounds are known to be linked to liver necrosis and veno-occlusive liver disease (VOD) [3–5]. C. laureola

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_28, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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is commonly known as the oxeye daisy and referred to as Impila (meaning health) in the Zulu language. The tuber of the plant is traditionally used for the treatment of various ailments such as infertility, decongestion, and impotence [6, 7]. Senecio latifolius has been recommended by many authors for the treatment of a variety of ailments, which range from burns, cuts, chest pains, nausea, worm infections, constipation, and palpitations, and has also been reported to induce abortions and speed up childbirth [8–12]. Identification of ATR and PAs has evolved over the years from using thin layer chromatography (TLC) and immunoassays, to the use of gas chromatography-mass spectrometry (GC/MS) [13, 14]. These methods all have limitations such as lack of specificity and poor sensitivity as well as the requirement for derivatization. High performance liquid chromatography-photodiode array or ultraviolet absorption detection (HPLC-PDA/UV) has also been utilized [15]. These methods allow for identification of alkaloids, although one would need to know which alkaloid was present as it cannot always be identified without prior knowledge of the suspected compound [16]. More recently, methods have been developed using liquid chromatography tandem-mass spectrometry (LC-MS/MS) for the detection and quantitation of both ATR and retrorsine [17– 20]. This analytical technique is able to identify a wide range of compounds based on the ionization technique it utilizes. It is commonly used in metabolomics and small molecule research although advances have been made for the utilization of hybrid systems in proteomics [21–23]. One of the advantages of using GC/MS is that there are standardized libraries for the identification of the majority of toxic compounds, including drugs of abuse, pesticides, and analgesics [23, 24]. This is usually available on most systems, but if not, the National Institute of Standards and Technology (NIST) chemistry web book can be used [25]. This is an online database of all chemical compounds that have a GC/MS spectrum and allows for the identification of compounds based on their ion ratios, retention times, and percentage fit to the original standard [23]. However, for LC-MS/MS, although standardized libraries are available, these are for more common analytes such as drugs of abuse. Therefore, for less common analytes, the user would need to create their own libraries. The same is also true for GC/MS, but because this methodology is older, the libraries do contain more esoteric compounds. One of the advantages of using mass spectrometry-based techniques is that these provide unrivaled specificity and sensitivity and, in most cases of small molecule research, the analytical specificity can be increased by using multiple reaction monitoring (MRM) scanning mode [23]. This allows for the accurate detection of the

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Fig. 1 Multiple reaction monitoring to identify the compound of interest showing specificity of compound selection

compound of interest by fragmenting the structure into specific product ions based on the radio frequency applied within the first quadrupole and the collision energy applied in the second quadrupole (Fig. 1). In this chapter, we will describe the steps that need to be taken to identify, detect, and quantify the toxic compounds, ATR, and retrorsine identified in C. laureola and S. latifolius utilizing UPLCMS/MS.

2

Materials 1. C. laureola tubers and S. latifolius leaves. 2. 1 mg/mL potassium ATR pure standard purchased in 50% methanol-water solution for direct infusion into the mass spectrometer. 3. 90% HPLC pure retrorsine standard. 4. 1 μg/mL–100 μg/mL (seven concentrations) working standards of each certified standard in water. 5. Ultra-performance mass spectrometer triple quadrupole system (Quatro Micro) (UPLC-MS/MS) (Waters Corp; Milford, MA, USA). 6. Acquity UPLC BEH Shield RP18 column (50 mm
2.7 μM) (Waters Corp). 7. Oasis mixed-mode 1 cm3 weak cation exchange (WCX) solidphase extraction cartridges (SPE) (Millford, MA, US, Waters Corp) for extraction of the standard curve and plant extracts. 8. Mobile phase A: 5 mM ammonium acetate, 0.1% formic acid in deionized water. 9. Mobile phase B: 99.8% acetonitrile, 0.1% formic acid, and 0.1% 5 mM ammonium acetate in deionized.

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10. Electronic grinder. 11. 0.22 μM filter. 12. Vacuum manifold. 13. 2% formic acid in water. 14. 5% ammonium hydroxide in methanol.

3

Methods

3.1 Identification and Establishing the MRM for the Pure Standard (for each MS Parameter, See Table 1)

1. Infuse a 50% methanolic extract of the pure standard (ATR or retrorsine) at a concentration of 100 mg/mL into the mass spectrometer in MS mode for identification in the first quadrupole (without activating the argon gas) to allow for identification of the parent compound in full scan mode. 2. Adjust the cone voltage to enhance detection of the parent mass of each compound as required (see Note 1). 3. Once the parent compound has been identified, turn on the argon gas and establish the daughter ion in the third quadrupole. 4. Alter the scanning mode to MRM, which allows focusing of the parent compound within the first quadrupole and fragmentation in the second quadrupole (collision cell). 5. Adjust the collision energy to provide the best fragmentation pattern for the compound of interest (see Note 2). 6. Confirm the MRM parent > daughter fragment with the mobile phase to ensure there is no ion suppression by running the same sample infused with the mobile phase at a 50:50 (A:B) ratio to ensure that no other interferences are seen (see Note 3).

Table 1 Optimized parameters for the detection of ATR and retrorsine by UPLC-MS/MS Parameters

ATR

Retrorsine

+

ESI+

Ionization mode

ESI

Cone voltage

2.5 kv

2.8 kV

Collision energy

35 Ev

28 eV

Parent ion transition

804 m/z

352 m/z

Collision gas flow

0.14 L

0.14 L

Desolvation temperature

300  C

300  C

Nebulizing gas

500 L

500 L

Nebulizing temperature



800 C

800  C

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7. For validation and quantification of ATR and retrorsine (toxic compounds) within the plant extracts, prepare a standard curve (see Note 4). 8. Once the mass spectrometry and liquid chromatography method has been developed, subject the plant extracts of ATR and retrorsine to the solid-phase extraction method described in Subheading 3.4. 3.2 Optimizing Liquid Chromatography Settings

1. Inject 10 μL of the extracted ATR or retrorsine pure standards at a concentration of 100 μg/mL onto the column with a standard gradient run of mobile phase A and mobile phase B. 2. Carry out liquid chromatography as a gradient over 2 min on the Acquity UPLC BEH Shield RP18 column linked online to the mass spectrometer. 3. Run the gradient from 80% A/20% B to 100% B and then return to original settings for column equilibration (the retention times of ATR and retrorsine under these conditions are 0.70 min and 0.62 min, respectively) (Figs. 2 and 3).

Fig. 2 UPLC-MS/MS chromatogram of extracted ATR in C. laureola (a). The amount of ATR identified in this extraction of C. laureola (b) is 100 μg/mL, using the standard curve created for ATR

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0.62

0.62

100

MRM 8 channel ESI+ 352 > 137 195

%

A

u

0.50

0.62

1.00

u

0.50

1.50

2.00

B

2.50

MRM 8 channel ESI+ 352 > 94 7.50e3

%

100

%

Relative abundance

S.latifolius

1.00

1.50

2.00

2.50

0.25 1.11

1.48

1.82

2.12

2.22

3 0.50

1.00

1.50

2.00

2.50

Time (min)

Fig. 3 The UPLC-MS/MS chromatogram of extracted retrorsine in S. latifolius (a). The amount of retrorsine identified in this extract of S. latifolius (b) is equivalent to 80 μg/mL, using the standard curve created for retrorsine

4. Run blank samples which consist of 50% A and B (50:50) to ensure there is no carry over (see Note 5). 5. Run the seven-point standard curve for both compounds (see Note 4). 6. Once optimized, validate the method using the parameters described by the Food and Drug Administration (FDA) [26] for validating chromatographic techniques (Table 2) (see Notes 6 and 7). 3.3 Sample Preparation for Use in Extraction

1. Grind C. laureola tubers using the electronic grinder. 2. Air dry for up to 48 h until hardened and store at 4–8  C prior to extraction. 3. Place 1 g of each plant extract in a 15 mL glass tube and add 10 mL boiling water. 4. Cover the tube with Parafilm and leave for 15 min. 5. Centrifuge the sample at 700
g for 15 min. 6. Filter the supernatant through the 0.22 μM filter, aliquot, and stored at 20  C. 7. Air dry S. latifolius leaves for up to 48 h until hardened and crush into a fine powder. 8. Extract 1 g crushed leaves in 10 mL boiling water in a 15 mL glass test tube. 9. Cover with Parafilm and leave for 15 min. 10. Centrifuge the sample at 700
g for 15 min.

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Table 2 Validation parameters for the ATR and retrorsine quantification method described in this chapter Atractyloside validation parameters

Retrorsine validation parameters

Linearity (r ) over concentration range of 1–100 μg/mL

0.978

0.999

Accuracy (% difference from the assigned value of the standard curve)

87–116% over the standard curve range

92–107% over the standard curve range

Limit of detection (LOD)

1.5 μg/mL

0.8 μg/mL

Limit of quantification (LOQ)

5 μg/mL

2.67 μg/mL

Robustness

Sample elution is dependent on the C18 column being maintained at 40  C

Sample can be eluted off a phenyl column as well as a C18 column maintained at 40  C

Ion suppression

Combined infusion of mobile phase Combined infusion of mobile phase and sample to assess ion and sample to assess ion suppression at retention time suppression at retention time

Parameters 2

11. Filter the supernatant through the 0.22 μM filter, aliquot, and store at 20  C. 3.4 Extraction Procedure for C. laureola and S. latifolius Plant Extracts (See Note 8)

1. Connect the SPE cartridges to a vacuum manifold. 2. Wash the cartridges, condition with 1 mL water and then 1 mL methanol under vacuum (10 bar), taking care not to let the cartridges run dry (Fig. 6). 3. Load 1 mL pure standard or plant extract onto the cartridge and pull through without vacuum. 4. Once the sample has been pulled through the cartridge, wash the cartridges under vacuum with 2% formic acid. 5. Elute the standards and samples under vacuum by loading 1 mL 5% ammonium hydroxide and allow the cartridges to run dry. 6. Dry the eluant under nitrogen at 65  C. 7. Reconstitute the fractions in 200 μL of mobile phase A for analysis on the UPLC-MS/MS system.

4

Notes 1. Each parameter for each triple quadrupole mass spectrometer, which allows for the filtering and detection of ions, can be

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optimized for detection of the compound of interest. These parameters differ between instruments and should be optimized individually. For this chapter, the parameters that were optimized are for the Waters Quatro micro system and were the following: capillary voltage, the cone voltage, collision energy, and collision gas. The mass to charge (m/z) ratio for ATR is calculated using the molecular mass of 803 g/L, therefore, the m/z is 804 (M + H) in electrospray ionization positive mode (ESI+). Likewise, the molecular mass of retrorsine is 351.39 g/ L and, therefore, the m/z is 352 in ESI+. This was then used to optimize the MS detection settings and cone voltage and thereafter to determine the daughter ion for the MRM experiment. 2. The mass spectrometer scan settings are then adjusted to develop the fragmented mass representing the daughter ions using MRM scan for retrorsine and selected ion recording (SIR) for ATR. The use of SIR for ATR is due to the fragmentation of the compound. The compound is difficult to fragment, and SIR allows for the detection of the parent compound with limited fragmentation focusing on the parent transition. The collision energy, capillary voltage, ion source temperature, and the collision gas flow, and in other instruments, the declustering potential and the declustering temperature, can all be optimized to provide the best possible fragmentation of the parent compound. 3. This will ensure that no other interferences are seen and that the compound is compatible with the mobile phase used. This is determined by looking at the peak shape and whether the MRM transitions have no additional peaks, which might cause interference. If there is a shoulder on the peak, we suggest allocating the correct type of integration to prevent the incorporation of the shoulder. This is done by employing valley-to-valley integration. The mobile phase can also reduce interference by utilizing ammonium ions from an ammonium acetate or ammonium formate adduct. This binds to the initial parent compound, where a hydrogen ion might have been removed and will allow for a more stable ion with a higher m/z (+18), which could reduce chromatographic contamination. 4. Standard curves were used to validate the linearity and quantification of ATR and retrorsine in plant extracts. Pure standards are prepared in water and extracted as per Fig. 6. Once prepared, standards are stable for 6 months at 80  C and 2 months at 20  C. Setting up quantitation of the compound is software-dependent, and for the purposes of this chapter, the MassLynx software will be discussed. Integration parameters such as minimum height threshold, minimum peak width

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threshold, and smoothing should be determined from initial injection of a pure standard. For smoothing, no more than one smoothing iteration should be employed using Savitzky-Golay smoothing of shouldered peaks [27]. The peak should be identified with the correct transition and the allocated retention time 0.05 min. The concentration needs to be allocated for each standard in the curve to allow the software to compute the graphical fit. The curve should be allocated as linear without pulling the curve through zero. Graphical change on each point of the calibration curve should not change by more than 15% at all levels of the curve. 5. This will allow one to determine if there is a linear response for the compounds and will help with accurate quantitation once the validation has been completed. 6. Linearity, accuracy, precision, limit of detection (LOD), limit of quantitation (LOQ), robustness, ion suppression, and carryover are all elements that need to be addressed during method validation, according to accepted guidelines such as those published by the FDA [23]. These parameters ensure that the data obtained are valid and fit for use for the detection and quantification of the compounds identified. Validation should be carried out over a minimum of 5 days. 7. Linearity is assessed over 5 days by running standard curves in triplicate and assessing the curve fit defined by an R2 > 0.95 (Figs. 4 and 5). Accuracy and precision are determined by

Fig. 4 Linear curve for ATR on UPLC-MS/MS using a 5-point standard curve with a concentration range of 0–100 μg/mL

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Fig. 5 Linear curve for retrorsine on UPLC-MS/MS using a 5-point standard curve with a concentration range of 0–100 μg/mL

running the standard curve in triplicate five times per day over a total of 6 days. The accuracy is determined by calculating the difference of the mean values from the assigned value of each standard point. The precision is determined using the standard deviation (SD) and coefficient of variation (CV) for both intraday and interday variation for the standard curve as there are no controls or matrix-matched samples available. Acceptance criteria are based on the FDA guideline of 20% at the low range (i.e., that level is equivalent to the LOD) and 15% for all other results. The LOD is defined as five times the signal-to-noise ratio (S/N) and the LOQ is defined as ten times the S/N. This is calculated using the observed signal of the lowest standard and comparing it to the signal at the same retention time of a blank sample (noise). Robustness is defined as the difference that occurs due to a change of column (i.e., C8-C18) or change in mobile phase, pH, or temperature. Ion suppression is defined as an interference observed from the matrix of a sample or the mobile phase and is established in the beginning of optimization when the infusion of the pure sample is combined with the mobile phase. This is then checked with an extracted sample, where a drop in baseline or bad peak shape will provide information on ion suppression. Carryover is determined by running a blank after the highest standard and observing a chromatographic peak when none should be observed. 8. The WCX extraction cartridges employ the separation technique of ion exchange and reverse phase to purify samples,

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Fig. 6 Flow diagram depicting the extraction of plant products using 1 cm3 WCX solid-phase extraction cartridges

retain compounds of interest, and then finally elute off strong bases or quaternary amines (pKa ¼ 5). The procedure is performed using the WCX extraction cartridges on a vacuum manifold, where 20 samples can be extracted at one time. The extraction procedure is as per manufacturer’s recommendations. There are four separate steps in the elution of the compound of interest (see Fig. 6). Active compounds are eluted off the column using 1 mL of 5% ammonium hydroxide in methanol as the eluant.

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References 1. Stewart MJ, Moar JJ, Steenkamp P, Kokot M (1999) Findings in fatal cases of poisoning attributed to traditional remedies in South Africa. Forensic Sci Int 101(3):177–183 2. Elvin -Lewis M (2001) Should we be concerned about herbal remedies. J Ethnopharmacol 75(2–3):141–164 3. Obatomi DK, Bach PH (1998) Biochemistry and toxicology of the diterpenoid glycoside atractyloside. Food Chem Toxicol 36 (4):335–346 4. Steenkamp V, Stewart MJ, van der Merwe S, Zuckerman M, Crowther NJ (2001) The effect of Senecio latifolius a plant used as a south African traditional medicine, on a human hepatoma cell line. J Ethnopharmaco l78 (1):51–58 5. Flade J, Beschow H, Wensch-Dorendorf M, Plescher A, W€atjen W (2019) Occurrence of nine pyrrolizidine alkaloids in Senecio vulgaris L. depending on developmental stage and season. Plan Theory 8(3):1–13 6. Popat A, Shear NH, Malkiewicz I, Stewart MJ, Steenkamp V, Thomson S et al (2001) The toxicity of Callilepis laureola, a south African traditional herbal medicine. Clin Biochem 34 (3):229–236 7. Steenkamp V, Stewart MJ (2005) Nephrotoxicity associated with exposure to plant toxins, with particular reference to Africa. Ther Drug Monit 27(3):270–277 8. Neuman MG, Jia AY, Steenkamp V (2007) Senecio latifolius induces in vitro hepatocytotoxicity in a human cell line. Can J Physiol Pharmacol 85(11):1063–1075 9. Schoental R (1968) Toxicology and carcinogenic action of pyrrolizidine alkaloids. Cancer Res 28(11):2237–2246 10. Watt MG, Breyer-Branwijk M (1962) The medicinal and poisonous plants of Southern and Eastern Africa, 2nd edn. E. & S. Livingstone Ltd., Edinburgh and London, UK. ASIN: B00CQRBAF4 11. Dimande AF, Botha CJ, Prozesky L, Bekker L, Rosemann GM, Labuschagne L et al (2007) The toxicity of Senecio inaequidens DC. J S Afr Vet Assoc 78(3):121–129 12. Scot G (2003) Acute toxicity associated with the use of South African traditional medicinal herbs. Trans R Soc S Afr 58(1):83–92 13. Laurens JB, Bekker LC, Steenkamp V, Stewart MJ (2001) Gas chromatographic-mass spectrometric confirmation of atractyloside in a patient poisoned with Callilepis laureola. J Chromatogr B Biomed Sci Appl 765(2):127–133

14. Conradie J, Stewart MJ, Steenkamp V (2005) GC/MS identification of toxic pyrrolizidine alkaloids in traditional remedies given to two sets of twins. Ann Clin Biochem 42 (Pt 2):141–144 15. Dhooghe L, Mesia K, Kohtala E, Tona L, Pieters L, Vlietinck A et al (2008) Development and validation of an HPLC-method for the determination of alkaloids in the stem bark extract of Nauclea pobeguinii. Talanta 76 (2):462–468 16. Huang P, Qian X, Li J, Cui X, Chen L, Cai B et al (2014) Simultaneous determination of 11 alkaloids in crude and wine-processed Rhizoma coptidis by HPLC-PAD. J Chromatogr Sci 53(1):73–78 17. Steenkamp PA, Harding NM, FRv H, van Wyk BE (2004) Determination of atractyloside in Callilepis laureola using solid-phase extraction and liquid chromatography–atmospheric pressure ionisation mass spectrometry. J Chromatogr A 1058(1–2):153–162 18. Carlier J, Romeuf L, Guitton J, Priez-BarallonC, Bevalot F, Fanton L et al (2014) A validated method for quantifying atractyloside and carboxyatractyloside in blood by HPLC-HRMS/ MS, a non-fatal case of intoxication with Atractylis gummifera. J Anal Toxicol 38(9):619–627 19. Vassiliadis S, Elkins AC, Reddy P, Guthridge KM, Spangenberg GC, Rochfort SJ (2019) A simple LC-MS method for the quantitation of alkaloids in endophyte-infected perennial ryegrass. Toxins 11(649):1–17 20. Valese AC, Molognoni L, de Sa´ Ploeˆncio LA, de Lima FG, Gonzaga LV, Go´rniak SL et al (2016) A fast and simple LC-ESI-MS/MS method for detecting pyrrolizidine alkaloids in honey with full validation and measurement uncertainty. Food Control 67:183–191 21. Pitt JJ (2009) Principles and applications of liquid chromatography-mass spectrometry in clinical biochemistry. Clin Biochem Rev 30 (1):19–34 22. Youssef Moustafa AM, Khodair AI, Saleh MA (2009) GC-MS investigation and toxicological evaluation of alkaloids from Leptadenia pyrotechnica. Pharm Biol 7(10):994–1003 23. Ching J, Soh WL, Tan CH, Lee JF, Tan JYC, Yang J et al (2012) Identification of active compounds from medicinal plant extracts using gas chromatography-mass spectrometry and multivariate data analysis. J Sep Sci 35 (1):53–59 24. Al-Rubaye AF, Hameed IH, Kadhim MJ (2017) A review: uses of gas chromatography-

The Detection of Toxic Compounds in Extracts of Callilepis laureola. . . mass spectrometry (GC-MS) technique for analysis of bioactive natural compounds of some plants. Int J Toxicol Pharmacol 9 (1):81–85 25. Wallace WE (2018).“Mass Spectra” in NIST Chemistry WebBook, NIST Standard Reference Database Number 69; Linstrom PJ and Mallard WG eds. National Institute of Standards and Technology, Gaithersburg MD. 10.18434/T4D303. Retrieved November 27, 2020

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Chapter 29 Impact of Curcumin on Hepatic Low-Density Lipoprotein Uptake Mohammad Jalili-Nik, Khadijeh Mahboobnia, Paul C. Guest, Muhammed Majeed, Khalid Al-Rasadi, Tannaz Jamialahmadi, and Amirhossein Sahebkar Abstract Elevated levels of plasma low-density lipoprotein cholesterol (LDL-C) are causally related to atherosclerotic cardiovascular disease. Enhancing the removal of LDL particles from the plasma, mainly by the liver, is the most efficient strategy for reducing LDL-C and the ensuing atherosclerosis. In this context, polyphenolic compounds like curcumin have generated interest owing to their lipid-modifying capacity. The promising effect of curcumin has been studied in attenuating atherosclerosis (in experimental models), and correcting dyslipidemia (in clinical studies). The underlying mechanisms of the effects of curcumin are relatively unknown, and the impact of curcumin on hepatic LDL uptake warrants further investigations. Here, we present a protocol to assess the effects of curcumin on LDL uptake in hepatocytes. Keywords Cholesterol, Atherosclerosis, Curcumin, LDL-C uptake, Hepatocyte

1

Introduction Impaired lipid metabolism and accumulation of cholesterol, mainly low-density lipoprotein cholesterol (LDL-C), in the arterial wall is a causal risk factor for atherosclerosis, which is the leading reason for cardiovascular disease (CVD), myocardial infarction, and stroke [1, 2]. Beyond LDL-C concentrations, it has been recently discovered that the number of LDL particles in plasma is a key determinant of atherosclerotic CVD risk. Reduction of plasma LDL particle number via enhancing LDL receptor density and activity has been proposed as a potentially superior anti-atherosclerotic strategy, compared with merely reducing the cholesterol content of LDL [3]. Throughout recent decades, statin therapy has been used for the prevention of CVD by reducing plasma LDL-C levels

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4_29, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Fig. 1 Chemical structure of curcumin (molecular weight 368.38 g/mol)

[4, 5]. Nevertheless, patients treated with statin even at maximally tolerated doses still have the residual risk of CVD [6]. To address the residual risk gap, there has been a recent trend on the use of nutraceuticals and phytochemicals to improve lipid profiles and blunt atherosclerosis [7]. Among these, curcumin [1,7-bis(4-hydroxy-3-methoxyphenyl)-1,6-heptadiene-3,5-dione; Fig. 1], the principal bioactive ingredient of turmeric (Curcuma longa Linn), has been considered as a natural lipid-lowering agent [8, 9]. Curcumin possesses numerous health benefits [10–13] and affects several pathways involved in cholesterol trafficking [14, 15]. Curcumin decreases the area of lipid deposits throughout the whole aorta, thereby slowing down atherosclerotic plaque formation and development. Also, as a reactive oxygen species (ROS) scavenger, curcumin reduces the risk of atherosclerosis and CVD by reducing the oxidative stress-induced inflammatory response [16]. The results of animal studies have suggested that long-term administration of curcumin regulates hepatic lipid metabolism pathways to reduce dyslipidemia and atherosclerosis [17, 18]. Curcumin has also been shown as a modulator of hepatic proprotein convertase subtilisin/kexin type 9 [19], a key regulator of the hepatic LDL receptor and LDL uptake. Herein, we present a protocol for testing the effects of curcumin on LDL uptake in hepatocytes using a cell-based assay kit, which introduces a unique mechanism for atherosclerosis treatment.

2 2.1

Materials Cell Culture

1. HepG2 cell line (National Cell Bank of Iran (NCBI), Pasteur Institute; Tehran, Iran). 2. Culture medium: Dulbecco’s Modified Eagle Medium (DMEM), containing 10% fetal bovine serum (FBS), 100 μg/mL streptomycin, 100 U/mL penicillin. 3. Phosphate-buffered saline (PBS; pH 7.4): 10 mM Na2HPO4, 1.8 mM KH2PO4, 2.7 mM KCl, 137 mM NaCl. 4. 0.05% trypsin-ethylenediaminetetraacetic acid (EDTA) from Sigma-Aldrich (St. Louis, MO, USA).

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2.2 Determining the Minimal Toxic Dose of Curcumin

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1. 3-(4,5-dimethyl-2-thiazolyl)-2, 5-diphenyl-2H-tetrazolium bromide (MTT) cell metabolism assay kit (see Note 1). 2. Dimethyl sulfoxide (DMSO). 3. Stat FAX303 microplate reader. 4. Curcumin powder (Sigma, USA).

2.3 LDL Uptake Assay

1. LDL Uptake Cell-Based Assay Kit (Abnova, Taiwan) containing: (a) Cell-based assay fixative. (b) Rabbit anti-LDL receptor primary antibody. (c) Cell-based assay blocking solution. (d) LDL-DyLightTM 550 working solution. (e) DyLightTM 488-conjugated goat anti-rabbit IgG secondary antibody. 2. Heavy salt solution: 2.63 M NaCl, 2.97 M KBr, 0.27 M EDTA. 3. Tris-buffered saline (TBS)-Triton buffer (TBST): 50 mM Tris (pH 7.4), 150 mM NaCl, and 0.1% Triton-X 100. 4. A fluorescence microscope equipped with filter sets capable of detecting fluorescein (excitation/emission ¼ 485/535 nm) and rhodamine (excitation/emission ¼ 540/570 nm). 5. PD10 desalting column (GE Healthcare Bio-Sciences AB, Sweden). 6. 1,10 -dioctadecyl-3,3,30 ,30 -tetramethylindocarbocyanine chlorate (DiI) (Molecular Probes; Eugene, OR, USA).

per-

7. Bicinchoninic acid (BCA) protein assay kit.

3

Methods

3.1 Cell Viability Assay

1. Seed 104 HepG2 cells/well in culture medium in a 96-well plate and incubate overnight at 37  C. 2. After cell adherence to the bottom of the plate, treat, and incubate the cells with 0–100 μM curcumin for 24 h at 37  C (see Note 2). 3. Add 10 μL 5 mg/mL MTT solution to each well and incubate for 4 h at 37  C. 4. Add DMSO, and after 60 min, measure the absorbance at 570 and 620 nm wavelength (background). 5. Normalize the results with the control group mean and calculate % viability relative to the 0 μM curcumin control (see Note 2).

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3.2 Treatment of HepG2 Cells with Isolated LDL and Curcumin and Evaluation of LDL Uptake

1. Seed 3  104 HepG2 cells/well in a 96-well plate and let the cells grow for 48 h. 2. Treat cells with 10 and 20 μg/mL curcumin for 24 h (see Note 3). 3. At the end of the treatment period, replace the culture medium with 100 μL/well LDL-DyLight 550 working solution from the kit and incubate the cells for 24 h (see the next point). 4. The LDL treatment can be performed using the LDL extracted from serum/plasma as described below: (a) Overlay 1 mL serum/plasma with 2 mL heavy salt solution and 10 mL PBS in a clear polycarbonate tube (with ten different serum/plasma samples). (b) Centrifuge the tube(s) in an ultracentrifuge at 30,000  g for 10 h at 4  C. (c) After centrifugation, remove the upper white very low-density lipoprotein (VLDL) layer using a Pasteur pipette without disturbing the yellow-orange LDL layer. (d) Carefully transfer the yellow-orange LDL fractions to a new tube with a Pasteur pipette to reach a minimum of 3 mL. (e) According to the manufacturer’s protocol, equilibrate the PD10 desalting column with 20 mL PBS. (f) Transfer the collected LDL fraction to the desalting column and, after discarding the first eluate fraction, elute the LDL from the column with 3.5 mL of PBS into a new tube. (g) Label the collected LDL with DiI [20]. (h) Sterilize the labeled LDL by passing through a 22 μm syringe filter. (i) Quantify the concentration of total isolated LDL using the BCA assay kit [21, 22]. 5. Replace the culture medium with fresh culture medium or PBS. 6. Examine the LDL uptake level under a fluorescence microscope at excitation and emission wavelengths of 540 and 570 nm, respectively.

3.3 Immunofluorescence Staining of LDL Receptors Using Abnova LDL Uptake Cell-Based Assay Kit

1. After treatment with curcumin and LDL-DyLight™ 550, as mentioned above, remove the culture medium and wash the wells gently with TBS. 2. Use 100 μL/well cell-based assay fixing solution to fix the cells according to the manufacturer’s protocol (see Note 4). 3. Wash the cells with TBST buffer three times for 5 min each.

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4. Incubate the cells 30 min with 100 μL/well cell-based assay blocking solution according to the manufacturer’s protocol (see Note 5). 5. Next, incubate the cells 60 min with 100 μL/well of diluted rabbit anti-LDL receptor primary antibody (see Note 6). 6. Wash the cells with TBST buffer three times for 5 min each. 7. Incubate the cells in the dark for 1 h with 100 μL/well of diluted DyLight 488-conjugated secondary anti-rabbit antibody. 8. Repeat washing step above (Subheading 3.3, step 6). 9. Observe the staining under a fluorescence microscope with a filter capable of excitation and emission at 485 and 535 nm, respectively.

4

Notes 1. MTT is a colorimetric assay for assessing the viability of cells. This assay quantifies viable cells number based on the cleavage of tetrazolium salts and the formation of formazan crystals, which are read in a microplate reader. Resazurin (or Alamar Blue) can also be used for cell viability assay [23]. 2. The highest curcumin concentration with the lowest cytotoxic effect should be used for downstream experiments (usually 1/4 or 1/8 IC50 is recommended). Further, a group of cells treated with the vehicle (0.1% DMSO) as a negative control and lovastatin (1 μM) as a positive control should be considered. 3. Mi-Hsueh Tai et al. treated the cells with 5, 10, and 20 μg/mL of curcumin as nontoxic doses [19]. 4. Alternatively, the cells can be fixed with 4% formaldehyde and 0.2% glutaraldehyde in PBS. 5. This blocking solution contains 0.1% bovine serum albumin (BSA) and 10% normal goat serum (NGS) in PBS. 6. In case of weak signal after 60 min of incubation, the cells can be alternatively incubated for 24 h at 4  C in the presence of the anti-LDL receptor primary antibody. Conflict of Interest: Muhammed Majeed is the CEO of Sabinsa Corporation and Sami-Sabinsa Group Limited.

References 1. Abdolmaleki F, Hayat SMG, Bianconi V, Johnston TP, Sahebkar A (2019) Atherosclerosis and immunity: a perspective. Trends Cardiovasc Med 29(6):363–371

2. Kiaie N, Gorabi AM, Penson PE, Watts G, Johnston TP, Banach M et al (2020) A new approach to the diagnosis and treatment of atherosclerosis: the era of the liposome. Drug Discov Today 25(1):58–72

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3. Silverman MG, Ference BA, Im K, Wiviott SD, Giugliano RP, Grundy SM et al (2016) Association between lowering LDL-C and cardiovascular risk reduction among different therapeutic interventions: a systematic review and meta-analysis. JAMA 316(12):1289–1297 4. Afshari AR, Mollazadeh H, Henney NC, Jamialahmad T, Sahebkar A (2020) Effects of statins on brain tumors: a review. Semin Cancer Biol:S1044-579X(20)30173-5. https://doi. org/10.1016/j.semcancer.2020.08.002. Online ahead of print 5. Paseban M, Butler AE, Sahebkar A (2019) Mechanisms of statin-induced new-onset diabetes. J Cell Physiol 234(8):12551–12561 6. Mohammadzadeh N, Montecucco F, Carbone F, Xu S, Al-Rasadi K, Sahebkar A (2020) Statins: Epidrugs with effects on endothelial health? Eur J Clin Invest 50:e13388. https://doi.org/10.1111/eci.13388. Online ahead of print 7. Feng WW, Kuang SY, Tu C, Ma ZJ, Pang JJ, Wang YH et al (2018) Natural products berberine and curcumin exhibited better ameliorative effects on rats with non-alcohol fatty liver disease than lovastatin. Biomed Pharmacother 99:325–333 8. Simental-Mendı´a LE, Pirro M, Gotto AM, Banach M, Atkin SL, Majeed M et al (2019) Lipid-modifying activity of curcuminoids: a systematic review and meta-analysis of randomized controlled trials. Crit Rev Food Sci Nutr 59(7):1178–1187 9. Panahi Y, Ahmadi Y, Teymouri M, Johnston TP, Sahebkar A (2018) Curcumin as a potential candidate for treating hyperlipidemia: a review of cellular and metabolic mechanisms. J Cell Physiol 233(1):141–152 10. Panahi Y, Khalili N, Sahebi E, Namazi S, Simental-Mendı´a LE, Majeed M, et al (2018) Effects of Curcuminoids Plus Piperine on Glycemic, Hepatic and Inflammatory Biomarkers in Patients with Type 2 Diabetes Mellitus: A Randomized Double-Blind PlaceboControlled Trial. Drug Res 68(7):403–409 11. Momtazi AA, Derosa G, Maffioli P, Banach M, Sahebkar A (2016) Role of microRNAs in the therapeutic effects of curcumin in non-cancer diseases. Mol Diagn Ther 20(4):335–345 12. Ghandadi M, Sahebkar A (2017) Curcumin: An effective inhibitor of interleukin-6. Curr Pharm Des 23(6):921–931 13. Teymouri M, Pirro M, Johnston TP, Sahebkar A (2017) Curcumin as a multifaceted compound against human papilloma virus infection

and cervical cancers: A review of chemistry, cellular, molecular, and preclinical features. Biofactors 43(3):331–346 14. Shin SK, Ha TY, McGregor RA, Choi MS (2011) Long-term curcumin administration protects against atherosclerosis via hepatic regulation of lipoprotein cholesterol metabolism. Mol Nutr Food Res 55(12):1829–1840 15. Zhao JF, Ching LC, Huang YC, Chen CY, Chiang AN, Kou YR, et al (2012) Molecular mechanism of curcumin on the suppression of cholesterol accumulation in macrophage foam cells and atherosclerosis. Mol Nutr Food Res 56(5):691–701 16. Li H, Sureda A, Devkota HP, Pittala` V, Barreca D, Silva AS et al (2020) Curcumin, the golden spice in treating cardiovascular diseases. Biotechnol Adv 38:107343. https://doi. org/10.1016/j.biotechadv.2019.01.010 17. Coban D, Milenkovic D, Chanet A, KhallouLaschet J, Sabbe L, Palagani A et al (2012) Dietary curcumin inhibits atherosclerosis by affecting the expression of genes involved in leukocyte adhesion and transendothelial migration. Mol Nutr Food Res 56(8):1270–1281 18. Shin SK, Ha TY, McGregor RA, Choi MS (2011) Long-term curcumin administration protects against atherosclerosis via hepatic regulation of lipoprotein cholesterol metabolism. Mol Nutr Food Res 55(12):1829–1840 19. Tai MH, Chen PK, Chen PY, Wu MJ, Ho CT, Yen JH (2014) Curcumin enhances cell-surface LDLR level and promotes LDL uptake through downregulation of PCSK9 gene expression in HepG2 cells. Mol Nutr Food Res 58(11):2133–2145 20. Sawamura T, Kume N, Aoyama T, Moriwaki H, Hoshikawa H, Aiba Y et al (1997) An endothelial receptor for oxidized low-density lipoprotein. Nature 386 (6620):73–77 21. Aoyama T, Chen M, Fujiwara H, Masaki T, Sawamura T (2000) LOX-1 mediates lysophosphatidylcholine-induced oxidized LDL uptake in smooth muscle cells. FEBS Lett 467(2):217–220 22. Bainor A, Chang L, McQuade TJ, Webb B, Gestwicki JE (2011) Bicinchoninic acid (BCA) assay in low volume. Anal Biochem 410(2):310–312 23. Pr€abst K, Engelhardt H, Ringgeler S, Hu¨bner H (2017) Basic colorimetric proliferation assays: MTT, WST, and resazurin. Methods Mol Biol 1601:1–17

INDEX A Acrylamide.................................................. 179–188, 290, 295, 364, 368 Activity assays ......................................185, 232, 236, 267 Africa ........................................................... 37–50, 75, 77, 80, 81, 84, 310, 381 α-glucosidase inhibition....................................... 167, 171 Annexin.......................................260, 261, 265, 268, 269 Anti-cancer ................................................... 4, 5, 7, 8, 12, 13, 67, 159–164, 181, 215–220, 222, 224–226, 229, 230, 239, 271–284, 288, 310, 321 Anti-cancer activity..................... 159–164, 215–226, 230 Anti-diabetic ................................. 29, 175, 176, 332, 374 Anti-inflammation ................................................ 271–285 Antimicrobial activity ........................................... 216, 222 Antioxidants ............................................... 20, 21, 23–25, 30, 66, 159, 165, 166, 168, 170, 174, 175, 180–183, 185, 187, 204, 216, 219, 222, 225, 229, 230, 233, 235, 237, 241–257, 300, 309–313, 315, 316, 371–377 Apoptosis .................................................. 11, 21, 28, 159, 235, 238, 239, 248, 259, 260, 264, 265, 268, 269, 321, 361, 362 Aquilaria crassna ....................... 332, 333, 335, 337–340 Atherosclerosis ......................................... 20, 93, 95, 100, 105, 111, 316, 395, 396 Atractyloside ................................................ 381, 383, 387

B Barberry ...............................................310–312, 315, 316 Berberine .............................................................. 309–316 β-sitosterol (β-S)................................................... 229–239 β-sitosterol-glucoside (β-SG) .............229–236, 238, 239 Biomarkers.................................................. 21, 25, 27, 61, 62, 77, 93–111, 139, 150, 185, 186, 188, 192, 194, 209–211, 248, 295, 356 Bouea macrophylla ................................................ 215–226

C Callilepis laureola................................................. 381–391 Cancer cell models .............................. 4, 7–9, 11–13, 160 Cancer research ............................................3–15, 67, 160

Cardiometabolic diseases (CVDs).................... 38–50, 72, 77, 80, 81, 128 Cardiomyoblasts.................................. 247–257, 259–269 Cardiovascular diseases (CVDs) ....................... 20, 93–95, 111, 125, 140, 247, 309, 396 Cholesterol ...........................................47, 48, 94, 95, 98, 99, 103–105, 192, 309, 310, 395, 396 Cinnamon extracts .............................. 179–183, 185–188 Cognition ....................................................72–75, 77–84, 86, 87, 203 Colorectal cancer (CRC) .................... 287–296, 319–328 C-reactive protein ..................................95, 98, 107, 108, 132, 150, 186, 204, 321, 349 Curcuma heyneana rhizome extract ................... 299–306 Curcumin.........................................................7, 191, 204, 287–296, 320, 321, 362, 372, 373, 375, 376, 395–399 Curcuminoids............................. 302, 319–328, 371–377 Cyclooxygenase (COX) inhibition............. 273, 275, 281 Cytokines ...................................................... 9, 11, 21, 22, 27, 47, 105, 108, 128, 132, 134, 139, 149–151, 156, 180, 259, 288, 316, 321, 326, 328 Cytotoxicity ......................... 12, 226, 320, 331–343, 362

D Depression ...................................... 74, 82, 192, 203–212 Diabetes ...................................................... 20, 29, 38, 40, 41, 45–46, 50, 81, 107, 120, 122, 128, 138, 165–176, 204, 215, 247, 255, 267, 309, 310, 331, 347, 371, 372 Dialysis .................................................................. 323, 325 Drug response ................................................................... 6 Drug targets .................................................................. 197 Dyslipidemia (DLD) .......................................... 21, 47, 93

E Electrochemical biosensors.................................. 241–246 Epigallocatechin gallate (EGCG)..................67, 159–164 Exercise ...............................................20, 26, 86, 93–111, 120–122, 124–126, 128, 129, 132, 134, 136–140, 149–158, 192, 203, 204, 345–358 Exercise training (ET).....................94, 96–111, 119–140

Paul C. Guest (ed.), Physical Exercise and Natural and Synthetic Products in Health and Disease, Methods in Molecular Biology, vol. 2343, https://doi.org/10.1007/978-1-0716-1558-4, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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402 Index

Extraction ................................................... 181, 183, 196, 231, 234, 249, 251, 256, 273, 275, 276, 282, 289, 332–335, 337, 340, 383, 385–391 Extracts ..........................................................96, 165–176, 183, 185–188, 215–226, 230, 232, 234, 238, 272, 275–278, 282, 283, 291, 300–303, 305, 306, 326, 331–343, 365, 381–391

L Liposomes............................................300, 302, 305, 306 Liquid chromatography mass spectrometry ...............192, 274, 381–391

M

Gas chromatography-mass spectrometry..................... 332 Glioblastoma multiforme (GBM) ...............................361, 362, 369 Gluconeogenesis .................................................... 28, 332 Glucose metabolism........................................................ 22 GLUT-4........................................................247–257, 260 Gluteofemoral fat ......................................................41, 49 Glycogen synthesis ........................................................ 332

Medicinal plants ..................................166, 271–285, 332 Menopausal stages.............................................72, 73, 76, 77, 79, 80, 82–84, 87 Menopausal symptoms ......................... 72–76, 80–83, 86 Mental disorders............................................................ 204 Metabolic syndrome .................................. 21, 25, 29, 43, 48, 96–98, 309–316, 373 Metabolism.........................................4, 7, 11, 22–26, 28, 29, 57–67, 94, 121, 132, 197, 289, 309, 345, 346, 363, 371, 372, 395–397 Metabolism and cancer ..............................................7, 11, 58–60, 63, 64, 66, 309 Molecular modification.............................................60, 67 Multiple reaction monitoring (MRM) .............. 382–384, 388 Myelin ...........................................................191–201, 206

H

N

Hashimoto thyroiditis................................................... 204 HCT116 .............................................................. 217, 224, 226, 273, 280, 281, 285 HeLa ....................................................217, 224, 226, 238 Hepatocytes .................................. 20, 21, 23, 27, 28, 332 HepG2 .............................................................5, 9, 23, 28, 30, 230, 231, 233–236, 238, 331–343, 396–398 Histologic analysis......................................................... 305 Histology ........................................................25, 303, 304 Huh7 ................................................................... 230, 231, 233–236, 238 Hyperglycemia....................................................... 29, 165, 259, 331, 332, 374 Hypertension (HTN) ................................ 19, 20, 46–47, 97, 105–107, 310

Natural products .............................................6, 7, 15, 30, 66–67, 159–164, 215, 242, 271–273, 345, 362 Neuronal antibodies...................................................... 204 Non-alcoholic fatty liver disease (NAFLD)............19–23, 25–30, 48

F 5-FU ............................................................ 291, 292, 296 Flow cytometer .......................................... 261, 263–266, 268, 289, 291

G

I Indigofera zollingeriana Miq .............................. 229–239 Inflammation .............................................. 20–22, 24, 25, 27, 29, 44, 95, 97, 98, 105, 119–140, 149, 150, 179–188, 191, 211, 259, 272, 283, 293, 296, 321, 326, 347, 371 Insulin resistance .................................. 19–22, 25, 26, 29, 45, 48, 97, 102, 107, 119, 121, 122, 128–132, 137, 138, 316, 331, 347, 355, 358, 375 Isolated compounds............................................ 168, 172, 235, 274, 280

O Obesity........................................................ 20, 21, 27, 30, 38–49, 94, 98, 105, 106, 119–128, 130, 132, 136–140, 287, 309, 310, 319, 347, 371, 372 Oligodendrocyes ........................................................... 191 Omega 3 fatty acids ............................345, 346, 349, 357 Overweight...........................................25, 39, 41, 42, 48, 102, 107, 108, 121, 123, 125, 126, 130, 132, 139, 345 Oxidative stress........................................... 19–30, 41, 59, 122, 165, 179–188, 192, 242, 260, 309, 310, 371

P Pathways ................................................. 7, 23, 25, 27–29, 49, 58–60, 62, 63, 67, 104, 121, 180, 195, 197, 236, 247, 256, 259–269, 272, 288, 361, 372, 373 Phosphoglycerate kinase 1 (PGK1) ................ 58–67, 256 Physical activities ...............................................25, 86, 94, 109, 110, 119, 122, 132, 150, 152, 345, 351 Physical performance .................................................... 152

PHYSICAL EXERCISE

AND

NATURAL

Polyphenols ............................................. 20, 22, 225, 287 Proteome .............................................................. 191–201 Proxidant-antioxidant balance...................................... 315 Psychiatric symptom scores ................................. 204, 209

Q Quantitative polymerase chain reaction (qPCR)............................ 335, 336, 340–343, 362

R Reactive oxygen species (ROS) ...............................21–24, 27, 28, 165, 242, 259, 260, 309, 310, 371, 396 Regulation .............................................. 8, 22, 29, 60–63, 67, 105, 132, 247, 288, 321, 332, 362 Resistance exercises .............................104, 154, 345–358 Resistance training .............................................. 107, 132, 136–139, 150, 152–154, 345, 347, 353 Resveratrol ........................................................ 20–30, 362 Retrorsine .....................................................381–388, 390

S Schizophrenia ............................. 192, 196–198, 203–212 Senecio latifolius.................................................... 381–392 Skin penetration ............................................................ 306 Solid phase extraction ................................. 383, 385, 391 Streptozotocin (STZ) ................................. 166, 172, 173 Sub-Saharan Africa ............................................37, 38, 72, 80–82, 87 Superoxide .................................................... 21, 242, 243, 245, 289, 309, 372, 375

AND

SYNTHETIC PRODUCTS

IN

HEALTH

AND

DISEASE Index 403

T 3d cell culture..................................................... 4–15, 160 Tocopherol ........................................................... 241–246 Total antioxidant capacity.................................... 373, 377 Trolox .................................................................. 247–257, 260–265, 374–377 Turmeric ..........................................................7, 191, 287, 320, 321, 372, 396 Type 2 diabetes mellitus (T2DM) ...................19, 21, 30, 96, 98, 103, 105, 106, 120, 122, 125, 127–131, 137–140, 309, 310, 371–377

U Ultraviolet (UV)................................ 167, 217, 234, 235, 241–246, 274, 276, 278

V Visceral fat ............................................. 39–41, 44–47, 49 Vitamin D ............................................345–349, 356, 357

W Western blot .................................................................. 267 Western blot analysis ...........................236, 289, 291, 292

X XTT assays ...........................................275, 280, 281, 283

Z Zerumbone........................................................... 361–369