Magnetic Nanoparticles in Human Health and Medicine: Current Medical Applications and Alternative Therapy of Cancer [1 ed.] 1119754674, 9781119754671

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Magnetic Nanoparticles in Human Health and Medicine

Magnetic Nanoparticles in Human Health and Medicine Current Medical Applications and Alternative Therapy of Cancer

Edited by

Costica Caizer Department of Physics, West University of Timisoara, Timisoara, Romania

Mahendra Rai UGC-Basic Science Research Faculty, Department of Biotechnology, SGB Amravati University, Amravati, Maharashtra, India

This edition first published 2022 © 2022 John Wiley & Sons Ltd All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions. The right of Costica Caizer and Mahendra Rai to be identified as the authors of the editorial material in this work has been asserted in accordance with law. Registered Offices John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK Editorial Office 9600 Garsington Road, Oxford, OX4 2DQ, UK For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com. Wiley also publishes its books in a variety of electronic formats and by print-on-demand. Some content that appears in standard print versions of this book may not be available in other formats. Limit of Liability/Disclaimer of Warranty The contents of this work are intended to further general scientific research, understanding, and discussion only and are not intended and should not be relied upon as recommending or promoting scientific method, diagnosis, or treatment by physicians for any particular patient. In view of ongoing research, equipment modifications, changes in governmental regulations, and the constant flow of information relating to the use of medicines, equipment, and devices, the reader is urged to review and evaluate the information provided in the package insert or instructions for each medicine, equipment, or device for, among other things, any changes in the instructions or indication of usage and for added warnings and precautions. While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. Library of Congress Cataloging-in-Publication Data Names: Caizer, Costica, editor. | Rai, Mahendra, editor. Title: Magnetic nanoparticles in human health and medicine : current medical applications and alternative therapy of cancer / edited by Costica Caizer, Mahendra Rai. Description: Hoboken, NJ : Wiley-Blackwell, 2022. | Includes bibliographical references and index. Identifiers: LCCN 2021007068 (print) | LCCN 2021007069 (ebook) | ISBN 9781119754671 (hardback) | ISBN 9781119754732 (adobe pdf) | ISBN 9781119754749 (epub) Subjects: LCSH: Magnetic nanoparticles–Therapeutic use. | Nanomedicine. | Cancer–Alternative treatment. Classification: LCC R857.N34 M34 2021 (print) | LCC R857.N34 (ebook) | DDC 610.28–dc23 LC record available at https://lccn.loc.gov/2021007068 LC ebook record available at https://lccn.loc.gov/2021007069 Cover Design: Wiley Cover Image: © Getty Images/Andras Szada/EyeEm Set in 9.5/12.5pt STIXTwoText by Straive, Pondicherry, India

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Contents List of Contributors

1

1.1 1.1.1 1.1.2 1.1.3 1.1.4 1.1.5 1.1.6 1.1.7 1.1.8 1.1.8.1 1.1.8.2 1.2 1.2.1 1.2.2 1.2.3 1.2.4 1.3

An Introduction to Magnetic Nanoparticles: From Bulk to Nanoscale Magnetism and Their Applicative Potential in Human Health and Medicine 1 Costica Caizer, Shital Bonde, and Mahendra Rai Magnetism of Nanoparticles: From Bulk to Nanoscale 1 Introduction 1 The Atomic Magnetic Moment, Magnetization, and Magnetic Moment of the Nanoparticle 3 Magnetic Structures 5 Magnetic Saturation 7 Magnetic Anisotropy 10 Magnetic Behavior in External Magnetic Field 15 Magnetic Relaxation in Nanoparticles – Superparamagnetism 18 Dynamic Magnetic Behavior 21 Relaxation Time, Measurement Time, and Blocking Temperature 21 The Heating of Magnetic Nanoparticles in an Alternating Magnetic Field 23 Magnetic Nanoparticles as a New Tool for Biomedical Applications 24 Magnetic Nanoparticles for Diagnosis and Detection of Diseases 24 Magnetic NPs as a Smart Drug Delivery System 26 Magnetic NPs in Therapeutic Applications 27 Theranostic Applications of Multifunctional Magnetic NPs 27 Conclusion 29 References 30

Part I 2

2.1 2.2 2.2.1 2.2.2

xiii

Current Biomedical Applications of Magnetic Nanoparticles

Magnetic Nanoparticles in Nanomedicine 37 Gabriela Fabiola Ştiufiuc, Cristian Iacoviță, Valentin Toma, Rareș Ionuț Ştiufiuc, Romulus Tetean, and Constantin Mihai Lucaciu Introduction 37 Biomedical Applications 38 MNPs as Contrast Agents in MRI 39 Magnetic Particle Imaging (MPI) 44

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2.2.3 MPI Cell Tracking 45 2.2.4 MNPs in Magnetic Hyperthermia 47 2.3 Conclusions and Final Remarks 52 Acknowledgments 53 References 53 3 3.1 3.2 3.2.1 3.2.2 3.2.3 3.2.4 3.3 3.3.1 3.3.2 3.3.3 3.3.4 3.3.5 3.3.6 3.4 3.5

Clustering of Magnetic Nanoparticles for Nanomedicine Giacomo Mandriota and Riccardo Di Corato Introduction 59 Clustering Theory 60 Molecular Interaction 61 Van der Waals Forces 62 Magnetic Interaction 63 Electrostatic Interaction 64 Clustering Methods 66 Synthetic Approach 66 Inorganic Coatings 69 Polymer-Assisted Clustering 69 Polysaccharides Coatings 73 Lipidic Coatings 74 Other Molecules 75 Theranostic Relevant Examples 76 Conclusion and General Remarks 78 References 80

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4

Multifunctional Bioactive Magnetic Scaffolds with Tailored Features for Bone Tissue Engineering 87 Teresa Russo, Roberto De Santis, Valentina Peluso, and Antonio Gloria

4.1 4.2 4.3 4.4 4.5

Introduction 87 Scaffolds for Bone Tissue Engineering: An Overview Surface Presentation 94 Bioactive Magnetic Scaffolds 96 Conclusions and Final Remarks 102 References 103

5

Magnetic Nanoparticles in the Development of Polymer Scaffolds for Medical Applications 113 Larissa Stieven Montagna, Ana Paula da Silva, Amanda de Sousa Martinez de Freitas, and Ana Paula Lemes Introduction 113 Production Methods for Scaffolds and Hydrogels Based on Polymer Nanocomposites Filled 116 Freeze-drying 118 Freeze-thawing 118 Electrospinning 119 3D Printing 120

5.1 5.2 5.2.1 5.2.2 5.2.3 5.2.4

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5.3 5.3.1 5.3.1.1 5.3.1.2 5.3.2 5.4

Applications of Scaffolds Filled with MNPs Oncological Therapies 122 Hyperthermia Therapy 122 Drug Delivery Therapy 123 Tissue Regeneration 125 Conclusion 128 References 128

6

Magnetic Polymer Colloids for Ultrasensitive Molecular Imaging 135 Sundas Riaz, Sumera Khizar, Nasir M. Ahmad, Gul Shahnaz, Noureddine Lebaz, and Abdelhamid Elaissari Introduction 135 Molecular Imaging 137 Magnetic Resonance Imaging 137 Basic Components of an MRI Machine 138 Development of Contrast Agents for MRI 141 Development of MRI as a Tool for Ultrasensitive Molecular Imaging 143 Development of Iron Oxide-Based Contrast Agents for Ultrasensitive Imaging Development of an Imaging Platform for MRI 144 Electrostatic Layer-by-Layer Self Assembly for Magnetic Thin Films 144 Conclusion and Final Remarks 147 Acknowledgments 147 References 147

6.1 6.2 6.2.1 6.2.2 6.2.3 6.3 6.3.1 6.3.2 6.3.3 6.4

7

7.1 7.2 7.3 7.4

8

8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.7.1 8.7.2 8.7.3 8.7.4

122

Iron oxide Nanoparticles in Anticancer Drug Delivery and Imaging Diagnostics Miroslava Nedyalkova, Boyan Todorov, Haruna Barazorda-Ccahuanac, and Sergio Madurga Introduction 151 SPIONs – Anticancer Drug Delivery 153 SPIONs in Imaging Techniques for Biomedical Applications 157 Conclusion 159 References 159

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Functional Addressable Magnetic Domains and Their Potential Applications in Theranostics 164 Sihomara Patricia García-Zepeda and Jaime Santoyo-Salazar Introduction 164 Magnetite: The Addressable Compass 165 Magnetite Magnetic Moments 166 Magnetic Domains and Superparamagnetism in Magnetite Nanoparticles (MNPs) SPIONs Synthesis 169 MNPs Functionalization 170 Theranostics: Concepts and Possibilities 171 Hyperthermia 171 Magnetic Resonance Imaging (MRI) 173 Drug Delivery 173 Preliminary Theranostics for Medicine 175

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8.8

Conclusion 175 References 175

9

Nuclear/MR Magnetic Nanoparticle-based Probes for Multimodal Biomedical Imaging 181 Eirini Fragogeorgi, Sophia Sarpaki, Maritina Rouchota, Panagiotis Papadimitroulas, and Maria Georgiou Introduction 181 Overview of Imaging Techniques 182 SPECT/PET/MRI Tracers 182 Surface Labeling Strategies 185 Direct Labeling (Chelator-free) 186 Chelated-based Labeling 186 Preclinical Imaging Applications 186 Conclusion and Final Remarks 189 References 196

9.1 9.2 9.3 9.3.1 9.3.2 9.3.3 9.3.4 9.4

Part II 10

Magnetic Nanoparticles in Alternative Cancer Therapy

201

Magnetic Nanoparticles Hyperthermia: The Past, The Present, and The Future Dawn Blazer, Yohannes Getahun, and Ahmed El-Gendy 10.1 Introduction 203 10.1.1 Historical Background 207 10.1.2 Types of Hyperthermia 208 10.1.3 MNPs for Local Hyperthermia 210 10.1.4 Magnetic Nanoparticles 210 10.1.4.1 Magnetic Properties of MNPs for Hyperthermia 210 10.1.5 Heating Mechanism 211 10.1.5.1 Hysteresis Loss 212 10.1.5.2 Néel Relaxation 214 10.1.6 Brownian Relaxation 214 10.2 Synthesis Methods 214 10.2.1 Physical Methods 215 10.2.2 Biological Methods 216 10.2.3 Chemical Methods 217 10.2.4 Functionalization of Magnetic Nanoparticles 218 10.3 In Vitro/In Vivo and Preclinical MNH Research 219 10.4 State-of-the-Art of MNH 223 10.5 Conclusion 224 References 224 11

11.1 11.2

203

Drug Delivery and Magnetic Hyperthermia Based on Surface Engineering of Magnetic Nanoparticles 231 Guilherme N. Lucena, Caio C. dos Santos, Gabriel C. Pinto, Bruno E. Amantéa, Rodolfo D. Piazza, Miguel Jafelicci Jr, and Rodrigo Fernando C. Marques Introduction 231 Magnetic Properties of Iron Oxide Nanoparticles 232

Contents

11.3 11.3.1 11.3.2 11.3.3 11.3.4 11.4 11.5 11.6 11.7

Surface Engineering of MNP 234 Surface Modification of MNP 234 Surface Coating with Multifunctional Organic Molecules 234 Surface Coating with Multifunctional Polymers 235 Surface Coating with Multifunctional Inorganic Materials 235 Surface Engineering of MNP in Magnetic Properties and Colloidal Stability 236 Surface Engineering of MNP in Drug Delivery and Magnetic Hyperthermia 238 MNP Surface Engineering for Drug Delivery: Hydrophobic Medicines 242 Conclusion and Outlook 243 References 244

12

Improving Magneto-thermal Energy Conversion Efficiency of Magnetic Fluids Through External DC Magnetic Field Induced Orientational Ordering 250 Barid Baran Lahiri, Surojit Ranoo, Fouzia Khan, and John Philip Introduction 250 Linear Response Model for RFAMF-Induced Heating of Magnetic Nanofluids 252 Effect of Medium Viscosity on RFAMF Induced Heating Efficiency 254 External DC Magnetic Field-Induced Orientational Ordering 256 Experimental Determination of RFAMF-Induced Heating Efficiency 261 Enhancement of Heating Efficiency upon Orientational Ordering 262 In situ Orientational Ordering in Water-based Magnetic Nanofluids 262 SAR Enhancement in Oriented Magnetic Nanoemulsions in Agar Medium 265 Conclusion and Final Remarks 266 References 267

12.1 12.2 12.3 12.4 12.5 12.6 12.6.1 12.6.2 12.7

13

13.1 13.2 13.2.1 13.2.2 13.2.3 13.3 13.3.1 13.3.1.1 13.3.1.2 13.3.1.3 13.3.2 13.3.2.1 13.3.2.2

Classical Magnetoliposomes vs. Current Magnetocyclodextrins with Ferrimagnetic Nanoparticles for High Efficiency and Low Toxicity in Noninvasive Alternative Therapy of Cancer by Magnetic/Superparamagnetic Hyperthermia 272 Costica Caizer, Cristina Dehelean, and Codruta Soica Introduction 272 Basic Physical Aspects That Lead to the Heating of MNPs 273 Heat of Nanoparticles by Eddy Currents 273 Heat of MNPs by Hysteresis Effect 275 Heat of MNPs by Relaxation Processes 278 MNPs – Liposomes/ CDs as High Potential in Cancer Therapy by Magnetic/ Superparamagnetic Hyperthermia 281 Classical Magnetoliposomes (MLPs) in Cancer Therapy by Magnetic/Superparamagnetic Hyperthermia 281 Liposomes 282 MNPs Bioencapsulated in Liposomes (Magnetoliposomes) for Cancer Therapy by Magnetic/Superparamagnetic Hyperthermia (MHT/SPMHT) 285 Results (in vitro, in vivo) 288 MNPs Bioconjugated with CDs as High Potential in Noninvasive Alternative Cancer Therapy 290 α, β, γ - CDs: Structure and Biological Properties. Current Pharmaceutical Purposes 290 Core-Shell MNPs – CDs (Magneto – CDs) in Cancer Therapy: Synthesis and Bioconjugation 292

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13.3.2.3 MHT/SPMHT in vitro and in vivo Using MCDs for Possible Noninvasive Alternative Therapy of Cancer 296 13.4 Specific Absorption Rate in SPMHT Using MLPs and MCDs 297 13.5 Conclusion 300 Acknowledgments 300 References 300 14

14.1 14.2 14.3 14.3.1 14.3.1.1 14.3.1.2 14.3.1.3 14.3.2 14.3.2.1 14.3.2.2 14.3.2.3 14.4 15

15.1 15.2 15.2.1 15.2.2 15.2.3 15.3 15.3.1 15.3.2 15.3.2.1 15.3.2.2 15.3.2.3 15.3.2.4 15.3.3 15.4

Efficiency of Energy Dissipation in Nanomagnets: A Theoretical Study of AC Susceptibility 307 Francois Vernay, Jean-Louis Déjardin, and Hamid Kachkachi Introduction 307 General Formalism: The SAR in Terms of the Dynamic Susceptibility 308 Linear and Nonlinear Susceptibility: Study of Two System Examples 310 2D Monodisperse Assembly with Oriented Anisotropy 311 Linear Susceptibility 311 Cubic Susceptibility 315 Results and Discussion 318 3D Polydisperse Assembly with Random Anisotropy 320 Linear, Cubic, and Fifth-Order AC Susceptibility 321 Application to Specific Samples 322 Effect of Magnetic Field Frequency 323 Conclusion 324 References 325 Magnetic Nanoparticle Relaxation in Biomedical Application: Focus on Simulating Nanoparticle Heating 327 Ulrich M. Engelmann, Carolyn Shasha, and Ioana Slabu Introduction 327 Theory of Magnetic Particle Heating 328 Physics of Magnetic Particle Relaxation 328 Stoner–Wohlfarth Model-Based Theory of Magnetic Particle Heating 331 Linear Response Theory of Magnetic Particle Heating 332 Predicting the Magnetic Particle Heating 333 Implementation of Magnetic Particle Heating in Monte Carlo (MC-) Simulations 333 Comparison of Magnetic Particle Heating Results from MC-Simulation, LRT, and SWMBT 334 Size-Dependent Magnetic Particle Heating Predictions 336 Field-Dependent Particle Heating Predictions 336 Anisotropy-Dependent Heating Predictions 343 Summary of Magnetic Particle Heating Results from MC-Simulation, LRT, and SWMBT 344 Discussion of Validation and Applicability of Magnetic Particle Heating MC-Simulation 344 Conclusion 346 Appendix 346 15.A.1 Applying the Stratonovic–Heun Scheme 346 15.A.2 Step-by-Step Implementation of MC-Simulations 348 Acknowledgments 350 References 351

Contents

16

16.1 16.2 16.2.1 16.2.2 16.3

17

17.1 17.2 17.2.1 17.2.2 17.2.2.1 17.2.2.2 17.2.2.3 17.2.3 17.3 17.3.1 17.3.2 17.3.2.1 17.3.2.2 17.3.2.3 17.3.3 17.3.3.1 17.3.3.2 17.4 17.4.1 17.4.2 17.4.2.1 17.4.2.2 17.4.2.3 17.4.2.4 17.4.3 17.5 17.5.1 17.5.2 17.5.3 17.5.4 17.5.5

Magnetic Nanoparticles in Alternative Tumors Therapy: Biocompatibility, Toxicity, and Safety Compared with Classical Methods 355 Costica Caizer and Mahendra Rai Introduction 355 Biocompatibility, Toxicity, and Safety of Magnetic Nanoparticles for Alternative Cancer Therapy 356 Biologically Generated Biocompatible Magnetic Nanoparticles 358 Biocompatible Magnetic Nanoparticles Obtained in the Laboratory 358 Conclusion 372 References 372 The Size, Shape, and Composition Design of Iron Oxide Nanoparticles to Combine, MRI, Magnetic Hyperthermia, and Photothermia 380 Barbara Freis, Geoffrey Cotin, Francis Perton, Damien Mertz, Sebastien Boutry, Sophie Laurent, and Sylvie Begin-Colin Introduction 380 Structure, Magnetic Properties and Synthesis Methods of Iron Oxide NPs 382 Spinel Iron Oxide 382 Effect of the Size and Doping on the Magnetic Properties of Iron Oxide NPs 382 Superparamagnetism 382 Influence of the Size and Shape on Magnetic Properties 384 Effect of Doping on Magnetic Properties of Iron Oxide NPs 385 Main Chemical Synthesis Methods of Iron Oxide NPs 388 Iron Oxide as Contrast Agent for MRI 389 MRI Contrast Agents 389 Cellular Magnetic Labeling 391 Specific Magnetic Labeling of Cells 391 Nonspecific Magnetic Labeling of Cells 392 Applications of Cellular Magnetic Labeling 393 MRI Monitoring of Cells after Magnetic Labeling in vivo 397 Inflammation 397 Tumors 398 Magnetic Hyperthermia with Iron Oxide NPs 399 Principle and Main Parameters 399 Optimization of Magnetic NPs for Magnetic Hyperthermia 401 Size Effect 401 Effect of Concentration/Dipolar Interactions 402 Composition of NPs: Doping of Iron Oxide or Core-Shell NPs 407 Shape Effects 407 In vitro/In vivo Experiments 408 Iron Oxide Nanoparticles Used for Photothermal Treatment 410 Photothermia with Iron Oxide NPs 410 Photothermia Results of Iron Oxide NPs Enhanced Thanks to a NIR-Absorbing Polymer Coating 411 Influence of the Crystallinity and Composition of Iron Oxide NPs 411 Influence of the NPs Shape 412 Dual Treatment MH/PT Treatments 412

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17.5.6 17.6

Magneto-Plasmonic Nano-Objects 413 Conclusion and Final Remarks 413 References 416

18

Magnetic/Superparamagnetic Hyperthermia in Clinical Trials for Noninvasive Alternative Cancer Therapy 430 Costica Caizer Introduction 430 Magnetic/Superparamagnetic Hyperthermia in Clinical Trials 431 Increase Efficacy of MHT/SPMHT in Cancer Treatment by Using Dual-Therapy Conclusions 457 Acknowledgments 457 References 457

18.1 18.2 18.3 18.4

Index

464

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List of Contributors Nasir M. Ahmad Polymer Research Lab School of Chemical and Materials Engineering (SCME) National University of Sciences and Technology (NUST) Islamabad, Pakistan Bruno E. Amantéa Magnetic Materials and Colloids Laboratory Institute of Chemistry São Paulo State University (UNESP) Araraquara, SP, Brazil Haruna L. Barazorda-Ccahuanac Centro de Investigación en Ingeniería Molecular-CIIM Universidad Católica de Santa María Arequipa, Peru Sylvie Begin-Colin Université de Strasbourg, CNRS Institut de Physique et Chimie des Matériaux de Strasbourg Strasbourg, France Dawn Blazer Department of Physics University of Texas at El Paso El Paso, TX, USA Shital Bonde UGC – Basic Science Research Faculty Department of Biotechnology SGB Amravati University Amravati, Maharashtra, India

Sebastien Boutry Université de Mons General Organic and Biomedical Chemistry Unit NMR and Molecular Imaging Laboratory Mons, Belgium; Center for Microscopy and Molecular Imaging (CMMI) Gosselies, Belgium Costica Caizer Department of Physics West University of Timisoara Timisoara, Romania Geoffrey Cotin Université de Strasbourg, CNRS Institut de Physique et Chimie des Matériaux de Strasbourg Strasbourg, France Ana Paula da Silva Department of Science and Technology Polymers and Biopolymers Technology Laboratory (TecPBio) Federal University of Sao Paulo São José dos Campos, SP, Brazil Cristina Dehelean Faculty of Pharmacy Department of Toxicology “Victor Babes” University of Medicine and Pharmacy Timisoara, Romania

xiv

List of Contributors

Jean-Louis Déjardin Laboratoire PROMES CNRS UPR8521 Université de Perpignan Via Domitia Rambla de la Thermodynamique Tecnosud, Perpignan, France Amanda de Sousa Martinez de Freitas Department of Science and Technology Polymers and Biopolymers Technology Laboratory (TecPBio) Federal University of Sao Paulo São José dos Campos, SP, Brazil Roberto De Santis Institute of Polymers Composites and Biomaterials National Research Council of Italy Naples, Italy Riccardo Di Corato Institute for Microelectronics and Microsystems (IMM) CNR, Via Monteroni Lecce, Italy Caio C. dos Santos Magnetic Materials and Colloids Laboratory Institute of Chemistry São Paulo State University (UNESP) Araraquara, SP, Brazil Abdelhamid Elaissari University Claude Bernard Lyon-1 CNRS, ISA-UMR 5280 Lyon, France Ahmed A. El-Gendy Department of Physics University of Texas at El Paso El Paso, TX, USA Ulrich M. Engelmann Department of Medical Engineering and Applied Mathematics FH Aachen University of Applied Sciences Aachen, Germany; Applied Medical Engineering Helmholtz Institute, Medical Faculty RWTH Aachen University Aachen, Germany

Eirini Fragogeorgi Institute of Nuclear & Radiological Sciences Technology, Energy & Safety (INRASTES) NCSR “Demokritos” Ag. Paraskevi-Athens, Greece; Bioemission Technology Solutions (BIOEMTECH) Lefkippos Attica Technology Park NCSR “Demokritos” Ag. Paraskevi-Athens, Greece Barbara Freis Université de Strasbourg, CNRS Institut de Physique et Chimie des Matériaux de Strasbourg Strasbourg, France Sihomara Patricia García-Zepeda Departmento de Toxicología Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional CINVESTAV-IPN, Av. IPN 2508 Zacatenco, Ciudad de Mexico, Mexico Maria Georgiou Bioemission Technology Solutions (BIOEMTECH) Lefkippos Attica Technology Park NCSR “Demokritos” Ag. Paraskevi-Athens, Greece Yohannes Getahun Department of Physics University of Texas at El Paso El Paso, TX, USA Antonio Gloria Institute of Polymers Composites and Biomaterials National Research Council of Italy Naples, Italy Cristian Iacoviță Department of Pharmaceutical Physics and Biophysics “Iuliu Hațieganu” University of Medicine and Pharmacy Cluj-Napoca, Romania

List of Contributors

Miguel Jafelicci Jr Magnetic Materials and Colloids Laboratory Institute of Chemistry São Paulo State University (UNESP) Araraquara, SP, Brazil Hamid Kachkachi Laboratoire PROMES CNRS UPR8521 Université de Perpignan Via Domitia Rambla de la Thermodynamique Tecnosud, Perpignan, France Fouzia Khan Smart Materials Section Corrosion Science and Technology Division Materials Characterization Group Metallurgy and Materials Group Indira Gandhi Centre for Atomic Research, HBNI Kalpakkam, Tamil Nadu, India Sumera Khizar Polymer Research Lab School of Chemical and Materials Engineering (SCME) National University of Sciences and Technology (NUST) Islamabad, Pakistan Barid Baran Lahiri Smart Materials Section Corrosion Science and Technology Division Materials Characterization Group Metallurgy and Materials Group Indira Gandhi Centre for Atomic Research, HBNI Kalpakkam, Tamil Nadu, India Sophie Laurent Université de Mons General Organic and Biomedical Chemistry Unit NMR and Molecular Imaging Laboratory Mons, Belgium; Center for Microscopy and Molecular Imaging (CMMI) Gosselies, Belgium

Noureddine Lebaz University Claude Bernard Lyon-1 CNRS, LAGEPP UMR-5007 Villeurbanne, France Ana Paula Lemes Department of Science and Technology Polymers and Biopolymers Technology Laboratory (TecPBio) Federal University of Sao Paulo São José dos Campos, SP, Brazil Constantin Mihai Lucaciu Department of Pharmaceutical Physics and Biophysics “Iuliu Hațieganu” University of Medicine and Pharmacy Cluj-Napoca, Romania Guilherme N. Lucena Magnetic Materials and Colloids Laboratory Institute of Chemistry São Paulo State University (UNESP) Araraquara, SP, Brazil; Institute of Chemistry Institute of Bioenergy Research (IPBEN) São Paulo State University (UNESP) Araraquara, SP, Brazil Sergio Madurga Faculty of Chemistry Barcelona University Barcelona, Spain Giacomo Mandriota Istituto Italiano di Tecnologia, Via Morego Genoa, Italy

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Rodrigo Fernando C. Marques Magnetic Materials and Colloids Laboratory Institute of Chemistry São Paulo State University (UNESP) Araraquara, SP, Brazil; Institute of Chemistry Institute of Bioenergy Research (IPBEN) São Paulo State University (UNESP) Araraquara, SP, Brazil; Centre for Monitoring and Research of the Quality of Fuels, Biofuels, Crude Oil, and Derivatives (CEMPEQC) Institute of Chemistry São Paulo State University (UNESP) Araraquara, SP, Brazil Damien Mertz Université de Strasbourg, CNRS Institut de Physique et Chimie des Matériaux de Strasbourg Strasbourg, France Larissa Stieven Montagna Department of Science and Technology Polymers and Biopolymers Technology Laboratory (TecPBio) Federal University of Sao Paulo São José dos Campos, SP, Brazil Miroslava Nedyalkova Faculty of Chemistry and Pharmacy Sofia University “St. Kliment Ohridski” Sofia, Bulgaria Panagiotis Papadimitroulas Bioemission Technology Solutions (BIOEMTECH) Lefkippos Attica Technology Park NCSR “Demokritos” Ag Paraskevi-Athens, Greece Valentina Peluso Department of Neurosciences Reproductive and Odontostomatological Sciences University of Naples Federico II Naples, Italy

Francis Perton Université de Strasbourg, CNRS Institut de Physique et Chimie des Matériaux de Strasbourg Strasbourg, France John Philip Smart Materials Section Corrosion Science and Technology Division Materials Characterization Group Metallurgy and Materials Group Indira Gandhi Centre for Atomic Research, HBNI Kalpakkam, Tamil Nadu, India Rodolfo D. Piazza Magnetic Materials and Colloids Laboratory Institute of Chemistry São Paulo State University (UNESP) Araraquara, SP, Brazil Gabriel C. Pinto Magnetic Materials and Colloids Laboratory Institute of Chemistry, São Paulo State University (UNESP) Araraquara, SP, Brazil Mahendra Rai UGC – Basic Science Research Faculty Department of Biotechnology SGB Amravati University Amravati, Maharashtra, India Surojit Ranoo Smart Materials Section Corrosion Science and Technology Division Materials Characterization Group Metallurgy and Materials Group Indira Gandhi Centre for Atomic Research, HBNI Kalpakkam, Tamil Nadu, India Sundas Riaz Polymer Research Lab School of Chemical and Materials Engineering (SCME) National University of Sciences and Technology (NUST) Islamabad, Pakistan

List of Contributors

Maritina Rouchota Bioemission Technology Solutions (BIOEMTECH) Lefkippos Attica Technology Park NCSR “Demokritos” Ag. Paraskevi-Athens, Greece Teresa Russo Institute of Polymers Composites and Biomaterials National Research Council of Italy Naples, Italy Jaime Santoyo-Salazar Departmento de Física Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional CINVESTAV-IPN, Av. IPN 2508 Zacatenco, Ciudad de Mexico, Mexico Sophia Sarpaki Bioemission Technology Solutions (BIOEMTECH) Lefkippos Attica Technology Park NCSR “Demokritos” Ag. Paraskevi-Athens, Greece Gul Shahnaz Department of Pharmacy Faculty of Biological Sciences Quaid-i-Azam University Islamabad, Pakistan Carolyn Shasha Department of Physics University of Washington Seattle, WA, USA Ioana Slabu Applied Medical Engineering Helmholtz Institute, Medical Faculty RWTH Aachen University Aachen, Germany Codruta Soica Faculty of Pharmacy Department of Toxicology “Victor Babes” University of Medicine and Pharmacy Timisoara, Romania

Gabriela Fabiola Ştiufiuc Faculty of Physics “Babes-Bolyai” University Cluj-Napoca, Romania Rareș Ionuț Ştiufiuc Department of Pharmaceutical Physics and Biophysics “Iuliu Hațieganu” University of Medicine and Pharmacy Cluj-Napoca, Romania; MedFuture Research Center for Advanced Medicine “Iuliu Hațieganu” University of Medicine and Pharmacy Cluj-Napoca, Romania Romulus Tetean Faculty of Physics “Babes-Bolyai” University Cluj-Napoca, Romania Boyan Todorov Faculty of Chemistry and Pharmacy Sofia University “St. Kliment Ohridski” Sofia, Bulgaria Valentin Toma MedFuture Research Center for Advanced Medicine “Iuliu Hațieganu” University of Medicine and Pharmacy Cluj-Napoca, Romania Francois Vernay Laboratoire PROMES CNRS UPR8521 Université de Perpignan Via Domitia Rambla de la Thermodynamique Tecnosud, Perpignan, France

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1

1 An Introduction to Magnetic Nanoparticles From Bulk to Nanoscale Magnetism and Their Applicative Potential in Human Health and Medicine Costica Caizer1, Shital Bonde2, and Mahendra Rai2 1

Physics Faculty, Department of Physics, West University of Timisoara, Timisoara, Romania UGC – Basic Science Research Faculty, Department of Biotechnology, SGB Amravati University, Amravati, Maharashtra, India

2

1.1

Magnetism of Nanoparticles: From Bulk to Nanoscale

1.1.1 Introduction The bulk magnetic material has specific magnetic properties depending on the type of magnetic material and the form of magnetic ordering (Smit and Wijin 1961; Kneller 1962; Jacobs and Bean 1963; Vonsovskii 1974; Kojima 1982; Rosensweig 1985; Cullity and Graham 2009). Magnetic materials can be diamagnetic, paramagnetic, and with ordered forms of magnetism. The magnetic ordered materials can be ferromagnetic, antiferomagnetic, ferimagnetic, and some more complex magnetic structures. Diamagnetic materials show a very weak magnetization (M) induced by the application of the external magnetic field (H) (Figure 1.1a-(I)), in the opposite direction to the magnetic field (Figure 1.1b-(I)), due to the phenomenon of electromagnetic induction (Faraday) that modifies the orbital and spin motion of atomic electrons. In the absence of the magnetic field, this material has no atomic (or molecular) magnetic moment. The paramagnetic materials show a weak magnetization in an external magnetic field (Figure 1.1a-(II)), but in the same direction of the applied magnetic field (Figure 1.1b(II)), as a result of the reorientation of the permanent atomic magnetic moments in the magnetic field. This material has, at molecular level, permanent magnetic moments (in the absence of the external magnetic field), which does not interact magnetically with each other. In the case of ferromagnetic materials, an intense magnetization is obtained in the presence of the external magnetic field (Figure 1.1a-(III)), in the same direction with the applied magnetic field (Figure 1.1b-(III)), due to the existence of ordered (aligned) atomic (or molecular) magnetic moments under the action of exchange forces (exchange interaction) existing at the molecular level of a quantum nature. In the ferromagnetic crystal, the atoms with spin magnetic moment (the orbital magnetic moment being frozen by the presence of the crystalline electric field) are located at small distances between them, thus, generating the exchange interaction that aligns the spin magnetic moments over large spatial atomic distances, which can reach up to tens of microns (μm) (magnetic domains)

Magnetic Nanoparticles in Human Health and Medicine: Current Medical Applications and Alternative Therapy of Cancer, First Edition. Costica Caizer and Mahendra Rai. © 2022 John Wiley & Sons Ltd. Published 2022 by John Wiley & Sons Ltd.

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1 An Introduction to Magnetic Nanoparticles

(a)

(b) H

M

(III)

X >> 0 M

(II)

(III)

H X>0 M

H (I)

(II)

H X 0)

102 – 105 (χ 0)

1.1 Magnetism of Nanoparticles: From Bulk to Nanoscale

Mixed Fe(B)–O layer

O

Fe(A)3+

Fe(B)2.5+

[001] [010]

Figure 1.2 Fe3O4 bulk unit cell (inverse spinel structure). Source: Parkinson et al. (2012). CC BY 3.0.

superparamagnetic materials. This name was introduced by Bean (Bean and Livingston 1959) in order to distinguish this material from the bulk basic magnetic ones: paramagnetic and ferromagnetic/ferrimagnetic. This is because the material itself is ordered magnetically, ferro- or ferrimagnetic, but behaves in the external magnetic field like a paramagnetic material. This name was introduced considering that, at the microstructural level, we do not have individual atoms with magnetic moment isolated from each other, as in the case of paramagnetics, but a magnetic structure (magnetic domain) that contains a very large number of atoms with magnetic moments (even more greater than 105) coupled to each other (with magnetic ordering) as a result of the exchange or superexchange interaction. Superparamagnetic behavior is characteristic of magnetic materials with small sizes in the nanometers range, depending on the nature of the material. In biomedical applications, the most used materials are those with magnetic ordering of ferrimagnetic or even ferromagnetic type because they present an intense magnetism and fast response to an external magnetic field. However, the most used in applications and much studied today in research for various applications are materials based on iron oxides (ferrimagnetic) (Smit and Wijin 1961) with the magnetite (Fe3O4) typical representative (Figure 1.2). Magnetite is an inverse spinel (Fe2+ Fe23+O42−) with a cubic structure in which the magnetic cations of Fe2+ and Fe3+ are found in two magnetic subllatices A (tetrahedral) and B (octahedral) having opposite magnetizations: Fe3+ [Fe2+ Fe3+] O42, where the right parenthesis represents the ions from the sublatice B and Fe3+, from outside, the parenthesis represents the ions from the sublatice A. However, recent experiments (Garcia and Subias 2004) have shown a difference in the electric charge of Fe(B) ions, where Fe2.5+ is present, as shown in Figure 1.2 (Parkinson et al. 2012). The basic magnetic aspects of bulk magnetic material, ferromagnetic, or ferrimagnetic, and how they change in the case of nanomaterial, will be presented below considering the magnetic particles/nanoparticles for biomedical applications.

1.1.2 The Atomic Magnetic Moment, Magnetization, and Magnetic Moment of the Nanoparticle In the case of a bulk paramagnetic, ferro-, or ferrimagnetic material, the magnetism is due to the existence of the magnetic moment (total) at the atomic (or ionic/molecular) level (Kneller 1962; Jacobs and Bean 1963; Vonsovskii 1974; Caizer 2004a): μJ = gJ mJ μB

11

3

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1 An Introduction to Magnetic Nanoparticles

as a result of the spin–orbit coupling (vector summation of the spin magnetic moments (total) ( μ S) and the orbital magnetic moments (total) ( μ L ): the vector model of the atom ( μ J = μ L + μ S ). In Eq. (1.1), gJ is the spectroscopic splitting factor (Lande factor) at the atomic level, gJ = 1 +

J J + 1 + S S + 1 −L L + 1 2J J + 1

12

mJ is the internal magnetic quantum number (total), which can take (2J + 1) values (according to quantum physics, respectively –J, …, 0, …, +J), and μB is the Bohr magnetone: μB =

e 2m0

13

with the observables: e is the electron charge (e = 1.6 × 10−19 C), m0 is the resting electron mass (m0 = 9.1 × 10−31 kg), and h is the Planck constant (h = 6.63 × 10−34 Js). In Eq. (1.2), L is the internal orbital quantum number (total), and S is the internal spin quantum number. Macroscopically, the quantity that characterizes the bulk magnetic material, from a magnetic point of view, is the magnetization (M), defined as a numerical quantity equal to the resulting magn

netic moment ( i

μ i, μ i being the total magnetic moment of the atom/ion (Eq. 1.1), and i the num-

ber of atoms/ions in volume V) of the volume unit (Caizer 2004a), Δ M = lim ΔV

n i

0

μi

ΔV

=

dμ dV

14

respectively, in the hypothesis of a continuous environment. According to formula (1.4), the magnetization vector M has the same direction and sense as the elementary magnetic moment vector d μ . In accordance with Eq. (1.4), the magnetic moment of a volume of magnetic material will be μ=

MdV

15

In the case of reducing the volume of ferrous- or ferrimagnetic material in the nanometer range (nm – tens of nm), as in the case of magnetic nanoparticles, when there is a single magnetic domain (Weiss domain) (or in the case of a nanoparticle volume even smaller than the one corresponding to a magnetic domain), the magnetization (M) is uniform in the finite volume of material. Thus, in this case, of the single-domain magnetic nanoparticle, the resulting magnetic moment can be written as (Caizer 2016) μ = MV

16

or by using the common notations (Caizer 2019) mNP = V NP M s

17

where mNP is the magnetic moment of the nanoparticle, VNP the volume of the nanoparticle, and Ms the spontaneous magnetization of the magnetic material (the magnetization of a magnetic domain [M] corresponds to the spontaneous magnetization [or saturation]) (Ms) (M ≡ Ms). When the nanoparticle is spherically approximated, formula (1.7) is written as mNP =

πD3 Ms 6

18

1.1 Magnetism of Nanoparticles: From Bulk to Nanoscale

(a)

(b) M

V

e.m.a mNP

du dV

VNP Ms

Multidomain magnetic structure

D

Figure 1.3 (a) Representation of the magnetization vectors (M) and elementary magnet moment (d μ ) for an elementary volume dV of the bulk magnetic material of finite volume V, and an example of multidomain magnetic structures (in magnified image). Source: Caizer (2016). Reprinted by permission from Springer Nature; (b) Spherical nanoparticle for uniaxial crystalline symmetry; e.m.a. is the easy magnetization axis. Source: Caizer et al. (2020). Reprinted by permission from Springer Nature.

where D is the diameter of the nanoparticle, an approximation widely used both in theoretical calculations and in practical applications. From a magnetic point of view, it is important if the nanoparticle is spherical or has another shape, e.g. ellipsoidal, as the magnetic behavior in the external magnetic field may change a lot, especially due to soft magnetic materials case (see Section 1.1.5). To conclude, it can be said that, from a magnetic point of view, in the case of bulk magnetic material, the base observable for the magnetic characterization is the magnetization given by relationship (1.4) or the elementary magnetic moment du, where the magnetization is nonuniform (Figure 1.3a), whose field and space dependence must be known for the calculation of the integral. In the case of magnetic nanoparticles (Figure 1.3b), the aspects are simplified, these being characterized by the magnetic moment of the nanoparticles given by Eq. (1.7) (or Eq. (1.8) for spherical nanoparticles), where Ms is the spontaneous magnetization of the nanoparticle material which is a known observable (Ms is a material parameter), and VNP is the effective volume of the nanoparticle. VNP and in most theoretical or practical cases can be easily approximated by the volume of a sphere, ellipsoid of revolute or flattened, cylinder, etc., which radically simplifies the calculations. However, for this reason, the exact given situation will have to be taken into account, in order not to introduce errors.

1.1.3 Magnetic Structures The bulk ferromagnetic magnetic material consists of magnetic domains (Kneller 1962) spontaneously magnetized to saturation, resulting from the balance of exchange forces, which tend to align the atomic (ionic) magnetic moments in the network, and magnetostatic forces, which, through the created magnetic poles, tend to disorient the magnetic moments from their parallel alignment. The magnetic structure is stable when there is a balance between the exchange and magnetostatic forces, respectively, in the condition of minimum magnetocrystalline energy. Experimentally, different structures of magnetic domains were observed, the most common being those with free magnetic poles (Figure 1.4a) and magnetic structures without free magnetic poles

5

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1 An Introduction to Magnetic Nanoparticles

(a)

(b)

MS

Figure 1.4 Magnetic structures of nanoparticles: multidomain nanoparticles with (a) uniaxial and (b) cubic symmetry. Source: Caizer et al. (2017). Reprinted by permission from Springer Nature.

(with magnetic flux closing domains) (Figure 1.4b). The first magnetic structure is characteristic of uniaxial crystals and the second magnetic structure is characteristic of the magnetic crystals with cubic symmetry. The magnetic domains are separated from each other by narrow regions in the crystal (transition) called walls of magnetic domains. Within the walls is a continuous change in orientation of spins, from the direction of magnetization in one domain to the direction of magnetization in the neighboring domain. The most common walls found in magnetic structures are the Bloch-type walls (Bloch 1930) or 180 walls, which separate 2 neighboring domains with opposite magnetizations. They are also the most stable in magnetic structures. But there are also Nèel or 90’s walls, which separate adjacent domains, where the magnetizations in the domains are oriented at 90 . Nèel-type walls are generally unstable. The magnetic domains are magnetized uniformly (at saturation), characterized by the spontaneous magnetization of Ms. In the closing domains, the spontaneous magnetization is oriented at 45 in relation to the direction of separation of the domains (Figure 1.4b) so that the normal component of the magnetization is continuous along the boundaries separating the domains, and, thus, no magnetostatic energy will occur. The thickness of the domain walls is generally less than 105 A, and that of the walls in the range 10–103 A, strongly depending on the anisotropy of the material and the exchange forces. When the volume of the magnetic material is reduced in the nanometer range, the magnetic structure changes radically, reaching a unidominal structure, under a certain critical volume (Vcr) (Kittel 1946). Schematically, this aspect is shown in Figure 1.5, in the case of the spherical nanoparticle (Caizer 2004a). Above the critical volume (V > Vcr), the nanoparticle has an incipient structure of magnetic domains, which depending on the crystalline symmetry of the material, can be of the form: (a) case of uniaxial symmetry or (b) case of cubic symmetry. Using the classic model of the single-domain particle, it can estimate the critical diameter Dc (or the critical volume Vcr) at which the transition from the state with the structure of magnetic domains (multidomains) to the one with the single-domain structure takes place. Thus, for the critical diameter, the following formula is obtained: Dc =

18εP μ0 M 2s

19

where εP is the energy density of the domain wall, μ0 is the magnetic permeability of the vacuum (μ0 = 4π × 10−7 H m−1), and Ms the spontaneous magnetization of the material.

1.1 Magnetism of Nanoparticles: From Bulk to Nanoscale

(a)

(b)

(c)

or V > Vcr

V < Vcr

Figure 1.5 Multidomain magnetic nanoparticles with (a) uniform magnetization (uniaxial symmetry) and (b) nonuniform magnetization (cubic symmetry), and (c) single-domain nanoparticle. Source: Adapted from Caizer and Stefanescu (2003).

The energy density of the wall was determined by Landau–Lifschtz, finding the following formula: εp =

2k B T c K V a

1 10

where D is the constant in the crystalline network, TC is the Curie temperature of the magnetic material, KV is the constant magnetoscrystalline anisotropy, and KB is the Boltzmann constant. The critical diameter at which the transition from the multidomains structure to the singledomain structure takes place depending a lot on the magnetic anisotropy of the nanoparticle. For Co, the value of ~60 nm was found (…). However, in the case of Ni–Zn ferrite nanoparticles, Caizer finds a value Dc = 21.6 nm, for the energy of the domain wall εP of 0.145 erg cm−2 (Caizer 2003a). In conclusion, when conducting theoretical and practical studies on the use of nanoparticles, it is very important to know the critical diameter (Dc) under which the nanoparticle becomes one with a single-magnetic structure, for which a previous evaluation is needed.

1.1.4 Magnetic Saturation Another important aspect to consider, when a magnetic material is reduced to the nanoscale, is the saturation magnetization of the material, which is influenced by such reduction. In the case of bulk magnetic material, the saturation magnetization (Msat) (theoretically obtained in intense magnetic field and at low temperatures) is equal to the spontaneous magnetization (Ms), being a known parameter of material. Example, in the case of Fe, the saturation magnetization at room temperature is 1714 kA m−1 (Cullity and Graham 2009), and in the case of Fe3O4, it is 477.5 kA m−1 (Smit and Wijin 1961). The spontaneous magnetization of the bulk magnetic material decreases with temperature, having the maximum value at 0 K (Ms(0)) and zero at a temperature, generally high (hundreds of degrees), which is Curie temperature in the case of ferromagnetics and Nèel temperature in the case of ferrimagnetic materials. The temperature variation of the spontaneous magnetization of massive ferromagnetic material, such as Fe, Co, and Ni (Figure 1.6a), is a universal function that does not involve indeterminate constants: Ms T T =f Ms 0 TC

1 11

7

1 An Introduction to Magnetic Nanoparticles

σs σ0

(a) 1.0

0.8

J=1 2

J=1 0.6

Classical, J=∞ Fe Co, Ni

0.4

0.2

0 0

(b)

0.2

0.4

0.6

0.8

1.0

T/Tc

23 22 Experiment 21

Theory

(β) 20 Msat × 10–3 (A m−1)

8

19 18 17 16

(α)

15 14 13 50

100

150

200

250

300

T (K)

Figure 1.6 (a) Relative saturation magnetization of iron, cobalt, and nickel as a function of relative temperature. Calculated curves are shown for three values of J. Source: Cullity and Graham (2009). Reproduced with permission from John Wiley & Sons; (b) Curves that represent the dependence of the saturation magnetization on temperature according to Eq. (1.12) (curve α) and Eqs. (1.13) and (1.14) (curve β); experimental curve (□). Source: Caizer (2005a). Reproduced with permission from Springer Nature.

1.1 Magnetism of Nanoparticles: From Bulk to Nanoscale

At low temperatures, this variation is well described by Bloch’s law (law in T3/2 (Bloch 1930), deduced from the spin wave model, M s T = M s 0 1 − BT 3

2

1 12

which is the exact solution of the Hamiltonian Heisemberg at low temperatures. In Eq. (1.12), B is a constant whose value depends on the exchange integral. This dependence is well verified experimentally both for bulk ferromagnetic materials (Fe, Ni) (Aldred and Frohle 1972; Aldred 1975) and for some bulk spinel ferrites, such as MnxFe3 − xO4 ferrite for 0.2 < x < 1.0 (Dillon 1962). However, when the magnetic material has nanometric sizes, such as nanoparticles, some theoretical calculations and some experimental results have shown that the temperature exponent is greater than the value 3/2, corresponding to the bulk material (Hendriksen et al. 1992, 1993; Linderoth et al. 1993). Thus, Morais et al. (2000) showed that, depending on the temperature of the saturation magnetization in the range 4.2–293 K, in the case of a ferrofluid with NiFe2O4 nanoparticles having an average diameter of 11.1 nm, it deviates from the law corresponding to the bulk material. In the case of magnetite (Fe3O4) nanoparticles coated with oleic acid, Caizer (2003b) shows that the law is well verified for T2 instead of T3/2, and the constant of Ms(0) in Eq. (1.12) becomes in this case a function of temperature: M sat T = F T 1 − BT 2

1 13

However, in the case of Mn0.6Fe2.4O4 nanoparticles coated with oleic acid (Caizer 2005a), it is found that is verified in the law of Eq. (1.12), but Ms(0) is no longer a constant but is temperature-dependent according to the formula: F T = Ms 0

πn 6

4

cT i=0 i

2i

1 14

In this equation, n is the concentration of the nanoparticles, and ci are constants whose value is known, resulting from the fitting of the experimental data. In Figure 1.6b is shown the dependence on Msat − T in this case, where the deviation is highlighted: (α) is the curve for bulk and (β) is the curve for nanoparticles. These results as well as others (Caizer 2002) show that T3/2 valid in the case of bulk magnetic material is no longer verified in the case of magnetic nanoparticles, and there are different interpretations for this. Another important aspect in the case of nanoparticles is the fact that the saturation magnetization measured experimentally at room temperature is lower than that corresponding to the same bulk magnetic material (Berkowitz et al. 1975; Zhang et al. 1997; Kodama 1999; Caizer and Stefanescu 2002; Caizer 2003b). It has also been found experimentally that the decrease in saturation magnetization is all the more pronounced the smaller the nanoparticles, a few nm. In Figure 1.7 is shown the dependency of saturation magnetization as a function of the average nanoparticle diameter in the case of Ni0.35Zn0.65Fe2O4 nanoparticles (Caizer and Stefanescu 2002). Also, a similar dependency is shown in Figure 1.12b for the magnetic moment of the nanoparticles (Wu et al. 2017). In Ref. (Caizer 2016) is presented in more detail the aspects that lead to the decrease of the saturation magnetization of the nanoparticles, considering the core-shell model in which there is a layer on the surface of the nanoparticles where the magnetic moments are no longer aligned as in the ordered magnetic core. As a result, in the case of nanoparticles, a magnetic diameter (Dm) determined by the nanoparticle core in which the spins are magnetically aligned must be

9

1 An Introduction to Magnetic Nanoparticles

(a)

(b)

70 60

σs (emu g–1)

10

D

Dm

η

0

50 40 30 20

10

20

30

40

50

(311) (nm)

Figure 1.7 (a) Specific saturation magnetization as a function of the mean diameter of nanocrystallites. Source: Caizer and Stefanescu (2002). Reprinted by permission from IOP Publishing. (b) Core-shell pattern of the spherical nanoparticle. Source: Caizer (2016). Springer Nature.

considered, which is generally smaller than the physical diameter (D) of the nanoparticles: Dm < D. Difference (D − Dm) becomes even more pronounced in the case of ferrimagnetic nanoparticles (Berkowitz et al. 1975, 1980; Kodama et al. 1996), surfactated (Caizer 2002) or in SiO2 matrix, this reaching even up to 2–3 nm (Caizer et al. 2003; Caizer 2008). To conclude, if in the case of bulk magnetic material, the saturation magnetization is a welldefined value, being a material parameter, characteristic of the substance type, in the case of nanoparticles it is generally smaller, and decreases with the decrease in diameter to nanometers size. This is a very important aspect that must be taken into account in biomedical applications. Thus, in order not to introduce errors in the application of magnetic nanoparticles, it is recommended, before conducting any experiment, to determine/measure the saturation magnetization of the nanoparticles, and also the variation of saturation magnetization with temperature, if there is such a dependency in the targeted application.

1.1.5

Magnetic Anisotropy

Experimentally, it was found that in the case of ferro- or ferrimagnetic crystalline materials, there is a dependence of the magnetization of the single crystal on the crystallographic directions. The dependence of the magnetization of the crystalline magnetic material on the crystallographic axes determines the magnetocrystalline anisotropy (Kneller 1962; Caizer 2004a, 2019). Thus, the magnetization curves that are obtained in the same external magnetic field depend on the direction in which the crystalline material is magnetized. This type of magnetic anisotropy is characteristic of all bulk single crystalline (ferro- or ferromagnetic) magnetic materials (Fe, Co, Ni, Cd, their alloys, Fe oxides [Fe3O4, γ-Fe2O3], etc.). For example, in the case of the Ni bulk single crystal ferromagnetic material, which crystallizes in the cube system with centered volume (vcc), the magnetization curves have the shape shown in Figure 1.8 (Baberschke 2001). Thus, the magnetization is made easiest following the crystallographic direction [1,1,1], which represents the large diagonal of the cube, and its magnetization is made the hardest following the crystallographic direction [1,0,0], which is the edge of the cube.

1.1 Magnetism of Nanoparticles: From Bulk to Nanoscale

(a)

(b) [111] [111]

e.m.a 500

M (G)

[110] Ni vcc

[111]

300 [100]

[100]

μL ≈ 0.1 G

h.m.a Ni (vcc)

[100]

100 Ni 0

0

100

200

300

H (G)

Figure 1.8 (a) The crystallographic systems for Ni-single crystal. Source: Caizer (2016). Reprinted by permission from Springer Nature; (b) Room temperature magnetization curves for Ni along the easy ([111]) and hard ([100]) direction. Source: Based on Wijn (1986).

The direction [1,1,1] in this case is called the direction or axis of easy magnetization (e.m.a.), and the direction [1,0,0] is called the axis of hard magnetization (h.m.a). In the case of bulk ferromagnetic monocrystalline material with cubic symmetry, the energy of magnetocrystalline anisotropy can be determined with the following formula:

[0001] e.m.a.

φ

Ms

wk,c = K 1 α21 α22 + α21 α23 + α22 α23 + K 2 α21 α22 α23 + K 3 α41 α42 + α41 α43 + α42 α43 + …

1 15 written as a series development of powers using the model proposed by Beker, Doring, Akulov, Mason (Kneller 1962; Herpin 1968), based on [1010] h.m.a the symmetry properties of the crystal. In general, it was found that it is Co (hexagonal) sufficient to use only the first two terms of development, in K1 and K2. In Eq. (1.15), K1 and K2 are the magnetocystalline anisotopy constants, Figure 1.9 The and α1, α2 and α3 are the cosine directors of the vector of spontaneous crystallographic systems for magnetization (Ms) in relation to the main crystallographic axes of the Co-single crystal. Source: Caizer (2016). Reprinted by cube. In some cases, even the first term of development is sufficient. permission from Springer For example, in the case of the ferromagnetic Fe single crystal, Nature. 4 −3 3 −3 K1 = 4.8 × 10 J m and K2 = 5 × 10 J m were found, where K1 is in this case with approximately one order of magnitude larger than K2. In the case of uniaxial, hexagonal symmetry, as in the case of the ferromagnetic Co monocrystalline (Figure 1.9), the magnetocrystalline anisotropy energy is expressed as a function of the angle fi between the spontaneous magnetization vector Ms and the main axis of symmetry: Єk,u = K 1 sin 2 φ + K 2 sin 4 φ + K 3 sin 6 φ + …

1 16

11

12

1 An Introduction to Magnetic Nanoparticles

Also, in this case, the first two terms are used (in K1 and K2) in the energy expression of uniaxial magnetocrystalline anisotropy. In this case, the main axis of symmetry is the easy magnetization axis (e.m.a), and the direction perpendicular to it is the hard magnetization axis (h.m.a). In the case of bulk magnetic material, there is another important form of magnetic anisotropy, which should not be neglected as it can become dominant in some cases. This is the anisotropy of the shape (Kneller 1962; Caizer 2004a), which shows that the magnetization of a sample depends on its shape. As a general case, approximating the shape of the sample by the ellipsoid of revolution: a > b = c, where a, b, and c are the semiaxes of the ellipsoid (Figure 1.10), the anisotropy energy due to the shape of the sample is expressed by the following formula: Єsh = 1 2 μ0 M 2s N b − N a sin 2 θ

a MS αa

θ αb

αc

c

b

1 17

where Na and Nb are the demagnetization factors along the a Figure 1.10 The crystal and b directions of the ellipsoid, and θ is the angle that the approximated by an ellipsoid spontaneous magnetization vector Ms makes with the main axis (general case). Source: Caizer (2019). Reprinted by permission (a) of the ellipsoid. of Taylor & Francis Ltd. When the magnetization of the ellipsoid in the external magnetic field is done along the direction of the a-axis, the shape anisotropy energy is minimum (or zero). In contrast, when magnetization is done along a direction perpendicular to the a-axis (e.g. the b, c, or other directions), the shape anisotropy energy is maximum. In the latter case, taking into account the Eqs (1.17) and (1.16), the shape anisotropy constant can be expressed by the following formula: K sh = 1 2 μ0 M 2s N b − N a

1 18

in the approximation of the first order. When the magnetic material is reduced to the nanoscale, these forms of magnetic anisotropy remain valid. In addition, in the case of magnetic nanoparticles, the shape anisotropy becomes very important, reaching in some cases even larger, or much larger than the magnetocrystalline anisotropy. Thus, the neglect of this first aspect leads to important errors from a magnetic point of view, incompatible with the physical reality. For example, if the nanoparticle is spherical in shape (Figure 1.5), the semiaxes a, b, c become equal (Figure 1.10), and equal to the radius of the sphere. According to Eqs. (1.18) and (1.17), the shape anisotropy constant in this case is zero, as is the energy. So there is no shape anisotropy in the case of spherical nanoparticles. In contrast, in the case of elongated nanoparticles, when a b = c, and when they are soft magnetic (magnetocrystalline anisotropy is reduced), the shape anisotropy exceeds the magnetocrystalline anisotropy, or even becomes dominant. This is an important aspect in the case of magnetic nanoparticles that must be taken into account not only in practical applications, including biomedical ones, but also in theoretical calculations and models/experiments. Moreover, in the case of nanoparticles, generally in the field of nanometers, when the volume-tosurface ratio of spherical nanoparticles increases: S/V ~ 1/D, D is the diameter of the nanoparticle, a new form of anisotopy appears which must be taken into account, namely: surface anisotropy (Caizer 2019). This is because in the case of small and very small nanoparticles, and for soft magnetic materials such as ferrites (e.g. Fe3O4, γ-Fe2O3, Ni–ZnFe2O4, MnFe2O4), this form of anisotropy

1.1 Magnetism of Nanoparticles: From Bulk to Nanoscale

becomes dominant, sometimes much more larger than the magnetocrystalline (Caizer 2004b). This form of anisotropy results from the surface effects that occur in the case of small nanoparticles where the surface spines have an important contribution, the symmetry of the bonds with the nearest neighbors being different from that inside the core of nanoparticle. These aspects were first highlighted by Néel (1954) who showed that in the case of crystals with cubic symmetries and for surfaces of type (111) or (100) the surface anisotropy energy can be written as follows: Єs = K s cos 2 β

1 19

z

(100) n

β y

0 x

Ms

Figure 1.11 The orientation of spontaneous magnetization M s relative to normal n on the surface (a) (100) for the monocrystal with cubic symmetry. Source: Caizer (2019). Reprinted by permission of Taylor & Francis Ltd.

where B is the angle that the spontaneous magnetization vector Ms makes with the direction of the external normal to the considered surface (Figure 1.11), and Ks is the surface anisotropy constant (expressed in J m−2). For example (Caizer 2004a), in the case of spherical nanoparticles with a diameter D of 10 nm, the value of ~6 × 103 expressed in J m−3 is obtained for the surface anisotropy constant. This value is five times higher than the magnetocrystalline anisotropy of the Ni–Zn ferrite, which is 1.5 × 103 J m−3 (Broese Van Groenou et al. 1967). Therefore, this form of magnetic anisotropy must be considered in the case of magnetic nanoparticles. Moreover, in the process of abstaining from nanoparticles, as a result of physico-chemical methods of preparation, or when the nanoparticles are surfacted or embedded in different solid matrices, elastic stresses can occur which induces an additional magnetic anisotropy (stress anisotropy) compared to those above. And this anisotropy, in the case of nanoparticles, can become large or high compared to magnetocrystalline anisotropy, and it must be taken into account when it appears. Example Coey (Coey and Khalafalla 1972) obtains a value of 1.2 × 105 J m−3 for nanoparticles of 6.5 nm in diameter and Vassiliou et al. (1993) obtains the value of the anisotropy constant of 4.4 × 105 J m−3, values that are approximately twice higher in magnitude than the magnetocrystalline anisotropy constant of the α-Fe2O3 massive ferrite (K1 = 4.6 × 103 J m−3). To conclude, in the case of magnetic nanoparticles, a magnetic anisotropy determined by magnetocrystalline anisotropy, shape anisotropy, surface anisotropy, and induced anisotropy must be considered: Єma = Єk + Єsh + Єs + Єi

1 20

and an effective magnetic anisotropy constant K eff = K k + K sh + K s + K i

1 21

respectively. Typically, in the case of magnetic nanoparticles, this effective anisotropy constant increases when the magnetic nanoparticles become smaller, generally below 15–20 nm, depending on the nature of the material (Figure 1.12). The Figure 1.12b also shows the variation of the saturation magnetization (see Section 1.1.4) when the diameter of the nanoparticles decreases, this becoming smaller when the size of the nanoparticles decreases.

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1 An Introduction to Magnetic Nanoparticles

(b) 5

× 105 Ms

Msb

Core

Keff

× 104 8

4

6

3

4

2

2

Keff (J m−3)

(a)

Ms J (m−3 T)−1

14

Kb

Shell 1 0

10

20

30

40

0 50

D (nm)

Figure 1.12 (a) Schematic view of the general spin canting geometry (the core@shell model). (b) Theoretical Ms (blue solid line) and Keff (orange solid line) versus magnetite nanoparticle diameter D at 300 K. Horizontal dashed–dotted lines exhibit Msb and Kb, respectively. Theoretical data are compared with experimental ones. Blue diamonds from Abbas et al. (2013), blue hexagons from Goya et al. (2003), orange triangle from Guardia et al. (2007), orange squares from Vargas et al. (2008), orange pentagon from Ferguson et al. (2011), and orange circle from Park et al. (2004). Note: 1 J (m−3T)−1 = 1 A m−1. Source: Wu et al. (2017). Reprinted by permission of IOP Publishing.

(a)

(b) FM core

AFM shell 1 nm

Figure 1.13 (a) Schematic drawing of a core-shell structure and (b) transmission electron microscopy (TEM) image of an oxidized Co particle. Source: Reprinted from Nogues et al. (2005), with permission from Elsevier.

Moreover, in the case of magnetic core-shell nanoparticles, the presence of a unidirectional anisotropy (Nogues et al. 2005; Caizer 2019) has recently been highlighted as a result of the coupling between neighboring layers (surface-layer core) with different magnetic orders of magnetic moments in the network: ferromagnetic core (FM) and antiferomagnetic shell (AFM) (Figure 1.12). Also, in Ref. (Berkowitz and Kodama 2006) a review of the unidirectional (exchange) anisotropy for different FM-AFM nanostructures may be found. In the case of CoFe2O4/NiO ferrimagnetic/antiferromagnetic nanocomposites, a similar behavior was found (Peddis et al. 2009) (Figure 1.13). Such situations may occur frequently in the case of different more complex magnetic nanostructures which are currently developed in nanotechnology and bionanotechnology for various applications.

1.1 Magnetism of Nanoparticles: From Bulk to Nanoscale

(b)

Magnetization M Ms Mr

Magnetic saturation (M )

–Hei

H Applied field

Soft magnet

Magnetic saturation (M ) Hard magnet

A

Magnetization (M)

Hsat

Magnetization (M)

(a)

B Coercivity (Hz)

Coercivity (Hz)

2000 M = 1714

M (emu cm−3)

B

External magnetic field (H)

External magnetic field (H)

(c)

A

Fe Co

1500 1422 1000 500

Ni

484

H

0

Figure 1.14 (a) Typical hysteresis loop for ferromagnetic materials. Source: Reprinted from Sung and Rudowicz (2003), with permission of Elsevier. (b) A typical hysteresis loop such as that obtained for soft and hard ferromagnetic materials. Source: Mody et al. (2013). Reproduced with permission from Walter de Gruyter GmbH; (c) Magnetization curves of iron, cobalt, and nickel at room temperature (H-axis schematic). The SI values for saturation magnetization in A m−1 are 103 times the cgs values in emu cm−3. Source: Cullity and Graham (2009). Reproduced with permission from John Wiley & Sons.

1.1.6 Magnetic Behavior in External Magnetic Field The magnetization of the bulk magnetic material in the external magnetic field (Cullity and Graham 2009), between two maximum values corresponding to the magnetic saturation, is generally with hysteresis (Figure 1.14a and b), due to the existence of a phase shift between the magnetization of a material and the applied magnetic field. Magnetization of the magnetic material, represented by the type of magnetization curve in Figure 1.14c, takes place both by processes of displacement of the walls of the magnetic domain (in low fields) and by processes of rotations of spontaneous magnetization (in high fields and near saturation), processes that are both reversible and irreversible. The basic macroscopic magnetic quantities characteristic of the hysteresis cycle, which are determined experimentally, are the saturation magnetization (Msat), the remanent magnetization (Mr), the rectangular ratio, r = Mr/Msat, and the coercive field (Hc) (Figure 1.14a). Depending on their applications, certain values and different shapes of the hysteresis curve are targeted. For example in the case of use of magnetic materials in high-frequency fields, those materials are used that have the hysteresis cycle as narrow as possible with Hc and r as small as possible, close to 0 (preferably r < 0.1) (Figure 1.14b curve (2)); and in the case of applications for memory information, there magnetic materials are used that have the hysteresis cycle as rectangular as possible, with Hc and r as large as possible, theoretically close to the value 1 (preferably r > 0.9) (Figure 1.14b curve (3)), compared to the general case (curve (1)). For magnetization of the bulk magnetic material in the external field (Figure 1.14c), there is no universal function, the magnetization curve being specific to each material time. Only in low and high fields, there are mathematical functions that describe well the magnetization obtained experimentally. Thus, in low magnetic fields (lower than the coercive field of the material [~Hc/ 10]), magnetization is well described by Rayleigh’s law M = M + χi H − H ±

α H −H 2

2

1 22

15

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1 An Introduction to Magnetic Nanoparticles

where M is the magnetization obtained when applying the field H , χ i the initial magnetic susceptibility, and alpha a coefficient. The ± sign corresponds to the case when H > H (+) and H < H (−), respectively. In intense magnetic fields, close to saturation, magnetization is well described by the experimentally established Weiss–Forer law: M = Ms 1 −

a b c − − H H2 H3

+ χ0H

1 23

where a, b, and c are some coefficients. The last term (χ0H) is determined by the contribution of χ0, independent of the magnetic field H. This term becomes more important when the material is brought to a temperature close to the Curie temperature. However, in the case of magnetic nanoparticles, the magnetization can significantly change, depending on the nanoparticle system considered. Typically, hysteresis is absent in the case of small nanoparticles, the coercive field (Hc), and the remanent magnetization (Mr) becoming zero. In Figure 1.15. shows (□) the experimental and (-) theoretical curves calculated with the Langevin function (Jacobs and Bean 1963) for ferrimagnetic nanoparticles of Zn0.15Ni0.85Fe2O4 having mean magnetic diameter of 8.9 nm dispersed in amorphous silica matrix (SiO2) with volume fraction of 0.15 (magnetic nanocomposites) (Caizer et al. 2003; Caizer 2008). Magnetization (Figure 1.15.b) in this case follows a Langevin type function as in the case of paramagnetic atoms (Caizer 2004a): M = Nμ coth α −

1 α

1 24

where (coth α − 1/α) is the Langevin function and α=

μ0 μH kB T

1 25

In Eqs. (1.24) an (1.25), the observables are the following: N is the number of atoms and μ is magnetic moment of atom. In low fields, the magnetization varies linearly with the magnetic field (Figure 1.16a): M=

μ0 Nμ2 H 3k B T

1 26

whereas in high fields close to saturation, the magnetization is described by the following relationship: M

Nμ = M ∞

1 27

where M∞ is the saturation magnetization (theoretically, in the infinite magnetic field). In Figure 1.16a and b, these cases are given for Fe3O4 nanoparticles covered with oleic acid and dispersed in kerosene (magnetic ferrofluid with a magnetic packing fraction of 0.024) having an average magnetic diameter of 11.8 nm. Figure 1.16b shows the dependence M = f(1/H), which is a linear function with a negative slope near the magnetic saturation (M∞). This magnetic behavior in the external field, totally different from the bulk magnetic material (ferro- or ferrimagnetic), results from the existence of the superparamagnetism phenomenon, evidenced by Nèel and introduced by Bean in the case of nanoparticles. Nèel shows that the magnetic moment of the nanoparticle (mNP) can be reversed at 180 along the easy magnetization axis due to thermal activation (at a temperature), in the absence of the external magnetic field (Figure 1.16c). This behavior is similar to paramagnetic atoms, whose magnetic moments are oriented at a temperature in all directions.

1.1 Magnetism of Nanoparticles: From Bulk to Nanoscale

(a) 8 Experiment

6

Fit

M (kA m–1)

4 2 0 –2 –4

(S1)

–6 –8 –200

–150

–100

–50

0

50

100

150

200

H (kA m–1)

(b)

1.0

0.8

M/M∞

0.6

0.4

0.2

Experimental points Theoretical curve

0.0 0

50

100 H (kA

150

200

250

m–1)

Figure 1.15 (a) M versus H for (Zn0.15Ni0.85Fe2O4)0.15/(SiO2)0.85 sample. Source: Reprinted from Caizer et al. (2003), with permission of Elsevier; (b) Reduced magnetization curve of the (Zn0.15Ni0.85Fe2O4)0.15/(SiO2)0.85 nanocomposite registered at room temperature and 50 Hz frequency of the magnetization field (H). Source: Reprinted from Caizer (2008), with permission of Elsevier.

However, in the case of nanoparticles, there is an essential difference, namely that they are not dealing with individual atoms but with nanoparticles containing a multitude of magnetically aligned atoms, characterized by the magnetic moments (resulting) mp instead of the atomic magnetic moment (see Section 1.1.2). Formally, these systems behave the same; quantitatively the aspects being different, instead of atoms, there are nanoparticles. In the case of larger nanoparticles, tens of nm, the magnetic behavior in the external magnetic field is similar to that of bulk magnetic material, namely creating a narrow hysteresis, determined

17

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1 An Introduction to Magnetic Nanoparticles

mainly by the presence of a structure of incipient magnetic domains, or increased magnetic anisotropy in the case of nanoparticles that are still unidominal, as is discussed in the next paragraph.

1.1.7

Magnetic Relaxation in Nanoparticles – Superparamagnetism

When the size of nanoparticles decreases below the critical diameter (Dc), corresponding to the transition from the state of the structure with magnetic domains to the state with the single-domain structure, there is another nanoparticle-specific size, the threshold volume (Vth) (or threshold diameter [Dth]) at which the magnetization of the nanoparticle (the magnetic moment of the nanoparticle) is no longer stable, reversing at 180 , due to thermal activation (at a temperature). Thus, the magnetic moment of the nanoparticle, below the threshold diameter Vth, fluctuates along the direction of easy magnetization (Figure 1.16b) (Néel 1949). The inversion or not of the magnetic moment of the nanoparticle in the absence of the external magnetic field will depend on the barrier energy given by the uniaxial magnetic anisotropy energy (applied in the case of nanoparticles) (Caizer 2016): W V ,u = K u V sin 2 φ

1 28

where Ku is the uniaxial magnetic anisotropy, V is the magnetic volume of the nanoparticle, and φ is the angle between the magnetic moment and the easy magnetization axis. In this case, the barrier energy (KuVm) is maximum at φ = 90 (Figure 1.17a). Figure 1.17a shows the case of the Co ferrite nanoparticle with mean magnetic diameter of 10 nm and Ku = 1.6 × 105 J m−3, the energy being calculated in eV (electron-volt) (Caizer and Tura 2006). In the presence of an external magnetic field, the situation changes radically, depending on the orientation of the magnetic field and the magnetic anisotropy axes of the nanoparticle (Caizer and Tura 2006) (Figure 1.17b). The situation becomes more complex in a nanoparticles system when the uniaxial magnetic anisotropy axes are oriented in all directions (Caizer 2004b). In the absence of the magnetic field (H = 0) and for a type of material, there will be a statistical probability of the magnetic moments of the nanoparticles passing over the potential barrier, this being higher as the volume Vm of the nanoparticles will be lower and the temperature (T) higher. This process is characterized by a time called magnetic relaxation time (Nèel 1949), τN = τ0 exp

K uV kB T

1 29

where τ0 is a time constant that is generally of 10−9 (Back et al. 1998). In biomedical applications, the dispersions of magnetic nanoparticles (nanoparticles dispersed in pharmaceutical liquids) are often used for various purposes (Caizer 2010; Caizer 2017). Thus, in these cases, the magnetic nanoparticles can move freely in the liquid (due to thermal agitation) and/or under the action of an external magnetic field. Thus, in this case, besides the rotation of the magnetic moments inside the nanoparticles (Nèel magnetic relaxation) (Figure 1.18a), there will also be a rotation of the nanoparticles with its fixed magnetic moment along the easy magnetization (Figure 1.18b) (Laurent et al. 2008; Reeves and Weaver 2014). This process is Brown magnetic relaxation (Brown 1963) and is quantitatively characterized by Brown relaxation time, τB =

3ηV h kB T

where η is the viscosity coefficient and Vh is the hydrodynamic volume of nanoparticle.

1 30

(a) 7 6

M (kA m–1)

5 4 3 2 1 0 0

5

10 H (kA

15

20

m–1)

(b) 12

M∞

10

M (kA m–1)

8

6

4

2 1/H0 0 0

0.04

0.08 (1/H) ×

103

0.12

(A/m)–1

(c)

m

e.m.a.

Figure 1.16 (a) M versus H in low fields and (b) M versus 1/H in high fields. Source: Caizer (2003a). Reprinted by permission of IOP Publishing; (c) magnetic structure in single-domain nanoparticles with uniaxial anisotropy. Source: Caizer (2017). Reprinted by permission of Springer Nature.

(a)

0.7 0.6 0.5

W (eV)

0.4 0.3 0.2 0.1 0 –0.1

150 120

–0.2 90

0

60

ψ(°)

φ (°)

0

30

60 30

90

24

21 0 18 0 15 0 12 0

0

0

30

27

0

33

0

(b)

0.7 0.6 0.5

W (eV)

0.4 0.3 0.2 0.1 0 –0.1

150 120

–0.2 90 60

ψ(°)

0

60 30

90

0 24

21 0 18 0 15 0 12 0

0

0

30

27

0

33

0

30

φ (°)

(c) (z)

MS φ ψ

H

(q)

Figure 1.17 Nanoparticle energy as a function of ψ and φ angles for (a) H = 0 and (b) H = 100 kA m−1; (c) Orientation of spontaneous magnetization Ms of a nanoparticle with respect to external field H direction (q) and the easy magnetization axis (z). Source: Reprinted from Caizer and Tura (2006), with permission of Elsevier.

1.1 Magnetism of Nanoparticles: From Bulk to Nanoscale

Brownian relaxation

Néel relaxation (a)

After application of a magnetic field B

(b)

After application of a magnetic field B τB

τB

τN B

B

τN

τB τB

Figure 1.18 Illustration of the two components of the magnetic relaxation of a magnetic fluid: (a) Nèel and (b) Brown relaxation. Source: Reprinted with permission from Laurent et al. (2008). Copyright 2008 American Chemical Society.

Of course, in reality, in pharmaceutical suspensions both relaxation processes can take place, a situation in which a relaxation time given by the formula will be taken into account (…), 1 1 1 = + τ τN τB

1 31

In practice, on given applications, first, it will be necessary to analyze the contribution of each relaxation process (Nèel–Brown) to the total magnetic relaxation time (tau), as there may be situations in which one of the processes can be neglected. For example, in the case of highly viscous dispersion media, or in the case of injection of nanoparticles into tissues/tumors, in which small magnetically soft nanoparticles are dispersed, in general, the Brown relaxation time may be neglected. Similar situations can also occur in the case of biocompatible nanoparticles with core-shell structure for biomedical applications (coated with organic and/or biofunctionalized with large molecules), where the shell can be thick or really thick (even thicker than the diameter of the magnetic core of nanoparticles) (Figure 1.19) (Wells et al. 2017). In these cases, in the formula (1.30), the hydrodynamic diameter (Dh) must be taken into account: Dh = DNP + 2d

1 32

where d is the thickness of the organic layer from the surface of the nanoparticle, which will significantly increase the Brawn relaxation time (τB) compared to the Nèel relaxation time (τN). In many situations, tB can be higher or much higher than τN (τB>/>>τN), so only τN will be used in the calculations.

1.1.8 Dynamic Magnetic Behavior 1.1.8.1

Relaxation Time, Measurement Time, and Blocking Temperature

Below are some important aspects regarding the magnetic relaxation in nanoparticles and the determination of the threshold volume (Vth) from Eq. (1.29) in dynamic conditions (Caizer 2004a).

21

22

1 An Introduction to Magnetic Nanoparticles Functionalized shell diameter Single-core magnetic nanoparticle

Core diameter

Figure 1.19 Schematic diagram of a single-core magnetic nanoparticle. Note that the magnetic core is a single magnetic object that may be either a monocrystalline or a polycrystalline single magnetic domain, which responds to an applied magnetic field in a single, net, coherent manner. Source: Wells et al. (2017). CC BY 3.0.

Particle diameter Hydrodynamic diameter

However, in dynamic conditions, the measurement time (tm) (observation duration of the process) relative to the relaxation time is important. Thus, depending on the ratio in which the two times are found there may be the following cases: a) The case τN tm, which corresponds to the superparamagnetic state; in this case, the height of the energy barrier is very low, and after the application of a field (or its removal), the magnetization quickly reaches the thermodynamic equilibrium. b) The case τN tm, which corresponds to the stable state; in this situation, the height of the energy barrier is very high, and the probability of the magnetic moment passing over the barrier is very low and, therefore, the magnetization does not change over time tm. c) The case τN ≈ tm (when the two times are of the same order of magnitude), which corresponds to the intermediate state; when the magnetization, on the one hand, does not reach immediate thermodynamic equilibrium, and on the other hand, does not remain in the state of balance (stable) for a long time; this is the case of magnetic relaxation (under dynamic conditions). Under dynamic conditions, the threshold volume of the nanoparticle can be determined from the condition: τN = t m

1 33

Thus, imposing this equality in Eq. (1.29), the threshold volume (magnetic volume [Vmp]) result is V mp =

kB T ln t m τ0 Ku

1 34

When the relaxation process takes place in an alternating magnetic field (harmonic) with small amplitude, the period of the alternative field (TH) is considered as the measurement time (tm = TH). Under these conditions, the blocking temperature, according to relation (1.29), will be TB =

K uV m k B ln t H τ0

1 35

1.1 Magnetism of Nanoparticles: From Bulk to Nanoscale

However, when an alternative (harmonic) high amplitude magnetic field is applied on the nanoparticles system, the measurement time (tm), threshold volume (Vth), and blocking temperature (TB) of magnetic moments change. A study on this aspect is presented in Ref. (Caizer 2005b). 1.1.8.2

The Heating of Magnetic Nanoparticles in an Alternating Magnetic Field

Due to the reduced dimension at nanoscale of magnetic materials, another very important aspect from a practical point of view is the fact that in an alternating harmonic magnetic field, the nanoparticles heat up (Pankhurst et al. 2003) due to the superparamagnetic relaxation processes that take place in nanoparticles up to 20–25 nm (in the case of soft magnetic materials). This effect is used in magnetic hyperthermia (MHT) as an alternative method for tumor therapy, a matter of great interest in current research. The power dissipated in such a process is given by the following relationship (Rosensweig 2002): PMHT = μ0 πfH 2 χ 0

2πf τ 1 + 2πf τ

2

1 36

where H and f are the amplitude and frequency of the harmonic alternative magnetic field, tau the magnetic relaxation time, and h0 is the static magnetic susceptibility. For the usual magnetic fields used in magnetic hyperthermia (until several tens of kA m−1), which generally exceed the linear range of the magnetization variation (Figure 1.16a), the magnetic susceptibility χ 0 will no longer be given by the initial susceptibility (χi), but by the following: χ0 = χi

3 1 coth ξ − ξ ξ

1 37

because the Langevin variation (Langevin 1905) of the magnetization with the magnetic field must be taken into account (Jacobs and Bean 1963). In Eq. (1.37), ξ is the Langevin parameter, which in the case of nanoparticles is ξ=

μ0 M s V NP H kB T

1 38

In the case of a monodisperse nanoparticles system, under adiabatic conditions, the specific absorption rate (SAR) or specific loss power (SLP) will be SLP =

PMHT ρ

1 39

where ρ is the density of the nanoparticle material. Thus, the heating rate (ΔT/Δt) of the biological tissue is ΔT PMHT = Δt cδ

1 40

In the given formula, c is the specific heat of the environment. These are very important observables used in magnetic hyperthermia in order to quantitatively establish its effectiveness in the thermal destruction of tumors. Figure 1.20 shows such a variation of SLP calculated in the case of γ-Fe2O3 monodispers nanoparticles system for 10 kA m−1 magnetic field (H) and frequency (f) in the range (100–500) kHz (Caizer 2010), from which it results that a maximum power can be obtained only at a certain size of the nanoparticle diameter. This is a very important aspect for the practical application of magnetic hyperthermia. Thus, it results that the

23

1 An Introduction to Magnetic Nanoparticles

γ-Fe2O3; H = 10 kA/m

40 30

35

25

30

20

25

15

20

10

15

5

10

0

5 0

SLP (Wg–1)

35

40

SLP (Wg–1)

24

0 45

Figure 1.20

0 40

0 0 35 30 250 0 f (kHz) 20 150

8

0 4 10

6

10

12 > Dth, the magnetization of unidominal magnetic nanoparticles will present a deviation from the Langevin function, more or less pronounced, depending on the nature of the nanoparticle material (reflected in the magnetic anisotropy), the size (volume) of the nanoparticle and the temperature at which it is found, or even the appearance of a small, narrow hysteresis, at larger sizes in the considered interval. In the case of magnetic dispersions for biomedical and technical applications, there will be in addition a Brown time relaxation, processes characterized quantitatively by a resulting relaxation time (Nèel– Brown). For D closer to Dc, but with D < Dc, the magnetization of single-domain nanoparticle is stable, and nanoparticle is magnetized according to the Stoner–Wohlfarth model: with rectangular hysteresis when the magnetization is done along the direction of easy magnetization of the nanoparticle, and linear until magnetic saturation when the magnetization of the nanoparticle is done in a direction perpendicular to that of easy magnetization. In dynamic conditions, in harmonic alternating magnetic field, the magnetic relaxation process must be viewed in relation to the measurement time, in which the process is observed (quantitatively, the relaxation time related to the measurement time). The situation changes radically depending on the ratio in which the two times are found: the magnetic relaxation time and the measurement time. Thus, for τ tm, there will be a pure magnetic relaxation process, and for τ tm, there will

29

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1 An Introduction to Magnetic Nanoparticles

be a blocking of the magnetic moments of the nanop. Between the two cases, there will be a magnetic drag. In the alternating magnetic field (harmonic), magnetic relaxation processes lead to a heating of nanoparticles, an effect with applications in biomedicine such as in the alternative therapy of tumors by magnetic hyperthermia. Also, the rapid response of nanoparticles to the application of an external magnetic field makes them easy to manipulate, with application in target medication and drug delivery. In addition, in biomedicine, the magnetic nanoparticles are also used as contrast agents in magnetic resonance imaging (MRI) based on two essential characteristics of nanoparticles: their magnetism and small size.

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Broese Van Groenou, A., Schulkes, J.A., and Annis, D.A. (1967). Magnetic anisotropy of some nickel zinc ferrite crystals. Journal of Applied Physics 38: 1133. Brown, W.F. (1963). Thermal fluctuations of a single-domain particle. Physical Review 130: 1677–1686. Bulte, J.W.M. and Kraitchman, D.L. (2004). Iron oxide MR contrast agents for molecular and cellular imaging. NMR in Biomedicine 17 (7): 484–499. Bulte, J.W.M., Duncan, I.D., and Frank, J.A. (2002). In vivo magnetic resonance tracking of magnetically labeled cells after transplantation. Journal of Cerebral Blood Flow and Metabolism 22 (8): 899–907. Caizer, C. (2002). Magnetic behavior of Mn0.6Fe0.4Fe2O4 nanopartciles in ferrofluid at low temperatures. Journal of Magnetism and Magnetic Materials 251: 304. Caizer, C. (2003a). Structural and magnetic properties of nanocrystalline ZnO.65NiO.35FeO4 powder obtained from heteropolynuclear complex combination. Materials Science and Engineering B 100: 63. Caizer, C. (2003b). T2 law for magnetite-based ferrofluids. Journal of Physics: Condensed Matter 15: 765. Caizer, C. (2004a). Magnetic Nanofluids (in Romanian). Timisoara: Eurobit Publishing. Caizer, C. (2004b). Magnetic Nanoparticles Systems (in Romanian). Timisoara: Ed UVT. Caizer, C. (2005a). Deviations from Bloch law in the case of surfacted nanoparticles. Applied Physics A: Materials Science & Processing 80: 1745. Caizer, C. (2005b). The effect of the external magnetic field on the thermal relaxation of magnetization in systems of aligned nanoparticles. Journal of Physics: Condensed Mater 17 (12). Caizer, C. (2008). Magnetic properties of the novel nanocomposite (Zn0.15Ni0.85Fe2O4)0.15/(SiO2)0.85 at room temperature. Journal of Magnetism and Magnetic Materials 320: 1056–1062. Caizer, C. (2010). Nanobiomagnetism (in Romanian). Timisoara: Ed UVT. Caizer, C. (2013). Bioelectromagnetism (in Romanian). Timisoara: Eurobit Publishing House. Caizer, C. (2016). Nanoparticle size effect on some magnetic properties. In: Handbook of Nanoparticles (ed. M. Aliofkhazraei). Switzerland: Springer International Publishing. Caizer (2017). Magnetic hyperthermia using magnetic metal/oxide nanoparticles with potential in cancer therapy. In: Metal Nanoparticles in Pharma (eds. M. Rai and R. Shegokar). Springer. Caizer, C. (2019). Magnetic anisotropy of nanocomposites made of magnetic nanoparticles dispersed in solid matrices. In: Advances in Nanostructured Composites (ed. M. Aliofkhazraei). CRC Press – Taylor & Francis Group. Caizer, C. and Stefanescu, M. (2002). Magnetic characterization of nanocrystalline Ni-Zn ferrite powder prepared by the glyoxylate precursor method. Journal of Physics D 35: 3035. Caizer, C. and Stefanescu, M. (2003). Nanocrystallite size effect on σs and Hc in nanoparticle assemblies. Physica B: Condensed Mater 327: 129–134. Caizer, C. and Tura, V. (2006). Magnetic relaxation/stability of Co ferrite nanoparticles embedded in amorphous silica particles. Journal of Magnetism and Magnetic Materials 301: 513–520. Caizer, C., Popovici, M., and Savii, C. (2003). Spherical(ZnδNi1-δFe2O4)γ nanoparticles in an amorphous (SiO2)1-γ matrix, prepared with the sol–gel method. Acta Materiala 51: 3607–3616. Caizer, C., Buteica, A.S., and Mindrila, I. (2017). Biocompatible magnetic oxide nanoparticles with metal ions coated with organic shell as potential therapeutic agents in cancer. In: Metal Nanoparticles in Pharma (eds. M. Rai and R. Shegokar). Springer International Publishing. Caizer, C., Dehelean, C., Coricovac, D.E. et al. (2020). Magnetic nanoparticles nanoformulations for alternative therapy of cancer by magnetic/superparamagnetic hyperthermia. In: Nanoformulations in Human Health (eds. S. Talegaonkar and M. Rai). Cham: Springer. Chomoucka, J., Drbohlavova, J., Huska, D. et al. (2010). Magnetic nanoparticles and targeted drug delivering. Pharmacological Research 62 (2): 144–149. Coey, J.M.D. and Khalafalla, D. (1972). Superparamagnetic γ-Fe2O3. Physica Status Solidi 11: 229–241.

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Cullity, B.D. and Graham, C.D. (2009). Introduction to Magnetic Materials, 2e. Hoboken, NJ: Wiley. Déjardin, J.L., Vernay, F., and Kachkachi, H. (2020). Specific absorption rate of magnetic nanoparticles: nonlinear AC susceptibility. Journal of Applied Physics 128: 143901. Dillon, J.F. (1962). Magnetic properties I. In: Landolt-Börnstein, Vol. II(9): 50–51. Berlin: Springer-Verlag. Enpuku, K., Hotta, M., Nakahodo, A., and Physica, C. (2001). High-Tc SQUID system for biological immunoassays. Physica C: Superconductivity 357–360: 1462–1465. Ferguson, R.M., Minard, K.R., Khandhar, A.P., and Krishnan, K.M. (2011). Optimizing magnetite nanoparticles for mass sensitivity in magnetic particle imaging. Medical Physics 38: 1619. Fortin-Ripoche, J.P., Martina, M.S., Gazeau, F. et al. (2006). Magnetic targeting of magnetoliposomes to solid tumors with MR imaging monitoring in mice: feasibility. Radiology 239 (2): 1–20. Gao, Y., Liu, Y., Xu, C., and Cai, W. (2014). Magnetic Nanoparticles for Biomedical Applications: From Diagnosis to Treatment to Regeneration. London: Springer-Verlag. Garcia, J. and Subias, G.J. (2004). The Verwey transition – a new perspective. Journal of Physics: Condensed Matter 16: R145–R178. Goya, G., Berquo, T., Fonseca, F., and Morales, M. (2003). Static and dynamic magnetic properties of spherical magnetite nanoparticles. Journal of Applied Physics 94: 3520. Grimm, J., Perez, J.M., Josephson, L., and Weissleder, R. (2004). Novel nanosensors for rapid analysis of telomerase activity. Cancer. Res. 64: 639–643. Guardia, P., Batlle-Brugal, B., Roca, A. et al. (2007). Surfactant effects in magnetite nanoparticles of controlled size. Journal of Magnetism and Magnetic Materials 316: e756. Guo, T., Lin, M., Huang, J. et al. (2018). The recent advances of magnetic nanoparticles in medicine. Journal of Nanomaterials 7805147: 1–8. Hassen, W.M., Chaix, C., Abdelghani, A. et al. (2008). An impedimetric DNA sensor based on functionalized magnetic nanoparticles for HIV and HBV detection. Sensors and Actuators B: Chemical 134: 755–760. Hendriksen, P.V., Linderoth, S., and Lindgard, P.A. (1992). Finite-size effects in the magnetic properties of ferromagnetic clusters. Journal of Magnetism and Magnetic Materials 104–107: 1577–1579. Hendriksen, P.V., Linderoth, S., and Lindgard, P.A. (1993). Finite-size modifications of the magnetic properties of clusters. Physical Review B 48: 7259. Herpin, A. (1968). Theorie du Magnetism. Paris: Universitaires de France. Hilty, F.M., Arnold, M., Hilbe, M. et al. (2010). Iron from nanocompounds containing iron and zinc is highly bioavailable in rats without tissue accumulation. Nature Nanotechnology 5 (5): 374–380. Jacobs, I.S. and Bean, C.P. (1963). Fine particles; superparamagnetism. In: Magnetism III (eds. G.T. Rado and H. Suhl). New York: Academic Press. Jain, R.K. (2001). Delivery of molecular and cellular medicine to solid tumors. Advanced Drug Delivery Reviews 46: 149–168. Jangpatarapongsa, K., Polpanich, D., Yamkamon, V. et al. (2011). DNA detection of chronic myelogenous leukemia by magnetic nanoparticles. Analyst 136 (2): 354–358. Kaittanis, C., Santra, S., and Perez, J.M. (2009). Role of nanoparticle valency in the nondestructive magnetic-relaxation-mediated detection and magnetic isolation of cells in complex media. J. Amer. Chem. Soc. 131 (35): 12780–12791. doi: 10.1021/ja9041077. Kim, C., Lee, Y., Kim, J.S. et al. (2010). Thermally triggered cellular uptakeof quantum dots immobilized with poly(N-isopropylacrylamide) and cell penetrating peptide. Langmuir: The ACS Journal of Surfaces and Colloids 26 (18): 14965–14969. Kim, S., Lewis, B., Steiner, M. et al. (2016). Superparamagnetic iron oxide nanoparticles for direct labeling of stem cells and in vivo MRI tracking. Contrast Media & Molecular Imaging 11 (1): 55–64. Kittel, C. (1946). Theory of the structure of ferromagnetic domains in films and small particles. Physics Review 70: 965.

References

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Part I Current Biomedical Applications of Magnetic Nanoparticles

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2 Magnetic Nanoparticles in Nanomedicine Gabriela Fabiola Ştiufiuc1, Cristian Iacoviță2, Valentin Toma3, Rareș Ionuț Ştiufiuc2,3, Romulus Tetean1, and Constantin Mihai Lucaciu2 Faculty of Physics, “Babeș-Bolyai” University, Cluj-Napoca, Romania Department of Pharmaceutical Physics and Biophysics, “Iuliu Hațieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania 3 MedFuture Research Center for Advanced Medicine, “Iuliu Hațieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania 1 2

2.1

Introduction

Magnetic materials are in the limelight of modern nanotechnological applications. Over the last decades, a tendency of miniaturization has been observed for different types of magnetic materials, which can be understood from the point of view of their size-dependent properties. The advancements in the field of nanotechnology have shown that Magnetic Nanoparticles (MNPs) display completely different properties as compared to those of bulk materials. By reducing their size to values of the order of their single-domain dimension (~20 nm) or even lower, the MNPs, which at room temperature can exhibit a ferro- or ferri-magnetic behavior, become superparamagnetic (SP). In other words, the reduction of their size can be used for modulating their physical properties by diminishing the magnetic interaction manifesting between them. This finding represented a very good starting point, in terms of the applicability of MNPs in nanomedicine. On the other hand, nanomedicine is a research topic that has seen a tremendous development in recent years. Basically, nanomedicine can be defined as the use of nanomaterials/nanostructures in medical applications. Several nanoformulations have been tested so far for such applications. Among them, the inorganic nanoparticles and, more precisely, the MNPs proved to possess numerous benefits over conventional medicines, making them valuable candidates in various fields of biomedical applications (Martins et al. 2020). As a direct consequence of their high versatility, the MNPs were proposed for numerous applications. However, a complete and comprehensive classification of these applications is not a very easy task. Over the years, three major types of MNPs applications in biomedicine have emerged: diagnosis, therapy, and targeting. By either functionalizing their surface with biomolecular components or by creating hybrid nanoformulations, in combination with polymers, fluoro-phores, liposomes, plasmonic, or silica shells, the MNPs gain multiplexing capabilities. Among numerous research groups that have performed extensive research in this area (Salgueiriño-Maceira et al. 2006; Arruebo et al. 2007; Colombo et al. 2012),

Magnetic Nanoparticles in Human Health and Medicine: Current Medical Applications and Alternative Therapy of Cancer, First Edition. Costica Caizer and Mahendra Rai. © 2022 John Wiley & Sons Ltd. Published 2022 by John Wiley & Sons Ltd.

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our research group reported in 2019 the successful synthesis of multifunctional magneto-plasmonic nanoliposomes that could be employed in target drug delivery applications. Their synthesis was based on the synergistic use of hydrophobic and electrostatic interactions, acting between the three major components involved in the synthesis of the multifunctional nanohybrids: superparamagnetic iron oxide nanoparticles (SPIONs), cationic liposomes and anionic plasmonic nanoparticles (Stiufiuc et al. 2015, 2019). This is a direct proof of the fact that such hybrid multifunctional nanosystems, possessing desired physico-chemical properties, can be successfully created for a specific application. There are many potential bioapplications involving nanoplatforms containing MNPs but only a few were translated to clinical applications. At the time of writing this chapter, according to the website http://www.clinicaltrials.gov, 22 clinical trials are in progress in the following fields: brain tumors, MR angiography, lymph node imaging, esophagus, stomach, bladder/prostate/kidney, cardiology, and bone brain inflammation (not tumoral). In this chapter, we present the most “appealing” and trendy biomedical applications that involve the use of MNPs: Magnetic Resonance Imaging (MRI) (the first-approved clinical application), its development Magnetic Particle Imaging (MPI) and magnetic hyperthermia (MH), which defines a research area in our group devoted to the development of MNPs with high heating powers (Iacovita et al. 2015, 2016, 2020). For each application, a short theoretical explanation of the physical phenomenon the application is based on is provided. We hope that this approach will ease their understanding, especially, in the case of the readers that are not necessarily familiarized with this topic. Due to the focused aim of this chapter, the synthesis methods developed for the MNPs of various sizes, shapes, and compositions were not included. For a detailed description of these synthesis procedures and their subsequent physical properties, please refer to the following literature (Lu et al. 2007; Reddy et al. 2012; Wu et al. 2016).

2.2

Biomedical Applications

According to the underlying interaction mechanism of MNPs with various forms of external applied magnetic fields, we have identified three types of application that could have a major impact in nanomedicine, in the near future: 1) Applications based on the existence of a magnetic force. The magnetic force can be defined as the force developed when MNPs, as tiny nanoscale magnets possessing a dipolar magnetic moment, interact with an external static magnetic field gradient. The acquired magnetic mobility of MNPs, due to this interaction, leads to their movement toward the higher magnetic field zones, a phenomenon known as magnetophoresis. Magnetophoresis can be used in some specific applications such as magnetic drug targeting, magnetic cell targeting, magnetofection, magnetic purification/separation of the cell or its constituents (molecules, exosomes, and organelles), controllable in vivo genome editing, or induction into apoptosis. 2) Applications based on magnetic relaxation of protons. In this case, the non-uniform local dipolar magnetic fields generated by MNPs, in their vicinity, significantly modify the longitudinal (T1) and transversal (T2) relaxation times of protons. This is the main mechanism involved in the use of MNPs as contrast agents for MRI applications. So far, MRI has been successfully used in diagnostic imaging, cell tracking, molecular imaging, and image-guided drug delivery. 3) Applications based on magnetic heating. The conversion of electromagnetic energy, resulted from the interaction of MNPs with an external alternating (AC) radiofrequency (RF)

2.2 Biomedical Applications

magnetic field, into thermal energy, is exploited in MH for different purposes as: apoptosis induction in cancer cells, thermal ablation of tumors, nanowarming, magnetogenetics, or controlled drug release. In the following section, we will address the use of MNPs as contrast agents in MRI, which represented their first biomedical application introduced in clinical practice. Afterward, we will introduce the Magnetic Particles Imaging (MPI) technique, which is a transverse to the static magnetic field and irradiating recent imaging technique possessing a much higher resolution as compared to MRI. Lastly, we will present a short overview of recent advancements reported in the field of MH.

2.2.1 MNPs as Contrast Agents in MRI The use of the MNPs as contrast agents in MRI was the first application for which Food and Drug Administration (FDA) and European Medicines Agency (EMA) approved their use in clinical practice (see Table 2.1). MRI is based on the Nuclear Magnetic Resonance (NMR) of the protons constituting the nucleus of the hydrogen atoms. In the human body, protons represent 63% of the body mass. NMR can occur when the proton’s nuclear magnetic momentum, aligned parallel to a static external magnetic field, reverses its orientation to an antiparallel one, by resonantly absorbing a certain amount of external energy. More precisely, the energy of an external RF electromagnetic field, transverse to the static magnetic field and irradiating the proton-containing sample, has to be equal to the energy difference between the two orientation states. Translating the space in terms of the values of the magnetic field, B, allows one to get information about the position of the protons, by using the measured resonance frequencies. In MRI, the measurements are performed in pulses of RF electromagnetic field, which has the “role” to perturb the orientation states of the nuclear spins. The perturbed orientation will relax by the end of the pulse, a phenomenon that is known as spin relaxation. There are two mechanisms that are responsible for this phenomenon: the spin–lattice relaxation and the spin–spin relaxation. The spin–lattice relaxation process is characterized by the time interval (time constant) in which the magnetization along the direction of the static magnetic field decreases to zero, when the static field is inactivated. This time constant is called the longitudinal relaxation time and usually is denoted as T1. On the other hand, the spin–spin relaxation mechanism is characterized by the time interval (also called transverse relaxation time, T2) in which the magnetization in the direction perpendicular to the external magnetic field B0 decreases to zero. The spin–spin relaxation process is also strongly correlated with the existence of inhomogeneities in the magnetic field the protons feel that leads to a decorrelation in their rotation frequencies around the axis of B0. Human tissues have different values of both relaxation times due to their different proton concentrations and structure (environment). These differences are responsible for the “quality” of the images obtained in NMR. However, there are many situations in which these differences are small. In this case, a reduced contrast NMR image will be recorded. Usually, even for the same tissue, there can be differences in the values of T1 and T2 relaxation times; T1 being usually longer than T2. As such, it becomes possible to record either T1 or T2 weighted MRI images. The T1-weighted NMR images are obtained by reducing the repetition time (i.e. the time between two successive pulses), while the T2-weighted MRI images are recorded by reducing the echo time (the time after which the magnetic resonance signal is recorded). Over time, it was demonstrated that the contrast of MRI images can be increased by using different contrast agents (CAs). The first CAs that have been employed are the paramagnetic ions possessing large magnetic momentum (Mn2+, Gd3+). Their effect on the effective relaxation time is measured in terms of relaxivity, according to the following equation:

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Ri,obs =

1 T i,eff

=

1 + c ri Ti

where i is either 1 or 2, and Ri,obs is the observed relaxation rate which is defined as the reverse of the effective relaxation time Ti,eff. Ti is the relaxation time in the absence of any CA, c is the CA concentration, and ri is the relaxivity, which is characteristic of CA. Higher the ri values are, higher the effectiveness of the CA, meaning that a smaller concentration of CA leads to measurable effects. The effects of the CA on the two relaxivities are very often completely different. As such, CAs that reduce the T1 values (high r1) and increase the signal in T1-weighted images are called positive CAs, whereas CAs that reduce the T2 values and subsequently reduce the intensity of the signal in T2weighted images are called negative CAs. The mechanism by which CAs influence the relaxation times is related to the value of their magnetic moment and the time spent by the protons (mostly belonging to water molecules) in their proximity (retention time). Thus, paramagnetic ions with large magnetic moments (Mn2+, Gd3+, Dy3+) allow a close interaction of the ions with water molecules present in the first hydration sphere, leading to an increase of r1 relaxivity values. These paramagnetic ions are usually administrated in the form of ion complexes that have the role to decrease their mobility and to increase their relaxivities. The phenomenon is known as Proton Relaxation Enhancement (PRE). These ions are known as T1-positive CAs. On the other hand, the advancement in the synthesis of different classes of MNPs with improved magnetic properties has represented a major discovery in the field of CAs. MNPs have huge values of their magnetic moments, with respect to paramagnetic ions, influencing the relaxation behavior of water molecules beyond the first hydration layer. Nevertheless, their coatings, used for improving their biocompatibility, impede a direct contact with water molecules. For these reasons, the MNPs are mostly used as negative T2-CAs. The first commercially available MNPs approved for clinical applications as CAs in MRI are Resovist and Feridex (Table 2.1). They consist of SPIONs of small magnetic cores (approximately ~10 nm) obtained by the coprecipitation method. Their r2 values are lower than 100 s−1 mM−1. The relaxivity values are directly proportional to the square of MNPs magnetic moment, which in turn is proportional to their magnetization saturation (Ms) and volume. Therefore, MNPs with larger volumes and Ms values present several fold higher relaxivities. The use of thermal decomposition methods led to the synthesis of MNPs with improved crystallinity. This increases their magnetic moments as well as their relaxivities. However, monocrystalline MNPs with sizes higher than 20 nm are difficult to obtain because they involve laborious seed-mediated growth synthesis methods. Moreover, the increase of MNP size can induce their transition into the so-called “blocked state” in which they will have a nonzero remanent magnetization (Mr – induced magnetization remaining at zero magnetic field). A direct consequence of this nonzero Mr will be the occurrence of dipolar interaction and MNPs’ self-aggregation that make them less suitable for biomedical applications. For example, a 20 nm diameter appears to be an upper limit in the case of MNPs applications such as MRI CAs. Another approach for improving the relaxivity properties of the MNPs is to include them in preformed aggregates or clusters of controlled structure, shape, and size. The existence of a cluster creates a stronger magnetic field gradient around it, thereby, changing the relaxation rate R2 and the relaxivity r2. However, the experimental results obtained for these types of structures show that the cluster size and MNPs composition influence the transverse relaxation rate and relaxivity in a nonmonotonous manner (Kostopoulou et al. 2014). With increasing the size and the number of clustered MNPs, the transverse relaxation rate increases, and this regime is called the “motional average regime.” Once the size limit is reached, the water molecules feel a constant magnetic field during

2.2 Biomedical Applications

Table 2.1

Examples of the MNPs clinically approved or in the phase of clinical trials.

Commercial name

Formulation

Application

Status

Feridex (Ferumoxide)

Iron oxide coated with dextran

MRI

FDA approval discontinued in 2008

Combidex (Ferumoxtran)

Ultrasmall iron oxide coated with low Mw dextran

MRI

Approval in Europe, withdrawal in 2007

Resovist (Ferucarbotran)

Iron oxide NPs coated with carboxyldextran

MRI

Approval in Europe, production abandoned in 2009

Gastromark (Ferumoxsil)

Silicone-coated iron oxide NPs

MRI

FDA approval, discontinued in 2012

Feraheme (Ferumoxytol)

Iron oxide coated Siliconecoated iron oxide NPs with polyglucose sorbitol carboxymethylether

Iron replacement therapy in patients with chronic kidney failure, MRICNS imaging, macrophage imaging, blood pool agent, cellular labeling, lymph node imaging

FDA approval withdrawn from EU market

Abdoscan

Sulfonated poly(styrenedivinylbenzene) copolymer

Oral gastrointestinal imaging

Clinical trial

Nanotherm

Iron oxide NPs with aminosilane coating

Hyperthermia in solid tumors

Clinical trial

Magtrace Sienna+

Superparamagnetic iron oxide particles

Sentinel lymph node mapping

Clinical trials

their relaxation. This regime is called the “static dephasing regime” and determines the maximum relaxivity limit. If the MNPs’ size is further increased, the relaxivity decreases and the measured relaxation rate depends on the echo time. This regime is called “echo limited regime.” Interestingly, in the case of longitudinal relaxivity, it has been observed that its value tends to decrease with increasing the size of the cluster. This effect is explained by the reduction of the surface accessible for water molecules as the size of the cluster increases. In fact, the accessibility of water molecules to the magnetic core is a key factor in determining the effect of MNPs on relaxivities. This means, on the one hand, that the optimum coating allows for sufficient diffusion of water molecules to affect the relaxivity of protons and, on the other hand, it assures a rapid exchange for a maximum number of water molecules near the CAs (Laurent et al. 2008). The diffusion of water molecules around the CA as a function of the coating might be assessed by measuring the NMR dispersion (NMRD) profile. In this type of measurement, the relaxivity r1 is measured as a function of the magnetic resonance frequency (which is determined by the value of the static magnetic field B0). It also facilitates the acquisition of the frequency or the value of B0 at which the CA is the most effective. A typical NMRD profile of magnetite MNPs is presented in Figure 2.1.

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30

25 Proton relaxivity (s–1∙ mM–1)

42

20

Theoretical fit Magnetite (experimental points)

Rmax ~ C∙M3s∙τD

Low field relaxation rate: depends on the anisotropy energy

ωI –τD ~ 1 τD = r2

15

D

10

5

0 10–2

Low field dispersion: an indication of anisotropy energy

ωi

10–1 100 101 102 Proton Larmor frequency (MHz) Fitted parameters: r = 4 nm, MS = 53 A.m2 kg–1

103

Figure 2.1 Example of a NMRD profile for a colloidal suspension of SPIONs showing the evolution of the r1 proton relaxivity with the applied external magnetic field/frequency. Source: Reprinted with permission from Laurent et al. (2008). Copyright 2019 American Chemical Society.

By fitting the experimental data with adequate theories, various parameters can be extracted, such as Rmax, the maximal relaxivity, Ms of the MNPs, tD, water diffusion correlation time, and MNPs’ anisotropy energy (Muller et al. 2005). But the most common application of MNPs, like MRI CAs, is the early detection and diagnosis of cancer. The MNPs’ effectiveness in cancer–tumor detection is mainly dictated by their fate after they are administrated in the systemic circulation. There are three main mechanisms underlying the biodistribution of MNPs. First, the MNPs are rapidly captured by the Mononuclear Phagocyte System (MPS), also known as Reticuloendothelial System (RES). MPS is composed of the liver, spleen, lymph nodes, and bone marrow and leads to MNPs accumulation in these organs (Weissleder et al. 1990). Their accumulation in the liver’s Kupffer cells will make the liver tissue to appear dark in the T2-weighted images. However, in the presence of a liver tumor, deficient phagocytic activity will be highlighted as a bright spot because MNPs do not accumulate in the tumor cells. Based on the same mechanism, normal lymph nodes will become dark in T2-weighted images, and the lymph nodes produced by the metastasis will remain white and will be easily identified in the MRI pictures (Figures 2.2 and 2.3) (Motomura et al. 2011). The development of these applications led to the approval of the first MNPs that were used as contrast agents (Feridex and Resovist, see Table 2.1) in Europe and USA. In the organs not associated with MPS, or in the case of MNPs that are functionalized such as they escape the MPS, the Enhanced Permeability and Retention effect (EPR) in solid tumors plays an important role in their penetration into tumor tissue. Moreover, due to the lack of functional lymphatic vessels in malign tumors, the MNPs can accumulate in these tumors. This accumulation can be visualized in dark

2.2 Biomedical Applications

(a)

(b)

(c)

(d)

1 mm

Figure 2.2 (a) CT lymphography demonstrated a sentinel node (arrow). (b) The corresponding node was identified on T2∗-weighted axial MR imaging (arrow). The node showed high signal intensity before the administration of superparamagnetic iron oxide (SPIO). (c) After the administration of SPIO, the node showed strong SPIO enhancement and was diagnosed as benign (arrow). (d) Histologic findings confirmed it as benign. Source: Reproduced with permission from Motomura et al. (2011). Copyright © 2011, Springer Nature DOIhttps://doi.org/10.1245/s10434-011-1710-7.

(a)

(b)

(c)

(d)

1 mm

Figure 2.3 (a) CT lymphography demonstrated a sentinel node (arrow). (b) The corresponding node was identified on T2∗-weighted axial MR imaging (arrow). The node showed high signal intensity before the administration of superparamagnetic iron oxide (SPIO). (c) After the administration of SPIO, the node showed no SPIO enhancement and was diagnosed as malignant (arrow). (d) Histologic findings confirmed it as malignant. This node was almost entirely replaced by metastatic tissue (arrowheads). Source: Reproduced with permission from Motomura et al. (2011). Copyright © 2011, Springer Nature. DOI-https://doi.org/10.1245/ s10434-011-1710-7.

contrast images (Jain and Stylianopoulos 2010). Another approach for increasing the accumulation of MNPs in tumor tissues is to functionalize them with ligands targeting tumor markers like vascular or epithelial growth factors, αvβ3 integrins expressed by the endothelial cells in tumor vessels, folate receptors, and transferrin receptors. Apart from their use as CAs for tumor detection, MNPs in conjunction with MRI were used in MR angiography for the detection of cardiovascular diseases, vascular abnormalities, and inflammations (Nahrendorf et al. 2008). Another important application of MNPs in MRI is the monitoring of cell therapies by cell tracking. In order to generate high-contrast MRI images, the tracked cells are loaded with MNPs. Large numbers of MNPs can be loaded into the cells by electroporation, magnetofection, or cell-

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penetrating peptides. In this manner, single cell detection can be achieved in vitro. Moreover, recent studies showed that the MNPs accumulate in lysosomes without affecting the cell functions (Ou et al. 2020). Several studies have shown that the delivery of antigen-specific cytotoxic T-lymphocyte, natural killer cells, and dendritic cells to the tumor or regional lymph nodes, could be monitored in vivo in real time (de Vries et al. 2005). Another important advantage of this type of approach is the possibility to monitor and to identify individuals who do not respond to the therapy. Other important applications of the combined use of MNPs and MRI are based on the observation that the MNPs could be taken up by monocytes and macrophages involved in the inflammation response; this provides information in different pathological processes such as atherosclerosis, pancreatic islet inflammation, or cardiac allograft rejection (Tong et al. 2019). The development of a nanoplatform able to create dual T1 − T2 contrast agents would represent a great advancement for medical applications of MNPs. This implies to create a CA with a high r1 but, in the same time, with a low ratio r2/r1 (close to 1) (Blanco-Andujar et al. 2016). Several strategies have been tested so far: doping the MNPs with T1 ions, attaching T1 ions on the surface of MNPs, and elaboration of core-shell nanostructures having a r2/r1 ratio close to 1 but with the cost of a low r2 (Xiao et al. 2014). Core@shell structures led to MNPs with higher r2 values, especially if the distance between the core and the shell is increased by adding a nonmagnetic layer (SiO2). Recent studies show that, in a case of a dual core@shell nanostructure, by increasing the thickness of the nonmagnetic layer, the r2/r1 ratio decreased. Very interestingly, the r2 was quite high, reaching a value of 312 m M−1 s−1 (Yang et al. 2015a). This finding demonstrates the huge potential of these nanostructures in MRI applications.

2.2.2

Magnetic Particle Imaging (MPI)

MRI cell-tracking applications and inflammation response characterization by using MNPs might be replaced soon by a novel emerging technique called Magnetic Particle Imaging (MPI) (Gleich and Weizenecker 2005). As it was stated before, the use of MNPs in MRI does have several drawbacks worth mentioning. Arguably, the most relevant is their rapid elimination from the bloodstream by MPS, hampering their use as more specific targeting agents. The negative contrast they produce is often masking the underlying anatomical tissue structure. Concurrently, the presence of different endogenous sources of contrast such as hemorrhage, air tissue interfaces, and magnetic field imperfections may lead to artefactual images. Because the contrast is produced by the change in the relaxation time of the protons, which in turn is inextricably connected to MNPs concentration, a reliable quantification of their concentration is difficult. Some of these restrictions are eliminated in MPI. The MPI is based on the principle that MNPs that are magnetized by an external magnetic field can exhibit a nonlinear response in a near-zero external magnetic field. When the MNPs are placed in an external magnetic field, the magnetization will follow it until a positive or negative saturation value is reached. In a basic MPI scanner setup, the structure of the static magnetic field is such that there is only 1 point in the 3D space where the magnetic field is zero. This point is called “field-free point” (FFP). When, apart from the static magnetic gradient field, another AC magnetic field (in the range of few kHz) is created, only the MNPs situated in the FFP will follow the oscillations of the AC magnetic field. As such, only these MNPs can induce an electric current in a pick-up coil. Moreover, due to the nonlinear dependence of the magnetization on the magnetic field strength (which usually is a Langevin function type dependence), the induced current will consist not only in the fundamental frequency of the applied AC magnetic field but also in multiples of the fundamental frequency (harmonics). By measuring the third harmonic, one may separate the contribution of

2.2 Biomedical Applications

paramagnetic ions or impurities to the induced current. This is possible because the paramagnetic response is linear and contains only the fundamental frequency. Following the spatial reconstruction of the signals recorded in every point, an MP image can be created. In order to reduce the acquisition time, it is possible to create a static field with a “field-free line” (FFL), but at the cost of resolution. The as-obtained image represents the spatial distribution of SPIONs since the amplitude of the signal is proportional to the amount of magnetic material, usually expressed in Fe concentration. The foremost advantage is that the recorded signals do not depend on the aggregation state of MNPs, which in most biological applications cannot be neither monitored nor detected. This finding represents the huge advantage of MPI over MRI. One can consider that MPI is a development of Magnetic Nanoparticle Spectroscopy (MPS) (Wu et al. 2019). This very recent technique can be defined as a zero-dimensional MPI scanner. Like in MPI, a sinusoidal magnetic field is applied to the SPIONs and their magnetization will be periodically driven in and out of saturation. The nonlinear SPIONs’ magnetic response, containing unique spectral information, is recorded and separated into its spectral components. MPS has been actively explored as a portable, highly sensitive, cheap, in vitro, and easy-to-use bioassay testing kit. The MPS spectra (including harmonic amplitudes and phases) are unique for each type of SPIONs (Tu et al. 2014). In this manner, by conjugating the SPIONs with specific antibodies, it is possible to label different target analytes (even different cells) with specific types of SPIONs. This feature can be also used in MPI, as we will show later.

2.2.3 MPI Cell Tracking The first major application of MPI was cell tracking (Bulte 2019). As mentioned above, the MPI’s signal intensity linearly depends on MNPs’ concentration (iron content for pure magnetite or maghemite) regardless of their state, their uniform distribution in a solution or their aggregation in clusters. This property is essential for biomedical applications because it is well known that in a biological environment the MNPs are either attached to cell surfaces or agglomerated in cytosol or endosomes after internalization by the cell. In the case of MRI, the aggregation state of the MNPs strongly influences the relaxation times, large clusters leading to a significant decrease of the observed transverse relaxation time. Usually, cell tracking is performed by loading the cells with MNPs. The distribution of these MNPs in the body will be monitored by MPI. It was reported that neural cells loaded with MNPs were detected in the rat brain. Moreover, the detection has been reconfirmed after several months from the first measurement (Zheng et al. 2016). Another important feature of MPI with respect to MRI is its higher sensitivity. The sensitivity depends mainly on the magnetic momentum of MNPs which in turn depends on the saturation magnetization and crystal volume. Janus-like MNPs specially synthesized for MPI applications proved to be three times more effective as compared to Resovist and seven-time more effective as compared to Feraheme (Song et al. 2018). While using MRI for tracking purposes, the cell’s average iron content is 5–10 pg cell−1; in MPI, an entire field of view (FOV) in the case of a rat body measurements needs around 250 cells or 1 pg of iron. This higher sensitivity facilitates, at least from a theoretical point of view, the possibility to attain single cell tracking by using the MPI technique. For the above mentioned Janus MNPs, an in vivo sensitivity of 250 cells within the FOV of an entire mouse was reported (Song et al. 2018). This type of experiment cannot be visualized with MRI. Due to the EPR effect, systemic injection of the MNPs can lead to their accumulation within the tumor, allowing the tumor detection with a tumor-to-background ratio of 50 at the peak, six hours after the injection (Yu et al. 2017).

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(a) hMSCs, 1 hour postinjection

(b) hMSCs, 12 days postinjection

(c) SPIOs, 1 hour postinjection (positive control)

(d) Saline, 1 hour postinjection (negative control)

930

200

1060

200

Fe [μM]

Fe [μM]

Fe [μM]

Fe [μM]

310

10

100

10

Figure 2.4 MPI-CT imaging of intravenously injected hMSCs, Resovist, and saline control, with representative coronal, sagittal, and axial slices shown from full 3D MPI datasets. (a) MPI imaging of hMSC tail vein injections less than one hour postinjection shows substantial hMSC localization to lung. (b) At 12 days, hMSC tail vein injections show significant total clearance and liver migration. (c) MPI imaging of Resovist-only tail vein injections less than one hour postinjection shows immediate SPIO uptake in liver and spleen. (d) Control injections of isotonic saline show no detectable MPI signal. Source: Reproduced with permission from Zheng et al. (2016).

On the other hand, it has been recently shown that MNPs loaded mesenchymal stem cells (MSCs) systemically injected and distributed within the lungs in a first step were found in the liver and the spleen one day later (Figure 2.4) (Zheng et al. 2016). This distribution was also observed in the case of radiolabeled MSCs by single-photon emission computed tomography (SPECT). The distribution has been detected for both large and small animals. One can also notice from Figure 2.4 that in the case of a direct injection of MNPs in the tail vein, they are rapidly captured (one hour) by the MPS, the MNPs being detected in liver and spleen (Figure 2.4c). The versatility of the MPI technique allows the use of several classes of MNPs with different magnetic responses at different frequencies. In this manner, it is possible to separately collect multicollor MPI images for the different subclasses by assigning them different colors. This creates the possibility to concurrently study in vivo the interaction between the cells loaded as well as the MNP classes they are loaded with (Rahmer et al. 2017). Another important application of MPI is represented by MPI-guided hyperthermia. The main advantage of using MPI in MH is the ability to check MNPs’ distribution at the site of the tumor before applying the external magnetic fields. This is a real advantage, particularly when the MNPs are administered systemically (Tay et al. 2018). Moreover, it was observed that if the AC magnetic fields used for MPI, exhibiting ~20 kHz frequency, are applied alone no heating of the tissues occurs. However, if the AC frequency is increased to 340 kHz, heating of the tissue can be easily detected. At this point, the application of gradient magnetic fields will generate heat only in the FFP or FFL regions. As such, by positioning the FFP or FFL in the position of the tumor one might obtain heating only in the tumor area, without affecting neighboring healthy tissues. In conclusion, one can observe that MPI has several advantages over MRI and other imaging techniques: high sensitivity, lack of background signal, and the possibility of quantitative analysis.

2.2 Biomedical Applications

In opposition to MRI, MPI could be applied in hemorrhagic tissue and air-tissue interfaces. On the other hand, the major disadvantage of MPI consists in its lack of anatomical information and the necessity to be used in conjunction with another morphological imaging technique. Up until present-day, MPI was not translated in clinical applications, although there were some initiatives to build a human scanner (Bulte 2019). We are at the very beginning of MPI biomedical applications, but we are very confident that the technological progress will extend the area of its use toward clinical applications.

2.2.4 MNPs in Magnetic Hyperthermia The current standard of cancer care comprises the elimination of solid tumors by surgery followed by treatment with chemotherapeutic drugs (Bhattacharjee et al. 2010). However, it has been shown that most of anticancer drugs used in chemotherapy also target other healthy tissues in the body, causing major toxicity problems to vital organs. A typical example is the treatment with doxorubicin that provokes major heart problems as side effect (Minotti et al. 2004). Hyperthermia therapy or thermotherapy was considered a potentially useful alternative of chemotherapy. In this case, the body tissues are exposed to higher temperatures in order to damage or kill cancer cells by inducing cell apoptosis (Kerr et al. 1994). The concept of hyperthermia has been introduced in “clinical” practice many centuries ago by Greeks, Egyptians, Romans, and Indians. During the nineteenth century, it was observed that fever can cause tumor regression (Moyer and Delman 2008) and scientific studies were performed to treat cervical cancer by hyperthermia (Baronzio and Hager 2006). Beginning with 1970, the cancer treatment by hyperthermia was taken more seriously and controlled clinical trials started to be conducted. It has been discovered that cancer cells undergo apoptosis at temperatures of 42–45 C in contrast to healthy cells that are able to withstand those temperatures (Cavaliere et al. 1967). Depending on the location, depth, and stage of the malignancy, three main types of hyperthermia have been developed for clinical applications: whole body, regional, and local hyperthermia. In the case of deep-seated and propagated metastasis, whole-body hyperthermia is used. In this case, the entire body is heated up through hot water baths, electric blankets, hot wax, thermal chambers, or infrared radiators (Chicheł et al. 2007). Heat delivering to advanced stage tumors is realized by regional hyperthermia by means of thermal perfusion or external arrays of applicators (Falk and Issels 2001). The treatment of localized superficial tumors is often carried out by local hyperthermia, in which the heat is applied using electromagnetic waves such as radio waves, microwaves, and ultrasound, generated by applicators placed at the surface or under the skin of superficial cancer. Although in local hyperthermia, there is a better control of the area exposed to heat and a better heat uniformity, canceling the drawbacks of the first two types of hyperthermia, it is mainly focused on small and superficial cancer regions. The small penetration depth of the generated heat (in the order of a few centimeters) hampers its utilization for the cure of deep cancerous regions. However, deep cancer cell therapy can be achieved by replacing the heating sources with MNPs delivered only to the cancer cells. The capability of MNPs, once internalized in cancer cells, to convert electromagnetic energy into thermal energy, upon their exposure to an external alternating magnetic field (AMF), allows to locally raise the temperature of the cancerous region up to a level at which cellular apoptosis can be initiated. As such, the new noninvasive local hyperthermia method, called magnetic hyperthermia (MH), has become one of the most promising innovative cancer therapies (Piñeiro et al. 2015). It possesses numerous advantages over “traditional” therapies, mostly relying on the physico-chemical properties of MNPs. First, the MNPs can be potentially injected anywhere in the body, the injection being

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less invasive and allowing the treatment of all kinds of tumors with limited side effects (Nedelcu 2008). Second, the MNPs can be functionalized with a recognition moiety (i.e. antibodies, proteins) in order to increase the selectivity to malignant cells, therefore, increasing the internalization of the MNPs in a specific type of cancer cells (Cherukuri et al. 2010). Nevertheless, the MNPs can be magnetically targeted toward the cancer region by using an external magnetic field gradient. Once the MNPs have been internalized into the cancer cells, they can remain inside the cells even after their multiplication, meaning that a subsequent hyperthermic treatment can be applied without large reinjection of MNPs (Jordan et al. 1999). It is known that at room temperature, the macroscopic magnetic materials hold a permanent magnetic dipole moment. All the individual magnetic spins originating from electrons movements are aligned along a particular direction called the easy axis. As a result, the individual magnetic spins can possess two opposite orientations (up and down). These two orientations are separated by a barrier of magnetocrystalline anisotropy energy. When the size of the magnetic materials is reduced to the nanoscale, up to several tens of nanometers, this energetic barrier can be overcome with the aid of the thermal energy. Other ways saying, the magnetic dipole moment of MNPs is not anymore fixed along the easy axis as in the case of macroscopic magnetic materials. This new magnetic property is known as superparamagnetism (SP). In this novel state, the value of the magnetization (which basically represents the sum of all individual magnetic spins) is randomly distributed by the thermal effect. Upon the application of an external AMF, all the individual magnetic spins are flipped, while the magnetization direction is reversed. The provided magnetic energy is released as heat in a phenomenon known as Neel relaxation. The delay between the application of the AMF and the magnetic spins flipping gives rise to a torque that leads to the rotation of MNPs in liquids. The rotational friction between MNPs and the liquid environment also produces heat in a process described as Brownian relaxation. The capacity of MNPs to generate heat under an external AMF is quantified by the specific absorption rate (SAR) or specific loss power (SLP). This parameter provides a measure of the rate at which energy is absorbed per unit mass of MNPs. The SAR values strongly depend on the magnetic properties of MNPs (saturation magnetization, coercive field, and magnetic anisotropy) which in turn are governed by the structure, size, size distribution, shape, and composition of MNPs (Périgo et al. 2015). On the other hand, the SAR values can theoretically be increased as much as necessary, by increasing the frequency (f) and the amplitude (H) of the applied AMF (Glöckl et al. 2006). From the practical point of view, this approach is limited by difficulties in designing equipment able to generate large f and high H and, more importantly, by the increased harm produced to healthy cells as a consequence of the occurrence of eddy currents in conducting media (Spirou et al. 2018). For clinical applications, several safety conditions in terms of the H × f product were proposed (Mamiya and Jeyadevan 2019). Based on real tests on patients who were exposed to AMF for a duration that exceeds one hour, according to Atkinson–Brezovich criterion, it was largely accepted that the product H × f should be limited to 5 × 108 A m−1 s−1 (Hergt and Dutz 2007). This limit can be increased 10 times if the treatment is applied to small body regions (Hergt and Dutz 2007). Two classes of SPIONs, magnetite (Fe3O4), and maghemite (Fe2O3) have been approved for clinical use by FDA for MRI applications. They have been both tested in vivo for clinical MH therapy (Maier-Hauff et al. 2011; Wilczewska et al. 2012). In Europe, this form of therapy was clinically approved in the case of glioblastoma treatment. A clinical trial was also performed on prostate cancer (Maier-Hauff et al. 2011). Since the SAR values of spherical SPIONs (having a diameter of ~10 nm) are very low, drastically decreasing when they are localized into cells or tissues as a consequence of the intracellular clustering (Hilger et al. 2005), the SPIONs were not able to deliver

2.2 Biomedical Applications

sufficient heat to completely destroy the tumors. As such, for a complete elimination of the tumor, the MH has been used in conjunction with other therapies (chemo- and/or radiotherapies). In this case, aggressive side effects have been observed. As a result, the scientific community involved in MH research has focused on the elaboration of biocompatible iron oxide MNPs (IOMNPs) with enhanced magnetic properties and better MH performance. They have to be capable of completely destroying the tumors at doses below their intrinsic toxicity and safety levels of AMF. In order to accomplish this goal, two major scientific strategies emerged. The first strategy consisted in increasing the size of SPIONs, by keeping them in the SP limit, thereby increasing the Ms and consequently their SAR values. The Neel relaxation, which prevails when SPIONs are confined inside cellular endosomal compartments due to the considerable reduction of Brownian relaxation, is governed by the magnetic anisotropy. In the case of MNPs with large surface to volume ratio, surface contributions to magnetic properties become significant. Hence, the magnetic anisotropy of MNPs is dominated by the surface anisotropy, which originates from the spin direction discrepancy between core and surface. As such, it is directly associated with MNPs shape. This is the reason why the second strategy focused on controlling the shape of SPIONs by using different synthesis methods. The influence of the mean size of SPIONs on SAR values has been the subject of many studies. For instance, Jeun et al. reported an increase of the SAR values from 45 to 322 W gFe−1 H × f = 1.3 × 109 A m−1 s−1) when the SPIONs diameter is increased from 4.5 to 22.5 nm (Jeun et al. 2012). Other studies reported maximum SAR values of 447 W gFe−1 (H × f = 9.8 × 109 A m−1 s−1) (GonzalesWeimuller et al. 2009), 702 W gFe−1 (H × f = 6.3 × 109 A m−1 s−1) (Müller et al. 2013) and 950 W gFe−1 (H × f = 18.9 × 109 A m−1 s−1) (Lévy et al. 2008) for SPIONs with mean diameter of 14, 15.2 and 17.7 nm, respectively, synthesized using different protocols. Finally, Fortin et al. demonstrated both experimentally and theoretically that the SAR values of SPIONs increase from 4 to 1650 W gFe−1 (H × f = 17.5×109 A m−1 s−1) when the mean SPIONs diameter is increased from 5 to 16.5 nm (Fortin et al. 2007). Besides the mean size of SPIONs, their size distribution can have a significant impact on the SAR value. As shown by Gazeau et al., the size selection of SPIONs with 30 nm in diameter increases their heating performance to 600 W gFe−1, at clinically relevant conditions (H × f = 4.1 × 109 A m−1 s−1) (Gazeau et al. 2008). An alternative approach for increasing SPIONs heating rates turned out to be the control of their surface coating. It has been shown that dextran-coated SPIONs with a diameter of 7 nm display a SAR value of 626 W gFe−1 (H × f = 6.25 × 109 A m−1 s−1) (Mornet et al. 2004). Liu et al. reported a maximum SAR value of 930 W gFe−1 (H × f = 10.8×109 A m−1 s−1) when SPIONs with a diameter of 19 nm are coated with a 6 nm shell of phosphorylated methoxy polyethylene glycol 2000 (Liu et al. 2012). Interestingly, the high heating capacity of PEGylated SPIONs is maintained in various physiological conditions. On the other hand, the inorganic coating can also improve the SAR value of SPIONs. For example, Mohammad et al. found that the hyperthermic effect of SPIONs is four- to fivefold enhanced (920 W gFe−1) on coating with a gold shell of 0.5 thickness (Mohammad et al. 2010). A maximum SAR value of 1300 W gFe−1 (H × f = 7.9×109 A m−1 s−1) was measured for dumbbell-like shaped dimers formed by an iron oxide domain of 24 nm in size and a gold seed of 9 nm in diameter (Guardia et al. 2017). When the SPIONs size exceeds the SP limit, the thermal energy cannot overcome anymore the barrier of magneto-crystalline anisotropy, and the MNPs acquire a permanent magnetic dipole moment, pointing in the direction of the easy axis. The MNPs become ferromagnetic at room temperature, developing hysteresis loops, which are characterized by Mr and coercivity (Hc – magnetic field strength required for demagnetization). The MH properties of ferromagnetic IOMNPs (FeMIONs) are now dictated by their dynamic hysteresis behavior (Carrey et al. 2011). The synergistic

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contribution from the hysteresis and susceptibility (Neel and Brown) loss enhance the SAR values of FeMIONs in comparison with SPIONs. Several research teams have obtained the following maximum SAR values for FeMIONs of different diameters synthesized via thermal decomposition of magnetic precursors in organic solvent: 650 W gFe−1 (H × f = 19.1 × 109 A m−1 s−1) for 52 nm FeMIONs (Nemati et al. 2018); 716 W gFe−1 (H × f = 7.75 × 109 A m−1 s−1) for 22 nm FeMIONs (Chen et al. 2013); 801 W gFe−1 (H × f = 13.2 × 109 A m−1 s−1) for 28 nm FeMIONs (Mohapatra et al. 2018) and 2560 W gFe−1 (H × f = 6.7 × 109 A m−1 s−1) for 40 nm FeMIONs (Tong et al. 2017). The increase of FeMIONs sizes can be realized up to a certain threshold value; above it, the FeMIONs might enter into a multimagnetic domains state that will lead to a decrease in their SAR values (Chen et al. 2013; Mohapatra et al. 2018; Nemati et al. 2018). Despite the large amounts of generated heat, FeMIONs are less favorable for biomedical applications due to their colloidal instability and Hc that facilitate their aggregation. The dipole–dipole interactions manifested between FeMIONs significantly influence their heating efficiency (Serantes et al. 2010; Salas et al. 2014; Coral et al. 2016). But when these interactions, coupled with the uniaxial shape anisotropy, will arrange (Toulemon et al. 2016) or align (Jiang et al. 2016) the FeMIONPs into chain-like superstructures, their Hc and Ms will increase. Consequently, the heating performances will be enhanced as it was shown theoretically (Serantes et al. 2014) and experimentally (Myrovali et al. 2016). Through polyol-mediated synthesis, the stabilization of the FeMIONs may occur as multicore aggregates: nanoclusters (Sakellari et al. 2016), hollow nanospheres (Gavilán et al. 2017), and nanoflowers (Hugounenq et al. 2012; Gavilán et al. 2017). Due to the collective spin rotation, the SAR value of these aggregates is much greater than of their constituents. For instance, nanoflowers of 50 nm consisting of spherical FeMIONs of 11 nm displayed SAR values of 1790 W gFe−1 (H × f = 7.7 × 109 A m−1 s−1) (Hugounenq et al. 2012), while nanoflowers of 60 nm consisting of spherical FeMIONs of 22 nm presented SAR values of 1180 W gFe−1 (H × f = 17 × 109 A m−1 s−1) (Gavilán et al. 2017). A particular class of iron oxide MNPs that hold great potential for MH applications are the magnetosomes, produced by magnetostatic bacteria. Unlike chemically synthesized iron oxide MNPs, the magnetosomes are directly synthesized in chain-like structures consisting of perfectly stoichiometric nanocrystals with controlled sizes and shapes, surrounded by a biocompatible membrane. These characteristics reduce magnetosomes’ cellular toxicity. At the same time, they are able to deliver large amounts of heat (Prabhu 2016; Cypriano et al. 2019). For instance, two studies reported SAR values of 880 W gFe−1 (H × f = 5 × 109 A m−1 s−1) (Muela et al. 2016) and 960 W gFe−1 (H × f = 4 × 109 A m−1 s−1) (Hergt et al. 2005) for magnetosomes produced by the same bacteria: Magnetospirillum gryphiswaldense. As shown by Alphandery et al., chains of magnetosomes inside Magnetospirillum magneticum strain AMB-1 bacteria yielded a SAR value of 864 W gFe−1 (H × f = 7.6 × 109 A m−1 s−1) (Alphandéry et al. 2011). It was enhanced up to 1242 W gFe−1, upon the extraction of magnetosomes chains from bacteria, potentially due to the Brownian friction within the liquid. The removal of the membrane surrounding the magnetosomes followed by the disruption of the chains resulted in a decrease of the SAR value down to 950 W gFe−1. The highest SAR values reported so far were obtained for magnetosomes inside M. gryphiswaldense bacteria dispersed in water: 2400 W gFe−1 (H × f = 9 × 109 A m−1 s−1) (Gandia et al. 2019). The heating efficiency of the magnetosomes was reduced by half (~1200 W gFe−1), when the bacteria were randomly distributed in 2% agar medium. When bacteria were aligned parallel to the AFM, the SAR values almost returned to its initial value (2100 W gFe−1). This could be a strong evidence of the fact that in water, the bacteria align parallel with the AFM. In this case, the Brownian relaxation of the magnetosomal chains played a minor role being embedded in bacterial matrix. As a consequence, their mutual magnetic interactions are strongly reduced. When these bacteria have been internalized in human lung carcinoma cells A549, the cellular viability and growth were not

2.2 Biomedical Applications

affected. But the MH experiments, performed on these cells, strongly affected the cancer cell proliferation, making these bacteria promising candidates for cancer applications. Spherical IOMNPs exhibit multiple facets featuring many edges and corners. This type of curved morphology displays many disordered surface spins. The large surface canting effects and high-surface anisotropy strongly affect the heat dissipation properties of spherical IOMNPs (Noh et al. 2017). As it was pointed out before, the second strategy for heat generation improvement consisted in tuning the effective anisotropy of IOMNPs by modifying their shape. It has been theoretically demonstrated that cubic MNPs have lower surface anisotropy compared to spheres due to a smaller amount of disordered spins (4 vs. 8%). Several experimental studies have confirmed this phenomenon. The comparison between cubic and spherical IOMNPs, with similar magnetic volumes, show an important increase of SAR values in the case of cubic IOMNPs: 356.2 vs. 189.6 W gFe−1 (H × f = 6 × 109 A m−1 s−1) (Bauer et al. 2016); 314 vs. 140 W gFe−1 (H × f = 20 × 109 A m−1 s−1) (Das et al. 2016); 395 vs. 150 W gFe−1 (H × f = 19.1 × 109 A m−1 s−1) (Nemati et al. 2018) and 1963 vs. 410 W g−1 (H × f = 6.6 × 109 A m−1 s−1) (Elsayed et al. 2017). An extensive research on the heating properties of cubic IOMNPs with sizes ranging from 13 to 38 nm has been performed by Guardia et al. under different conditions of field and frequency (Guardia et al. 2012, 2014). They found that the nanocubes with a mean size of 19 nm exhibit SAR value as high as 2453 W gFe−1 (H × f = 15 × 109 A m−1 s−1). Smaller SPIONs nanocubes (13 nm) and larger FeMIONs nanocubes (38 nm) exhibited lower heating performances (10 kT) leads to a rapid aggregation of the nanoparticles in a disordered assembly due to kinetically trapped structure. Moreover, for moderately attractive potentials (2–3 kT), the formation of more ordered clusters is obtained due to the higher degree of reversibility in the interaction between the nanoparticles through the breakdown of the bonds activated thermally. In this context, the clustering process should take place near equilibrium to obtain a slow and controllable process. Furthermore, it is demonstrated that long-range interactions concerning the assembling component sizes were preferred. However, many interaction forces, as van der Waals forces, act only on very low molecular distances. Therefore, to apply them on a larger molecular scale and to allow assembly, it needs to use small components, more precisely in the order of nanometers (2–30 nm). Numerous factors influencing the strength of the colloidal interaction between nanoparticles are taken into account to obtain a monodisperse suspension of selectable dimensions of clusters with

3.2 Clustering Theory

internal order. These factors could be considered as control parameters during the formation of clusters. For magnetic nanoparticles, van der Waals attraction and the dipole–dipole interaction of magnetic nanoparticles can lead to well-ordered assembly structures. Therefore, in this section, we aim to describe the characteristics of various classes of interparticle interactions, as van der Waals, electrostatic, magnetic, and molecular at the nanoscale. In this regard, we focus on the nanoscale effects that emerge with respect to the smaller molecular systems or, the larger colloids. Furthermore, considerable attention has been posted on theoretical tools to describe interactions at different levels of approximation and finally on their limits. Each described interaction was accompanied by numerous experimental works to gain a better understanding, by allowing us to evaluate the effects of the assembling process for different interactions. Therefore, our purpose is to describe a general view of the different interparticle potentials to be implemented in the nanoparticle assembly.

3.2.1 Molecular Interaction A variety of attractive short-range forces, such as covalent bonds, dipolar interactions, hydrogen bond, and donor–acceptor interaction, are used to build both complex molecules and crystals (Desiraju 1995; Moulton and Zaworotko 2001). In this regard, hydrogen bonds allow the organization of nanorods in linear chains (Thomas et al. 2004; Guo and Dong 2011). Besides, there are reports in the literature on DNA as a linker for assembling particles selectively and reversibly (Alivisatos et al. 1996; Mirkin et al. 1996). Finally, other examples relate to dipole–dipole interactions between groups of photoisomerizable surfaces allowing rapid assembly and disassembly of ordered nanoparticles (Steiner 2002). In this context, these interactions give rise to interparticle potentials that allow the organization in highly ordered structures. These forces depend on the number of individual bonds (covalent or noncovalent) and the binding force characteristic of the molecular interaction. While the interactions can be quite weak, the forces between suitably functionalized surfaces can be quite strong due to the interaction of many molecular groups. These interactions show a variable length from nanometers to angstroms (molecular size λ) and depend on the specific interacting molecules. Therefore, the interactions will not take place based on the distance, but in contrast, they will be dependent on the λ factor as in an on–off mechanism. In this respect, the hydrogen bonds, as well as the polar interactions, are electrostatic (Abe et al. 1976; Steiner 2002) by allowing the nanoparticles (Johnson et al. 1997; Boal et al. 2000; Kimura et al. 2004) and nanorods (Thomas et al. 2004; Sun et al. 2008; Guo and Dong 2011) assembly. The hydrogen bonding is shown to induce the aggregation of metal nanoparticles functionalized with hydrogen bonding ligands where the degree of aggregation and order depends on the strength of the individual hydrogen bonds formed. Therefore, Nonappa and Ikkala (2018) in their work, provide an example, how the anisotropic colloidal interactions of H-bonding nanoparticles can direct colloidal self-assemblies of nanorods. Recently, Yue et al. (2015) described the formation of ZnO nanoparticle chains and demonstrated the importance of the nanoparticle–solvent interactions, notably, the hydrogen bond, in obtaining the stability of the chain structure by using different simulations. Therefore, the Molecular Dynamic (MD) confirmed the role of hydrogen bonding in stabilizing the chain-like structure, and Dissipative Particle Dynamics (DPD) simulations revealed the importance of nanoparticle–solvent interactions in guiding anisotropic self-assembly.

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3.2.2

Van der Waals Forces

The interactions between the most straightforward molecular systems with no permanent charges or dipoles are always due to van der Waals forces, which originate from the electromagnetic fluctuations due to the continuous interactions that occur between opposite charges, within atoms and molecules (Bishop et al. 2009; Stolarczyk et al. 2016). These floating dipoles induce the polarization of nearby atoms or molecules, causing an induced dipole-like interaction (Hamaker 1937). These fluctuations depend on the different parameters such as the fluctuation of the charge distributions, the rotating dipole, and the dipole-induced interactions of the nearby molecules or atoms. Moreover, the interactions can be classified into dispersion-type (London), orientation-type (Keesom), or induction type (Debye) contributions (Lin et al. 1989). The dielectric properties are significant since the electromagnetic field of the permanent dipole influences the interaction. A relation of proportionality between the constant quantifying the interaction strength (Hamaker constant) and the static and frequency-dependent material polarizability (dielectric function) was demonstrated. When the interacting objects increase their distance, a decrease in the force between inductive and induced dipoles is obtained, thus reducing the strength of the interaction, which is called delay. Hamaker (1937) demonstrated how the particle interaction depends on the van der Waals forces, thus elaborating an analytical expression. This expression shows an attractive interaction between similar materials and a repulsive interaction for different materials that act through a third medium (Casimir and Polder 1948). A different approach, element – surface integration approach was demonstrated by Bhattacharjee and Elimelech (1997), which allowed the calculation of the interaction energy between objects of arbitrary form. Furthermore, a further expression to describe the interaction energy of the spheres is the Derjaguin approximation. This expression was applied when the interaction is smaller than the particle size. Therefore, this approximation will hardly apply to interactions between nanoparticles. Moreover, the van der Waals forces between colloidal particles were calculated using Dzyaloshinskii–Lifshitz–Pitaevskii (DLP) (Dzyaloshinskii et al. 1992; Lifshitz and Hamermesh 1992) by combining it with the Derjaguin approximation (Levins and Vanderlick 1992), to account for particle curvature with spherical or rod-shaped particles. For intermediate separations, a standard approach is to use an additive Hamaker approach (1937). Briefly, several methods to describe different types of nanoparticles were mentioned. In this regard, the DLP and Hamaker approaches gave consistent results for higher nanoparticle distances, compared to a certain disagree results for lower nanoparticle distances (10% of the diameter of the nanoparticles) (Bishop et al. 2009). However, the Hamaker approximation (1937) is applied due to the challenge to observe short distance nanoparticle interactions to obtain ordered assembly (Ninham 1999). Moreover, by controlling the van der Waals interactions through the use of appropriate stabilizing ligands or solvents, it is possible to drive the two- and three-dimensional assembling processes of different nanostructures, nanoparticles (Harfenist et al. 1996), and nanorods (Sau and Murphy 2005). By increasing the nanoparticle concentration, until reaching a solubility threshold, the nanoparticles nucleate and grow, to obtain an ordering assembly increase. It was interesting to observe how the van der Waals forces influence the polydispersed nanoparticle assembling by improving their final arrangement through a size-selective sorting effect (Ohara et al. 1995; Murthy et al. 1997; Lin et al. 2000). This effect was easily represented in two dimensions and resulted from the sizedependent magnitude of the van der Waals interaction. The van der Waals forces can also influence the highly anisotropic nanoparticle assembly as nanorods (Jana 2004) and rectangular nanoparticles (Sau and Murphy 2005). In this regard, the nanorods interaction builds a side-by-side

3.2 Clustering Theory

assembling rather than an end–end arrangement due to higher van der Waals forces. In this regard, recently, Rance et al. (2010) demonstrated how van der Waals interactions between nanoparticles significantly and crucially depend on the structural parameters of the component nanostructures. Moreover, the composition and structure of nanoparticle assemblies through van der Waals interactions was precisely controlled.

3.2.3 Magnetic Interaction The assembly of the magnetic nanoparticles determines an alignment of the single magnetic moments in the direction of the surrounding magnetic field due to the influence of the nearby magnetic nanoparticles or to the applied external magnetic field, by allowing to have a specific directionality of interaction, inducing an increase (Bishop et al. 2009) (Figure 3.1).

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Figure 3.1 Interactions between magnetic nanoparticles. (a) Schematic illustration of the behavior of weakly interacting in magnetic particles; (b) interaction potential between superparamagnetic particles; (c) interactions between nanorods magnetized along their long axis and interacting end to-end (left) or side-byside (right). Source: Adapted with permission from Bishop et al. (2009). Copyright 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Thus, the applied magnetic field will cause the formation of aggregate phases from particles with smaller dipole moments than would be possible in the absence of the magnetic field (specifically, for about 2 kT). Moreover, the resulting phases are oriented concerning the field. Therefore, by using magnetic nanoparticles with characteristic dipole energy between 2 and 8 kT, it is even possible to induce an assembling/disassembling process by applying/removing the magnetic field as reported in Stolarczyk et al. (2016). These interactions allow the formation of chains (Tanase et al. 2001; Wu et al. 2009), wires (Tanase et al. 2005), or rings (Tripp et al. 2002, 2003) of onedimensional magnetic nanoparticles when the magnitude of the interaction exceeds about 8 kT as reported by Goyal et al. (2008). The super assembly can improve the order of the nanostructures due to the coherent alignment of the magnetic moments of all the nanoparticles (Pileni 2001; Singamaneni and Bliznyuk 2005). However, the magnetic interactions are not the only forces responsible for the assembling process. Indeed, they compete with other effects, such as those of van der Waals (and possibly other types) which become increasingly important as the size of the nanoparticles decreases. Lalatonne et al. (2004) studied the influence of two different interactions during the assembling process, van der Waals interactions and dipolar strength. They studied the transition of maghemite nanocrystal organization from chain-like to random structures when nanoparticle solutions were evaporated under a magnetic field. It was observed that the dipole–dipole interactions between the maghemite particles do not have sufficient strength to cause the formation of chains. In contrast, when the distance between the nanocrystals is short, van der Waals forces determine assembling. An exciting example of self-assembly by using magnetic forces was reported by Sim et al. (2015). Their work was about the encapsulation of Fe3O4 nanoparticles within the chaperonin GroEL protein. The chaperonin was decorated with metal ion-binding molecules, triggering the polymerization in fibers a few microns long in the presence of Mg2+. These fibers subjected to an external magnetic field were assembled in thick bundles, dismantled when the magnetic field was removed. The properties of the nanoparticle assembling depend strongly on the particle size. Butter et al. (2003) studied the influence of nanoparticle size on the assembling process. An increase of their size, a sudden transition from separate particles to disordered, oriented linear aggregates and branched chains or networks is observed. When these aggregates are placed within a magnetic field, these chains align and form thick, elongated structures.

3.2.4

Electrostatic Interaction

The surface electrostatic charge of the nanoparticle is a fundamental force to obtain interactions with the other nanoparticles. This charge may be due to several factors, such as a specific effect of ions absorption from the solution, a protonation/deprotonation effect of the surface groups, or the presence of charged ligands. Therefore, these interactions affect the situation of hydrophilic nanoparticles dispersed in polar solvents, such as water, unlike hydrophobic nanoparticles, dispersed in nonpolar solvents. The reason lies in the attraction of the counterions in solution by the charged nanoparticles, thus forming an electrical double layer (Bishop et al. 2009). In this regard, the Gouy–Chapman model approximates the electrostatic potential in the electric double layer through the combination of the Poisson equation with a Boltzmann ion distribution. Therefore, the obtained equation, called Poisson–Boltzmamm, allows the determination of the concentration profile of the ionic species outside a charged surface. The free energy of the interaction upon double-layer overlap depends on and is associated with the potential electrochemical change of the dissolved ionic species. The energy interaction can be defined as electrostatic interaction or doublelayer electrical interaction due to the rigid coupling of ion concentration and electrical potential obtained through the Poisson–Boltzmann equation. The attractive or repulsive strength depends

3.2 Clustering Theory

on the surface charge and the decay properties of the electric field. While the former depends on the surface charge density on the nanoparticle, the latter depends on the screening ability of the dissolved ions expressed by the inverse Debye length. By modifying both the surface charge and the Debye length of the double layer, an electrostatic interaction regulation was allowed (Stolarczyk et al. 2016) (Figure 3.2). Therefore, the assembly of the nanoparticles is induced by the variation of the interaction force. When nanoparticles within a dispersion exhibit opposite sign charges, the assembly process begins with the alternating placement of the nanoparticles (Lalatonne et al. 2004) or the formation of coreshell super-structures (Sim et al. 2015). As previously reported, the surface charge determines aggregation or repulsion between the nanoparticles. Furthermore, the nanoparticles randomly and uncontrolled aggregate at the isoelectric point. Greater control of the assembling process is

(a) Φ Electrostatic Total interaction

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Figure 3.2 Electrostatic stabilization of the nanoparticles by (a) Derjaguin–Landau–Verwey–Overbeek (DLVO) colloidal-stability theory-based interaction potential profiles of nanoparticles combining van der Waals and electrostatic forces as a function of separation distance. (b) Interaction potential profiles for sterically stabilized nanoparticles as a function of separation distance. Source: Stolarczyk et al. (2016). Reproduced with permission from John Wiley & Sons.

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obtained for the pH-sensitive ligands on the surface of the nanoparticles. The latter can be protonated or deprotonated, thus altering the surface charge density. In this case, the charge and the surface potential changes are observed during the interaction between nanoparticles (Butter et al. 2003). Therefore, when the nanoparticles are very far apart, the charge is shielded; in contrast, the interactions occur when the nanoparticles get close. Fresnais and coworkers (2009) described the role of desalting kinetics on the nanoparticle clustering. About the assembly monitoring, different procedures were tested as direct mixing, dialysis, dilution, and quenching. Moreover, the kinetics of assembly of the electrostatic clusters were led by the rate dIS/dt at which the salt was removed from the solution, where IS denotes the ionic strength. Moreover, it was shown how the assembling process was driven by the desorption–adsorption transition of polymers on the nanoparticles surface. An ionic strength decrease caused the polymeric nanoparticles clustering. Furthermore, it was demonstrated that by regulating the desalination kinetics, the size of the clusters varied from 100 nm to over 1 μm. Meyer et al. (2006), in his work studied the influence of charges on the nanoparticles assembling process. It was demonstrated how the continuing accumulation of charges during the clustering process led to an increase in electrostatic repulsion. This phenomenon can be used to regulate the cluster growth process. On the base of the previously described work, Xia and coworkers (2012) showed the spontaneously assembling inorganic nanoparticle with nonuniform distributions in superparticles with core-shell morphologies. The electrostatic repulsion and the van der Waals attraction led this self-growth process.

3.3

Clustering Methods

In the last two decades, considerable efforts have been undertaken for the development of approaches for the controlled clustering of multiple magnetic nanoparticles. Several groups have also provided proofs of concepts for the applications of such magnetic clusters as sorting probes for cells/analytes separation, as vehicles for magnetically guided drug delivery, or as contrast agents in magnetic resonance imaging. In the following subsections, some relevant studies on the topic are discussed, focusing on preparation methods, on main properties enhancements, and significant achievements. The studies are grouped according to the clustering approach or the molecular coating class (Scheme 3.1).

3.3.1

Synthetic Approach

The nanostructures reported here are not obtained by the assemblies of presynthesized nanoparticles, but by promoting the in situ nucleation of the magnetic core in a molecular or polymeric matrix. Most of the nanostructures were prepared by using a solvothermal approach at high temperature in autoclave, but some additional methods will also be considered in this section. In 2005, Deng et al. in a pioneering article described for the first time the solvothermal synthesis of magnetic microsphere of different crystal phases (Fe3O4, MnFe2O4, ZnFe2O4 or CoFe2O4) by promoting the nucleation of magnetic nanoparticles in the presence of ethylene glycol, sodium acetate, and polyethylene glycol and obtaining regular magnetic sphere from 200 to 800 nm (Deng et al. 2005). Ge et al. proposed a one-pot preparation route based on the synthesis of magnetic nanoparticles followed by their controlled clustering at high temperature in the same reaction flask (Ge et al. 2007). In detail, a mixture of iron chloride, diethylene glycol, and poly(acrylic acid) was heated at high temperature, 220 C; then the hot-injection of sodium hydroxide induced first the

3.3 Clustering Methods

Scheme 3.1 Schematic illustration of magnetic nanoparticles clustering and covering some of the principal superstructures reported in the literature.

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nucleation of single crystals with a diameter of 6–10 nm, and subsequently, caused their agglomeration in flower-like nanostructures. The cluster size could be tuned from 30 to 180 nm by simply changing the rate of hydrolysis of NaOH. By performing the synthesis under nitrogen reflux in flask, instead of using the autoclave, Cha et al. investigated the intermediate steps that bring to the cluster formation (Cha et al. 2013). The authors suggested that at the initial stage, the hydrolysis/condensation of FeCl3 occurred to generate an amorphous ferrihydrite. Whereupon, the dehydration process induced a phase transformation to crystalline lepidocrocite, followed by a second phase transformation to magnetite crystals. According to this solid-state phase transformation model, the final grains of magnetic nanoparticles were generated directly into the resulting cluster matrix that acted as a synthetic environment. A similar approach has been exploited recently by Casula et al. by introducing a doping element in the superparamagnetic nanoparticles to enhance the magnetic properties of the nanostructure. Manganese was chosen as a typical dopant, mainly used for the replacement of Fe(II) in the lattice of magnetic phases. In detail, a mixture of iron(III) chloride and manganese(II) chloride salts was used as metal precursor. Interestingly, the presence of dipolar interactions induced a blocked state at room temperature, with evidence of coercivity at 310 K. The obtained structures were investigated both in MRI, thanks to their considerable performances, by showing a maximum value of r2 of 571 mM−1 s−1 at 0.5 T, and magnetic hyperthermia (Casula et al. 2016). Also, Lu et al. in 2012 reported a one-pot approach to synthesize the magnetic microspheres by using a solvothermal method. In detail, iron chloride, sodium polyacrylate, sodium acetate, and ethylene glycol were mixed and autoclaved at 210 C for 10 hours. During this process, first, some magnetic seeds were formed and subsequently assembled in controlled clusters, protected by a layer of PAA. The microsphere sizes (from 100 to 500 nm) were tuned by simply modifying the water amount in the reaction. These nanosystems exhibited a quasi-superparamagnetic behavior with an excellent saturation magnetization of 81.6 emu g−1 (Lu et al. 2013). A similar synthetic approach

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has been proposed recently with the introduction of urea in the precursors mixture, obtaining dense nanoclusters with a size ranging from 250 to 640 nm (Ganesan et al. 2019). Lin et al. by using a similar method investigated the contribution of ethylenediaminetetraacetic acid disodium salt (EDTA-2Na) and sodium acetate in the formation of magnetic nanosphere. In this work, a growth–dissolution–regrowth model is reported for the formation of single crystals in the superstructure. The sodium acetate amount governed the size of the magnetic grains, ranging from 5 to 30 nm. In contrast, the EDTA amount and the sonication pretreatment time were considered for controlling the overall size of the nanocluster (Lin et al. 2013). The synthesis of magnetite nanoclusters by using sodium citrate within a mixed-solvent system of diethylene glycol and ethylene glycol was evaluated by Wang et al. in 2015. In this solvothermal method, the sodium citrate acted not only as a ligand for the stabilization of the resulting clusters but also as one of the key parameters to control the cluster size, ranging from tens to hundreds of nanometers (Wang et al. 2015). By using a similar approach, recently, another study reported the preparation of a multifunctional nanosystem. In this regard, the citrate-coated nanoclusters were first covered by a NIR molecule, namely cypate, and then enveloped in a red-blood-cell ghost membrane. The as-obtained biomimetic complex showed a significantly improved physiological stability and an enhanced tumor accumulation after intravenous injection in mice (Wang et al. 2020). In 2013, Daniele et al. adapted a classic coprecipitation reaction to functionalize magnetic nanoclusters through a modified copolymer by exhibiting an alkyne surface functionality. This structure can be exploited for rapid click chemistry functionalization. In details, poly(acrylic acid-co-propargyl acrylate) was used as a model, in which the acrylic acid guarantees for the carboxylate groups that anchor onto the iron oxide surface, whereas propargyl acrylate acts as the functional comonomer due to its general application in click reactions. The polymer was added just after the ammonium hydroxide addition in the nanoparticles synthesis, leading to the formation of the cluster with a hydrodynamic diameter around 150 nm. By AC susceptometry analysis, the authors observed that the relaxation time was dominated by Brownian relaxation, suggesting that the interaction between the nanoparticles and the copolymer arose before the clustering process (Daniele et al. 2013). Bain et al. proposed the synthesis of some polymeric capsules, namely polymersomes, by using an amphiphilic copolymer as lipid mimics. These vesicles were extruded by a dried film, after rehydration with a basic solution of sodium hydroxide, that filled the polymersome core. So prepared structure was used as nanoreactor for the in situ synthesis of magnetic nanoparticles. In detail, polymersomes were dispersed in a FeCl2/FeCl3 solution, and the mixture was electroporated to open up pores within the membrane. By this method, ultrasmall magnetic nanoparticles (average diameter of 2.5 nm) were coprecipitated in the bilayer of the polymersome (Bain et al. 2015). Hugounenq et al. exploited a polyol synthesis for the preparation of a multicore superstructure, henceforth referred to as nanoflower. These colloidal nanoparticles were obtained by alkaline hydrolysis of iron(II) and iron(III) in the presence of diethylene glycol and N-methyldiethanolamine, by addition of NaOH and annealing at high temperature (220 C). The flower-like structure resulted from the maghemite nanoparticles assembly whose size is about 11 nm, whereas the overall nanocluster size ranged from 24 to 55 nm. The magnetic nanoflowers exhibited a higher-level heating performance in magnetic hyperthermia, with a SAR value close to 2000 W g−1 (Hugounenq et al. 2012). Recently, these nanostructures have been used as a model for the in vivo analysis of heating performance once the nanomaterials are administered to tumor target. So the authors found that the suppression of effective heating efficiency is neither due to Brownian mechanism inhibition nor to particles aggregation, but it is mainly related to the irregular distribution of the nanomaterial in the tumor matrix (Coral et al. 2018).

3.3 Clustering Methods

3.3.2 Inorganic Coatings Various preparation methods of magnetic clusters considered inorganic coatings for the stabilization of multistructures. The magnetic nanoparticles encapsulation within a silica sphere is one of the most followed approaches, as described and developed by Taboada et al. First, the nanoparticles were aggregated in a controlled manner by a sol-gel method in a mixture of acetone and hexane. The magnetic clusters served as nucleation sites for the subsequent condensation of hydrolyzed tetramethoxy silane (TMOS), leading to the formation of the silica shell. The obtained structures had a diameter of approximately 100 nm, and the production of grams of magnetic clusters was demonstrated (Taboada et al. 2009). Also, Niu et al. chose the encapsulation into silica for the preparation of their nanocomposite (Niu et al. 2010). By using an oil-in-water approach, the hydrophobic magnetic nanoparticles were first incorporated into the copolymer micelles core composed of polystyrene100-block-poly(acrylic acid)16. Therefore, a silica layer was grown on top of the micelles by using 3-mercaptopropyltrimethoxysilane (MPMTS) as priming molecule. Also, in that case, nanostructures with a final diameter smaller than 100 nm were fabricated. Kralj and Makovec (2015) assessed the preparation of superparamagnetic nanostructures with highly anisotropic shapes, called nanochains. In this work, their group used some commercial nanoclusters, obtained through a nanoemulsion process and finally stabilized by a tuned silica shell. These nanostructures were formed by interaction between nanoclusters and a controlled magnetic field in presence of PVP molecules. By this way, the authors achieved the formation of small chains composed of different monomers, by tuning the field strength and exposure duration, the PVP concentration, and the stirring speed. The purpose of this clustering approach should lead to applications of the nanochains in the cancer treatment and in the ability to magnetically manipulate liquid and photonic crystals (Kralj and Makovec 2015). Recently, Tregubov et al. used a metal-organic framework as a substrate for the magnetic nanoclusters coating. The authors used the citrate-capped iron oxide nanoparticles as starting material, obtained by autoclave and by using urea as precipitant. This magnetic core with a size of 80 nm and composed by several single magnetic domains was further coated by a matrix of iron(III) trimesate (also known as MIL-100(Fe)) and synthesized by autoclaving the mixture of nanoparticles and metal precursor. Finally, a carboxymethyl dextran layer was grafted onto the surface of the system for achieving optimal colloidal stability. An advantage of such multilayered object was the assessed biocompatibility since the iron(III) trimesate can be readily degraded in physiological conditions because of the collapse of the framework in the presence of phosphates (Tregubov et al. 2018).

3.3.3 Polymer-Assisted Clustering Polymers, large molecules composed of many repeated subunits, are probably the most studied class of molecules used in the nanoparticle clustering. These compounds have several specific physical–chemical properties that allow to, first, help the nanoparticles assembly and, second, provide some specific functional groups on the surface for the conjugation of ligands. Di Corato et al. developed a strategy to cluster hydrophobic magnetic nanoparticles within a shell of an amphiphilic polymer, namely poly(maleic anhydride alt-1 octadecene) (Di Corato et al. 2009). The protocol was based on the controlled destabilization of a suspension of nanoparticles and polymer in tetrahydrofuran obtained with slow addition of acetonitrile. In the resulting clusters, nanoparticles were collapsed in the core, whereas the polymer enrolled the structure with a dense shell. The thickness of the coating was proportional to the polymer concentration, ranging from few to

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30–40 nm. In this contribution, the polymer was functionalized with an organic dye for cell separation and detection, but actually, the structure offered many possibilities of modification. By the same group, colloidal quantum dots were introduced in the assembly, creating a magnetic-fluorescent platform based on inorganic nanoparticles (Di Corato et al. 2011). CdSe@ZnS dots were dispersed in the nanoparticles suspension before the clustering, and the protocol was applied with no modification. Interestingly, the fluorescent nanoparticles were not collapsed in the core with the magnetic but were confined in the polymer shell, avoiding the fluorescent quenching of the resulting structure. This phenomenon was explained by a different grade of the insolubility of the nanoparticles in acetonitrile, due to the different surfactants on particles surface (TOPO and TOP on QDs, oleic acid, and oleylamine for magnetic nanoparticles). The functionalization with folic acid and the use of different QDs allowed performing a specific ligand separation and a multiplex analysis of sorted cells. As claimed before, this magnetic nanocluster was further modified with thermo-responsive polymer (Deka et al. 2011) or with silver nanoparticles nucleated in situ on the polymeric surface (Di Corato et al. 2012). A variant of this clustering method involves the aggregation of the nanoparticles (dispersed in tetrahydrofuran) by adding a volume of acetonitrile in a 1 : 1 ratio. By this approach, very dense and organized, but unstable, clusters were obtained. Thus, immediately after the clustering, a polymeric shell was grafted on the surface of the ordered assemblies of nanoparticles, by condensation of a solution of poly(maleic anhydride alt-1 octadecene) (Bigall et al. 2013). The separation of the two phases, clustering and polymer coating, was also investigated in a recent study, in which the hydrophobic nanoparticles were first collapsed in the above-described tetrahydrofuran/acetonitrile mixture and subsequently coated with a thermo-responsive hyaluronic acid derivative. By comparison with simultaneous one-pot clustering, the two-phases approach was considered more efficient to increase the concentration of nanoparticles in the structure core, with a consequence on the magnetic moment and magnetic responsiveness (Rippe et al. 2020). In the last decade, magnetic nanocubes have aroused interest in the field of materials science as a heat mediator, due to different crystalline and shape anisotropies, compared to the most common spheres, resulting in higher heat capacity (Guardia et al. 2012; Noh et al. 2012). From clustering point of view, this class of nanomaterial is not straightforward to be managed because of the strong interparticle interaction. Materia et al. modified the previously reported procedure for spherical particles adjusting the solvent mixture and the injection rate of the polar solvent. When clustered, the nanocubes showed a lower SAR value, due to the suppression of Brownian contribution into the blocked polymeric superstructure. On the opposite, the relaxivities analysis resulted in a very low r1 value and a definite increase of the r2/r1 ratio, in comparison to the individual nanocubes (Materia et al. 2015). Recently, the same group investigated how the heat performance of the iron oxide nanocubes could be preserved or even enhanced by clustering. A possible answer is represented by nanoparticles assemblies with a 2D arrangement. Very small clusters composed of two and three nanocubes, namely dimers and trimers, showed a SAR valued almost doubled if compared to individual nanoparticles. When the nanocubes number overcame the threshold of four particles per cluster, an impressive fall of SAR value was observed (Niculaes et al. 2017). Nanocubes assembled with a 2D-arrangement were also obtained by using an esterase-sensitive biopolymer as an encapsulating agent. The enzyme activity resulted in the disassembly of the multiparticle cluster and, as confirmation of the above-described study, in an enhanced SAR performance. In fact, the 2Dclusters were split into smaller clusters composed of very few particles, in a chain-like configuration (Avugadda et al. 2019). Another modified-amphiphilic polymer, poly(isobutylene-alt-maleic anhydride), was used for the fabrication of small nanocluster based on the assembly of hydrophobic nanoparticles. The maleic anhydrides of the polymer backbone acted as an anchor point for the addition of PEG

3.3 Clustering Methods

(10%), dopamine (70%) and cystamine, a disulfide linker (20%). The three ligands ensured, respectively, high biocompatibility to the cluster, a high affinity to the nanoparticles surface and an amine for an additional functionalization. Therefore, chlorin e6, a photosensitive drug, was linked to the cystamine for the preparation of this multifunctional polymer. The cluster was prepared by a solvent exchange strategy, mixing the chloroform-dispersed nanoparticles with a solution of the polymer in DMSO. After ultrasonication and evaporation of the chloroform, the DMSO was changed with water by dialysis. The resulting redox-responsive nanocluster was suitable for the detection of the high-reductive intracellular environment (typical of tumors) because of the cleavage of the disulfide bridge and the subsequent release of the drug, for MR imaging and the photodynamic therapy of solid tumors (Yang et al. 2018). Paquet et al. in 2010 reported the clustering process of hydrophobic nanoparticles in regular assembly assisted by sodium dodecyl sulfate (SDS). This was one of the first paper in which was obtained a fine control over the nanocluster size, ranging from 40 to 200 nm. The method was based on a microemulsion of two components: the fatty acid-coated nanoparticles dispersed in toluene and an aqueous solution of SDS. By ultrasonication and subsequent ripening at 90 C, the organic solvent was entirely evaporated, and dense spherical aggregates were obtained. Some key parameters, as surfactant and nanoparticles concentration, the volume ratio of the emulsion, were monitored to control the clustering process and the final diameter of the magnetic nanospheres. As shown in this contribution and also in more recent ones, the SDS clusters need an additional surface coating to stabilize the structure. In this chapter, a 20 nm-additional shell of polymethacrylate derivates was grafted on the cluster surface (Paquet et al. 2010). Starting from the SDS-coated cluster, the research group also investigated as the nature and the thickness of the additional polymer shell could vary the relaxivities of the magnetic clusters. By using a precipitation polymerization method, a pH-sensitive hydrogel coating composed of acrylic acid, N,N’methylenebis-acrylamide and N-isopropylacrylamide was polymerized onto the clusters. The hydrogel significantly enhances the transverse relaxation rates by lowering the diffusion coefficient of water molecules near the magnetic nanoparticles. By tuning the pH or the initial thickness of the hydrogel, an r2 increase (in comparison to the bare magnetic nanoparticles) was observed from 44% (low pH, the low water content in the thin shell) to 85% (neutral pH, the high water content in the thick shell) (Paquet et al. 2011). Also, Wu et al. in 2015, reported the clustering of hydrophobic magnetic nanoparticles by emulsification method assisted by SDS surfactant. A toluene dispersion of NPs was mixed with a SDS aqueous solution, and the mix was sonicated and kept at 90 C for two hours. The resulting cluster had a diameter below 200 nm and a fine distribution. To ensure higher nanosystem stability, a shell of polydopamine was polymerized on the cluster surface in alkaline conditions, starting from dopamine monomer. The polydopamine ensured a higher NIR absorption to the cluster, exploitable for photothermal therapy. In a proof of concept magnetophoresis experiment, cancer cells were incubated with polydopamine-nanocluster with an external magnet and irradiated with a 808 nm laser, achieving a 90% cytotoxicity at the highest concentration (Wu et al. 2015b). Starting from this protocol, Mandriota et al. evaluated many different parameters (choice and concentration of surfactant, size of nanoparticles, choice of organic solvent, oil/water phase ratio, and scalability) to produce clusters with a size around 100 nm. Then, a polydopamine shell was grafted on the cluster (from 4 to 27 nm), and the efficiency of a pHsensitive release was assessed, loading a chemotherapy drug as a model, the cisplatin. Below pH 5, an abrupt release of the drug was obtained after 24 hours, with a partial degradation of the nanocluster, and a release of nanoparticles, at pH 3 after 72 hours. In vitro experiments confirmed that nanocluster significantly improved the cellular uptake of the platinum drug, by increasing its cytotoxicity at low dose (Mandriota et al. 2019).

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Various encapsulation methods have been employed for the synthesis of iron oxide clusters by using block copolymers, either bihydrophilic or amphiphilic and stabilizing agents. In general, these methods involve the formation of micelles. Ai et al. reported the clustering of monodisperse iron oxide particles inside the hydrophobic core of micelles made of PEG-modified polycaprolactone polymer (Ai et al. 2005). These micelles were obtained by an oil-in-water approach performed via sonication; in detail, the nanoparticles and the polymer, dissolved in hexane, were dispersed in an aqueous polymer solution, and the resulting dispersion was sonicated, thus leading to the formation of the micelles, whose mean diameter was of 110 nm. Finally, the organic solvent was removed under reduced pressure. Following a similar approach, also block copolypeptide (Euliss et al. 2003) or copolymers of acrylic acid, styrenesulfonic acid, and vinylsulfonic acid have been studied (Ditsch et al. 2005). More recently, Schmidtke et al. reported a method for clustering colloidal nanoparticles by using a diblock copolymer system. The process was mainly described for magnetic nanoparticles, but a proof of clustering was also provided for semiconductor and plasmonic nanoparticles. First, the native ligand of nanoparticles was exchanged with polymer PI-DETA; then the coated-NPs were mixed with PI-b-PEG diblock copolymer and transferred in water by different injection approaches (manual, mechanical, and microfluidic). Finally, the polymer was thermally crosslinked by addition of a radical initiator. The resulting nanosphere was ultrastable and with a size ranging from 54 to 750 nm. The size was tuned by modifying the ratio polymer : NP, from 400 : 1 (smaller clusters) to 20 : 1 (larges ones). After magnetic characterizations (relaxometry, magnetization, and magneto-rheological measurements), the authors observed that the cluster magnetic moment derived by the sum of entrapped NPs moments and that the dipolar interaction between the NPs as the cause of collective effect observer in magnetic clusters (Schmidtke et al. 2014). Another block copolymer, namely poly(aspartic acid)-b-poly(ε-caprolactone), was used for the clustering of 12 nm-hydrophobic nanoparticles. The clusters showed an average diameter of 125 nm with good dispersion and an excellent r2 relaxivity (335 mM−1 s−1 at 1.5 T). In this study, the nanoclusters were exploited as a contrast agent for the labeling and the in vivo tracking of dendritic cell, achieving fine response for viability, proliferation, and differentiation capacity. The subcutaneous injection of labeled cells in mice footpad allowed to monitor the presence of cells and their migration in lymph nodes up to 72 hours without a significative loss of signal in MRI (Wu et al. 2015a). Recently, Vishwasrao et al. reported an extensive study on the clustering of hydrophobic magnetic nanoparticles by using a modified block copolymer. The clusters were obtained with nonmodified PLE-b-PEG block copolymer (via electrostatic binding of carboxylate groups of the PLE blocks and the nanoparticle surface) and with an alendronate sodium trihydrate (ALN)modified PLE-b-PEG polymer. In the latter, the alendronate acted as an anchor molecule due to the bisphosphonate groups of the molecule. In both cases, the cluster size remained quite small in the range between 40 and 70 nm. Moreover, the cluster was loaded with cisplatin and conjugated with luteinizing hormone-releasing hormone (LHRH) to target corresponding overexpressed receptors on ovarian cancer cells membranes (Vishwasrao et al. 2016). Peng et al. described the synthesis of PLGA-coated nanoclusters for the delivery of siRNA. An aqueous suspension of presynthetized magnetic nanoparticles was mixed with a one-pot precursor solution, composed of PLGA, siRNA, iron chloride, and citrate acid, and left to react for three hours at 60 C. Dense clusters from 100 to 300 nm were obtained. The efficacy of these composite to deliver the siRNA was evaluated at 37 C in a tube, achieving a full release of the payload after 12 days, and as inhibition of TNF-α expression in cocultured murine cancer cells RAW264.7 (Peng et al. 2012). An unusual precursor, the iron(III) 3-allylacetylacetonate, was used for the synthesis, and assembly, of magnetic nanoparticles. The obtained particles that resulted grafted on the surface with allyl

3.3 Clustering Methods

groups, suitable for thiol-ene click (TEC) reaction. Usually, this chemistry approach has been used for the bioconjugation of specific ligands on the particles; in this work, the allyl groups acted as a platform for the TEC reaction with thiol-functionalized PEG (SH-PEG), resulting in the formation of pegylated nanoclusters with a size of 60–100 nm. The use of SH-PEG modified with folic acid resulted in nanocluster functionalized with the vitamin, without any interference on the clustering process. The obtained nanocomposite was injected intravenously into mice for testing its capability in MRI and hyperthermia treatment. After 24 hours, the clusters accumulated mainly in the grafted tumor, in liver and spleen. The magnetic particles that reached the tumor were sufficient to enhance an evident contrast in MRI and a reduction of tumor growth of 90% in comparison to control mice (Hayashi et al. 2013). Li et al. investigated the role of cationic electrolytes in the assembly of poly(acrylic acid)-coated magnetic nanoparticles. Interestingly, the interaction between these building blocks, that is fast and wild, was simply controlled by tuning the ionic strength of the polymers. In this case, the NPs suspension and the polymer solution were mixed, and the assembly was monitored over time: in a first step (40 minutes) the magnetic particles were clustered in dense and regular assemblies of 250 nm. Afterward, the preformed clusters started to overassembly in noncontrolled structures, that the authors defined as coral-like aggregates, with micrometer-range size. By repeating the entire experiment in the presence of an external magnetic field, well-defined and regular 2 μm, cylindrical bundles were obtained. These large aggregates also occurred in this configuration as a second overassembly, since during the first 40 minutes seeding step spherical magnetic cluster were formed (Li et al. 2017). The preparation of hybrid nanoparticles, composed of a donor–acceptor-type conjugated polymer (PCPDTBT), hydrophobic magnetite nanoparticles and a phospholipid, was recently described. The nanoparticles were obtained first drying an organic suspension of the three main components, followed by hydration of the obtained film. The resulting particles, with a nonregular shape and a size between 100 and 150 nm, were further functionalized and stabilized with PEG molecules via NHS chemistry. The hybrid composite showed a 22-fold photoacoustic intensity increase in the optical window (NIR-I) as well as a shortening of T2 relaxation time, with a r2 relaxivity of 309.3 mM−1 s−1 at 7 T for the best nanocomposite (Pham et al. 2019).

3.3.4 Polysaccharides Coatings Another class of molecules extensively used for the coating of magnetic nanocluster is represented by polysaccharides. These molecules are highly biocompatible and, in a certain case, of natural derivation. It is noteworthy that the first FDA-approved formulations based on magnetic nanoparticles were obtained by assisted nucleation of magnetite, or maghemite, in the presence of dextranderivative (e.g. ferucarbotran and ferumoxide). Kim et al. set a method for the preparation of nanoclusters based on the self-assembly of magnetic nanoparticles in a modified-dextran. First, the polysaccharide was modified with the introduction of different oleic acid amount; after that, the NPs, dispersed in the organic phase, was mixed with modified-dextran and a nanoemulsion was inducted by ultrasonication step. After solvent evaporation, the clusters were resuspended in water. The substitution grade of dextran and the polymer amount used during clustering were selected as main parameters to govern the overall size of the nano-object (below 100 nm) and the T2 relaxivities response. Moreover, the dextran-modified surface properties exhibited sufficient affinity to macrophages, and therefore, the nanocluster was tested for the diagnosis, by MRI, of atherosclerotic plaques in vitro and in vivo (Kim et al. 2014).

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Recently, Tran et al. modified some commercial nanoclusters, based on the assembly of single nanoparticles in a matrix of dense dextran, for a smart lateral flow application. The surface was modified with imidazole groups for the rapid conjugation with fluorescent Quantum Dots and/ or receptor for cellular isolation. The purpose of this nanosystem (overall size around 200 nm) was to develop a future point-of-need diagnostics device able to magnetically isolate some specific targets (i.e. cells) and to exploit a smartphone camera for the detection of bright spots (Tran et al. 2019). Park et al. reported the preparation of regular nanoclusters, based on the aggregation of hydrophobic nanoparticles in natural amphiphilic levan polysaccharides. Via an ultrasonication treatment, the nanoparticles were clustered in the polymeric matrix and therefore transferred in the aqueous phase. The size and the shape of the obtained cluster were heavily affected by the nanoparticle concentration: the cluster size increased with nanoparticles amount up to a critical threshold that avoids the formation of three-dimensional super-structures, favoring the bidimensional assembly. The authors demonstrated the universal method for assembly of magnetic, gold NPs, and Quantum Dots, as an individual cluster or as hybrid multifunctional systems. Concerning magnetic nanoparticles, the assembly in clusters of 200–300 nm resulted in a transverse relaxivity increase of 45% (from 65 to 95 mM−1 s−1) at 4.7 T (Park et al. 2020).

3.3.5

Lipidic Coatings

Liposomes represent one of the most investigated platforms for drug administration. These lipidic vesicles are stable, biocompatible, and their preparation is very well-established. In this section, some examples of nanoparticle clustering obtained by the use of different lipids are described. Martina et al. proposed one of the first examples of the inclusion of magnetic nanoparticles in lipidic vesicles. Aqueous maghemite NPs obtained by coprecipitation (and stabilized with a citrate capping) were mixed with egg-yolk L-α-phosphatidylcholine (EPC) and 1,2-diacyl-SN-glycero-3phosphoethanolamine-N-[methoxy(poly(ethylene glycol))-2000] (DSPE-PEG2000), and unilamellar magnetic liposomes were prepared by thin-film hydration method coupled with sequential extrusion. By this method, 200 nm liposomes were obtained, sterically stabilized by PEG chains and containing superparamagnetic maghemite particles whose concentration can be varied. Magnetophoresis confirmed the superparamagnetic profile and the effect of particles confinement into the vesicle core (Martina et al. 2005). Ménager group reported the preparation of unilamellar magnetic liposomes by a different approach, namely reverse-phase evaporation method. In this approach, an aqueous suspension of citrate-coated magnetic nanoparticles and a chloroform solution of phospholipids (DPPC/ DSPC/DSPE-PEG 2000) were mixed and ultrasonicated to induce the formation of a nanoemulsion. Soon after, the organic solvent was removed by rotary evaporation, and the magnetic liposomes were dispersed in the remaining aqueous phase. After filtration (to discard liposomes with a size above 0.45 μm), nonmagnetic liposomes were removed after magnetic separation. By magnetophoresis, the volume fraction corresponding to magnetic nanoparticles (7 nm) into the liposome was estimated as 33% of total volume (Bealle et al. 2012). These magneto-liposomes have been further developed for a multiple therapeutic application. A photosensitizer used in photodynamic therapy, namely the hydrophobic m-THPC, was introduced into the lipidic bilayer of the liposomes. Thus, the multifunctional system was tested in vitro and in vivo for the application of a dual-treatment, combining magnetic hyperthermia and laser-assisted photodynamic therapy. A small dose of nanoclusters was intratumorally injected, and the mice were exposed to the noninvasive treatments for three consecutive days. The single-treatment groups showed only a reduction of tumor volume

3.3 Clustering Methods

and regrowth after seven days. The synergistic combination of magnetic hyperthermia and photodynamic therapy produced a total regression of tumoral tissue four days after injection, instead (Di Corato et al. 2015). Amstad et al. suggested a different architecture for magnetic lipidic vesicle. In their work, the authors investigated the effects of iron oxide capping agents on the localization of NPs in the liposome. By using the traditional oleic acid-capped NPs, an evident agglomeration of nanoparticles was obtained, and a micelle profile was preferred. By functionalizing the magnetic nanoparticles with palmityl-nitroDOPA, a selective localization was achieved, with confinement in the lipidic bilayer, with a concentration of 10 wt %. Alternating magnetic fields were used to control timing and dose of repeatedly released cargo from this pegylated vesicles; the inducted local heating of the membranes caused a transient change of the permeability, without effect on the system structure (Amstad et al. 2011). Nandwana et al. reported the preparation of lipidic nanocapsules with a peculiar hollow-core structure. In details, these nanocapsules were obtained by an emulsion process of cationic lipids and water-dispersed ferrites. As a result, a micellar architecture was obtained, with a hollow hydrophobic core, exploited for drug loading, and a hydrophilic surface, entirely decorated with a very high density of magnetic nanoparticles. Interestingly, the initial Mn–Zn ferrites, synthesized by thermal decomposition method, show a high r2 relaxivity at 3 T (425 mM−1 s−1), and that what resulted even increased when the particles were confined in the nanocapsule structure (680 mM−1 s−1). These results were explained by the synergistic interactive magnetism between adjacent nanoparticles (Nandwana et al. 2018). Salvatore et al. described the preparation of a sophisticated system based on the assembly of different building blocks: a DPPC-based liposome, a ds-DNA conjugated with a cholesteryl unit (that inserts spontaneously into the liposome membrane), hydrophobic iron oxide nanoparticles, and hydrophilic iron oxide@gold core-shell nanoparticle (transferred in water by functionalization with a methoxy-PEG and a thiolated oligonucleotide). By the sequential assembly of these blocks, a peculiar architecture was obtained, with hydrophobic particles embedded in the lipidic bilayer. In contrast, the core@shell nanoparticles were grafted on the liposome surface via interaction with ds-DNA-cholesteryl and subsequent insertion in the liposome. The liposome core was instead used as a carrier for a test payload. The authors demonstrated that the different confinement of these magnetic nanoparticles could be exploited for a sequential release of payload or oligonucleotide by just tuning into alternate magnetic field (AMF) impulses. In detail, 3.22 kHz AMF for five minutes provoked the release of the hydrophilic drug contained in the aqueous core of magnetoliposomes. Subsequently, the application of a 6.22 kHz AMF for 15 minutes induced the melting of DNA strands and the release of the zipper therapeutic oligonucletotide (Salvatore et al. 2016).

3.3.6 Other Molecules In this last subsection, some other molecules, not classified in the previous groups, were explored for the clustering of magnetic nanoparticles. Qiu and coworkers have set a general method for the preparation of nanoparticle clusters in an oil-in-water emulsion using cetyltrimethylammonium bromide (CTAB) as an emulsifier (Qiu et al. 2010). To show the general applicability of the method, they prepared clusters of metallic and semiconductor nanocrystals besides magnetic nanoparticles. The obtained clusters were spherical and were composed of densely packed individual nanoparticles, regardless of the type of nanocrystals employed.

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Wu et al. started from magneto-plasmonic nanoparticles (IONPs@Au core-shell) of 6 nm to prepare nanoclusters, with a diameter of 180 nm, by oil-in-water microemulsion method. In detail, hydrophobic nanoparticles obtained by thermal decomposition, in hexane, were mixed with an aqueous solution of sodium dodecyl sulfate. After sonication, the mixture was heated in a water bath at 80 C for 10 minutes to evaporate the organic solvent. Their superstructure was easily functionalized, by exploiting the gold outer surface of nanoparticles, with thiolated PEG or antibody to ensure a high biocompatibility and a specific target recognition, respectively. The magnetic cluster deserved their superparamagnetic profile, and in addition, the close proximity of the core-shell particles in the nanocluster led to strong near-infrared (NIR) plasmon resonances for medical application (Wu et al. 2014). Smith et al. reported the clustering of 5 nm-diameter oleic acid-capped SPIONs in superstructures with very high relaxivity due to control of cluster size coupled with optimization of hydrophilicity at the surface. The authors synthesized different hyperbranched polyglycerol molecules to mimic the properties of glycogen to adsorb water molecules. By emulsification method and subsequent evaporation of the organic phase, regular clusters between 42 and 80 nm were obtained, by tuning the polyglycerol molecular architecture. Interestingly, the r2 relaxivity passed from 122 mM−1 s−1 of the bare unclustered SPIONs to a maximum value of 719 mM−1 s−1, which was close to their theoretical maximal limit. The described effect was due to two factors: the molecular architecture and to the polyglycerol thickness, and consequently to the hydrophilicity of such coating (Smith et al. 2015).

3.4

Theranostic Relevant Examples

The main problem for the use of magnetic nanoparticle in therapeutic treatments is the suitable concentration of nanoparticles at the target. Specifically, in magnetic hyperthermia, the local increase of temperature is mainly due to a mass effect of several nanoparticles that “heat” the whole region. As claimed in a paper from Pellegrino’s group, the single-particle heating capability is limited to 0.5 nm from the nanoparticles surface (Riedinger et al. 2013). Many research groups overcome this limitation injecting, as proof of concept application, magnetic nanoparticles into the solid tumor. This methodology is accepted to validate the efficacy of novel nanomaterial, but it is not useful in clinical. Other groups injected nanoparticle intravenously, but with very high iron concentration, far from values usually approved by FDA. Albarqi et al. started from the synthesis of alternative nanomaterials to exploit the clustering for delivery of a high quantity of material to the tumor mass. The exotic nanomaterials are based on the synthesis of hexagonal iron oxide nanoparticles doped with cobalt and manganese (CoMn-IONPs). These elements were incorporated in the crystal lattice of iron oxide, leading to an enhancement of the magnetic properties. Moreover, nanoparticles with a different surface magnetic anisotropy, based on cubic or hexagonal shape, showed a superior heating performance recently. The CoMn-IONPs show a diameter of 14.80 ± 3.52 nm, with a dopant concentration of 8% for cobalt and 5% for manganese. These nanoparticles possessed a saturation magnetization of 93 emu g−1, higher than iron oxide nanoparticles, and a very high SAR of 1718 W g−1, measured in an organic solvent at 420 kHz with an applied field of 26.9 kA m−1. CoMn-IONP nanoclusters were obtained by a solvent evaporation process, by using a pegylated poly(ε-caprolactone), with a hydrodynamic size of 80 nm. After water-transferring in clusters, the SAR value is still suitable for therapeutic approach (1237 W g−1) and higher than the value obtained with a suspension of single nanoparticles in water (997 W g−1), as an effect of strong magnetic dipole−dipole interactions into the cluster core. Concerning the in vivo experiment,

3.4 Theranostic Relevant Examples

CoMn-IONP nanoclusters were intravenously injected in nude mice grafted with a xenograft subcutaneous tumor. The clusters were detected in the tumor after 10 minutes, with a maximum accumulation after 5 hours and a decrease after 24 hours. The application of an alternating magnetic field (10 minutes), 12 hours after nanocluster injection, induced temperature increase up to 44 C. The application of four hyperthermia cycles within 30 days inhibited the growth of subcutaneous ovarian tumors in comparison to control groups (Albarqi et al. 2019) (Figure 3.3). In another relevant study, Nie et al. modified one of the synthetic methods described in Section 3.1 for the preparation of small nanoclusters for the release of active compound in a T-cell therapy approach. The cluster was obtained by a solvothermal method in argon atmosphere, mixing iron sulfate, polyethyleneimine (PEI) in a mixed solution of EG/DEG and inducing nanoparticles nucleation by addition of NaOH/DEG at 220 C. The obtained nanocluster exposed primary amine groups on the surface because of PEI molecules; these groups were then exploited for the conjugation of a benzaldehyde-PEG2000-tetrazine, where benzaldehyde reacted with amine group to form

(a) PEG

Hydrophobic PCL core

PCL o

H C

= Co = Mn

o

+

o 117

o

H 88

PEG layer

Hexagonal CoMn-IONP

PEG-PCL

Nanocluster

(b) Before

10 minutes

1 hours

2 hours

3 hours

5 hours

8 hours

12 hours

24 hours

8.71E–1

Tumor

1.08E–3

Figure 3.3 Schematic illustration of the nanoclusters prepared by encapsulation of hexagon-shaped cobaltand manganese-doped iron oxide nanoparticles (a). NIR fluorescence biodistribution analysis at various time points after i.v. injection (b). Source: Reprinted with permission from Albarqi et al. (2019). Copyright 2019 American Chemical Society.

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(a) -TCO BD-PEG-Tz

pH sensitive N

C H

(c) CTL:NC-aP(m)

1500

CTL:NC-aP CTL + aP

1000

CTL PBS

500 0 6

8

Percent survival (%)

(b) Tumor volume (mm3)

78

100

10 12 14 16 18 20 Time (days)

75 50 25 10 15 20 25 30 35 40 45 50 Time (days)

Figure 3.4 Schematic illustration of magnetic nanoclusters armed with PD-1 antibody for immunotherapy (a). Average tumor growth curves and survival percentages of mice after different in vivo treatment (b, c). Source: Reprinted with permission from Nie et al. (2019). Copyright 2019 American Chemical Society.

a pH-sensitive benzoic-imine bond. Moreover, the tetrazine was used for a click-addition of a therapeutic antibody (via inverse-electron-demand Diels−Alder cycloaddition). The antibody release was monitored at pH 7.4 and 6.5, observing an evident difference between the two values. The nanosystem was bond to T-cells via interaction between the antibody and the cell receptor PD-1 and administrated to mice intravenously. The overall complex was then guided by an external magnetic field (commercial neodymium magnetic, N35 grade) and by MRI observation to the solid tumor target. In the conditions that ensured the maximum accumulation of the multifunctional nanocluster, tumor growth was almost inhibited at all, and all tested mice remained alive for the observed period (36 days). This result was due to the synergistic effect deriving from the immune cytotoxicity (acted by T-cells) and the presence of antibody for PD-1, responsible for the molecular pathway that blocks the efficacy of the immune therapy in vivo (Nie et al. 2019) (Figure 3.4).

3.5

Conclusion and General Remarks

In this chapter, several principal areas of super assembly as they apply to nanoparticles were analyzed. Briefly, the super assembly refers to the spontaneous self-organized process of the nanomaterials, through thermodynamic driving forces inherent to the system. However, this process provides to material design new tools for a bottom-up approach. In this context, the clustering of the nanoparticles can be induced and guided from internal and external

3.5 Conclusion and General Remarks

forces, which utilizes van der Waals forces, magnetic and electrostatic interactions e molecular interactions. In all, by combining these different modes, it was shown how the strength of the assembly of nanoparticles increased. All the contributions considered in this chapter pointed out that the clustering of magnetic nanoparticles certainly offers numerous advantages compared to individual nanoparticles. A point to be taken into consideration for the design of these nanostructures is certainly the planned application for the nanocomposite. It is complicated for a nanostructure to simultaneously meet the requirements of MRI or MPI in the diagnostic field, magnetic hyperthermia, or drug delivery in the therapeutic field. Taking into account the specific application, for the magnetic separation of analytes, the size of the nanocluster is undoubtedly not a limitation, it is instead essential that the clusters respond very quickly to the magnetic field, that they are stable/reusable and that the attraction to the magnet is complete. The overall size takes on particular importance only in case the nanoclusters have to be uptaken by the cells that had to be separated. In this case, superordinate structures, or obtained by direct synthesis, even of submicrometric dimensions are to be favored as they respond more to the applied magnetic field. Concerning magnetic resonance imaging, on the other hand, it is very important to guarantee to magnetic nanoparticles surface complete access to the protons of the water molecules in the tissues, to generate a correct interference induced by the magnetic field applied during the measurement. The best nanostructures that offered a higher relaxivity than the starting nanoparticles are those that involved the use of porous coatings; also, a very ordered clustering that supports the dipole–dipole interaction between the nanoparticles in the cluster generates an increase in relaxivity r2. Magnetic hyperthermia is probably the application that is most affected by the clustering process of the nanoparticles because some of the phenomena that guarantee the increase in temperature in the presence of an alternating magnetic field are suppressed. In particular, this phenomenon concerns Brownian relaxation: the nanoparticles, being blocked in a dense core by the shell that protects the cluster and by interparticle interactions, have no possibility of rotating inside the fluid. This also happens for those agents in which the main cause of hyperthermia is considered hysteresis losses. Very small clusters of nanoparticles, even in 2D, can preserve high SAR values. Furthermore, the possibility of using biodegradable polymers, with the consequent release of the individual nanoparticles at the target site after structure decomposition, can help to recover those properties lost through the clustering process. Regarding the in vivo applications of nanoclusters, it is essential to keep the dimensions below 100 nm to allow the nanodevice not to be sequestered quickly by the liver and spleen and, therefore, to reach the target site through extravasation. Furthermore, the possibility of grafting a coating that allows a specific functionalization and, therefore, a specific target recognition (avoiding a passive EPR distribution) in the tissues is certainly an added value for medical nanoclusters. On the other hand, magnetic targeting requires small nanoclusters, but at the same time, they must respond to an external magnetic field very strongly to be guided by an external magnetic field. The use of nanoclusters as a carrier for drug delivery must also take these considerations into account; in this case, the polymers that act as drug reservoirs could even affect the physical properties of the magnetic nanoparticles and limit further applications. Probably, the only application that still does not have a clear response on the usefulness of clustering of nanoparticles is magnetic particle imaging (MPI). It is a fairly recent technique in which Ferucarbotran is still considered the standard. Theoretically, interparticle interactions limit the use of this technique for clusters. Still, recently the scientific community started to report about multicore nanoparticles or superferromagnetism in elongated oriented clusters (e.g. chain-like structures)

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whose use in vivo must, however, overcome the in-depth evaluation of biocompatibility and colloidal stability of structures (Bulte 2019).

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4 Multifunctional Bioactive Magnetic Scaffolds with Tailored Features for Bone Tissue Engineering Teresa Russo1, Roberto De Santis1, Valentina Peluso2, and Antonio Gloria1 1

Institute of Polymers, Composites and Biomaterials, National Research Council of Italy, Naples, Italy Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy 2

4.1

Introduction

Since the concept of “tissue engineering” has been proposed, bone tissue engineering has been continuously investigated. Langer and Vacanti first proposed a definition of tissue engineering as “an interdisciplinary field that applies the principles of engineering and life sciences toward the development of biological substitutes that restore, maintain, or improve biological tissue function or a whole organ” (Langer and Vacanti 1993). Successively, Mac Arthur and Oreffo (2005) defined the concept of tissue engineering as “understanding the principles of tissue growth and applying this to produce functional replacement tissue for clinical use.” A further description goes on to say that an “underlying supposition of tissue engineering is that the employment of natural biology of the system will allow for greater success in developing therapeutic strategies aimed at the replacement, repair, maintenance, or enhancement of tissue function” (Mac Arthur and Oreffo 2005). As easily understood, the basic principle in tissue engineering is represented by a multidisciplinary knowledge gathered from the fields of engineering, biotechnology, life sciences, biology and, recently, from the appearance of micro- and nanomechanical approaches for predicting the mechanical properties of natural tissues (Ebenstein and Pruitt 2006; Cheung et al. 2007; Gloria et al. 2010). The functional restoration of damage tissues by delivering a combination of cells, biological factors, and a biomaterial scaffold as a – permanent or temporary – support is the rationale in tissue engineering and regenerative medicine strategies (Shekaran and Garcia 2011). A complex interaction of nanoscale physical and chemical signals determines in vivo cell fates. To this aim, scaffolds for tissue engineering often incorporate biosignals or signaling biomolecules to create a controlled, bioinspired extracellular environment for directing tissue-specific cell responses. These are mediated by proper cell receptors that will bind to the signaling biomolecules and transmit the signals at intracellular level, activating signaling cascades that will modulate gene expression and determine important cell fate processes such as differentiation to ultimately regenerate functioning tissue.

Magnetic Nanoparticles in Human Health and Medicine: Current Medical Applications and Alternative Therapy of Cancer, First Edition. Costica Caizer and Mahendra Rai. © 2022 John Wiley & Sons Ltd. Published 2022 by John Wiley & Sons Ltd.

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In this scenario, nanotechnology has emerged as a promising tool due to its capability to recapitulate the submicron spatial orientation of extracellular signaling molecules, thus enhancing cell-biomaterial interaction. More in details, signals from the extracellular microenvironment may be incorporated into biomaterials as (i) insoluble extracellular matrix (ECM) macromolecules, (ii) diffusible/soluble molecules, and (iii) cell–cell receptors. Insoluble ECM molecules include structural proteins (e.g. collagens, elastin, and laminin), glycoproteins (e.g. fibronectin and vitronectin), as well as glycosaminoglycans (e.g. chondroitin sulfate) (Alberts et al. 2002). In vivo, these secreted ECM proteins form a meshwork of fibers or fibrils with ECM glycoproteins incorporated into them. The resulting matrix acts as both a structural and signaling scaffold. Clearly, ECM composition, immobilization and spatial arrangement vary for each tissue type – i.e. bone ECM consists mostly of collagen I (Rossert et al. 2002), mineral, and noncollagenous proteins such as osteocalcin, fibronectin, and vitronectin (Robey et al. 2002), while cartilage ECM is predominantly composed of collagen II and aggrecans (Zhang et al. 2003). Tissue specificity may be instructive in tissue engineering since different ECM macromolecules regulate cell growth and differentiation by selectively stimulating different signaling pathways through ECM interactions with various cell receptors (Aplin et al. 2002). Transmission of chemical and mechanical signals from the ECM is primarily mediated by integrins, a family of cell-surface transmembrane receptors composed of both α and β subunits. Most integrins bind to several types of ECM molecules and, vice versa, each ECM protein can bind to more than one integrin. Integrins can also undergo bidirectional signaling. In general, α and β integrin subunits pass through the cell membrane once and possess large 700–1100 residue extracellular domains as well as small 30–50 residue cytoplasmic domains. The extracellular domains of integrins serve to recognize and bind ECM. Upon ECM binding, integrins cluster and their cytoplasmic domains associate with both cytoskeletal and intracellular signal transduction molecules. The association of integrins with the cellular signaling network initiates downstream signaling cascades such as the protein kinase C, Rac, Rho, and mitogen-activated protein kinase (MAPK) pathways. The coordinated clustering of ECM ligands, integrins, and cytoskeletal components forms macromolecular aggregates known as focal adhesions on the inside and outside of the cell membrane (Petit and Thiery 2000). These integrin–ECM interactions govern cell survival, growth, migration, and differentiation (Chen et al. 1997; Bourdoulous et al. 1998) and are, therefore, useful targets of biomimetic tissue engineering strategies. Innovative chemical and processing technologies have been proposed and developed, the aim being to achieve biomimetic scaffolds capable of mimicking the native ECM on various levels (Shin et al. 2003; Stevens 2008; Ma 2008; Holzwarth and Ma 2011; Dang et al. 2018). Unfortunately, none of the proposed solutions alone showed a marked ability to robustly regenerate high-quality bone (Neuss et al. 2008; Porter et al. 2009). The addition of stem cells and/or progenitor cells can significantly improve and accelerate bone healing (Tuan et al. 2002; Li et al. 2005; Gronthos et al. 2006; Caplan 2007). However, cell-based therapies present their own limitation – the source of cells, in vitro manipulation of cells, the rigorous regulatory approval process, and the associated high costs (Derubeis and Cancedda 2004; Bueno and Glowacki 2009; Burdick et al. 2013). In large defect repair or impaired tissue function, endogenous signal cues are not sufficient in type and/or amount to regenerate the damaged tissue and the addition of exogenous signal cues is necessary for regeneration. The promotion and the acceleration of the bone-healing process have been proven to be promoted by the adoption of a “biomimetic tissue engineering strategy,” consisting of incorporating signaling cues – both soluble and insoluble – (Wei et al. 2007; Bose et al. 2012;

4.1 Introduction

Burdick et al. 2013), and several products containing growth factors have been approved in orthopedic practice like spinal fusions (Minamide et al. 2001; Lieberman et al. 2002) and dental surgery (Nevins et al. 2003; Kitamura et al. 2008). Small molecules (Mouriño and Boccaccini 2009; Johnson and García 2015), peptides/proteins (Wei et al. 2007; Buket Basmanav et al. 2008), hormones (Chan and McCauley 2012; Dang et al. 2017), antibodies (Virdi et al. 2012; Taut et al. 2013), and nucleic acids (Gafni et al. 2004; Zhang et al. 2016a) have been investigated for their ability to induce and accelerate bone regeneration. More in detail, growth factors such as bone morphogenetic protein-2 (BMP-2 – Li et al. 2006; Kempen et al. 2008), BMP-7 (Wei et al. 2007; Yilgor et al. 2009; Berner et al. 2012), vascular endothelial growth factor (VEGF – Eckardt et al. 2005; Kleinheinz et al. 2005), and fibroblast growth factors-2 (FGF-2 – Maehara et al. 2010; Kigami et al. 2013) have been proven to be involved in regulating the bone-regeneration process with a great potential in many preclinical studies. Unfortunately, probably because of the concern related to their side effects and safety, clinical translation is still challenging. On the other hand, endocrine secretion molecules (e.g. hormones) delivered at specific time points with a specific release pattern (Timko et al. 2011; Chertok et al. 2013) should represent an alternative strategy to improve bone-healing process. Endocrine secretion molecules represent a class of signaling molecules produced by glands in multicellular organisms, transported by the circulatory system, and then targeting distant organs to regulate physiology such as tissue growth, function, and development. To date, parathyroid hormone (PTH) is the only FDA-approved anabolic (i.e. bone building) agent for osteoporosis treatment in the United States (Neer et al. 2001; Dempster et al. 2001) and its anabolic action has also been demonstrated to improve osseous healing (Bashutski et al. 2010; Kuroshima et al. 2013). Anyway, current strategies in systemic injections of PTH have been shown to be unsuitable for localized defect regeneration, although a pulsatile delivering system of PTH to the local site should preserve its bioactivity inducing the optimal anabolic action (Chan and McCauley 2012). Furthermore, an alternative strategy has been provided by nucleic acids, with their ability to alter cellular function and to “genetically” modulate the tissue regeneration process. DNAs and mRNAs encoding for growth and differential factors can enable protein expression for an extended period (Franceschi 2005). For example, genes encoding for BMPs, FGF-2, insulin-like growth factors (IGFs), TGF-β, platelet-derived growth factor (PDGF), and VEGF have been shown to induce bone regeneration (Kang et al. 2004; Geiger et al. 2005; Park et al. 2007; Capito and Spector 2007; Chang et al. 2010; Qu et al. 2011; Gonzalez-Fernandez et al. 2016; McMillan et al. 2018). In addition, noncoding genes such as siRNA (Ghadakzadeh et al. 2016; Zhang et al. 2016b) and miRNA (Zhang et al. 2016a) have recently emerged as novel therapeutic agents with a great potential in bone tissue engineering because of their marked ability in regulating gene expression and cell activity. Owing to electrostatic repulsion, negatively charged nucleic acids (DNAs and RNAs) cannot easily cross the negatively charged cell membrane (Nitta and Numata 2013). The rapid degradation of some RNAs in vivo presents another challenge (Guo et al. 2010). For these reasons, viral or nonviral gene vectors are usually used to protect and deliver genes in vivo (Pack et al. 2005; Zhang and Godbey 2006). In addition, it is worth noting that a proper combination of antibiotics, anti-inflammatory drugs, and scaffolds has also been considered for bone tissue engineering (Mouriño and Boccaccini 2009; Feng et al. 2010) to avoid inflammation related to the implantation of the tissue engineering constructs. Among the others, vancomycin-loaded polycaprolactone (PCL) membrane has been developed as a Drug Delivery System (DDS) to control infection in a rabbit critical bone defect model (Shijun

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et al. 2018) highlighting its efficacy in reducing inflammatory cell infiltration, controlling bone infection, and improving bone repair. Finally, insoluble physical cues have also attracted significant attention in improving bone tissue formation (Engler et al. 2006; Li et al. 2013). Such cues can significantly alter the cell shape, activity, and gene expression through the ECM–cell interactions, and ultimately, regulate cell migration, proliferation, and differentiation. They could directly facilitate the delivery of soluble signals to the site of bone defect, as well as to improve the fixation and stability of the bone implant or tissue engineering constructs (Gong et al. 2015; Cattalini et al. 2016). Although different types of signal molecules require specific delivery mechanisms, many important and “universal” considerations have to be underlined in designing advanced delivery platforms. In this context, the first important aspect should be the proper selection of material, technologies, and design strategies to develop scaffolds for bone tissue engineering, also involving biomimetic and advanced approaches.

4.2

Scaffolds for Bone Tissue Engineering: An Overview

Depending on specific tissue engineering requirements (i.e. hard or soft tissue), scaffolds must possess peculiar structural and functional features. Historically, the limitations of bone replacement materials have resulted in the utilization of synthetic alternative materials for bone repair, replacement, and enhancement. “Biomaterials” appeared in the early 1960s (Burny et al. 1995). The first generation of biomaterials appeared in the 1960s (Ratner et al. 2004). It aimed to achieve the performance of the biomaterial to match the replaced tissue with the least toxic reaction to the host. They are generally bioinert and interact minimally with the surrounding tissues. The firstgeneration biomaterials mainly include metals (e.g. titanium or titanium alloys), synthetic polymers (e.g. PMMA and PEEK), and ceramics (e.g. alumina and zirconia). The most important feature of the second-generation biomaterials is their bioactive nature, and some could be biodegradable in vivo. They consist of synthetic and natural polymers (e.g. collagen), calcium phosphates, calcium carbonate, calcium sulfates, and bioactive glasses. The third-generation biomaterials are designed to induce specific beneficial biological responses by the addition of instructive substances based on the second-generation biomaterials with excellent properties and/or new biomaterials with outstanding performance. Some of the instructive substances include, but are not limited to, biological factors or external stimuli. Selection of matrix material plays a crucial role in the properties of bone scaffolds. Various polymers have been developed to fabricate bone tissue engineering scaffolds. Different techniques and technological solutions have been proposed to obtain nanocomposite scaffolds that reproduce the complex structure of natural bone. Natural bone presents a hierarchical structure based on the length and width scale, which consists of the macroscale (trabecular bone, also known as cancellous or spongy bone, and compact bone, also named cortical bone), microscale and submicroscale (haversian canals, osteons, and lamellae), nanoscale (fibrillar collagen), and subnanoscale (such as minerals, collagen, and so on). The structure of natural bone has been widely reported in many scientific works (Barth et al. 2011; Ma et al. 2018). Compact bone is nearly solid, except for ~3–5% of rooms for canaliculi, osteocytes, and so on (Wang et al. 2016). However, trabecular bone is an interconnected porous network and has a higher bone surface-to-bone volume (BS/BV) ratio than compact bone (Qu et al. 2019). An overview of different biomaterials including their characteristics, advantages, and disadvantages is given in Table 4.1.

4.2 Scaffolds for Bone Tissue Engineering: An Overview

Table 4.1

An overview of various biomaterials for tissue engineering applications.

Biomaterials

Characteristics

Advantages

Disadvantages

Metal

Suitable mechanical properties of biocompatible metallic scaffolds

Outstanding mechanical properties Biocompatible

Non-biodegradable Corrosion

Tantalum

Bioactive and corrosion resistance

Extensively used as implant biomaterials

Almost no degradation leads to a second surgery for removing the implant

Magnesium

Good porous and biodegradable implant

Mechanical properties like human bone Biodegradable

Toxicity risk caused by metal ion or particle leaching

Titanium and titanium alloys

Durable, biocompatible, highly corrosion resistant and very similar modulus of elasticity for trabecular bone

High bone affinity

Non-biodegradable

Nickeltitanium alloy (nitinol)

Particular mechanical properties (such as the shape memory and superelastic effects)

Low modulus of elasticity, pseudo-elasticity, and high damping capacity, better match the properties of natural bone than any other metals

Almost no degradation for nitinol, the relatively high stiffness of titanium can cause stress shielding and implant loosening

Natural polymer

Similarity to ECM, specific degradation rates and good biological properties

Biocompatible

Low mechanical strength

Collagen

Important part of natural bone organic materials

Excellent biocompatibility Various forms of scaffolds (e.g. sheets)

Biodegradable disinfection and handling are relatively difficult

Gelatin

Denaturalized collagen

Forming blends through cross-linking

Silk fibroin

Silk fibroin with outstanding mechanical properties

Chitosan

Polysaccharide with positive charge, biocompatibility, and resistance to bacteria

Alginate

Polysaccharide with negative charge, and can cross-link and print by injection

Hyaluronic acid

Glycosaminoglycan with negative charge, biocompatibility, forming hydrogel through crosslinking

Synthetic polymer PLA, PGA, and PLGA

FDA-approved materials for clinical applications

Ease to chemical functionalization and degradability

Changeable mechanical and physical properties

Possible adverse tissue reactions caused by acidic degradation

Water solubility and crystallinity tuneable by changing hydroxylation degree

Non-hydrophobic and shortage of cell adhesion

(Continued)

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Table 4.1 (Continued) Biomaterials

Characteristics

Advantages

Disadvantages

PCL

Excellent crystallinity and mechanical properties

In situ cross-linking and printing by injection

Degradation rate in years

PVA

Hydroxylated synthetic polyvinyl acetate

Ability to manufacture implants with various characteristics such as shape, porosity, and degradation rate

PPF

Has numerous nonsaturable double bonds and the cross-links may be toxic

Adjustable mechanical strength and rates of degradation

Polyurethane (PU)

Remarkable mechanical properties

Bioinert ceramic

Cannot perform medical reactions with living tissue after implantation

Aluminum, e.g. aluminum oxide (Al2O3)

Improve mechanical properties; lack of biological activity

Zirconia

Interconnected structures Lack of chemical bonds and biological reactions between living tissues Can show medical reactions with living tissue after implantation

Bioactive ceramic HA

Tricalcium phosphate (TCP), e.g. betatricalcium phosphate (β-TCP)

The main inorganic component of natural bone Highly biocompatible, nontoxic and osteoconductive The ratio of calcium to phosphorus is close to natural bone tissue

Calcium sulfate (CaSO4)

CaSO4 is a good material to choose after tumor resection

Akermanite (ca, Si, Mg)

Excellent mechanical properties and controllable degradation rate

Diopside (MgCaSi2O6)

Low temperature and fast firing and good thermal expansion properties

Bioactive glasses (BGs)

The main components for Na2O, CaO, SiO2, and P2O5.

Source: Adapted from Qu et al. (2019).

Biocompatibility, no rejection, and can provide calcium and phosphorus for new tissue

α-TCP has excessive dissolution and rapid degradation Degradation rate and osteogenic speed are inconsistent

Better osteogenic differentiation and increased gene expression compared to β-TCP

Brittleness

4.2 Scaffolds for Bone Tissue Engineering: An Overview

In brief, scaffolds made of either ceramics or polymers should be either too brittle or too flexible, respectively. Synthetic polymers are characterized by higher flexibility and processability, as well as by tailored physicochemical, mechanical, and degradation properties if compared to ceramic materials. Among all the biodegradable polymers, poly(lactic acid) (PLA), poly(glycolic acid) (PGA), their copolymer poly(lactic-co-glycolic acid) (PLGA), and poly(ε-caprolactone) (PCL) are the most commonly used polymers in the field of tissue engineering. Therefore, none of these materials used on their own can satisfy all the required goals, such as suitable fracture strength, toughness, stiffness, osteoinductivity/osteoconductivity, in vitro and in vivo controlled rate of degradation (Meng and Boccaccini 2010). As consequence, much research attention has been focused on the development of polymerbased composite scaffolds consisting of polymers reinforced with inorganic ceramic micro-/ nano-fillers (Devin et al. 1996; Mathieu et al. 2006; Gloria et al. 2009, 2010, 2011). Polymer-based composite scaffolds possess improved mechanical properties, while showing flexibility and structural integrity better than ceramic scaffolds. Mechanical features clearly play a key role because hard tissues such as bone are stronger (higher strength) and stiffer (higher elastic modulus) than soft tissues (Russo et al. 2010). Typical biomaterials widely used in a variety of orthopedic implants and scaffolds (Wei and Ma 2004; Rezwan et al. 2006; Yang et al. 2008) include bioactive glasses, hydroxyapatite (HA), calcium phosphates such as tricalcium phosphate (TCP) and biphasic calcium phosphate (BCP), and calcium carbonates. Showing better osteoconductivity, these minerals and the released ions have been demonstrated to promote preosteoblast proliferation and differentiation. (Liu et al. 2009; Lin et al. 2017). Uniform and controlled deposition of minerals throughout the implants can be achieved by several methods. Simulated body fluid (SBF) incubation was originally developed to obtain mineral deposition onto scaffolds, but this process was time-consuming, taking several weeks to form ideal mineral deposition (Wei and Ma 2006). Subsequently, mineral electrodeposition has been developed and was able to rapidly generate mineralized CaP coating on the scaffold surface. This approach offers significant advantages over conventional SBF mineralization in that a high-quality mineral coating can be achieved within a short time (0.5–3 hours typically) and the surface topography of the deposits can be tailored by controlling the electrochemical process parameters (He et al. 2010). More recently, they have been adopted as inorganic reinforcing phase of composite scaffolds, wherein polymers (i.e. PCL, PLA, PGA, and PLGA) represent the organic matrix (Gloria et al. 2010). If compared to conventional composites, nanocomposites based on a polymer matrix and inorganic-reinforcing nanofillers seem to better reproduce the natural structure of bone, a natural nanocomposite, and represent a relevant candidate for bone tissue engineering. Moreover, it has been widely demonstrated that nanocomposites induce a more efficient cell response and generally possess enhanced mechanical performances (Rogel et al. 2008; Gloria et al. 2010). Anyway, the approaches for bone regeneration will make giant steps with the exploitation of novel biomaterials and new strategies, particularly the deep integration of nanotechnology, stem cell science, and other fields. Traditional approaches concern scaffolds loaded with growth factors before the implantation, where a temporal control of the various aspects of the tissue growth is hardly achievable. Preloading affects a localized and temporally controlled delivery of growth factors, reducing the scaffold tissue regeneration potential. The possibility of developing innovative scaffolds, able to modify on-demand intrinsic properties, should offer new perspectives and possibilities to control bone regeneration process.

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4.3

Surface Presentation

Surface/pattern features represent another important issue in designing advanced devices for tissue engineering. In particular, surface morphology/roughness and, more importantly, the concentration and the spatial distribution of signal molecules exhibited by scaffolds for bone tissue engineering have proven to play a pivotal role in tissue regeneration and development (Baldwin and Mark Saltzman 1998). The concentration gradient of signal molecules influences the nearby cells that respond in a concentration-dependent way (Wang et al. 2009). The main determinant factor of the drug efficacy and effects is represented by the drug concentration and spatial distribution. Biocompatibility and safety are required for drug delivery systems (DDSs) and their tissue engineering applications. Many different materials can be used to fabricate the delivery vehicles, including synthetic polymers, natural polymers, and inorganic materials (Langer 2000). The materials and their degradation products must be safe and biocompatible without causing an excessive immune response (Sokolsky-Papkov et al. 2007). Typical synthetic polymers include poly(α-hydroxyester)s, polyanhydrides, polyorthoesters, poly(ethylene glycol) (PEG), and poly(vinyl alcohol) (PVA). The most commonly used poly(α-hydroxyester)s are homo- and copolymers of lactide and glycolide, because of their wide range of biodegradability and well-accepted biocompatibility (Makadia and Siegel 2011). Some natural polymers such as fibrin, collagen, chitosan, alginate, and hyaluronic acid have also been widely used as these materials have an innate capacity to interact with cells and some undergo cell-mediated degradation (Malafaya et al. 2007). Silica-based inorganic materials have been investigated as drug carriers in preclinical studies, and while they show low cytotoxicity, most of them are nondegradable in the human body (Slowing et al. 2007, 2008). Additionally, some responsive DDSs require external stimuli such as pH (Zhu et al. 2005; Fang et al. 2012), temperature (Dai et al. 2006; Kim et al. 2013), light (Timko et al. 2014; Nazari et al. 2016), ultrasound (Schroeder et al. 2009; Klibanov et al. 2010), electrical stimulation (Jeon et al. 2011), and magnetic fields (Hoare et al. 2009). The safety issues together with the application of such stimuli should also require a careful analysis. The possibility to translate safer and lessinvasive stimuli into clinical applications would be more easy. Several techniques have been explored to present drug molecules on the scaffold surface to favor the contact with cells migrating into the scaffold, acting as localized biological cues for the regulation of the cell behavior (Zhang et al. 2012). Surface presentation enables site-specific drug delivery, however, reducing eventual off-target side effects of the drugs. The major methodological approaches for presenting drug molecules on the surface include physical adsorption and chemical conjugation. Physical adsorption is based on the interaction between drug molecules and scaffold surface, such as electrostatic interactions, hydrogen bonding, or hydrophobic interactions (Liu et al. 2005; Yoo et al. 2009; Dang et al. 2018). The scaffold surface can be further modified to improve its affinity for drug molecules (Goddard and Hotchkiss 2007). Heparin has often been employed to change the surface chemically or physically to enhance binding of the growth factors to the scaffold. Some studies describe the controlled release of PDGF, BMPs, VEGF, and further growth factors in heparin surface modified devices (Singh et al. 2011; Fu et al. 2011; Martino et al. 2013). Even if there are specific preferred aspects, a limited control over drug retention together with potential burst release and reduced bioactivity in many cases could be ascribed to the passive adsorption method (Zhang et al. 2012). The physical interactions are clearly influenced by physiological conditions (e.g. temperature, acidity, and mechanical movement), which may affect the

4.3 Surface Presentation

effectiveness of surface presentation. In comparison to the physical adsorption approach, a prolonged and more stable situation in terms of drug molecule presentation can be obtained using a chemical conjugation, or covalent bonding. Thus, the first step is the surface activation with functional groups and the successive drug molecule conjugation using specific chemical reactions (Goldberg et al. 2007). Even though biodegradable polyesters are the most commonly employed polymers for bone tissue regeneration, they do not present functional groups. There are many methods to surface activate the scaffold using different methods (e.g. chemical etching, plasma treatment, and surface coating), but it should be noted that the activation treatment conditions need to be properly adjusted to maintain scaffold integrity (Gao et al. 1998; Park et al. 2005; Gloria et al. 2012). A further approach involves functionalization or blending of functional molecules with the matrix materials prior to manufacture the scaffold. A primary concern is related to the conjugation reaction which could lead modify the conformation of the drug molecule, resulting in bioactivity loss. Thus, many modifications of drugs such as the conjugation to a spacer (Greenwald et al. 2003; Veronese and Pasut 2005) or drug mimics (e.g. growth factor peptide mimics – Zhang et al. 2015) are generally considered. Several bioconjugation reactions have been investigated, focusing on reactions performed in aqueous solution or under mild reaction conditions. Amidation, esterification, and click reactions are among the most used reactions (Biju 2014). As an example, the conjugation of BMP-2 mimicking peptide, P24, onto acrylic group-bearing PLLA nanofibrous (NF) scaffold has been performed using the thiol-ene click reaction. The structures modified with BMP-mimicking peptide demonstrated the ability to retain bioactivity and to promote osteogenic differentiation of rabbit bone marrow-derived mesenchymal stem cells in comparison to the unmodified ones, also favoring the formation of ectopic bone in nude mice (Zhang et al. 2015). A simple strategy to obtain a sustained drug delivery is represented by the possibility to load the drugs into the scaffold matrix. In this sense, different methods have been widely proposed also involving in situ polymerization, solvent casting, phase separation, gas foaming, and electrospinning (Davies et al. 2008; Blaker et al. 2008). The possibility to protect the drug bioactivity during the scaffold fabrication represents the main challenge. The bioactivity of many growth factors and biomolecules may be negatively affected by the solvents which are generally employed to prepare polymer solutions. With regard this strategy, a further drawback consists in the difficulty to control the release kinetics. As demonstrated by some authors, growth factors have properly been processed to develop electrospun NF scaffolds, however, obtaining frequent aggregations on the outer surface, which resulted in a burst release (Zhang et al. 2012). A promising strategy consists in the encapsulation of drugs in properly designed devices acting as delivery vehicles, without considering the direct loading into the scaffold matrix. Micro- and nanospheres have been employed for encapsulating drugs, and several techniques have been analyzed with the aim of retaining efficiently the drug bioactivity as well as of obtaining controlled release kinetics. In addition, solvent annealing has also been considered as a method for the immobilization of drug-loaded microspheres on the scaffold surface (Jin et al. 2008). Such technique allows for a spatial and temporal control of the release of single or multiple drugs throughout the scaffold as well as for the specific design of drug release profiles avoiding altering the scaffold structure. However, novel methodologies are currently being considered to overcome the limitations in gene delivery for bone tissue regeneration. Many researches have been devoted to the design of innovative bioactive devices for bone tissue engineering, whose main features result in the possibility to be manipulated in situ using magnetic

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field gradients. The idea should be to benefit from the combination of external magnetic fields and properly designed magnetic devices for tailoring biological events at different levels as well as for releasing biofactors and biomolecules which may be linked to magnetic nanocarriers (Schieker et al. 2006; Bock et al. 2010).

4.4

Bioactive Magnetic Scaffolds

Innovative strategies to improve hard tissue regeneration consist in the application of magnetic field and magnetic nanoparticles, which have been shown to influence cellular metabolism. Static and pulsed magnetic field (SFM, PMF) has been commonly used in medicine to increase wound healing, bone regeneration, and as an important feature for magnetic resonance technique. However, recent data showed the mechanism of SMF action on biochemical properties of different cell populations, including stem cells. Today, it is well known that a magnetic field can be used for future therapies and approaches in bioengineering due to its easy application and a wide range of possible effects on cells and organisms (Marycz et al. 2018). Furthermore, the concept of magnetic guidance spans from biomedicine to tissue engineering, involving drug delivery, hyperthermia treatment of tumors, magneto-mechanical stimulation of cell constructs and mechanosensitive ion channels, magnetic cell-seeding procedures, and control of cell proliferation and differentiation (Pankhurst et al. 2003; Markaki and Clyne 2004, 2005; Ito et al. 2005a, b, c; Dobson et al. 2006; Perea et al. 2006; Pislaru et al. 2006; Dobson 2006, 2008; Shimizu et al. 2007; Barry 2008; Muthana et al. 2008; Mannix et al. 2008; Hughes et al. 2008; Mack et al. 2009; Bock et al. 2010; Kanczler et al. 2010). In this scenario, magnetic nanoparticles (MNPs), because of their peculiar physical properties, provide some attractive possibilities. Their dimensions, which range from a few nanometers up to tens of nanometers, allow them to be comparable with several biological entities, being close to or smaller than those of a virus, a protein, a cell or a gene. Basically, their magnetic features can be manipulated by applying an external magnetic field gradient. The application of an external magnetic field could allow for the manipulation of their magnetic aspects, also promoting the immobilization and/or transportation of the magnetic bioaggregates and MNPs themselves. MNPs can respond to a time-dependent magnetic field with several advantages obtained by the energy transfer from the applied magnetic field to MNPs. For example, MNPs may be heated up, allowing their use as hyperthermia agents able to deliver thermal energy to tumors or as elements able to improve chemotherapy or radiotherapy through the destruction of malignant cells. For this reason, different kinds of magnetic micro-/nanoparticle carriers have been optimized and used for drug delivery applications. Interestingly, the nanomagnetic actuation of receptor-mediated signal transduction has been already reported in the field of magnetic nanotechnology with the aim to activate a biochemical mechanism normally activated by binding of multivalent chemical ligands (Mannix et al. 2008). An interesting approach related to a selective activation of mechanosensitive ion channels using magnetic particles has been developed as an innovative method for the treatment of human diseases without pharmacological drugs (Hughes et al. 2008). The earlier reports showed that magnetic (e.g. Fe3O4) nanoparticles could enhance the in vitro bioactivity of biocoatings (Chowdhury et al. 2017; Jiang et al. 2017). The integration of magnetic nanoparticles with other bioactive components represents a novel strategy to produce nanocomposites with integrated functionalities for biomedical applications. Based on a preliminary research, MNPs incorporated into organic or inorganic materials have showed an expected effect on the process of bone repair. On the other hand, it is worth noting that delivery devices allowing

4.4 Bioactive Magnetic Scaffolds

remote, repeatable, and reliable switching of drug flux would provide a great impact on the treatment of a wide range of medical conditions. Ideally, a drug delivery device for in situ and on-demand administration of specific drugs should contain a large quantity of drug, and its operating process should expect a little or even null drug release in the “off ” state. Furthermore, it should be repeatedly switchable to the “on” state without inducing any mechanical failure of the device and should be triggered noninvasively for delivering a significant dosage demanded by a patient (e.g. local pain relief ) or prescribed by a doctor (e.g. localized chemotherapy). To date, none of the developed drug delivery devices are applied in clinical practice because of their peculiar limitations, related to the inability to be effectively triggered in vivo in the absence of a local implanted heat source, the inability to provide a reproducible release over multiple thermal cycles, the slow response times to external stimuli, and the inability to dynamically adjust drug dosing according to patient needs. As an example, a rapid on-demand drug delivery can be achieved using radio frequency-activated microchips which contain drug-filled reservoirs (Santini et al. 1999; Grayson et al. 2003; Hoare et al. 2009), however, delivering only fixed doses of drug and requiring implanted electronics. Protein may be released on-demand using nearIR responsive nanoparticles (i.e. mixtures of PNIPAM and gold-gold sulfide nanoshells), even if a release of inconsistent doses has been demonstrated upon multiple triggering cycles (Sershen et al. 2000; Hoare et al. 2009). A remote activation of ferrofluid-loaded polymer sheets, liposomes, microcapsules, microspheres, and nanospheres may be carried out by magnetic fields, even if single-burst release events or inconsistent dosing over multiple thermal cycles may be obtained as a consequence of the flux triggering mechanism and the disruption of the drug-polymer matrix (Hoare et al. 2009). This suggests the needs for alternative methods and technologies. Hydrogels, gel-based microparticles or nanoparticles, together with surface-grafted polymers based on thermosensitive poly(N-isopropylacrylamide) (PNIPAM) have been proposed for triggerable devices, due to the thermoresponsive PNIPAM features and on the discontinuous phase transition in water, switching from hydrophilic to hydrophobic state. In PNIPAM-based hydrogels, such phase transition is responsible for a deswelling response generally reducing the drug flux from the hydrogel. On the other hand, if PNIPAM is employed for filling the pores present in a membrane, the entrapped polymer may shrink since the pores may be opened by heating, increasing drug flux through the membrane (Yoshida et al. 1994; Dinarvand and Demanuele 1995; Hoare et al. 2009). These membranes have been developed of grafting PNIPAM to the membrane networks (MullerSchulte 2007) or through the entrapment of PNIPAM microgels within a membrane matrix. PNIPAM-based systems would be permanently “on” at 37 C (i.e. physiological temperature) as the transition temperature is at about 32 C. Current technologies would require the possibility to employ an implanted heating device for the in vivo activation. With the aim to obtain an “ondemand” drug delivery benefiting from an oscillating magnetic field, composite membranes were manufactured (Hoare et al. 2009). They consisted of an ethyl cellulose support, a triggering entity based on superparamagnetic MNPs (i.e. magnetite), and a switching entity (i.e. thermosensitive PNIPAM-based nanogels), allowing for a rapid, repeatable, and tunable drug delivery according to the application of an external time-dependent magnetic field (Figure 4.1). Co-evaporation method was employed to obtain the membranes which showed a uniform bulk composition, however, showing relatively less iron (ferrofluid) near the surface. Membrane-based devices were employed, and the on–off release of sodium fluorescein was assessed considering multiple magnetic cycles using. It was demonstrated that the duration of the “on” pulse was directly to the total delivered drug dose. The noncytotoxicity, biocompatibility, and the ability to retain the switchable flux properties after 45 days from the subcutaneous implantation were evaluated (Hoare et al. 2009) More recently, to further study the synergistic effect between magnetic force and magnetic nanocomposites, Zhao et al. (2011) presented a macroporous ferrogel using Fe3O4 nanoparticles, which

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Minimal or no flux

Membrane

98

Figure 4.1 Stimulus–responsive membrane triggering in vitro of the proposed mechanism of membrane function. Source: Reprinted with permission from Hoare et al. (2009). Copyright 2009 American Chemical Society.

Strong flux

NP

NP

NP

NP

NP

NP

NP NP

Nanogel

NP

Heat NP

NP

NP

NP

NP NP

Drug reservoir

promoted the adhesion and viability of the resident cells controlled by a magnetic field (Zhao et al. 2011). Normally, there is a natural magnetic field in the earth, and geomagnetic fields provide good biological effects (Ossenkopp and Barbeito 1978). Besides, it is not convenient to operate during the period of repair with external artificial magnetic field. Moreover, the external magnetic field might bring about unexpected side effects to lesion area or normal tissue. In order to stimulate organic component of extracellular matrix, a lot of natural polymers with good compatibility have been investigated for fabrication of biomedical scaffolds (Udhayakumar et al. 2017). It is well known that, collagen I (Col I) is the primary protein with triple-helical structure in ECM, where the dense network of collagen fibrils provide a good tensile strength to the scaffolds (Prabhu et al. 2014; Miri et al. 2016). Furthermore, chitosan (CS) is biologically renewable, biodegradable, biocompatible, antibacterial, and nontoxic. Hence, CS has been widely used as an organic component for scaffold in orthopedic and other biomedical applications (Liu et al. 2004; Xu et al. 2016; Fabiano et al. 2017). As inorganic component of bone, hydroxyapatite nanoparticles (nHAP) have a wonderful biocompatible, especially the good osteoconductive, which was widely used in medicine and dentistry (Gong et al. 2015; Jakus and Shah 2017). In this context, Yun et al. (2015) synthesized magnetic nanocomposite porous materials showing that the incorporation of MNPs at a proper concentration accelerated cellular adhesion and proliferation. Aliramaji et al. (2017) mixed the MNPs with the solution of silk and CS to prepare silk fibroin/CS/ magnetite scaffolds by freeze-casting technique. The results found that the degradation of scaffolds decreased in PBS and possessed appropriate influence on cellular behavior. Nazeer et al. (2017) prepared NH2-modified nHAP thus developing CS/nHAP composites by freeze-drying method, characterized by marked bioactive surface and better osteogenic differentiation. Aggregation of inorganic nanoparticles in the polymer matrix cannot achieve nanodistribution, thus negative mechanical properties and bioactivity of the scaffolds. On the other hand, the local conglomeration of MNPs will produce potential toxic effects to physical security and would be unable to provide a synchronized magnetic effect during the magnet therapy. Based on the idea of in situ bionics (Li et al. 2007; Guo et al. 2015; Chen et al. 2015) Zhao et al. (2019) incorporated the precursor solutions of HAP and Fe3O4 nanoparticles with appropriate dosage into the CS/Col organic matrix to prepare CS/Col/Fe3O4/nHAP magnetic composite scaffold by in situ technology. The microstructure and magnetic properties of the CS/Col/Fe3O4/nHAP scaffold were assessed, and the effects of the Fe3O4 on the scaffold properties and osteoblast behavior, including degradation, mechanical properties, and bioactivity, as well as osteogenic differentiation were investigated both in vitro and in vivo. Actually, a study by Zhao and colleagues featured the creation of in situ magnetically functionalized nanocrystals. Through pH control, the authors were

4.4 Bioactive Magnetic Scaffolds

capable of crystallizing hydroxyapatite nanocrystals with magnetic nanoparticles of iron(III) oxide. Crystallizing the nanocrystals onto a collagen and chitosan hybrid scaffold resulted in a bone regeneration scaffold that exhibited promising performance in vitro and in vivo (Zhao et al. 2019). In the context of bone repair and regeneration, magnetic scaffolds should be also employed to achieve efficient scaffold fixation via magnetic forces providing a very smart solution to the clinical problems of fixation that many traditional scaffolds meet. Today, regarding the treatment of small osteochondral lesions, most surgeons do not use any fixation system, while in the treatment of wide bone defects, fixation is ensured through the use of external systems, such as intramedullary nails, screws, and plates, which require continuous control and often multiple surgical interventions. With this aim, Russo et al. (2012) proposed an innovative magnetic fixation approach based on the application of a magnetic scaffold highlighting a saturation value of 17 emu g−1 (Figure 4.2). In their study, different configurations were proposed, and a finite element modeling (FEM) was exploited to investigate the fixation efficiency. It was found that for most appropriate magnetic materials and optimized magnet-scaffold positioning, all the considered configurations should provide an interesting solution in terms of scaffold fixation (Russo et al. 2012). Novel methodologies, defined as “magnetic force-based tissue engineering,” for designing tissueengineered tubular and sheet-like constructs using magnetite NPs and magnetic force has been also proposed (Ito et al. 2005a, b, c), while another group designed a novel magnetic force mechanical conditioning bioreactor for tissue engineering (Dobson et al. 2006). Moreover, by binding MNPs to the surface of cells, the possibility to control cell function through the application of an external magnetic field has been studied (Dobson 2008). Magnetic scaffolds may generate higher magnetic field gradients that are able to provide significant magnetic attractive forces. The use of a superparamagnetic material in the design and development of magnetic scaffold may be able to reach appropriate magnetization values (i.e. up to 15 emu g−1 at 10 kOe) for ferrofluid or MNPs adhesion when applying an external magnetic field (Bock et al. 2010), but it may also be magnetically “turned off” by removing the applied magnetic field. These magnetization values can generate magnetic gradients potentially able to attract and take up cells or other bioagents bound to MNPs. Benefiting from magnetic guidance concept and from rapid prototyping techniques, the possibility to obtain magnetic polymer-based nanocomposite scaffolds by embedding superparamagnetic PVP-coated Fe3O4 nanoparticles in a PCL matrix has been also shown. Their biological and mechanical performances have been preliminarily evaluated (De Santis et al. 2011b). These scaffolds seem to be fixed station,

(a)

(b)

(c) PM PM

EM

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SS SS

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Scaffold

Figure 4.2 Schematic representation of magnet-scaffold configurations: (a) external permanent magnet ring (EM); (b) implanted permanent magnet pins (PM); (c) implanted stainless steel pins in the field of external magnet (EM + SS). Source: Reprinted from Russo et al. (2012) with permission of Elsevier.

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whose magnetization can be switched on and off by means of external magnetic fields. However, the long-term effects in human body of iron-oxide-based phases such as maghemite or magnetite remain still unclear (Lewinski et al. 2008; De Santis et al. 2011b). The possibility to apply surfacemodification methods for the design of specific biocompatible layers consisting of polymers, inorganic phases, or metals deposited on their surface should avoid the problems related to their eventual toxicity (Berry and Curtis 2003; Singh et al. 2010). In this scenario, a novel biocompatible and bioresorbable super-paramagnetic-like phase (FeHA) by doping hydroxyapatite with Fe3+/Fe2+ ions has been proposed (Tampieri et al. 2012) trying to minimize the formation of magnetite as secondary phase. Microstructural, physico-chemical, and magnetic analyses were carried out on the nanoparticles, highlighting their intrinsic magnetization and suggesting new perspectives for devices for bone tissue engineering and for anti-cancer therapies based on hyperthermia. PCL/FeHA nanocomposite substrates were designed and characterized using different polymerto-particle weight ratios, spanning from 10 to 30 wt% of FeHA nanoparticles. The effect of FeHA nanoparticle inclusion on morphological, mechanical, magnetic, and biological performances was assessed (De Santis et al. 2015). Scanning electron microscopy (SEM) analysis allowed to evaluate morphological features of the substrates. The synergistic contribution of both surface chemistry and topography influence the overall features of the substrates, thus allowing to enhance not only the hydrophilic character but also cell attachment and proliferation, as shown by confocal laser scanning microscopy and cell viability assays. The inclusion of a specifically modified hydroxyapatite into the polymer matrix can improve the mechanical properties, in terms of higher maximum load, if compared to neat PCL substrates, as shown by small punch tests (Maietta et al. 2018). However, beyond a specific limit of nanoparticle amount, by further increasing the nanoparticle concentration, mechanical performances of nanocomposite substrates should decrease since the nanoparticles play as “weak points” instead of a reinforcement for the polymer matrix. It is worth noting that weakness in a structure may be due to discontinuities in the stress transfer and generation of stress concentration at the nanoparticle/matrix interface. This effect may be ascribed to the difference in ductility between the polymer matrix and the inorganic nanofillers. From a biological point of view, FeHA nanoparticles enhance scaffold bioactivity and cell response also evidencing the role of the HA in promoting surface mineralization as expressed by the increase of ALP activity (Gloria et al. 2013). Benefiting from the intrinsic magnetism of FeHA nanoparticles, nanocomposite PCL/FeHA substrates have shown a superparamagnetic character at body temperature with a saturation value spanning from 0.3 to 0.9 emu g−1, strictly proportional to the FeHA content. Even though the values of saturation magnetization value obtained for FeHA nanocomposites are lower than those reported in literature for dip-coated scaffolds (Bock et al. 2010) or those shown by PCL/Fe3O4 nanocomposites with the smallest nanoparticle amount (De Santis et al. 2010, 2011a). These results are very promising since it would be possible to obtain magnetic field gradients able to attract bioaggregates into the fully interconnected pore network of the completely biodegradable scaffolds. Benefiting from magnetically charged cells and magnetic scaffolds, further analyses were also performed, the aim being to assess the possibility to increase scaffold cell loading efficiency. The in vitro results showed that the cell growth in the magnetized scaffolds is greater than that in nonmagnetized ones. Preliminary in vivo experiments, performed on a rabbit animal model, suggested the use of a 3D nanocomposite magnetic scaffold as potential alternative to autologous bone implantation, eventually benefiting from the application of an external magnetic field (De Santis et al. 2011a, 2015; Russo et al. 2013).

4.4 Bioactive Magnetic Scaffolds

Anyway, it is worth noting that magnetic force may cause adaptive changes in microenvironments, including the cell membrane, cell matrix, cytoskeleton, nucleoprotein, and genome. Consequently, signals are transduced to the cell nucleus, regulating and stimulating a series of biological responses. Various signaling pathways, including the mitogen-activated protein kinase (MAPK) pathway are involved in this biological process (Rosen 2003; Miyakoshi 2005; Hashimoto et al. 2007). Expression of MAP protein kinases plays a predominant regulatory role in every aspect of cell biology (Cunha et al. 2012). The activated MAP kinases catalyze the phosphorylation of numerous substrate proteins including transcription factors, protein kinases and phosphatases, and other functional proteins. The MAPK pathway is composed of a series of Ser/Thr kinases, including extracellular signal-regulated kinase (ERK)1/2, c-Jun N-terminal kinase (JNK), p38 and ERK5 subfamilies, which after phosphorylation cascade, regulate the activity of specific transcription factors. The MAPK signaling pathway is closely associated with bone resorption of osteoclasts and the bone formation of osteoblasts. The effect of magnetic field on osteogenic markers expression through different signaling pathways including the protein kinase A (PKA) and the mitogen-activated protein kinase (MAPK) (Sun et al. 2015; Rinaldi et al. 2016) remains still unclear. Accordingly, Russo et al. (2020) proposed the design and development of magnetic nanocomposite substrates for bone tissue engineering consisting of a PCL matrix loaded with iron oxide (Fe3O4) nanoparticles. Specifically, a further insight into the combination design of a time-dependent magnetic field and such magnetic nanocomposites was provided. The mechanical properties of the designed nanocomposites were first assessed through small punch tests. Although the results did not provide information such as yield stress and elastic modulus, the mechanical properties were evaluated as punching properties, however, allowing for a comparison between the neat PCL and PCL/Fe3O4 substrates. Relative measures of the strength and the ability of the material to absorb energy before breaking were obtained by the determination of the peak load and the work to failure, respectively. If compared to PCL substrates, the inclusion of MNPs enhanced the punching properties (i.e. higher values of peak), while maintaining the ability to absorb energy during the loading process (i.e. similar values of work to failure). In addition, the effects of the combination of magnetic stimulation and magnetic nanocomposites on the behavior of hMSCs was analyzed, also focusing on the MAPK signaling pathway. In many cases, specific analyses based on Alamar Blue assay, normalized ALP activity (ALP/DNA), confocal laser scanning microscopy, cell shape factor, and p-ERK1/2 expression showed intriguing results, also stressing the impact of the synergistic combination of magnetic nanocomposites with a discontinuous application of a magnetic field (i.e. 6 hours per day with 20 intervals of 18 minutes each) on the behavior of hMSCs (Figure 4.3). The differentiation process is clearly related to the degree of cell spreading (Song et al. 2011). An increased cell spreading would enhance osteogenic differentiation of hMSCs as a consequence of a potential improvement of the cytoskeletal contractility, which favors osteogenesis. However, osteogenic differentiation is a complex process involving many biological factors and biophysical cues. Even though cell spreading plays an important role in regulating the process, some concerns remain about its influence on maintaining the committed phenotype after MSC differentiation (Yang et al. 2019). The activation of the MAPK pathway was enhanced by the magnetic field, since an increase of ERK phosphorylation was evidenced for both polymeric and nanocomposite substrates Anyway, the effect of the combination of the time-dependent magnetic field with the developed PCL/Fe3O4 nanocomposites was also demonstrated by the highest phosphorylation levels of ERK1/2.

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7 Days

14 Days

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EGf 0ʹ 15ʹ 30ʹ 0ʹ 15ʹ 30ʹ

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Figure 4.3 Effect of time-dependent magnetic field on PCL and PCL/Fe3O4 substrates. A schematic representation of the experimental setup (upper left) and hMSC behavior over time – CLSM analysis (right), cell shape factor (bottom left), (ERK)1/2 phosphorylation (middle left). The magnetically stimulated substrates were indicated as PCL Mag and PCL/Fe3O4Mag. Source: The image was adapted from Russo et al. (2020). CC BY 4.0.

4.5

Conclusions and Final Remarks

Recently, many efforts have been devoted to the design of multifunctional and advanced devices for enhanced bone tissue engineering. Bioactive magnetic scaffolds represent an intriguing perspective in bone tissue engineering, integrating advances in physics, engineering, biology, and life science. The potential to design advanced, multifunctional, and bioactive magnetic scaffolds by properly combining Additive Manufacturing technologies and time-dependent magnetic field should be a promising strategy to improve in situ osteointegration. Clearly, improvements are needed in terms of further understanding of cell behavior, trying to obtain additional and important information on the osteogenic differentiation, through different biological assays (e.g. alizarin red staining and gene expression of osteogenic markers such as BMP-2, runt-related transcription factor 2 – Runx2, and collagen type 1 alpha 1 – COL1A1). Finally, a further focus on MAPK pathway alterations related to the magnetic stimulation in cell-laden constructs should also provide key information on the potential bone integration.

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5 Magnetic Nanoparticles in the Development of Polymer Scaffolds for Medical Applications Larissa Stieven Montagna, Ana Paula da Silva, Amanda de Sousa Martinez de Freitas, and Ana Paula Lemes Department of Science and Technology, Polymers and Biopolymers Technology Laboratory (TecPBio), Federal University of Sao Paulo, São José dos Campos, SP, Brazil

5.1

Introduction

The development of new materials for application in medicine has been one of the most explored subjects in scientific research. In the field of tissue engineering, one of the challenges is to create materials that can replace and/or repair damaged tissues, performing their functions, supporting cell growth, and assisting in tissue regeneration; they are called scaffolds. The scaffolds consist of three-dimension porous solid biomaterials that can be applied to regenerate several kinds of tissues, including bone, skin, cartilage, muscle, etc., that were damaged by any disease or trauma. They can also be used for controlled and targeted release of bioactive agents. A scaffold is desired to promote cellular adhesion, proliferation and differentiation, efficient transport of gases and nutrients with minimum inflammatory or toxic effect (Dhandayuthapani et al. 2011; Jafari et al. 2017; Eltom et al. 2019). Polymers have been one of the most studied materials for production of different types of scaffolds, including porous scaffold, microsphere scaffold, hydrogel scaffold, fibrous scaffold, composite, nanocomposite scaffold, and acellular scaffolds. Among these types of scaffolds, hydrogels have attracted the attention of tissue engineering (Dhandayuthapani et al. 2011; Jafari et al. 2017; Eltom et al. 2019). The hydrogel scaffolds are compounded by threedimensional (3D) hydrophilic polymer networks that allow the absorption and retention of water in their structure. The scaffold properties depend on their physical structure and chemical composition. So the control of these characteristics is important to modulate scaffolds properties and then to make possible their utilization in specific applications. Nanotechnology has had an important role in the development of new scaffolds, since the addition of nanoparticles is an interesting route to modulate materials properties. In this context, the nanoparticles result in a dispersed phase inside a continuous matrix and are classified as nanofillers, which consist of fillers that have, at least, one dimension in nanometer scale. Thus, the polymer materials filled with nanofillers are classified as polymer nanocomposites.

Magnetic Nanoparticles in Human Health and Medicine: Current Medical Applications and Alternative Therapy of Cancer, First Edition. Costica Caizer and Mahendra Rai. © 2022 John Wiley & Sons Ltd. Published 2022 by John Wiley & Sons Ltd.

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A wide variety of nanoparticles has been used in scaffolds production to improve their properties or to obtain new ones. Some examples include cellulose nanocrystals (Ferreira et al. 2019; Montanheiro et al. 2019a, b; Pomari et al. 2019), carbon nanotubes (Xu et al. 2019b; Gonçalves et al. 2020; Hsiao et al. 2020; Zadehnajar et al. 2020), silver nanoparticles (Masood et al. 2019; Patil and Singh 2019; Alcântara et al. 2020), graphene nanosheets (Patil et al. 2019; Shamekhi et al. 2019; Shah et al. 2020), nanoclays (Zhai et al. 2018; Hakim et al. 2019; Zhou et al. 2019), and bioglass (Fan et al. 2016; Singh et al. 2019; Vukajlovic et al. 2019). The high superficial area to volume ratio from its nanometric dimensions results in a high interfacial area between nanofiller and matrix, which allows that low nanofiller addition to modify the material properties. Among the nanoparticles that have a great potential to medical applications are the magnetic nanoparticles (MNPs), consisting of a family of nanoparticles that respond to a magnetic field, and therefore, can be manipulated by using an external magnetic field. In this way, the MNPs show a high potential for application in different areas as engineering, biotechnology, materials science, and biomedicine. In the biomedical area, the MNPs can exhibit in vivo (within a living organism) applications for therapeutic and diagnostic purposes and in vitro (outside a living organism) applications for diagnostic purposes. Piñeiro et al. (2020) supply a great summary of MNPs’ biomedical applications and the involved magnetic stimulation. The summary brings the advantages and disadvantages related to each application, toxicity, and commercial kit availability. The MNPs biomedical applications include cell isolation, magnetofection, magnetic guiding, magnetometry Superconducting Quantum Interference Device (SQUID), Giant Magnetoresistance (GMR) sensors, impedance sensors, hyperthermia cancer treatment, thermally enhanced release of therapeutic agents, thermal stimulation, magnetic resonance imaging contrast agents, and 3D magnetic bioprinting. Figure 5.1a shows the increasing number of published papers concerning MNPs in the last 10 years. We observe that the number of papers concerning MNPs increased from 233 in 1999 to 10,249 in 2019, which corresponds to an increase of approximately 44 times. Regarding specific MNPs applications in the medical area, the increase was of almost 28 times from 2003 to 2019 (Figure 5.1b). The same behavior is observed for works related to MNPs application in scaffolds development (Figure 5.1c). In this case, the increase was even greater (139 times) within the same period, from 2003 to 2019. Therefore, these statistics reveal that the addition of MNPs in scaffolds consists of a very promising research field that will further enhance in the next years. The magnetic material that can compound the MNPs includes metal, metal oxide, and metal alloy. Iron, nickel, and cobalt are the metals commonly used in the production of MNPs, while metal oxide MNPs are mainly composed of iron oxides (γ-Fe2O3 and Fe3O4) and ferrites (CoFe2O4 and Mn0.6Zn0.4Fe2O4) and metal alloy MNPs are composed of FeCo, FePt, for example (Guo et al. 2018; Katz 2020). Iron oxides (γ-Fe2O3 and Fe3O4) has been the most investigated MNPs for biomedical application due to their biodegradability, low cytotoxicity, stability in air and water, facility in the production, size and shape control, and functionalization which allows that iron oxide MNPs are covered by many kinds of targeted ligands or antibodies (Akbarzadeh et al. 2012; Kudr et al. 2017; Guo et al. 2018; Gloag et al. 2019). The main challenge of MNPs synthesis is to produce a monodisperse distribution of particle size. The synthesis method influences the shape (spheres, cubes, hexagons, octahedra, hollow spheres, rods, plates or wires, etc.), particle size, distribution of particle size, chemical groups of surface nanoparticle, degree of structural defects, and impurities. All these characteristics of MNPs determine their magnetic properties (Akbarzadeh et al. 2012; Gloag et al. 2019). Whatever is the chosen synthesis method, it is desirable that the method is reproducible and supplies a narrow particle size

5.1 Introduction

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Figure 5.1 Number of published papers in the last decade, according to the Web of Science statistic, related to (a) magnetic nanoparticles; (b) magnetic nanoparticles and medical applications, and (c) magnetic nanoparticles and scaffolds. The search was performed using these keywords in the topic.

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distribution, the control of the particle size and shape, and stable nanoparticles over a long time (Akbarzadeh et al. 2012; Bedanta et al. 2013). There are many MNPs synthesis methods described in the literature, among them are the thermal decomposition, solvothermal or hydrothermal reactions, microemulsion, coprecipitation, chemical vapor deposition, etc. (Akbarzadeh et al. 2012; Gloag et al. 2019; Katz 2019; Piñeiro et al. 2020). Coprecipitation, hydrothermal decomposition, and thermal decomposition techniques are the most used methods for MNPs synthesis because they are scalable, easy to perform, and supply MNPs with high quality and narrow dispersion of MNPs size (Piñeiro et al. 2020). A typical problem encountered in the MNPs application is their high tendency to suffer oxidation and to form agglomerates that harm the colloidal stability. This way, coating or functionalization of MNPs is necessary to avoid their agglomeration and oxidation to provide the desired properties. In the case of MNPs medical applications, this surface modification of MNPs is required to obtain a better performance in the biological media, like fluids or tissues. The coating or functionalization of MNPs can occur during or after MNPs synthesis, and usually, it has the purpose of promoting biocompatibility and target-specificity and preventing the biodegradation in biological media (Akbarzadeh et al. 2012; Kudr et al. 2017; Piñeiro et al. 2020). While the MNPs core is responsible for the magnetic action, their surface modification is the key to achieve the desired outcome. Several molecules, biomolecules (proteins, antigens, antibodies, DNA, RNA, etc.), surfactants, polymer chains, noble metals (gold and silver), and inorganic materials (carbon, amorphous, and mesoporous silica) have been used in the coating or functionalization of MNPs to promote their surfaces modification. In the case of the polymer coating, we can observe the utilization of natural polysaccharides such as dextran, chitosan, and synthetic polymer such as polyethylene glycol (PEG), vinyl polyacetate (PVA), polylactic acid (PLA), polyvinylpyrrolidone (PVP), poly(acrylic) acid (PAA). The MNPs coating can result in different structure types, as MNPs with core-shell structure, MNPs with molecules grafted on their surfaces, or MNPs fully encapsulated by polymer or lipid coating (Kudr et al. 2017; Katz 2019; Piñeiro et al. 2020). For scaffolds based on polymer nanocomposites, the coating or functionalization of MNPs will have a function to further the dispersion, distribution, and mainly the nanofiller adhesion in the matrix, besides the previously elucidated functions. These subjects are essential to obtain a good material performance similar to any nanocomposites. For example, the stability of the colloidal suspension of MNPs is important to provide efficient nanofiller dispersion and distribution in nanocomposites produced by wet routes. This chapter elucidates some techniques used in the scaffolds based on polymer nanocomposites filled with MNPs. In addition, examples and advances obtained by different research about scaffolds containing MNPs are commented on. Among advances reported in the literature, we can highlight the improvement of cellular adhesion, proliferation and differentiation, biocompatibility, swelling capability, compressive strength, biomimetic mineralization, and the possibility to promote tissue repair in conjunction with cancer cells treatment.

5.2 Production Methods for Scaffolds and Hydrogels Based on Polymer Nanocomposites Filled Hydrophilic and hydrophobic polymers can be used in the production of scaffolds. However, the utilization of a hydrophilic polymer will result in the water absorption capability by the material, creating hydrogels scaffolds. In this case, water is used as solvent-replacing organic solvent, which

5.2 Production Methods for Scaffolds and Hydrogels Based on Polymer Nanocomposites Filled

is an advantage. There are different methods for scaffolds and hydrogels scaffolds production as electrospinning, additive manufacturing (3D printing), freezing-drying, freezing-thawing, and others. In most of them, the solution-mixing is a very important step because it is where the MNPs addition in polymer matrix occurs. An efficient solution-mixing will imply good nanofiller dispersion and distribution in the matrix, which is a key point to obtain a homogeneous material with the desired properties. Therefore, Figure 5.2 summarizes the production methods, possible structures of scaffolds, the properties improved by MNPs addition, and the properties improved by magnetic field stimulation. The solution-mixing step first involves the polymer solubilization, then nanoparticles and particles need to be dispersed in the same kind of solvent (Lee et al. 2005; Thomas et al. 2010; Rane et al. 2018). This dispersion can be done by mechanical stirring; however, it is usually done by the employment of an ultrasonic vibration process (ultrasound bath and ultrasonic tip) due to its higher efficiency. A good result depends on the cavitation effect produced by ultrasonic vibration, and it is related to solution viscosity. High loads of particles and high polymer concentrations increase the viscosity of solution that hinders the cavitation process. At the end of the solution-mixing step,

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Figure 5.2 Flowchart representing the main stages of production, scaffolding structures, improvements in properties, and properties stimulated by the magnetic field in polymer nanocomposites filled with magnetic nanoparticles (MNPs).

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the degree of dispersion of the particles in the polymeric matrix is determined by the interaction between the filler and the solvent (Lee et al. 2005; Deshmukh et al. 2017; Rane et al. 2018; Akpan et al. 2019). Although it is practical and widely used, when the solution-mixing step is applied for the development of composites and nanocomposites based on hydrophobic polymers, the large-scale processing is hindered by the necessity of organic solvents (Mtibe et al. 2018; Ghaleb et al. 2019). Furthermore, depending on the application of the developed composites, it should choose a solvent that is biocompatible, which does not leave residues and does not affect human health (Stice 2019). After the solution-mixing step, the porous structure of scaffolds and hydrogels scaffolds is obtained according to the chosen method for their production. A brief explanation and examples of some methods are discussed ahead.

5.2.1

Freeze-drying

Freeze-drying or lyophilization consists of a drying method, in which the solvent is removed by sublimation process from previously frozen samples. As the solvent leaves the sample without the necessity of heating, the freeze-drying method preserves the structure of samples. Because of this, it is widely used for biological samples. In the production of polymer scaffolds, the outlet of solvent in the freeze-drying process results in a porous structure, this is desired for the application. The freeze-drying process can also be part or a step of another production method when it has the purpose of removing the solvent from a predefined-structure. Ghorbani et al. (2019) used the freeze-drying technique for the fabrication of superparamagnetic responsive polylactic-co-glycolic acid (PLGA)/gelatin/magnetite (iron oxide nanoparticles – MNPs) hybrid scaffolds with the unidirectional and tunable porous structure for rat bone marrow mesenchymal stem cells performance. The methodology consisted of first the PLGA and gelatin that were dissolving, 2 wt% of MNPs that was added and stirred during one hour, and then were transferred to a mold and freezing. The end of this mold was placed on a copper rod, and the end of this rod was placed into a liquid nitrogen tank. The frozen samples were transferred into a freeze dryer and lyophilized. After that, the hybrid scaffolds were neutralized (0.1 M NaOH for 1 hour), washed with deionized water, and soaked in deionized water for half an hour. Again, the scaffolds were frozen to prevent pore deformation. Finally, the authors found in this research what indicated the potential of superparamagnetic constructs for further preclinical and clinical studies in the field of neural regeneration. In a similar way, Li et al. (2019b) also produced poly(lactic-co-glycolic acid) (PLGA) scaffolds with hydroxyapatite (HAP) and MNPs by freeze-drying method. Other works in the literature have used freeze-drying for preparing polymer scaffolds, with chitosan polymer, for example. Among them, we can cite the production of scaffolds from chitosan with dextran-grafted maghemite and arginine (L-Arg) amino acid (Scialla et al. 2019), hybrid scaffolds of chitosan/collagen/Fe3O4 nanoparticles/nano-hydroxyapatite (Zhao et al. 2019), and chitosan scaffold with mesoporous bioglass microspheres and MNPs (Lu et al. 2018).

5.2.2

Freeze-thawing

The freeze-thawing method involves cycles of freezing and thawing of the sample until a structure is formed due to a physical crosslinking of polymer chains. This crosslinking is compounded by entanglement points between polymer chains or by crystalline regions. The number of entanglement depends on length, chemical bond angle, and side groups of polymer chains. In the case of crystalline regions, the most stable folded chain structures formed during freezing are not destroyed on thawing, acting as connecting points to the surrounding amorphous areas.

5.2 Production Methods for Scaffolds and Hydrogels Based on Polymer Nanocomposites Filled

Hou et al. (2015) developed hydrogels using polyvinyl alcohol (PVA), Fe2O3 and nanohydroxyapatite (nHAP) nanoparticles to verify the synergistic effects of natural polysaccharides, and these nanoparticles on cell adhesion and growth on intrinsically cell nonadhesive PVA hydrogels. The Fe2O3/nHAP/PVA hydrogels were obtained by solution-mixing and, then, were freezethawed six times to produce magnetic nanocomposite hydrogels. According to the results obtained by the authors, it was possible to verify that the magnetic hydrogel and polysaccharides provided synergistic pro-motion to cell adhesion and growth. Another research work developed by Hou et al. (2013) was the investigation of novel magnetic nano-hydroxyapatite (m-nHAP)/PVA composite hydrogels through cyclic freeze-thawing with controllable structure, mechanical properties, cell adhesion, and proliferation properties, the solution-mixing methodology was also used. According to the authors, with the increasing m-nHAP content in the composite hydrogels, the adhesion density and proliferation of the osteoblasts were significantly promoted, especially at the content of around 50 wt%. Furthermore, the nanoparticle (m-nHAP) showed a remarkable influence on the porous structure, mechanical strength, and cell adhesion and proliferation of the hydrogels. Mahdavinia et al. (2018) used solution-mixing methodology to obtain magnetic chitosan/polyvinyl alcohol (PVA)/laponite RD hydrogel nanocomposites beads for adsorption study of a model protein, bovine serum albumin (BSA). Chitosan and magnetic PVA/laponite RD solutions were mixed together and stirred for 30 minutes. The generated magnetic beads were stirred for 30 minutes again aiming on their hardening. After being collected, the beads were kept frozen overnight. The frozen beads were then thawed at ambient temperature for five hours. This freeze-thawing cycle was done for four times, and then the purified samples were laid under freeze-drying. The protocol included flash freezing in liquid N2, freezing at −80 C for 48 hours, in order to form a porous structure in the nanocomposite beads. The authors observed that using this methodology, the presence of magnetic laponite RD can improve the adsorption capacity of magnetic beads for BSA. In Aliramaji et al.’s (2017) research was presented the methodology to develop tunable pore structures for bone tissue engineering applications using different amounts of MNPs (iron oxide – magnetite) in silk fibroin (cocoons of Bombyxmori) and chitosan in obtaining magnetic scaffolds nanocomposites by a freeze-casting method. This methodology consists of adding amounts of magnetite particles in the solutions, they were then freeze-casted. Finally, the solutions were poured in a mold that was placed on a copper cold plate, the temperature of the cold plate was controlled by liquid nitrogen and a heater connected to the plate, and the obtained solidified solutions (scaffolds) were dried through freezing during 48 hours. The methodology chosen by the authors was adequate for obtaining scaffolds and should be studied further to be used in vivo for bone tissue engineering applications.

5.2.3 Electrospinning Electrospinning is a relatively simple and reproducible method, once the parameters have been established (Bhardwaj and Kundu 2010). The obtaining of continuous fibers to diameters in the micro and nanoscale, to obtain polymeric nanocomposites through the electrospinning process, takes place through the electrostatic forces (Reneker and Chun 1996). In this way, electrospinning consists of pulling a charged liquid jet out of a polymer solution (or melt) using strong electrostatic forces, that is, when a high-voltage electric field is applied (Bailey 1988; Doshi and Reneker 1995). The small jet diameter allows rapid evaporation of the solvent, and as a result, nanofibers are deposited on the collector (Bhardwaj and Kundu 2010; Hulsey et al. 2017).

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The first reports on the electrospinning process were found between the 30 and 40 seconds in which it consisted of the description of an experimental installation for the production of polymer filaments using an electrostatic force; therefore, from these studies, numerous patents were published, reporting the electrostatic spinning (Formhals 1934, 1939, 1943; Doshi and Reneker 1995; Reneker and Chun 1996; Hulsey et al. 2017). However, only from the 90 seconds, methods for obtaining polymeric nanocomposites using the electrospinning process began to be reported in the literature, and together, there were many possibilities for advancing the methodology for obtaining polymeric nanocomposites (Huang et al. 2003; Zhao et al. 2018) for different applications, as biomaterials (Haider et al. 2015; Ding et al. 2019; Rodríguez-Tobías et al. 2019; Jain et al. 2020), such as scaffolds for use in tissue engineering (Ha et al. 2013; Dong et al. 2014; Mi et al. 2018), drug delivery (Savva et al. 2012; Qin et al. 2019), sensors (Amith et al. 2018; Rosenberger et al. 2020), reinforcement of engineering materials, and for the food industry (Mercante et al. 2017; Schmatz et al. 2019), in addition to numerous application possibilities for these nanofibers (Luo et al. 2018; Spagnol et al. 2018; Oveisi et al. 2019; Yin et al. 2020). Burke et al. (2017) verified a possibility of obtaining polymer scaffolds composed of magnetic iron oxide nanoparticles (MNPs) contained within electrospun nano and microfibers of two biocompatible polymers, poly(ethyleneoxide) (PEO) and poly(vinyl pyrrolidone) (PVP). In this study, the authors successfully developed a novel high through the possibility of production rates of magnetic nanoparticle–nanofiber composite scaffolds by the electrospinning technique. Furthermore, nanoparticle–nanofiber composite scaffolds displayed morphological properties as good as or better than those previously described and fabricated using complex multistage techniques. Therefore, the authors aim at possible applications in contrast to improve magnetic resonance imaging, targeted drug delivery, gene therapy, hyperthermia treatment, filtration, glucose sensing, peroxidase mimetic activity, and cell separation. Zhang et al. (2017) used the electrospinning technique for the development of novel 3D composite membrane composed of the tri-block copolymer poly(ε-caprolactone) (PCL), poly(ethylene glycol) (PEG), poly(ε-caprolactone) (PCL) (PCEC), and magnetic iron oxide nanoparticles (Fe3O4 – NPs). The electrospinning methodology consists in dissolving the PCEC copolymer in CH2Cl2 solution, then dried Fe3O4 NPs was dispersed in hexane to form a uniform solution through stirring and ultrasound sonication, finally electrospinning was carried out at room temperature, and the resulting PCEC/ Fe3O4 composite membranes were collected from aluminum foil collector, and then dried at 40 C for 48 hours, to remove any residual solvent. The authors developed this material for application in various biomedical applications including magnetic resonance imaging (MRI), diagnostic contrast enhancement, magnetic cell separation, and targeted drug delivery. Moreover, the authors verified that this study revealed that this material might have great potential for use in skin tissue engineering. Jedlovszky-Hajdu et al. (2016) developed 2D and 3D fibrous scaffolds by reactive electrospinning as a potential matrix for cell culturing, from poly(succinimide) (PSI) and MNPs (magnetite). According to the authors, the use of magnetic particles loaded into electrospun scaffolds may provide a unique platform for the design of biomimetic fibrous scaffolds for potential cell culturing. Furthermore, the preparation of submicrometer sized, two or 3D fibrous scaffolds from magnetite doped PSI that are cross-linked by cysteamine is a novel approach with great promise in tissue engineering applications.

5.2.4

3D Printing

Three-dimensional printing technology is associated with additive manufacturing, which can project and draw customized products according to the needs of the population, in several areas as civil

5.2 Production Methods for Scaffolds and Hydrogels Based on Polymer Nanocomposites Filled

construction, medical and dental fields (Yan et al. 2018; Buchanan and Gardner 2019; Vasamsetty et al. 2020). Three-dimensional printing consists of a computerized system that allows you to design virtual 3D models, of any size and shape created by Computer-Aided Design/Computer-Aided Manufacturing (CAD/CAM) into 3D objects in a layer-by-layer, in which conventional molding or machining is dispensed, and then the object is printed on a specific printer for 3D printing (Hull 1986). In the 1980s, 3D printing was created by (Hull 1986), since then 3D printing has been applied to several scientific areas such as water treatment (Balogun et al. 2019; Tijing et al. 2020), dentistry, and mainly in the medical field, such as tissue engineering (Turnbull et al. 2017; Hassan et al. 2019; Haleem et al. 2020), such as scaffolds (Ergul et al. 2019; Nikolova and Chavali 2019; Ghorbani et al. 2020; Wang et al. 2020), and hydrogels scaffolds (Xu et al. 2019a; Li et al. 2020) in 3D with connected pores, fibrous intended to permit transport of body liquids and gases, to promote cell interaction, for example, and another’s applications, that can be used to rapidly manufacture personalized tissue engineering, for example, to repair tissue defects in situ with cells and even directly print tissue and organs (Luo et al. 2019). Zhang et al. (2014) used the 3D printing technique to obtain MNPs (Fe3O4) containing mesoporous bioactive glass (MBG) and polycaprolactone (PCL) composite scaffolds (Fe3O4/MBG/PCL) with multifunctionality of bone regeneration, local anticancer drug delivery, and hyperthermia. Basically, the methodology consisted of Fe3O4 magnetic particles and MBG powder were mixed, and added to the PCL solution, then the mixture was quickly stirred at room temperature until it had formed a paste for injection. Finally, the prepared paste was introduced into a polyethylene injection cartridge that was fixed onto the 3D printing device. According to the study, the authors observed that Fe3O4/MBG/PCL scaffolds exhibited excellent apatite-forming bioactivity, sustained anticancer drug delivery and magnetic healing properties due to the mesoporous structure of MBG and Fe3O4 nanoparticles, in addition to the potential multifunctionality of the treatment and regeneration of bone defects caused by bone tumors through a combination of enhanced osteogenic activity, local anticancer drug delivery, and magnetic hyperthermia. Tanasa et al. (2020) investigated the impact of the magnetic field on 3T3-E1 preosteoblastes inside smart silk fibron-based scaffolds decorated with MNPs (Fe3O4). The authors synthesized by free radical polymerization technique the scaffolds of silk fibroin and poly(2-hydroxyethyl methacrylate) (HEMA) and decorated them with MNPs. The purpose of adding MNPs is to improve osteogenic process through response of magnetic structures to weak static magnetic fields. In this study, cell culture setup allowed authors to observe the cellular modification under exposition of weak static magnetic field, that is, the increasing of cellular proliferation potential of 3T3-E1 cell line. The authors conclude that the low static magnetic field contributes to osteogenic differentiation potential of the cells in the magnetic scaffolds. The study by Santis et al. (2016) developed hybrid scaffolds for osteochondral tissue regeneration using poly(ε-caprolactone) (PCL) and poly(ethylene glycol) (PEGDA) and MNPs to obtain nanocomposites, by stereolithography, that were processed through Fused Deposition Modeling (FDM) using a 3D to manufacture 3D cylindrical scaffolds. According to the authors, by combining fused deposition modeling and stereolithography, it is possible to manufacture a hybrid scaffold suitable for osteochondral tissue regeneration. Furthermore, the authors found that PCL/PEGbased magnetic nanocomposites scaffolds adequately reproduce viscoelastic properties of trabecular bone and articular cartilage tissues, respectively. In the study presented by Russo et al. (2013), a different injectable systems has been proposed, trying to reduce surgical invasiveness. In this way, the author’s development of 3D nanocomposite magnetic scaffolds by poly(ε-caprolactone)(PCL)/iron-doped hydroxyapatite (FeHA) using 3D

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fiber-deposition technique, for bone tissue engineering, providing a preliminary approach to assess magnetic attraction forces.

5.3

Applications of Scaffolds Filled with MNPs

In addition to the different production methodologies, several matrices (ceramic, polymeric, hybrid, among others) with the incorporation of MNPs, mainly of magnetite (Fe3O4 – Iron Oxides II and III), are used in the production of magnetic scaffold biomedical applications. This is due to the diversity of possibilities of formulations and the incorporation of other materials aiming at the desired application. Recent studies, in addition to characterizing the chemical, physical, mechanical, and electromagnetic properties, perform biological studies (in vitro and in vivo) aiming at the application of magnetic polymer scaffolds. The application of these materials arouse the interest of tissue engineering, being able to simulate the tissue, act as a similar tissue, act as a graft for artificial tissues, and assist in the treatment of the skin of people infected by some type of bacteria. In addition to the use in stimulation of osteoblastic properties and bone grafts when reinforced with rigid support materials, these materials are also used in cancer therapies, especially those that involve and release medications targeting lesions and hyperthermia. In the applications that will be discussed in detail throughout the chapter, hydrogels scaffolds were referred to only as hydrogels, for the sake of clarity in the approach to the type of scaffolds. Applications are divided into groups despite being closely interconnected.

5.3.1

Oncological Therapies

Hydrogel scaffolds with MNPs are widely used in therapies for the treatment of the most diverse types of cancer. This is due to the fact that they enable the realization of localized therapies with lesser side effects, the possibility of controlled release of drugs and heating of the area affected by the lesion. The controlled release of drugs by the applied magnetic field occurs with the vibration of the MNPs causing the gradual release of the drug, when it reaches the tumor. In the case of magnetic hyperthermia therapies, the tumor cells are affected by the elevation of the local temperature by the magnetic field, during a determined period, facilitating the death of the malignant cells. In some cases, the use of hyperthermia and the release of medications occur simultaneously, while heat attacks cancer cells, the drug acts to prevent rejection of the material or to prevent infection in the site affected by the tumor. Some studies on these applications will be presented below. 5.3.1.1 Hyperthermia Therapy

The use of magnetic scaffolds has shown satisfactory results in studies of hyperthermia therapy due to the presence of MNPs in the material responding to external stimulation of the magnetic field. The magnetic SrFe12O19 nanoparticles (M-type hexagonal ferrites) were added in a chitosan scaffold with mesoporous bioglass (BG) microspheres in the work of Lu et al. (2018). The modifiedmesoporous BG/CS scaffold (MBCS) with and without the MNPs were prepared by solution-mixing and freeze-dried varying the mass ratio of the component, SrFe12O19/BG (1 : 7 and 1 : 3). The formation of interconnected macropores and the homogeneous distribution of MPNs and BG in the scaffolds were observed. The values of saturation magnetization were 4.44 and 7.68 emu g−1 for MBCS1 : 7 and MBCS1 : 3, respectively. As expected, scaffolds are nontoxic and have good cytocompatibility. The results of cell proliferation, osteoogenic differentiation, and new bone regeneration were directly dependent on the amount of MNPs in the scaffolds, where phosphate formation

5.3 Applications of Scaffolds Filled with MNPs

in mineralization was accelerated during the osteogenesis process. The SrFe12O19 caused good results of anticancer efficacy in the magnetic scaffolds with the laser irradiation. These magnetic scaffolds presented excellent photothermal therapy functions to inhibit tumor cells. Hyperthermia therapy has also been researched through the development of MNPs synthesis of magnetite and encapsulation via polymerization by reverse miniemulsion, poly(acrylic acid), and direct, in poly(methyl methacrylate). The joint encapsulation of chemotherapeutics can create highly specific and selective markers generating complex nanoparticulate systems, providing less invasive and more efficient treatments since they act in a selective and concentrated manner in the affected tumor region. Thus, the application of an external alternating magnetic field can activate the MNPs so that, in the initial moments of application of the field, the vibrations of the nanoparticles would facilitate the release of the drug, acting on the weakening of the carcinogenic cells. Subsequently, the maintenance of the continued application of the magnetic field can generate enough heat to kill tumor cells, aiming at the application of hyperthermia in cancer therapies (Martins 2017). Magnetic hydrogels can also simulate cancerous tissue so that the interaction with nanoparticles can be studied. When dispersed in the magnetic fluid, these materials interact with the compromised breast tissue in different ways, influencing the heating efficiency of the nanoparticles. The quantification of this influence is complex since it is highly dependent on the mobility of MNPs contained in the environment affected by cancer, which in turn has a great influence on warming. The iron oxide MNPs were synthesized by alkaline co-precipitation of iron salts and coated with sodium acetate. So the hydrogel can simulate the fabric of this environment and have the mesh size adjusted to analyze this influence. Based on the context of Brownian and Néel relaxation times, the high inhibition of Brownian relaxation results in warming. The results of this study showed that for the highest immobilization status in acrylamide hydrogels with adapted mesh, heating becomes up to 35% less efficient. The ability of these hydrogels to simulate fabrics and mesh adjustment can be used to quantify the effects of immobilization: (i) heating efficiency, (ii) magnetic resonance and, (iii) image of diverse MNPs (Engelmann et al. 2019). 5.3.1.2

Drug Delivery Therapy

The magnetic field can also act on microrobots capable of delivering therapeutic drugs to a target lesion of a cancer cell. However, the magnetic MNPs that make up these devices can remain toxic in the body, even when the use of this medication is finished. In order to recover these particles and exclude this problem, the microrobot was made of MNPs, a hydrogel-based on gelatin/polyvinyl alcohol (PVA), with particles of polylactic-co-glycolic (PLGA) acid that transport doxorubicin (DOX) (PLGA-DOX particles). An integrated system of personalized electromagnetic actuation (EMA) and near-infrared (NIR) was developed in order to direct and recover these hydrogel nanoparticles. In this system, the device reaches a target lesion predetermined by the EMA system’s magnetic field. After irradiation with NIR, the gelatin/polyvinyl alcohol of the micro-robot hydrogel is decomposed. The MNPs that remained in the target lesion area are disassembled and recovered by the magnetic field of the personalized electromagnetic actuation system. Thus, the remaining particles of PLGA-DOX can finally release a drug that will produce the therapeutic anti-carcinogenic effect in the target lesion, since the DOX loaded in the particles is released naturally over time (Kim et al. 2019). In another study, a magnetically directed drug carrier was developed from a hydrogel, produced by copolymerizing N-(hydroxymethyl) acrylamide (HMAA) with a crotonic acid graft (CA) and in salecan. The pH-sensitive salecang-poly(CA-co-HMAA) hydrogel network was incorporated with Fe3O4 SiO2 nanoparticles to deliver doxorubicin (DOX). The results showed that DOX was able

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to (i) be charged effectively to the compound hydrogels; (ii) be released, in vitro, controlled according to the pH with a sustained character, and remain biologically active; (iii) preserve its bioavailability. The increase in the amount of salecan provided a faster release of the drug; the delivery was also greater in the presence of an external magnetic field. The cytotoxicity tests in human and animal cells and live-dead cells also showed promising results. Thus, the prepared magnetic compound hydrogels showed potential for delivering anticancer drugs, mainly for those magnetically directed (Hu et al. 2018b). The delivery and release capacity of DOX was also the subject of a study, which developed the photopolymerization coating of iron oxide magnetic nanoparticles (MIONPs) with functional and sensitive metalloproteinase (MMP) polyethylene glycol (PEG) hydrogel, to nanocarriers. The targeted nanocarriers were developed aiming at the triggered release of anti-cancer medication, DOX, in HeLa cells, and specific intracellular uptake of MIONP receptors. The results showed that the transport of coated nanocarriers to cancer cells was eleven times more efficient than the uncoated ones, and that the delivery and release capacity of DOX by these devices occur satisfactorily in the nuclei of HeLa cells in the period of two hours, and in these cells, an enhanced intracellular uptake of MIONPs has also been reported. Thus, with the developed targeted nanocarriers, it will be possible to minimize the adverse effects and reduce the resistance of the cancerous tissue to the medications, through the optimization of the chemotherapy treatments by the delivery of the drugs directly into the tumors, also having potential for application in the simultaneous generation of images of the drug, administration, and release of medications (Nazli et al. 2014). The inhibition of bacteria in these magnetic nanocomposites was analyzed in hydrogels consisting basically of polyacrylamide (PAAm) and modified or not with polysaccharides, clay minerals, and/or magnetic iron oxide nanoparticles functionalized with a polymeric material. The nanocomposites were prepared with 0.5–2.0% w/w MNPs, where all the studied proportions had magnetic properties. In the characterizations applying a constant 0.23 T magnetic field, there was a direct influence on all properties, such as an increase in the water absorption speed. There was a release, up to five times faster, of the active streptomycin, present in the structure, when compared to materials without application of a magnetic field. The application of the magnetic field also led to an average increase of 16.4% in the radius of inhibition of the studied bacteria, in the release tests in cultures of Escherichia coli bacteria, also demonstrating the bactericidal efficiency of hydrogels loaded with streptomycin. A pulsatile release behavior as a function of field application was observed. Therefore, the formulated hydrogels can be used in responsive drug delivery systems, since the material will release the active more efficiently under the action of a magnetic field besides being used in skin treatments of animals infected with some type of bacterium (Bortolin 2018). In another example of drug delivery therapy approach aimed at optimizing anti-cancer treatments, in postsurgical applications, was addressed with the development of a self-assembled injectable supramolecular magnetic hydrogel (MSH), for which cyclodextrins (DC) were used due to its ability to form a crystalline inclusion complex (IC) with polyethylene glycol (PEG). MSH was made using complexation of inclusion between Fe3O4, PEGylated, and α-CD nanoparticles. With the injection of MSH in the postoperative wound of the mouse with breast cancer, it was possible to verify the magnetocaloric capacity of the gel-sol and excellent combination with the irregular internal cavity formed after resection of the tumor without blind angle when exposed to the magnetic field of the alternating current (ACMF). The dual hierarchical structure of the biocompatible supramolecular hydrogels allowed the coloading of hydrophobic and hydrophilic drugs, in the lipid layer of MNPs and in the massive construction of the gel, respectively, with different processes of localized release, in the long term, of chemotherapeutic drugs and cell damage thermally induced. The hydrogel nanocomposite has a potential local therapeutic approach, as it has a minimally invasive

5.3 Applications of Scaffolds Filled with MNPs

injection in vivo, synergistically eliminates the tumor, and completely prevents local recurrence of breast cancer after surgical resection of the compromised tissue (Wu et al. 2018).

5.3.2 Tissue Regeneration In a large number of studies, scaffolds are used with the purpose of providing a favorable environment for cell growth to promote regeneration of several types of tissues. In this sense, the presence of MNPs in these scaffolds can result in changes in properties, such as porosity, swelling, mechanical resistance, which will enhance tissue regeneration. Besides that, the presence of the MNPs can activate signaling pathways and receptors present on the cell surface, thus guaranteeing cell activity during the treatment proposed for the use of scaffolds. In addition, the stimulation of the magnetic field can (i) favor the assimilation of scaffolds with the host bone, in the case of bone regeneration, increasing the calcium content, density, and healing; (ii) improve adhesion, growth, proliferation, and differentiation of bone cells in the osteogenesis or dental cells in the odontogenesis process, and other specific cells in tissue engineering. Some study examples on this type of application will be discussed below. Scialla et al. (2019) produced scaffolds from chitosan (CS), dextran-grafted maghemite (DM), bioactive agent, and the arginine (L-Arg) amino acid (0.1 M) through solution-mixing and freeze-drying. The scaffolds showed interconnected pores and DM distributed throughout the polymer. The combined addition of DM and L-Arg significantly increased the compressive strength of scaffolds (samples with 5, and 10 wt% of DM) and also improved swelling results. Cell proliferation was stimulated in the CS/DM-Ag scaffolds both in the application and in the absence of the magnetic field. Tanasa et al. (2020) produced scaffolds of silk fibroin/poly(2-hydroxyethyl methacrylate) (SF/PHEMA) by synthetization and by free radical polymerization techniques. With the addition of MNPs (Fe3O4), the authors observed the superparamagnetic performance and better biocompatibility (morphology, growth, and distribution) in the scaffolds. When the magnetic scaffolds were exposed to the magnetic field, they noted cellular modifications and an increase of cellular proliferation. The good dispersion of the MNPs in the scaffolds favors the improvement of the properties of the final material, so Yang et al. (2019) functionalized the MNPs (Fe3O4) with oleic acid (AO-MNPs) and added them in the matrix of poly-L-lactic acid (PLLA). The scaffolds were prepared using selective laser sintering (SLS) of the composite powders with the following proportions of MNPs with and without functionalization: 0, 4, 8, 12, and 16 wt%. AO-MNPs showed the same magnetic properties as MNPs without functionalization, however, AO-MNPs were better dispersed in the PLLA matrix. AO-MNPs have improved the mechanical properties of the scaffold, and these have a magnetization saturation of up to 10.7 emu g−1. As scaffolds with the addition of 12% AO-MNPs show better results in the mechanical properties (95% increase in compressive strength and 68% in compressive modulus compared to scaffolds without MNPs), cytocompatibility was also analyzed. In the results of in vitro tests, it was observed that AO-MNPs significantly improved the adhesion, proliferation, viability, and cell differentiation of scaffolds. A different methodology for obtaining the magnetic scaffolds for application in tissue engineering and drug release was studied by Li et al. 2019a). The scaffolds of silk fibroin and Fe3O4 nanoparticles were produced by electrospinning technology and cooperative assembly method. In this way, the scaffolds obtained contained the MNPs inside the fibers and in their surface, forming a core-shell structure. The proposed methodology was adequate, and the MNPs were well distributed inside and outside the scaffold nanofibers. With the presence of MNPs in the scaffolds, the authors observed better fixation, proliferation, and cell viability, which is also a consequence of large number of pores

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and pores interconnected in the magnetic scaffolds. The authors also observed that cell growth was not only on the surface but also throughout the scaffold. In the study, a simple method was developed to synthesize shell-core structures, with nuclei composed of MNPs with a thermoresponsive polymer shell, using the miniemulsion polymerization method. For this, magnetic iron oxide MNPs and a poly-N-isopropyl acrylamide hydrogel (PNIPAAm) were used. This set is interesting since MNPs generate heat through Neel and Brown relaxation and loss of magnetic hysteresis when exposed to a variable magnetic field, and the thermo-responsive polymers may collapse or expand with heating. The particles formed, when in water, swell below the phase transition temperature and shrink above it. The results show that the magnetic composites remained stable when kept at room temperature, even if there were long intervals without showing signs of precipitation, enabling their application in the biomedical area (Khan et al. 2012). In addition to simulating tissues, biomaterials have potential applications as tissues. The study sought to develop a nanomaterial like hyaline cartilage. The compounds were prepared by encapsulating MNPs and human hyaline chondrocytes in fibrin-agarose hydrogels. The analysis show that stronger and biomechanically stable biomaterials were obtained due to the inclusion of magnetic nanometric particles, which in turn did not interfere in cytocompatibility or in the viability and proliferation of chondrocytes. The incorporation of human hyaline chondrocytes led to the control of the swelling capacity in comparison with nonmagnetic and acellular magnetic fibrinagarose biomaterials. The fibrin-agarose hydrogels conferred a high degree of swelling to the materials. These results demonstrated the feasibility of producing artificial magnetic fabrics for application in the field of tissue engineering with promising in vitro cytocompatibility (Bonhome-Espinosa et al. 2020). Shuai et al. (2020) added magnetite (Fe3O4) nanoparticle to improve cell viability in scaffolds and thus promote bone regeneration. The magnetic scaffolds of poly-L-lactide/polyglycolic acid (PLLA/ PGA) were prepared using a SLS of the composites powders. The composites powders were elaborated through a PLLA/PGA solution with a concentration of MNPs at 0, 2.5, 5, 7.5, and 10 wt%. For the preparation of the composites powders, the solutions were further ultrasonicated, stirred in a grinding mill, centrifuged, and dried in a drying oven. The magnetic scaffolds presented a superparamagnetic performance and the addition of MNPs improved significantly the hydrophilicity of the scaffolds, which are great results for providing cell viability. The better result of compression testing was observed in the scaffolds with 7.5% MNPs, and this value is close to bone values. The results of the biocompatibility in vitro showed that the incorporation of 7.5% MNPs into scaffolds improved significantly the cells viability, adhesion, proliferation, and differentiation. Similarly, in vivo results exhibited that the MNPs increased the bone regeneration of scaffolds. The MNPs created a magnetic microenvironment within the scaffolds that improved cell viability thereby facilitating bone regeneration. The influence of the application of a pulsed electromagnetic field on the development of stem cells in magnetic scaffolds was analyzed by Huang et al. (2017). Scaffolds production of L-polylactic acid (PLLA), nano-hydroxyapatite (nHAP), and MNPs (Fe3O4) were by low-temperature rapid prototyping. The authors did not observe significant differences between cell proliferation results; however, positive action was observed in osteogenic differentiation in the combination of the MPNs and the pulsed electromagnetic field. Bone regeneration also showed interesting results in a study that carried out the addition of MNPs in hybrid matrices. Cojocaru et al. (2019) produced scaffolds of biopolymers with calcium phosphate and MNPs (magnetite coated with chitosan). The combinations of CS-based scaffolds were produced by a biomimetic co-precipitation method, varying the addition of hyaluronic acid,

5.3 Applications of Scaffolds Filled with MNPs

bovine serum albumin, and gelatin. The MNPs were added in concentrations of 1, 3, and 5 wt%. The formation of a macroporous structure was observed that allowed the retention of simulated biological fluids in the material. The magnetic scaffolds exhibited magnetic properties between 0.25 and 12.53 emu g−1. The addition of MNPs decreased the degradation of the scaffolds; however, the magnetic scaffolds present good results of biocompatibility and are propitious means for osteoblasts. The stimulation of osteoblastic properties was studied by preparing magnetic hydrogels of polyvinyl alcohol (PVA) with iron oxide III (Fe2O3) and hydroxyapatite (nHAP) nanoparticles, important components of the extracellular cartilage matrix (MEC) were also added, hyaluronic acid (HA), or chondroitin sulfate (CS). The PVA hydrogels were prepared in several compositions, where the chondrocytes were seeded and cultivated. Results had already demonstrated that the incorporated particles of Fe2O3 and nHAP acted in the desired way in increasing the growth of osteoblasts in a PVA matrix. In general, the presence of HA or CS led to an increase in pore size and the balance dilation ratio (ESR), without losing the mechanical resistance to compression. The combination of both PVA improved cell adhesion and proliferation when compared to a single polysaccharide. Thus, demonstrating synergistic effects of magnetic composites of polysaccharides and nanoparticles, in increasing the adhesion and proliferation of chondrocytes, showing a potential biomedical application (Hou et al. 2015). Zhao et al. (2019) used biomimetic in situ fabrication and freeze-drying techniques to prepare hybrid scaffolds of chitosan/collagen/Fe3O4 nanoparticles/nano-hydroxyapatite (Cs/Col/Fe3O4/ nHAP). Magnetic scaffolds showed high porosity, with interconnected pores, magnetic saturation at 0.025 emu g−1, and better mechanical compression properties compared to scaffolds without MNPs. The results of in vitro tests showed that the addition of MNPs caused an improvement in situ biomimetic mineralization and bioactivity in the scaffolds. And the data from the in vivo analysis confirmed the material’s potential for bone regeneration, in which they also observed better tissue compatibility. The authors attributed the good results of the Cs/Col/Fe3O4/nHAP scaffolds, as osteoinduction and material bioactivity, to two factors: magnetic effect of MNPs and greater nucleation of nHAP in the scaffolds due to the presence of MNPs. This greater nucleation of nHAP favors the proliferation of cells in the material. Monitoring the efficiency of the scaffolds in some cases can be aggressive during treatment, in this way Hu et al. (2018a) prepared a magnetic scaffold in which bone recovery was monitored without an invasive visualization. The authors produced by immersing a magnetic scaffold of gelatin sponges (GS) with MNPs, γ-Fe2O3 core, and a polyglucose-sorbitol-carboxymethyether (PSC) shell. The scaffolds were tested in vivo in which it was possible to verify that the addition of the MNPs helped significantly in bone regeneration, without the application of an external magnetic field, and that it was possible to monitor the development due to the presence of the contrast agent. The development of magnetized nanocomposites can also be performed aiming at the application as bone grafts, using polyethylene glycol (PEG) hydrogel containing cells from the stromal vascular fraction (SVF) of human adipose tissue, and MNPs as incorporated. The study of the stimulation of osteoblastic and vasculogenic properties due to an external static magnetic field (SMF) was carried out. The results showed the free movement, through and outside the material, of the MNPs and that the activated cells had increased metabolic activity. Tomographic analysis revealed that implants applied in mice show vascularized tissues that were more mineralized, dense, and faster when acted magnetically. The nanocomposite obtained can also be reinforced with rigid support materials, thus generating real free bone tissue, with greater possibilities for bone applications (Filippi et al. 2019). Scaffolds were used in another study aimed at application in dental pulp-dentin regeneration (Yun et al. 2015). MNPs (Fe3O4) were added in the poly-caprolactone (PCL) matrix in the following proportions: 0, 5, and 10 wt%. The scaffolds had a pore size of 250–500 μm, greater roughness with

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the addition of MNPs, and saturation magnetization values of 1.63 and 3.02 emu g−1 for PCL + MNPs 5%, and PCL + MNP 10%, respectively. Better results of adhesion, migration, and odontogenesis of human dental pulp cells were observed in scaffolds with MNPs. In order to repair bone defect and inactivate the tumor, Li et al. (2019b) added magnetite (Fe3O4) nanoparticle in scaffolds of poly(lactic-co-glycolic acid) (PLGA) with hydroxyapatite (HAP). The magnetic scaffolds (with 3, 5 and 10 wt% of MNPs) were prepared by solution followed by stirring, lyophilization, washing (to remove the salt responsible for the formation of the pores), and drying. The authors observed the formation of macropores in the structure and homogeneous distribution of MNPs in the scaffolds. The magnetic scaffolds showed good magnetic properties (magnetization saturation of 3.89 emu g−1) and compressive strength values of 3.74 ± 0.4 MPa with the addition of 5 wt% of MNPs. The addition of MNPs provided good results for bone cell adhesion and proliferation, and for tumor cell inactivation (78% cells died after hyperthermia), according to in vitro tests. In vivo results revealed that, after 12 weeks, the bone defect was practically healed, and the scaffolds were degraded. Thus, the addition of MNPs allows bone repair in conjunction with tumor treatment, since these nanoparticles are capable of killing tumor cells.

5.4

Conclusion

The increasing interest of the scientific community in the research relating to MNPs reflects their great potential for medical applications. Among medical applications, MNPs utilization for scaffolds development has been promising, especially for scaffolds that consist of polymeric nanocomposites. The methods used to introduce the MNPs in the polymeric matrix and produce the scaffolds are diverse as well as the obtained structures. The modulation of scaffolds properties by MNPs has been successful, as porosity, water absorption, and mechanical resistance. However, the main advantages in the MNPs utilization over other nanoparticles consist of affording magnetic propriety for scaffolds, allowing that a magnetic field action stimulates tissue regeneration and enables drug release and hyperthermia of tumor cells through the MNPs heating, among other examples discussed in this chapter. Numerous are the parameters that can be used to modulate the properties of the scaffolds according to the target application, such as type of MNPs, their surface modification, and concentration, besides the method and polymer chosen for scaffold production, among others. Thus, the use of MNPs in the development of scaffolds for medical applications is a rich field for investigation, despite the growing number of studies in the literature.

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Luo, Y., Wei, X., Wan, Y. et al. (2019). 3D printing of hydrogel scaffolds for future application in photothermal therapy of breast cancer and tissue repair. Acta Biomaterialia 92: 37–47. Mahdavinia, G.R., Soleymani, M., Etemadi, H. et al. (2018). Model protein BSA adsorption onto novel magnetic chitosan/PVA/laponite RD hydrogel nanocomposite beads. International Journal of Biological Macromolecules 107: 719–729. Martins, M.G. (2017). Encapsulamento de Nanopartículas Magnéticas em Polímeros Acrílicos e Avaliação de Hipertermia Para Potencial Tratamento de Câncer. Universidade Federal do Rio de Janeiro UFRJ/COPPE. Masood, N., Ahmed, R., Tariq, M. et al. (2019). Silver nanoparticle impregnated chitosan-PEG hydrogel enhances wound healing in diabetes induced rabbits. International Journal of Pharmaceutics 559: 23–36. Mercante, L.A., Scagion, V.P., Migliorini, F.L. et al. (2017). Electrospinning-based (bio)sensors for food and agricultural applications: a review. Trends in Analytical Chemistry 91: 91–103. Mi, H.Y., Jing, X., Napiwocki, B.N. et al. (2018). Fabrication of fibrous silica sponges by self-assembly electrospinning and their application in tissue engineering for three-dimensional tissue regeneration. Chemical Engineering Journal 331: 652–662. Montanheiro, T.L.A., Montagna, L.S., Patrulea, V. et al. (2019a). Enhanced water uptake of PHBV scaffolds with functionalized cellulose nanocrystals. Polymer Testing 79: 1–8. Montanheiro, T.L.A., Montagna, L.S., Patrulea, V. et al. (2019b). Evaluation of cellulose nanocrystal addition on morphology, compression modulus and cytotoxicity of poly(3-hydroxybutyrate-co-3hydroxyvalerate) scaffolds. Journal of Materials Science 54 (9): 7198–7210. Mtibe, A., Mokhothu, T.H., John, M.J. et al. (2018). Fabrication and characterization of various engineered nanomaterials. In: Handbook of Nanomaterials for Industrial Applications: Micro and Nano Technologies (ed. C.M. Hussain), 151–171. Elsevier Inc. Nazli, C., Demirer, G.S., Yar, Y. et al. (2014). Targeted delivery of doxorubicin into tumor cells via MMPsensitive PEG hydrogel-coated magnetic iron oxide nanoparticles (MIONPs). Colloids and Surfaces B: Biointerfaces 122: 674–683. Nikolova, M.P. and Chavali, M.S. (2019). Recent advances in biomaterials for 3D scaffolds: a review. Bioactive Materials 4: 271–292. Oveisi, M., Mahmoodi, N.M., and Asli, M.A. (2019). Facile and green synthesis of metal-organic framework/inorganic nanofiber using electrospinning for recyclable visible-light photocatalysis. Journal of Cleaner Production 222: 669–684. Patil, S. and Singh, N. (2019). Antibacterial silk fibroin scaffolds with green synthesized silver nanoparticles for osteoblast proliferation and human mesenchymal stem cell differentiation. Colloids and Surfaces B: Biointerfaces 176: 150–155. Patil, R., Kansara, V., Ray, D. et al. (2019). Slow degrading hyaluronic acid hydrogel reinforced with cationized graphene nanosheets. International Journal of Biological Macromolecules 141: 232–239. Piñeiro, Y., Gómez, M.G., Alves, L.C. et al. (2020). Hybrid nanostructured magnetite nanoparticles: from bio-detection and theragnostics to regenerative medicine. Magnetochemistry 6 (4): 1–27. Pomari, A.A.N., Montanheiro, T.L.A., Siqueira, C.P. et al. (2019). Chitosan hydrogels crosslinked by genipin and reinforced with cellulose nanocrystals: production and characterization. Journal of Composites Science 3 (84): 1–12. Qin, Z., Jia, X.W., Liu, Q. et al. (2019). Fast dissolving oral films for drug delivery prepared from chitosan/ pullulan electrospinning nanofibers. International Journal of Biological Macromolecules 137: 224–231. Rane, A.V., Kanny, K., Abitha, V.K., and Thomas, S. (2018). Methods for synthesis of nanoparticles and fabrication of nanocomposites. In: Synthesis of Inorganic Nanomaterials (eds. S.M. Bhagyaraj, O.S. Oluwafemi, N. Kalarikkal and S. Thomas), 121–139.

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6 Magnetic Polymer Colloids for Ultrasensitive Molecular Imaging Sundas Riaz1, Sumera Khizar1, Nasir M. Ahmad1, Gul Shahnaz2, Noureddine Lebaz3, and Abdelhamid Elaissari4 1 Polymer Research Lab, School of Chemical and Materials Engineering (SCME), National University of Sciences and Technology (NUST), Islamabad, Pakistan 2 Department of Pharmacy, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad, Pakistan 3 University Claude Bernard Lyon-1, CNRS, LAGEPP UMR-5007, Villeurbanne, France 4 University Claude Bernard Lyon-1, CNRS, ISA-UMR 5280, Lyon, France

6.1

Introduction

Magnetic resonance imaging (MRI), based on the concept of nuclear magnetic resonance, has become a popular diagnostic technique since the acquisition of the first clinical MRI scan in 1977. A typical clinical MRI machine uses a primary magnetic field with a magnetic field strength of 1.5–3 Tesla (termed as 1.5 or 3 T) and specifically designed radiofrequency induction coils to produce highly detailed images (Simonsen et al. 2019). The image acquisition is based on the interaction of hydrogen nuclei associated with water molecules present in the human body, with a radio frequency pulse applied in the presence of a uniform magnetic field. The details in an MR image are a consequence of the contrast generated due to a variation in the amount of water molecules present in different tissues of the body (Mastrogiacomo et al. 2019). MRI is used to detect the nucleus of hydrogen (H+) in the water molecules as present in the body. Protons are positively charged subatomic particles that are constantly rotating along their axis. The rotational movement of protons in an atom gives rise to a quantum-mechanic atomic property that is called spin. Since this technique uses a magnetic field and electromagnetic radiofrequency rather than ionizing radiation employed in other contemporary molecular imaging techniques such as X-ray computed tomography (X-ray CT or CT), and positron emission tomography (PET), it has become a gold standard as a considerably safe, noninvasive imaging technique in clinical diagnostics (Atabo and Umar 2019). Besides its use as an exceptional diagnostic technique, MRI has a diverse assortment of applications in both industry and academia. Some applications of MRI are based on the unique ability of this technique to noninvasively image live subjects and intact objects, whereas various other applications rely on its use as a high-resolution in vitro imaging technique. In the context of imaging of live subjects, MRI is used in the pharmaceutical industry for in vivo theranostic research during preclinical

Magnetic Nanoparticles in Human Health and Medicine: Current Medical Applications and Alternative Therapy of Cancer, First Edition. Costica Caizer and Mahendra Rai. © 2022 John Wiley & Sons Ltd. Published 2022 by John Wiley & Sons Ltd.

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trials of new drugs in small animals (Fiordelisi et al. 2019). Most of the currently available diagnosis and therapies are invasive, time-consuming, and associated with severe toxic side effects. Theranostic research refers to the simultaneous administration and observation of the effects of a therapeutic agent or drug in a live animal model in a noninvasive manner (Wong et al. 2020). The ability of MRI to obtain images solely based on water molecules in a sample has led to the use of MRI as an in vitro characterization technique for studying the hydration effect of materials like cement and concrete to improve the durability and performances of cement-based materials (Du et al. 2019). Similarly, a variety of imaging techniques are currently used within the field of pharmaceutics to help understand and determine a wide range of phenomena associated with drug release from hydrophilic matrix tablets. The hydration effects of tablets are also being studied in the pharmaceutical industry with the help of MRI (Ward et al. 2019). The use of MRI as an in vitro diagnostic tool for cellular imaging and analysis of ex vivo histological samples is also a very interesting prospect (Mastrogiacomo et al. 2019). A typical 1.5 T clinical MRI machine produces images in the resolution of the millimeter-to-submillimeter range. While this resolution is sufficient to obtain a clinical diagnosis, a relatively limited signal-to-noise ratio becomes a liability in the use of the same system for an in vitro diagnostic application, which requires detail at the level of single cells (Geraldi and Giri-Rachman 2019). Early diagnosis of infectious diseases represents powerful means to increase patient survival rate, avoid disease spreading, and decrease healthcare costs. Recent scientific progress in the field of magnetic resonance imaging is targeted at improving the sensitivity of MRI in terms of improvement in spatial resolution and signal-to-noise ratio so that the full potential of MRI as an ultrasensitive imaging technique can be reached. These research areas revolve around the following themes: i) Improvement in instrument design or hardware, such as the development of stronger primary magnetic fields up to 11 T, and the development of specialized gradient coils to improve resolution (Zubkov et al. 2018). ii) Development of exogenous contrast agents that significantly increase the signal-to-noise ratio and enhance the sensitivity of MR images by interacting with the magnetic spins of water molecules in a sample. Current trends in the development of ultrasensitive MRI contrast agents focus on the effect of size of contrast agent on its magnetic resonance properties and the significance of polymer-based coatings that may impart unique modalities to the contrast agent like stability or specific functionality. The implementation of the biocompatible surface coating to the inorganic iron core provides a stable behavior under physiological conditions (i.e. inhibits aggregation). A variety of substances include synthetic and natural polymer (e.g. proteins or dextran) and amphiphilic molecules such as fatty acids or phospholipids which can be used as coating materials. The controlled surface has been increasingly exploited in magnetic resonance imaging (MRI) for contrast enhancement (Khalid et al. 2020). iii) Another interesting research area involves the development of MRI “phantoms” that are composed of known quantities of magnetic contrast agents in aqueous solutions or gels that serve as standard test materials for calibration of instruments (Zubkov et al. 2018). iv) Integration of the concept of nuclear magnetic resonance with other more sensitive techniques like optical microscopy (magnetic resonance microscopy) and atomic force microscopy (magnetic resonance force microscopy), etc. (Grob et al. 2019). This integration allows us to detect MRI signals from nanoscale sample volumes, providing a paradigm-changing potential for structural biology and medical research. Thus far, however, experiments have not reached sufficient spatial resolution for retrieving meaningful structural information from samples.

6.2 Molecular Imaging

This chapter focuses on the utilization of MRI as a technique for ultrasensitive molecular imaging through the development of a combinatorial chip that can be used as a substrate for in vitro imaging of fluidic biological samples such as blood, or suspensions of cells and cell lysates. Conventional techniques for cellular imaging through MRI involve a sample preparation regimen where cell samples are mixed with different concentrations of a known contrast agent and placed inside agarose pockets before imaging. A gradient thin film capable of producing a significant contrast difference along the gradient will eliminate the need for such sample preparation steps and allow for a simple and quick surface-based imaging method (Khizar et al. 2020). Thinfilm gradients using the layer-by-layer technique which can be a promising technique in the future for disposable lab-on-chip as a dipstick approach for ultrasensitive molecular imaging of bioanalytes. The proposed materials chip is composed of a gradient thin film of colloidal core-shell magnetic nanoparticles that serve as exogenous contrast agents to generate a negative contrast in aqueous environments in an MRI (Khizar et al. 2020). The unique core-shell morphology of these colloids coupled with adequately tailored magnetic properties can significantly increase the signalto-noise ratio and consequently, the sensitivity of the MR images. The thin films when used as substrates can serve as a means to effectively image cells without changing the instrument in any way. The gradient thin films have been fabricated by a very simple self-assembly process that is easily reproducible and allows them to be used as a disposable, lab-on-chip device for a dipstick-like approach toward molecular diagnostics. Elimination of sample preparation steps and a quick, quantifiable response may even point toward the application of such films for point-of-care diagnostics.

6.2

Molecular Imaging

Molecular imaging refers to a variety of imaging techniques based on the imaging of specific target molecules. A molecular imaging technique might be capable of directly imaging a target molecule that is indigenously present in a sample or it may rely on the introduction of specifically designed molecular probes or tracers that bind to a target molecule and then indirectly image the molecule bound to the tracer or probe. Some examples of molecular imaging techniques include but are not limited to MRI, X-ray CT, and PET. X-ray CT uses X-rays and PET relies on the use of radioactive tracers to produce high-resolution two- and three-dimensional images. MRI, on the other hand, capitalizes on the nuclear magnetic resonance phenomenon of hydrogen nuclei present in the water molecules in a sample without the use of ionizing radiation or radioactive tracers which makes it a relatively safe, noninvasive imaging technique for clinical diagnostics (Gordon et al. 2019). Magnetic resonance imaging is an emerging technology that enables the noninvasive visualization, characterization, and quantification of molecular events within a living subject.

6.2.1 Magnetic Resonance Imaging Magnetic resonance imaging or MRI typically relies on the magnetic properties of hydrogen nuclei that are present in water molecules of the sample as reported before. Although some specialty applications of MRI target other atomic nuclei such as phosphorus, sodium, and carbon, hydrogen being the most abundant atom in the human body is usually targeted for imaging. The human body can be considered as an arrangement of cells and tissues with different water contents that make up different types of organs and organ systems. The MR image is therefore a product of differential distribution of these water molecules in a three-dimensional space (Atabo and Umar 2019).

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Figure 6.1 Effect of external magnetic field on hydrogen nuclei associated with water molecules. In the figure (a) Hydrogen nuclei are randomly aligned in the absence of a field. (b) In the presence of an external field B0, the moments of the nuclei align parallel or antiparallel to the external field. (c) The hydrogen nuclei develop a net magnetic moment (M) parallel to the field (d) Precessional motion of the aligned nuclei.

The hydrogen nucleus is a spinning charged species with an associated magnetic field termed as a magnetic moment (Mastrogiacomo et al. 2019). AS shown in Figure 6.1a, the spins of hydrogen nuclei in the human body are randomly oriented in the absence of an external magnetic field resulting in a zero net magnetic moment. When an external field is applied, the spins of hydrogen nuclei tend to align in a direction parallel or anti-parallel to the applied field to achieve a low energy state (Figure 6.1b). Two main properties of these nuclei should be taken into account to understand their behavior in MR imaging. i) At any given time, more nuclei tend to align parallel to the field than against it. As a result, the net magnetic vector is parallel to the applied field. This magnetization is termed as longitudinal magnetization (Mastrogiacomo et al. 2019) (Figure 6.1c). ii) The aligned nuclei exhibit a phenomenon called precession (Mastrogiacomo et al. 2019), where the axes of the spins revolve around the axis of the external magnetic field, B0, with a certain frequency, ωL, termed the Larmor frequency (ωL=γB0, where γ is the gyromagnetic ratio, a constant specific to the atomic nucleus) (Figure 6.1d). This can be explained by a vector diagram of the precessing hydrogen nucleus where at any given instant the net magnetic moment of the nucleus is along the direction of the external magnetic field B0 (Figure 6.2).

6.2.2

Basic Components of an MRI Machine

The basic components of an MRI machine are shown in Figure 6.3 and include the primary magnet, secondary gradient coil magnets, radiofrequency induction coils, and radiofrequency detectors connected to a computer system (Yan et al. 2010). The first component is the superconducting primary magnet that creates a strong, static, permanent magnetic field. The primary field strength of a typical clinical MRI machine is from 0.5 to 3 Tesla. The second component is a set of three secondary gradient magnets that are capable of producing gradient magnetic fields in the x, y, and z axes that allow selection of sections or “slices” chosen along these planes. The images obtained from specific slices along different axes are therefore termed as axial (z-axis), coronal (y-axis), and sagittal (x-axis) images. The secondary coils can also be programmed to incite signals or responses from cubic volumes or voxels that can be processed to create 3D images. The third component is a set of radiofrequency (RF) induction coils

6.2 Molecular Imaging

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Figure 6.2 Vector diagram of the precessing hydrogen nucleus. At any given instant, the Mz component of the magnetic moment M is along with B0, so that the net magnetization of the nucleus is along B0. Mxy is the component of M rotating in the xy plane.

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Figure 6.3 Components of a typical clinical MRI machine. The MRI machine consists of a system of primary and gradient magnets, RF coils, and detectors that translate the phenomenon of nuclear magnetic resonance of hydrogen nuclei in a sample and computer-generated image.

and detectors that bombard the chosen slice with short-lived electromagnetic radiation or RF pulses. The RF pulses incite a response or signal from the sample, which is also in the radiofrequency range and is detected by RF detectors placed close to the sample. To obtain an MR image in a chosen area of interest in the sample, the RF coils produce a radiofrequency pulse at 90 to B0. The magnitude of this RF pulse equals the Larmor precession or resonance frequency of hydrogen atoms and only lasts a few moments. Because of the RF pulse, energy is added to the system which temporarily changes the direction of nuclear spins in one of the following ways (see Figure 6.4): i) The spins of some hydrogen nuclei flip to a high-energy state and align antiparallel to B0. This results in a decrease in the longitudinal magnetization.

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ii) When an RF pulse is applied, the nuclei start to precess in phase with each other, which results in resonance causing a net magnetization, B1, orientated at 90 to B0, and rotating about the B0 field. This is termed as transverse magnetization (Mastrogiacomo et al. 2019). As soon as the RF pulse stops, the nuclei tend to return to their lower-energy states by readjusting their spins and releasing the absorbed energy. This is termed as relaxation (see Figure 6.5) and the released energy is detected by the RF detector coils in the machine. Two main types of signals can be observed. i) The nuclear spins revert to their original low-energy positions relative to B0 and release the absorbed RF energy into the surrounding lattice. This is termed as the spin-lattice relaxation (or longitudinal relaxation) and results in the recovery of the longitudinal magnetization (Mastrogiacomo et al. 2019). This signal is measured along the z-axis or B0 and is termed as a T1 signal. The T1 signal increases with time and the time taken by 63% hydrogen nuclei to realign with the field is termed as T1 relaxation (Mastrogiacomo et al. 2019). The image acquired by the processing of the T1 signal is termed as a T1-weighted image. ii) The precessing nuclei also tend to realign with B0, and the interaction of spins in an out-of-phase manner results in loss of transverse magnetization and release of absorbed RF energy. This is termed as transverse relaxation or spin-spin relaxation and the signal is termed T2 signal. The T2 signal is detected at 90 to B0 and is indicative of the reversal of transverse magnetization.

6.2 Molecular Imaging

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Figure 6.5 Longitudinal and transverse relaxation.

The intensity of the T2 signal decreases with time and the time taken by a T2 signal to completely decay is termed as T2 relaxation. The image acquired by the processing of the T2 signal is termed as a T2-weighted image (Mastrogiacomo et al. 2019). In order to generate tissue contrast, the duration of RF pulse along with the repetition times (or TR, i.e. the time between two RF pulses) and echo times (or TE, i.e. the time between RF pulse and detection of peak signal) controls image quality. For T1-weighted images, short TR and TE are required. A short TR value means that the RF excitation pulse is repeated rapidly. As a result, rapid changes in longitudinal magnetization are observed which leads to a greater intensity of the T1 signal. Moreover, the contrast is due to the difference in T1 recovery times of hydrogen nuclei associated with different molecules like fats and water. Usually, hydrogen nuclei in water molecules have longer T1 relaxation than fats so they appear dark in T1-weighted images (Yoshikawa et al. 2016). For T2-weighted images, long TR and TE are required, and the observed contrast is due to the difference in T2 decay times of hydrogen nuclei associated with different molecules. The local field inhomogeneity created due to the interaction of spins of neighboring protons also results in T2 relaxation. Since hydrogen nuclei in water molecules have long T2 relaxation times so water-based fluids appear brighter in T2-weighted images (Chavhan et al. 2009). The RF detector coils collect the T1 or T2 signals and relay it to a computer system that stores this information and then converts them in a pixel-by-pixel image (or a voxel by voxel image in case of 3D images). Both T1 and T2 images are equally useful and provide information of a slightly different nature. T1 images usually highlight the distribution of fat content that appears bright and T2 images highlight the distribution of water molecules and fluids (Yan et al. 2010). A standard clinical MRI has a resolution in the mm to sub mm range. This resolution provides sufficient detail to observe tissue and organ morphology and point out any anomaly in comparison with normal tissues but small changes in physiology like minor inflammation can be disregarded as an artifact due to a low signal-to-noise ratio. Contrast agents are molecules that enhance the sensitivity of an image and further improve image resolution (Chavhan et al. 2009).

6.2.3 Development of Contrast Agents for MRI As described in the previous section, several approaches have been reported in the literature to significantly enhance the sensitivity of MRI. Of these approaches, the development and use of

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exogenous contrast agents provide a means to improve resolution without changing the instrumentation in any way. As a general rule of thumb, the sensitivity of a molecular imaging probe depends on the distribution of the probe in the intra- and extracellular space, the type and intensity of the probe signal (T1 or T2), and the choice of imaging sequence (TR and TE values). To date, a number of contrast agents have been investigated for their ability to generate contrast in live subjects in a nontoxicological manner. These contrast agents can be categorized by their mechanism of action, by their chemical nature, and by their magnetic properties. For in vivo imaging, factors like the concentration of the contrast agent, its toxicity, and retention time in the target tissue along with the speed and mechanism of clearance also play an important role (Hu 2020). Paramagnetic materials, by their nature, become magnetized in the presence of an external magnetic field and lose their magnetization when the external field is removed. In case of use of these materials as MRI contrast agents, they provide local sites to the hydrogen nuclei where they increase the rate of their magnetic relaxation (thereby reducing T1 or T2 relaxation times) by interfering with their magnetic moments. On the other hand, superparamagnetic materials show a higher magnetic susceptibility as compared to paramagnetic materials, which in turn results in a far greater contrast generation. Superparamagnetism is a consequence of size where materials with dimensions in a nano range (1–100 nm) show enhanced magnetic properties. Paramagnetic materials were one of the earliest materials to be used as contrast agents for MRI. The use of manganese ion and its complexes, stable nitroxide free radicals, and molecular oxygen for contrast enhancement has also been investigated. They also carried out detailed toxicity studies and clearance patterns of these materials (Pan et al. 2011). The most common classification of contrast agents is the division into T1 and T2 contrast agents. T1 contrast agents are usually paramagnetic molecules that increase T1 recovery of hydrogen nuclei in water. The T1 contrast agents have specific sites that attract and bind water molecules, allow their protons to undergo T1 relaxation, and release them at a very fast rate. T1 contrast agents appear bright in MR images. T2 contrast agents are usually superparamagnetic particulate aggregates that enhance T2 contrast by decreasing T2 relaxation time by providing a strong magnetic field to the water protons that increases the spin-spin relaxation rates. T2 contrast agents appear dark in MR images (Chavhan et al. 2009). Current trends in research on contrast agents are based on three major groups of contrast agents. The first group includes chelates of paramagnetic gadolinium, termed as the gadolinium-based contrast agents (GBCA) which are usually T1 contrast agents. The GBCA increases both the T1 recovery and T2 decay by influencing the magnetic moments of water hydrogens through the seven unpaired electrons in the Gd+3 ion. The two signals may interfere with each other so a strong T1 signal is achieved through small TR and TE values (Splendiani et al. 2019). The second group of contrast agents is based on superparamagnetic iron oxide nanoparticles (Fe3O4/γ-Fe2O3). The superparamagnetic behavior results in a greater sensitivity at low concentrations. As with most nanoscale structures, surface modification becomes a necessity in designing iron oxide-based contrast agents to prevent agglomeration. This is usually achieved by the introduction of a polymeric coating. The polymeric coatings also allow for the addition of novel functionalities to the contrast agents (Yin et al. 2019). The third group of contrast agents is based on the hydrogen nuclei associated with water molecules that are chemically exchangeable with the hydrogen atoms in the contrast agents using saturation transfer mechanisms. These agents are termed as chemical-exchange-dependent saturation transfer (CEST) agents and usually cause a decrease in the local water-based signal which becomes visible in an MRI (Zhou et al. 2017).

6.3 Development of MRI as a Tool for Ultrasensitive Molecular Imaging

6.3 Development of MRI as a Tool for Ultrasensitive Molecular Imaging MRI is successfully being used for in vivo imaging of specific cells and molecular targets, however, live imaging can result in artifacts due to interference with the respiratory and cardiac rhythms of the live subject during imaging. This can limit the use of the technique for imaging of molecular targets present in small areas and low concentrations despite the ability of the technique to produce high-resolution images (Hu 2020). A logical alternative to overcome this limitation is in vitro imaging of excised tissue biopsies or cell suspensions using specific ultrasensitive molecular probes that can lead to the development of MRI as a tool for in vitro diagnostics. The use of MRI as a molecular imaging modality with superparamagnetic iron oxide-based contrast agents for point-of-care diagnostic applications in an in vitro setting is investigated hereafter. The conventional techniques previously demonstrated for their molecular imaging capabilities involve PET, optical imaging, ultrasound, and MRI. Each technique has its advantages and disadvantages in terms of resolution, depth, cost, and sensitivity. MRI can be used as a relatively low-cost molecular imaging technique because it offers a high spatial resolution of target molecules present in deep tissues. The only limiting factors are the sensitivity of the technique and a rather long image acquisition time, which can be overcome through the use of ultrasensitive molecular probes and a dynamic sensing platform that allow for quick surface-based imaging (Brodoehl et al. 2020).

6.3.1 Development of Iron Oxide-Based Contrast Agents for Ultrasensitive Imaging In comparison with the GBCA, iron oxide-based contrast agents produce images with significantly high signal-to-noise ratio and higher sensitivity (Splendiani et al. 2019). Magnetically engineered iron oxide nanoparticles can be synthesized using a number of high temperature, organic synthesis routes, and low temperature, water-based synthesis methods. Advantages such as tunable magnetism with added features such as biocompatibility and specificity allow the use of these materials as contrast agents for ultrasensitive molecular imaging in in vivo systems as systems (Wu et al. 2019). Iron oxide nanoparticles are usually designed with a core-shell structure where the size of the magnetic core has a direct influence on imaging capability and magnetic behavior of these particles and also influences the ability of the particles to be taken up by different types of tissues and cells and their retention time in the blood (Fernández et al. 2020). In terms of size, the iron oxide-based contrast agents can be divided into three main groups; micrometer-sized paramagnetic iron oxide (MPIO) particles (with a diameter of up to several micrometers), superparamagnetic iron oxide (SPIO) particles (with a diameter of 50–500 nm), and ultrasmall superparamagnetic iron oxide (USPIO) particles (with a diameter less than 50 nm) (Song et al. 2019; Yin et al. 2019). To use one of these particles for in vitro cellular visualization applications, the particles should have the ability to be readily taken up by the cells and insufficient concentrations to generate adequate contrast. All three types of iron oxide-based contrast agents have been tested for cellular imaging, and it has been demonstrated that while USPIO shows a greater signal enhancement, SPIO and MPIO are better suited for in vitro imaging. As compared to USPIO, lesser concentrations of SPIO and MPIO are readily taken up by the cells to generate sufficient contrast, whereas USPIO is required in a greater concentration and also show a limited uptake. Ultrasmall iron oxide nanoparticles (USIONPs) have been recently developed as labeling probes for T2 MRI contrast agents with enhanced cell proliferation and cellular uptake (Park et al. 2020).

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Many different core-shell iron oxide nanoparticles have been synthesized where polymeric and nonpolymeric, organic and inorganic molecules have been used for surface modification both during and after synthesis for the introduction of desirable properties such as biocompatibility, the introduction of targeting ligands, and prevention of agglomeration (Natarajan et al. 2019). Several studies have been carried out to evaluate contrast enhancement of core-shell iron oxide nanoparticles and the effect of different types of polymer coatings on contrast generation has been studied (Wu et al. 2020). Theranostic nanoplatforms with iron oxide NPs are normally utilized as T2 (negative) MRI contrast agents (Gauger et al. 2020). In all cases, the magnetic behavior and T2 relaxation rates are governed by the size and composition of magnetic core, whereas different types of polymeric shells impart specific surface characteristics to the polymer magnetic particles, such as hydrophilic or hydrophobic behavior, tissue specificity, and colloidal stability. In addition to the use of MR imaging for detection of morphological abnormalities in cells, diagnostic magnetic resonance (or DMR) is an up and coming field where highly sensitive detection assays are being developed using SPIO contrast agents that allow detection of specific target molecules through the concept of magnetic resonance switching. These assays are based on the pretext that the presence of certain molecules in an analyte can result in a change in the T2 signal intensity by influencing the aggregation and subsequent T2 relaxation times of SPIO contrast agents that can be correlated to the quantities of these molecules. A number of different detection assays have been developed that allow nanoscale materials combined with various engineered biological molecules (e.g. proteins, enzymes, oligonucleotides, polysaccharides, lipids, biological cofactors and ligands to detect biomolecules such as oligonucleotides, proteins, enzymes, carbohydrates, tumor cells, and even viruses and bacteria (Nagamune 2017).

6.3.2

Development of an Imaging Platform for MRI

General protocols for MR imaging of cells are designed after the concept of MRI phantoms. These methods are easy to perform in a lab, but the sample preparation steps may become cumbersome when MRI is being used for point-of-care DMR applications. Most in vitro DMR assays require free interaction of contrast agents with a target molecule, and the difference in signal intensity is based on a change in dispersity or agglomeration of the contrast agent. DMR technology encompasses numerous assay configurations and sensing principles, and to date, magnetic nanoparticle biosensors have been designed to detect a wide range of targets including DNA/mRNA, proteins, enzymes, drugs, pathogens, and tumor cells with exquisite sensitivity (Haun et al. 2011). The development of disposable, cheap, and dynamic platforms for MRI that actively generates contrast for fast ultrasensitive molecular imaging is relatively a novel area of research. Immobilization of specific quantities of contrast agents tailored for a specific target molecule onto a substrate can allow for a quick surface-based imaging method, where the change in signal intensity is due to adherence of the immobilized contrast agent with the target that limits its interaction with water molecules in solution.

6.3.3

Electrostatic Layer-by-Layer Self Assembly for Magnetic Thin Films

Electrostatic layer-by-layer (LbL) self-assembly is a simple, economic method to create thin films of desired components based on electrostatic attraction between two or more oppositely charged components. For thin-film fabrication, the LbL self-assembly technique has certain advantages in comparison with other contemporary deposition techniques such as vacuum deposition, solvent casting, spin coating, and Langmuir–Blodgett (LB) deposition. The requirement of expensive instrumentation, lengthy time-consuming processes along with requirements of specific substrates,

6.3 Development of MRI as a Tool for Ultrasensitive Molecular Imaging

Substrate

and the formation of thick nonuniform films are some of the disadvantages that hinder these techniques. Layer-by-layer self-assembly on the other hand provides a robust, environmentally friendly alternative that requires no expensive instrumentation and can be used for the deposition of uniform multilayers on a diverse range of substrates (Keeney et al. 2015). Since the starting material in LbL self-assembly is a charged substrate, the choice of substrate and surface charge of the substrate also considerably affects the growth of thin films. A diverse range of substrates can be used for LbL self-assembly including silicon wafers, mica, and glass. Moreover, thin films deposited on such substrates via other techniques can also be used as substrates for LbL self-assembly. It is based on the concept, where two oppositely charged species can be sequentially adsorbed onto a charged substrate leading to the formation of a bilayer composite. The process can be repeated to obtain multiple bilayer composites of up to hundreds of bilayers (Keeney et al. 2015). Moreover, more charged components could be added to create films of complex multilayered architectures with compound properties. Furthermore, a wide variety of self-assembled thin films can be fabricated ranging from polyelectrolytes and colloids to proteins and DNA, solely based on surface charge (Keeney et al. 2015) (Figure 6.6). Besides the predominant electrostatic attraction between oppositely charged species, many other molecular interactions at the bilayer interface also influence the growth of layer-by-layer selfassembled multilayers (LbL-SAMu) thin films such as hydrogen bonding, hydrophobic interactions, and van der Waals interactions (Rawtani and Agrawal 2014). Moreover, the growth of

Step 1: Polycation coating

Step 3: Polyanion coating

Step 2: Wash

Step 4: Wash

Substrate

Step 1 Polycation solution

Step 2 Water

Step 3 Polyanion solution

Step 4 Water

Figure 6.6 Basic concepts of electrostatic layer-by-layer self-assembly. In the figure, the molecular deposition of electrostatic layer-by-layer self-assembly of two oppositely charged polyelectrolytes onto a negatively charged substrate.

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multilayer thin films can also be explained based on the charge overcompensation phenomenon. Charge overcompensation refers to adsorption of a greater amount of an adsorbing electrolyte onto a previously adsorbed layer of the opposite charge leading to the reversal of surface charge rather than resulting in the neutralization of the previous charge. This charge inversion effect increases the amount of net surface charge on the top layer during the formation of subsequent bilayers and as a result, the quantity of adsorbing electrolytes also increases considerably with an increase in the number of bilayers (Keeney et al. 2015). The fabrication conditions such as salt, pH, and temperature also influence thin-film growth if the components involved are susceptible to particular conditions. Varying fabrication conditions like salt concentration, pH, and temperature can lead to the formation of stimuli–responsive thin films that change their features in response to a change in these conditions. Wide arrays of stimuli– responsive thin films have been fabricated in which salt, pH, or temperature-responsive polyelectrolytes are used in combination with dyes, enzymes, and drugs. Such films find applications in areas such as sensing, diagnostics, and drug delivery (Park et al. 2018; Rawtani and Agrawal 2014) In addition to changing fabrication conditions, the stimuli–responsive films can also be fabricated by the specific properties of the components involved in the film, for example, thin films capable of responding to environmental stimuli such as light (Shaikh et al. 2014) and magnetic field (Paterno et al. 2009) can also be fabricated. The ability to add structurally diverse components with specific properties alongside stimuli–responsive behavior can lead to the utilization of LbL-SAMu thin films for a wide range of applications, such as the introduction of magnetically active components for fabrication of magnetic thin films. Gorin et al. developed LbL-SAMu thin films of polyethyleneimine and iron oxide nanoparticles onto silicon wafer substrates and elucidated their optical and magnetic properties. They observed that properties like refractive index electron magnetic resonance vary with the adsorbed volume fraction of iron oxide nanoparticles, which in turn relate directly with the number of bilayers. The results indicate the controllability of optical and magnetic properties by varying the number of bilayers in the films (Gorin et al. 2009). Paterno et al. developed electrically and magnetically active LbL-SAMu thin films using poly(oethoxyaniline) (POEA), sulfonated polystyrene (PSS), and positively charged maghemite nanoparticles onto glass substrates. The electrical and the magnetic measurements indicated successful incorporation of maghemite nanoparticles into the films which exhibited a dual functionality, i.e. electrical conductivity and magnetic properties and prospective uses of such films in electromagnetic interference shielding and chemical sensing were suggested (Paterno et al. 2009). Among other uses, the magnetic properties of magnetically engineered LbL-SAMu films were specifically utilized in surface-based MR imaging. The utilization of layer-by-layer self-assembly technique for the synthesis of magnetically engineered thin films of contrast agents for surfacebased MR imaging was described by Hassan et al., where thin films of nickel ferrite nanoparticles and chitosan were fabricated onto microscopic glass slides using a manual fabrication protocol. The thin films were fabricated with a different number of bilayers per sample, which resulted in the different number of particles being adsorbed onto the top layer. These samples were tested for their ability to generate a difference in intensity using a thin film of blood as a test liquid, but the T1 and T2-weighted images were not described in detail (Hassan et al. 2013). Similarly, thin films of spherical negatively charged core-shell magnetic latex particles consisting of PDAC were fabricated using the layer-by-layer self-assembly approach by Ahsan et al. (2013) and characterized through SEM and AFM. The films showed adsorption of spherical particles as is without any change in particle morphology. The aqueous solutions of colloids were tested for their contrast-enhancing behavior, which revealed them, T2 contrast agents. The magnetic behavior of the

References

films was, however, not tested (Ahsan et al. 2013). Thin-film gradients of negatively charged magnetic colloidal particles and PDAC were fabricated using the layer-by-layer self-assembly techniques, and their diagnostic capability was evaluated by obtaining T1- and T2-weighted images using water as the test liquid. Film gradients showed a decreasing trend in signal intensity of T2 weighted images with an increase in the number of bilayers. These gradient films can be used as a dipstick approach in routine clinical diagnosis (Khizar et al. 2020).

6.4

Conclusion and Final Remarks

This chapter reports on magnetic resonance imaging (MRI) with a special focus on its development as a technique for ultrasensitive molecular imaging. In the first part, the fundamentals of MRI are introduced and its basic components are presented succinctly. Throughout this part, the general advantages and drawbacks of this technique are discussed compared to that of other imaging techniques. Recent scientific progress in the field of MRI is targeted at improving significantly its sensitivity. Hence, the development of relevant contrast agents may overcome sensitivity issues without changing the instrumentation. One of the promising candidates is iron oxide and its derivatives. The second part is dedicated to the utilization of MRI as a technique for ultrasensitive molecular imaging through the development of combinatorial thin-film gradients that can be used as a substrate for in vitro imaging of fluidic biological samples like blood, or suspensions of cells and cell lysates. Their fabrication is investigated through an electrostatic layer-by-layer self-assembly technique. The proposed materials chip is composed of a gradient thin film of colloidal core-shell magnetic nanoparticles that serve as exogenous contrast agents to generate a negative contrast in aqueous environments in an MRI. The unique core-shell morphology of these colloids coupled with adequately tailored magnetic properties can significantly increase the signal-to-noise ratio and consequently, the sensitivity of the MR images. The development of thin-film gradients will eliminate sample preparation steps and allow the development of a disposable chip for dipstick like approach toward molecular diagnostics.

Acknowledgments MS Thesis Chapters 1 and 2: Title of Thesis: Combinatorial Lab-on-chip Self-assembled Thin Films of Magnetic Polymer Colloids for Ultrasensitive Molecular Imaging. MS student name: Sundas Khalid. Supervisor Dr. Nasir M. Ahmad. MS Thesis, April 2016. School of Chemical and Materials Engineering (SCME), National University of Sciences and Technology (NUST), Islamabad, Pakistan.

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7 Iron oxide Nanoparticles in Anticancer Drug Delivery and Imaging Diagnostics Miroslava Nedyalkova1, Boyan Todorov1, Haruna L. Barazorda-Ccahuanac2, and Sergio Madurga3 Faculty of Chemistry and Pharmacy, Sofia University “St. Kliment Ohridski,”, Sofia, Bulgaria Centro de Investigación en Ingeniería Molecular-CIIM, Universidad Católica de Santa María, Arequipa, Perú 3 Faculty of Chemistry, Barcelona University, Barcelona, Spain 1 2

7.1

Introduction

A considerable progress has been made in the application of nanoparticles to biomedicine, diagnostics, or medical drug targeting. They are used in in vivo applications such as contrast agent for magnetic resonance imaging (MRI), for tumor therapy, or cardiovascular disease. The application based on superparamagnetic iron oxide nanoparticles (SPIONs) has attracted an expanding attention due to their high biological tolerability and large magnetic moments, giving rise to high (usually transverse) molar relaxivities. SPIONs are often synthesized to tune with the surface properties to improve aqueous solubility/stability, to prevent the aggregation, and to modulate biological uptake. This chapter sets the proof-of-concept of broad spectra of applications of SPIONs such as contrast enhancement in MR images and anticancer drug delivery platforms. Appropriate magnetism gives high spatial resolution and sensitivity which is influenced by shape, size, r1 and r2 relaxivity, size distribution, and crystallinity of the particles. Besides this property, the pharmacokinetic one is a major factor for in vivo application that can be controlled by the synthetics methods which demand to be properly selected for the preparation of SPIONs. The first used method for synthesis of Fe3O4 NPs was coprecipitation by this general reaction scheme: Fe2 + + 2Fe3 + + 8OH − − Fe3 O4 + 4H2 O, where variation of used starting materials (different salts such as chloride, nitrate, sulfate, perchlorate; bases such as NaOH, NH4OH, Na2CO3, and Fe2+/Fe3+ ratio) and reaction conditions (as temperature, pH, and ionic strength of solution) influence the static diameter and shape of obtained SPIONs (Petcharoen and Sirivat 2012). Advantages of this process are low cost and high yield, wild size distribution, 9 nm size, minutes, synthesis duration with well shape control, and 200–300r2 (mM−1 s−1).

Magnetic Nanoparticles in Human Health and Medicine: Current Medical Applications and Alternative Therapy of Cancer, First Edition. Costica Caizer and Mahendra Rai. © 2022 John Wiley & Sons Ltd. Published 2022 by John Wiley & Sons Ltd.

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Disadvantages are polysize of the NPs under production and potential oxidation/reduction of iron salts during the precipitation. Principle of thermal decomposition is the conversion of organoiron precursors under the action of high temperature in appropriate organic solvents. Uses of surfactants such as oleic acid, oleylamine, fatty acids, and hexadecylamine to ensure precise size control of the produced NPs, and also the variation of ratios and volumes of organometallic compounds, and the solvents, temperature, and reaction time are important factors for size and shape (Hufschmid et al. 2015). Advantages of this method are the production of monodisperse Fe3O4 NPs, narrow size distribution, 3–160 nm size, high shape control, and H1.

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13 Classical Magnetoliposomes vs. Current Magnetocyclodextrins with Ferrimagnetic Nanoparticles Ms

The characteristic sobservables of the hysteresis cycle are the saturation magnetization Ms, the remanent magnetization Mr, and the coercive field Hc. Hc In the case of nanoparticles, their magnetization and the Field (H) existence or absence of the hysteresis cycle depend a lot on the size of the nanoparticles. Thus, nanoparticles may have a multidomain or single-domain magnetic structure (without Magnetization (M) magnetic domains) (Figure 13.3), with nonuniform stable Figure 13.2 Saturation hysteresis loop magnetization, stable magnetization, or fluctuating magnet(black line) and minor loop (red line), with ization (Table 13.1) (Caizer 2016). indication of the most representative In Figure 13.3 and Table 13.1, the size Dc is the critical parameters: saturation magnetization (Ms), remanent magnetization (Mr) and coercive diameter (in the nanoparticle spherical approximation) at field (Hc). Source: Ortega and Pankhurst which the nanoparticle passes from the state with the struc(2013). Reproduced with permission from ture of magnetic domains (multidomains) to the singleThe Royal Society of Chemistry. domain state, and Dt is the threshold diameter corresponding to the transition to the fluctuating state of magnetization. Below the diameter Dt, there is no hysteresis and the coercive field Hc is zero in this region, the magnetization instantly following the variation of the external magnetic field. The value of the critical diameter (Dc) can be found using the formula (Kittel 1946; Smit and Wijin 1961): Mr

Dc =

18εP μ0 M 2S

13 9

where εP is the energy density of magnetic domain walls, and the diameter of threshold (Dt) with formula (Jacobs and Bean 1963; Caizer 2016): Dt =

6k B T τ ln πK τ0

1 3

13 10

e.m.a.

Ms

Single-domain magnetic structure

0

Multidomain magnetic structure

Dc

Dt D (nm)

Figure 13.3 The single- and multidomains magnetic structures of nanoparticles. Source: Caizer (2016). Reprinted by permission from Springer Nature.

13.2 Basic Physical Aspects That Lead to the Heating of MNPs

Table 13.1 structures.

Magnetization and magnetic behavior of nanoparticles according to their size and magnetic

Nanoparticle size (nm)

Magnetic structure

Magnetization state

Magnetic behavior

D > Dc

Multidomain

Stable nonuniform

Large hysteresis loop (like bulk)

Dt 1 under certain parameter combinations. For anisotropy values below the bulk value, e.g. Keff = 5 kJ m−3, LRT underestimates SLP(H0) compared to MC-simulations (Figure 15.2a), while for anisotropy values above bulk value, e.g. Keff = 17 kJ m−3, the situation is opposite and LRT overestimates SLP(H0) (Figure 15.2e). The trend can generally be summarized as SLP H 0 H 20 for both LRT and MC-simulation and dM = 15 nm. SWMBT can be applied for larger particle sizes, e.g. dM = 25 nm (Figure 15.2b, d, and f ), with a bulk anisotropy value of Keff = 11 kJ m−3 and high field amplitudes H0 ≥ 16 mT/μ0 (Figure 15.2d). For higher-than-bulk value of anisotropy constants, e.g. Keff = 17 kJ m−3, SWMBT largely overestimates SLP(H0) values compared to MC-simulation (Figure 15.2f ). For dM = 25 nm, ξ > 1 holds for all situations simulated and therefore LRT is invalid here for all field amplitudes investigated. However, the trends for LRT and MC-simulation agree for high anisotropy constants, e.g. Keff = 11 kJ m−3 and Keff = 17 kJ m−3 (Figure 15.2d and f ), respectively). In general, magnetite particles with dM > 18 nm are assumed to be ferromagnetic at excitation frequencies of f 100 kHz (Krishnan 2010) and their particle heating is determined primarily by hysteresis losses. These hysteresis losses are well described within the Stoner–Wohlfarth model (Hergt et al. 2006; Hergt and Dutz 2007), which is only valid for T = 0 (s. Section 15.3.2). At (relatively) high applied field amplitudes H 0 ≥ H C ≈ H2K , the particles’ magnetic moment, m, overcomes the intrinsic anisotropy field, HK (cf. Eq. (15.18)), aligns with the applied magnetic field (Carrey et al. 2011; Krishnan 2016; Mamiya and Jeyadevan 2011). Thus, a steep increase in SLP is observed for H 0 ≥ H2K , whereas SLP is zero for H 0 < H2K , where the particles’ magnetic moments are oriented by anisotropy. This effect can be reproduced by MC-simulations performed at T = 0, as shown by the dotted lines in Figure 15.3 for dM = 20 nm and various anisotropy values, Keff. Under thermal activation, e.g. at T = 300 K, thermal energy dominates the anisotropy energy barrier, εtherm = kBT > KeffVM, allowing for thermally driven combined Brownian and Néel particle relaxation, cf. Eqs. (15.3) and (15.4). Such thermally driven particle relaxation smoothes the steep increase in SLP for H 0 = H2K observed for T = 0, allowing a monotonous onset of particle heating already for H 0 < H2K. As MC-simulation is able to account for thermal activation by including thermal fluctuations, this onset of particle heating is also observed for MC-simulations with T = 300 K in Figures 15.2b and d and 15.3. From this, the trend of SLP(H0) predicted by MC-simulation can be assumed in detail as follows: SLP H 0 H 20 for H 0 < H4K, which is in line with the predictions from LRT (cf. Eq. (15.25)). This is followed by a linear dependency SLP(H0)

c1H0, for H4K ≤ H 0 ≤

HK 2 .

For H 0 > H2K a linear dependency is also observed, however, with a lower increase in particle heating. Therefore, the trend can be described by SLP(H0) c2H0, with arbitrary constants c1 and c2 for which c2 < c1 holds. The results for SLP(f) wit dM = 15 nm and dM = 25 nm are compared in Figure 15.4. The frequency behavior of the SLP generally predicts a linear dependency, SLP(f) f, within the frameworks of SWMBT and LRT (Figure 15.4, cf. Sections 15.3.2 and 15.3.3). From MC-simulation, the frequency-dependence can be approximated with SLP(f) f as well, within the modeled frequency interval f = [50, 1000] kHz. However, the onset of the SLP(f)-curve shows slight deviations from linear dependencies for MC-simulation in dependence of the Keff-values: For small fields, e.g. H0 = 6 mT/μ0, one observes a steep increase in SLP with f for small anisotropy values of

339

15 Magnetic Nanoparticle Relaxation in Biomedical Application: Focus on Simulating Nanoparticle Heating

(a)

(b)

1500

1500

11 kJ m–3 T = 0 11 kJ m–3 T = 300 K

SLP [Wg–1(Fe3O4)]

SLP [Wg–1(Fe3O4)]

5 kJ m–3 T = 0 5 kJ m–3 T = 300 K

HK = 25 mT/μ0 HK/ 2 HK/ 4

0

HK = 55 mT/μ0

HK/ 2 HK/ 4

0 0

10

20

30

40

50

60

0

10

20

30

40

50

60

Field amplitude [mT/μ0]

Field amplitude [mT/μ0]

(c) 1500

17 kJ m–3 T = 0 17 kJ m–3 T = 300 K

SLP [Wg–1(Fe3O4)]

340

HK / 2 = 42.5 mT/μ0

HK/ 4

0 0

10

20

30

40

50

60

Field amplitude [mT/μ0]

Figure 15.3 MC-simulation for field amplitude-dependent SLP for various anisotropy constants (a) Keff = 5 kJ m−3, (b) Keff = 11 kJ m−3, and (c) Keff = 17 kJ m−3. The particle magnetic size is fixed at dM = 20 nm. For T = 0 the results are equivalent to Stoner–Wohlfarth model predictions, while for T = 300 K thermal fluctuations enable particle thermally driven relaxations of the particles’ magnetic moment. The values of HK/4 and HK/2 are, where 2K eff (cf. Eq. (15.18)). Source: Engelmann (2019). Reprinted with permission from Infinite Science HK = μ0 M S Publishing.

Keff = 5 kJ m−3 (Figure 15.4a and g). Then, a weaker but nearly linear increase in SLP with f is observed for Keff = 11 kJ m−3 (Figure 15.4c) and a less-than-linear increase in SLP with f for Keff = 17 kJ m−3 (Figure 15.4e). The same trends in SLP(f) are observed at higher fields, e.g. H0 = 20 mT/μ0, when comparing Figure 15.4b with Figure 15.4d and f. This reveals a more complex dependency of SLP on the anisotropy constant, Keff, that is further discussed in the next Section 15.3.2.3. Nevertheless, the frequency-dependent trend in SLP predicted by MC-simulations can be approximated as linear: SLP(f) f.

15.3 Predicting the Magnetic Particle Heating

dM = 15 nm

(b)

500

MC-Simulation LRT SWMBT

SLP [W g–1(Fe3O4)]

400 300 200

(c)

0

200

400

600

800

(d)

500

6 mT/μ0 11 kJ m–3 SLP [W g−1(Fe3O4)]

SLP [W g−1(Fe3O4)]

2k

0

5k

200

400

600

800

1000

400

600

800

1000

400 600 800 Frequency [kHz]

1000

20 mT/μ0 11 kJ m–3

4k

300 200

3k 2k 1k

100

0

0 0

200

400

600

800

1000

0

(f)

500

6 mT/μ0 17 kJ m–3

5k

200

20 mT/μ0 11 kJ m–3

4k SLP [W g–1(Fe3O4)]

400 SLP [W g–1(Fe3O4)]

3k

0

1000

400

(e)

20 mT/μ0 5 kJ m–3

1k

100 0

5k 4k

6 mT/μ0 5 kJ m–3

SLP [W g–1(Fe3O4)]

(a)

300 200

3k 2k 1k

100

0

0 0

200

400

600

Frequency [kHz]

800

1000

0

200

Figure 15.4 Comparison of MC-simulation, LRT, and SWMBT for frequency-dependent SLP prediction for two different particle sizes, dM = 15 nm ((a)…(f )) and dM = 25 nm ((g)…(l)), at various field amplitudes, H0, and anisotropy constants, Keff: (a) and (g) 6 mT/μ0 and 5 kJ m−3, (b) and (h) 20 mT/μ0 and 5 kJ m−3, (c) and (i) 6 mT/μ0 and 11 kJ m−3, (d) and (j) 20 mT/μ0 and 11 kJ m−3, (e) and (k) 6 mT/μ0 and 17 kJ m−3, (f ) and (l) 20 mT/μ0 and 17 kJ m−3. The dotted lines indicate SLP values outside the range of validity for LRT and SWMBT. Source: Engelmann (2019). Reprinted with permission from Infinite Science Publishing.

341

15 Magnetic Nanoparticle Relaxation in Biomedical Application: Focus on Simulating Nanoparticle Heating

dM = 25 nm

(h)

500

MC-Simulation LRT SWMBT

SLP [W g–1(Fe3O4)]

400

200 100 0

0

200

400

600

800

2k 1k

0

200

400

600

800

1000

400

600

800

1000

400 600 800 Frequency [kHz]

1000

(j) 500

5k

6 mT/μ0 11 kJ m–3 SLP [W g–1(Fe3O4)]

300 200 100

3k 2k 1k 0

0 0

200

400

600

800

1000

0

(l)

500

6 mT/μ0 17 kJ m–3

5k

200

20 mT/μ0 17 kJ m–3

4k SLP [W g–1(Fe3O4)]

400 300 200 100 0

20 mT/μ0 11 kJ m–3

4k

400 SLP [W g–1(Fe3O4)]

3k

0

1000

(i)

(k)

20 mT/μ0

4k

6 mT/μ0 5 kJ m–3

300

5k

5 kJ m–3 SLP [W g–1(Fe3O4)]

(g)

SLP [W g–1(Fe3O4)]

342

0

200

400

600

Frequency [kHz]

Figure 15.4

(Continued)

800

1000

3k 2k 1k 0

0

200

15.3 Predicting the Magnetic Particle Heating

15.3.2.3

Anisotropy-Dependent Heating Predictions

The dependence of SLP(Keff) is arguably the most complex in both LRT and SWMBT as well as in MC-simulations. This is due to the nontrivial interplay of the anisotropy energy (constant), Keff, with particle (Néel) relaxation time (cf. Eq. (15.4)) and simultaneously with the anisotropy field (cf. Eq. (15.18)), which are both complexly rooted in the theories of MC-simulation (cf. Eqs. (15.9), (15.11), and (15.12)), LRT (cf. Eqs. (15.20) and (15.21)) and SWMBT (cf. Eqs. (15.23) and (15.25)) alike. The complexity is readily apparent from the previous discussion on particle size- and external field-dependent prediction of SLP values (cf. Sections 15.3.2.1 and 15.3.2.2), where it has been shown that Keff has a major impact on the SLP predictions. However, this impact is different for each theory evaluated:

• • •

For SWMBT, the trends for SLP(Keff) show that an increase in Keff generally increases the SLP value, as seen from Eqs. (15.19) through (15.21), in which the anisotropy energy scales linearly with Keff (s. Eq. (15.18)) as well as Figures 15.1, 15.2 and 15.4. For LRT, the trends for SLP(Keff) show that an increase in Keff generally decreases the SLP value within the regime of validity for LRT, as apparent from (Figures 15.1, 15.2 and 15.4). This is due to the exponential increase in Néel relaxation time (Eq. (15.4)) with increasing the anisotropy energy barrier ΔE = VMKeff, eventually blocking Néel relaxation totally and thereby cancelling Néel contributions to heating. For MC-simulations, the trend in SLP(Keff) is more complex, as it also depends on the particle magnetic size dM and applied field amplitude H0: From predictions of SLP(dM) in Figure 15.1, one sees that the absolute SLP values generally decreases with increasing Keff. However, if only specifically considering particles of a certain size, e.g. dM = 17.5 nm, one observes an increase in SLP when increasing anisotropy from Keff = 5 kJ m−3 to Keff = 11 kJ m−3 and Keff = 17 kJ m−3 (Figure 15.1b, d, and f), respectively. The same ambiguous trends can be observed for SLP(H0) in Figure 15.2: Generally, the absolute SLP values increase for increasing Keff. However, if considering a specific situation for fixed field amplitudes, e.g. H0 = 10 mT/μ0, the SLP(Keff)-values actually show no monotonous trend in Figure 15.3 with SLP(Keff = 11 kJ m−3) > SLP(Keff = 5 kJ m−3) > SLP(Keff = 17 kJ m−3). The reason for this behavior lies in the dependence of SLP(H0) on the anisotropy field: As the SLP value is generally low for H 0 < H4K (Figure 15.3) and HK Keff (cf. Eq. (15.18)), at such low fields, particles with lower anisotropy can generate higher SLP values. Consequently, SLP(Keff) predicted from MC-simulation demonstrates the complex interdependency between particle size, field amplitude, and anisotropy, therefore, actually reading SLP(dM,H0,Keff).

Overall, the anisotropy-(energy density)-dependency of particle heating is a topic of ongoing discussion in current research, as there is conflicting evidence of both increasing as well as decreasing SLP values due to increasing Keff (Ng and Kumar 2017; Blanco-Andujar et al. 2018), while the debate is further complexed by the influence of interparticle dipole–dipole interactions that change the effective anisotropy energy density (Branquinho et al. 2013; Engelmann et al. 2018a). For investigating SLP(Keff) experimentally, it has been suggested to vary the MNP material (Krishnan 2010), the microstructure (Dennis et al. 2015), or particle shape (Niculaes et al. 2017), whose effects are all interdependent on each other. In fact, the complex interplay between MNP intrinsic parameters, such as anisotropy constant, magnetization and size (distribution), interparticle interactioninduced effects, like MNP arrangement, and the AFM-parameters, only allow case-by-case interpretation, considering the characteristics of the specific MNP system under investigation. This complexity was vividly displayed recently by Niculaes et al., who demonstrated an increase in SLP value

343

344

15 Magnetic Nanoparticle Relaxation in Biomedical Application: Focus on Simulating Nanoparticle Heating

by approximately 19% for iron oxide nanocubes clustered in a mixture of dimers and trimers, and contrastingly a decrease by approximately 14% was reported for larger, centrosymmetric clusters (number of nanocubes per cluster n ≥ 4). We believe that further theoretical investigation via MC-simulations may provide further insight to that matter in the future, as the various effects can be probed independent as well as interdependent on each other (Shasha 2019). Such a systematic theoretical analysis could eventually allow to describe the effect of Keff on the SLP value thoroughly, especially when including MNP cluster effects (s. below, Section 15.3.3). 15.3.2.4 Summary of Magnetic Particle Heating Results from MC-Simulation, LRT, and SWMBT

As described in the foregoing section, several dependencies of magnetic particle heating under the influence of an AMF are accessible with simulations. The respective trends of SLP predicted by LRT, SWMBT and MC-simulations are summarized in Table 15.2. Both LRT and SWMBT are limited to specific ranges of particle sizes in combination with AFM parameters, consequently there is a large parameter field where only MC-simulations can be used to estimate the hysteresis area and particle heating. Nevertheless, both LRT and MC-simulations predict an optimal particle size for maximum SLP and furthermore agree in the general trend of field-dependence of SLP (SLP H 20 f). This can be attributed to the fact that both methods apply magnetic relaxation theory. In contrast to that, SWMBT predicts different trends, as it is based on a hysteresis switching on single-domain particles, whose trends generally do not agree with MCsimulation predictions of SLP, except for the frequency-dependence. Please note that no clear trends for the prediction for SLP(Keff) could be derived (cf. Section 15.3.2.3), and, therefore, no results for SLP(Keff) are presented in Table 15.2.

15.3.3 Discussion of Validation and Applicability of Magnetic Particle Heating MC-Simulation Generally, there is no formal limitation to the MC-simulations from a theoretical standpoint (as in contrast to LRT (ξ < 1, cf. Section 15.3.3) or SWMBT (κ < 0 7; H 0 ≥ H C ≈ H2K, cf. Section 15.3.2)), as long as superparamagnetism (and therefore magnetic relaxation theory) can be assumed and a sufficiently large number of particles is simulated to ensure statistical soundness (i.e. P ~ 1000), MCcan be applied. As shown in the foregoing Section 15.3.2, the absolute values of SLP predicted by MC-simulations are generally in the range of SLP 50 − 500

W g Fe3 O4

, which is exactly the order of

magnitude measured in typical MFH experiments (with dM ~ (10 − 30) nm, f ~ (100 − 1000) kHz, H ac (Hergt et al. 2008; Dennis et al. 2015; Röth et al. 2019; Engelmann et al. 5 − 50 kA m 2019a; Dadfar et al. 2020). In comparison, LRT and SWMBT tend to overestimate the SLP value, as already discussed in Section 15.3.2 before and also shown experimentally (Mehdaoui et al. 2011; Verde et al. 2012). MC-simulations as presented here have furthermore been successfully applied to and validated against experimental MPI data (Shasha 2019; Shasha et al. 2019), as well as MFH results for various particle sizes ranging between dM ≈ (10 − 30) nm (Engelmann 2019; Engelmann et al. 2019b). Furthermore, the MC-simulation model has been applied successfully to predict intracellular MNP relaxation dynamics and allowed for a reconstruction of MNP dipole–dipole interaction (Teeman et al. 2019). We therefore consider MC-simulations more accurate and versatile than LRT or SWMBT and can generally be chosen to predict particle heating for any currently available experimental situation, independent of particle properties or AFM parameters, as long as superparamagnetic particle

Table 15.2 Comparison of SLP dependencies from theories (LRT and SWMBT) and MC-simulation as a function of field amplitude, H0, and frequency, f, as well as particle size, dM. A generalized trend for the dependency on the anisotropy constant, SLP(Keff), could not be specified for MC-simulation (s. text).

Model

LRT SWMBT

MCsimulation

Limited to:

MSV M H0 < 1 kB T HK H0 ≥ 2 and kB T kB T κ= = ln KVM 4 μ0 H 0 M S V M f τ 0

SLP(dM)

Peak at

ξ = μ0

No general restriction

− ln

d∗M,LRT 1 dM

SLP(H0)

SLP (f)

H 20

f

for Keff

f

for Keff

− ln

1 H0

SLP(Keff)

2

c1H0 for

f

Complex and interdependable relation SLP (dM,H0,Keff).

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15 Magnetic Nanoparticle Relaxation in Biomedical Application: Focus on Simulating Nanoparticle Heating

relaxation applies. Nevertheless, MC-simulations allow for an even more realistic prediction of particle heating by overcoming the following two limitations: First, even though the MC-simulations presented here used uniaxial anisotropy, it is generally possible to include cubic anisotropy in MCsimulations. Implementing cubic anisotropy in MC-simulations is therefore of great interest for advancing more accurate magnetic particle heating predictions in the future, as uniaxial anisotropy is only an approximation, e.g. spherical magnetite particles (Garcia-Otero et al. 1998). Second, as described in the introduction, in vivo application of MNP is always associated with MNP-cell interactions, inevitably leading to particle agglomeration and clustering. Since in MC-simulations presented here, the particles are implemented as single entities, cluster effects could be added, including a model for the calculation of the magnetic dipole–dipole interaction energy. This enables the predictions of particle heating under more realistic conditions for in vivo application (Teeman et al. 2019).

15.4

Conclusion

MC-simulations provide an accurate and realistic approach for predicting MNP heating. By applying the Landau–Lifshitz–Gilbert (LLG) equation to describe MNP relaxation, and including thermal activation processes, MC-simulations advance the modeling of particle heating processes and thereby surpass the predictions of the commonly applied linear response theory (LRT) and the Stoner–Wohlfarth model based theory (SWMBT): In comparison, MC-simulations allow to calculate particle heating for unrestricted parameter sets (of MNP properties and AMF parameters) with otherwise unrivaled accuracy, while being an adaptable model capable of including currently discussed theoretical framework, such as including magnetic dipole–dipole interactions. By being based on general MNP relaxation processes, MC-simulations show furthermore great potential for modeling MNP-relaxation behavior in an AMF for diverse magnetic biomedical applications, such as MRI, (multimodal) MFH, MPI, or biosensor devices. All these biomagnetic applications of MNP rely on analysis of the dynamic M(H)-magnetization-loop. Hence, MC-simulations provide a powerful tool for validating experimental results or predicting MNP relaxation behavior without the need of running expensive and time-consuming experiments. Furthermore, since the MC-simulations accurately predict the relaxation process with respect to individual particle properties such as hydrodynamic and core size, magnetization, and effective anisotropy constant, their results could even be used for the application-specific design of MNP. Nevertheless, several physiological conditions such as (partial) MNP immobilization or agglomeration still need to be accounted for in the MC-simulation to correctly predict in vivo conditions.

Appendix 15.A.1

Applying the Stratonovic–Heun Scheme

We consider thermal fluctuations as Gaussian distributed white noise described by a stochastic differential equation (SDE) with the differentiable function f(X (t), t) and the nondifferentiable function g(X (t), t) of the form dX t = f X t , t dt + g X t , t dW t ,

15 A 1

Appendix

where the independent Gaussian stochastic process is described by a discretized Wiener process, W, with properties: W t=0 =0 W t

= 0 W t W t + Δt

2

= Δt

15 A 2

For thermal fluctuations expressed as a discretized Wiener process with time step Δt, the autocorrelation function W t W t + Δt eΔt tcorr must yield an autocorrelation time, tcorr, which is much shorter than the effective relaxation of magnetic particles, i.e. tcorr τR (Reeves 2015). In this limit of zero correlation time of the Wiener process, the SDE Eq. (15.A.1) can be solved with the Stratonovich–Heun scheme (Scholz et al. 2001): From the variance given in Eq. (15.A.2), the standard deviation of such a Wiener process, ΔW, scales as the square root of the chosen time step, Δt, according to ΔW = N 0, σ

Δt

15 A 3

where N(0, σ) represents the Gaussian distribution N x, μ, σ =

1 2πσ 2

exp

x−μ 2σ 2

2

15 A 4

Given the value xi at time tn of the discretization, the predictor x i at time tn + Δt, and the next value xi(tn + Δt) are given in the Stratonovich–Heun scheme by (Nowak 2001): x i t n + Δt = x i t n + f i x t n , t n Δt + gi x t n , t n ΔW t n

15 A 5

and x i t n + Δt = x i t n + +

f i x t n , t n + f i x t n + Δt , t n + Δt Δt 2 gi x t n , t n + gi x t n + Δt , t n + Δt ΔW t n 2

15 A 6

Inserting Gaussian distributed, white noise thermal fluctuations Eqs. (15.7) and (15.8) in the relaxation equations for the magnetic moment, m, and the direction of the easy axis, n Eqs. (15.5) and (15.6), respectively, allows rearrangement in a SDE equivalent to Eq. (15.A.1) with a differentiable component fm, n and nondifferentiable component gm, n and solving these SDEs by applying Eqs. (15.A.5) and (15.A.6): m t + Δt = m t + f m m, n, t Δt + gm m, n, t ΔW m

15 A 7

n t + Δt = n t + f n m, n, t Δt + gn m, n, t ΔW n

15 A 8

from which the next step in relaxation of m and n under thermal fluctuations after the time step Δt evolves as m t + Δt = m t +

n t + Δt = n t +

f m m, n, t + f m m, n, t + Δt g m, n, t + gm m, n, t + Δt Δt + m ΔW m , 2 2 15 A 9 f n m, n, t + f n m, n, t + Δt g m, n, t + gn m, n, t + Δt Δt + n ΔW n 2 2 15 A 10

347

348

15 Magnetic Nanoparticle Relaxation in Biomedical Application: Focus on Simulating Nanoparticle Heating

Here, the discretized Wiener processes are described by their magnitudes calculated by combining Eqs. (15.15) and (15.16) (with t = t + Δt) and Eqs. (15.A.2)–(15.A.4): ΔW m =

2k B T 1 + α2 Δt N 0, σ = 1 γ0 m α

15 A 11

ΔW n =

12k B T ηV H Δt N 0, σ = 1

15 A 12

where the magnitude of the magnetic moment is set to |m| = μ0 MS VM and the length of one time step in the numerical Monte Carlo simulation is chosen as Δt = f 1N t The initial conditions m(t = 0) and n(t = 0) are realized by individually placing the direction of the magnetization and easy axes of each particle in randomized directions when initializing the simulations. From this, the evolution of an entire M(H)-loop under the influence of an applied field and thermal fluctuations can be calculated with Eqs. (15.A.7) through (15.A.12) using recursive iteration. A fully detailed description of the mathematical background can be found in (Engelmann 2019; Shasha 2019).

15.A.2

Step-by-Step Implementation of MC-Simulations

An in-depth explanation of the implementation of MC-simulations is given in the following flow diagram: 1) The steps shown in Figure 15.A.1 comprise: The input parameters, describing the MNP and the AMF as well as the other input parameters, must be specified. They can generally be classified as simulation input, particle properties, and external parameters. The simulation input includes the number of particles simulated, P, the number of time steps simulated for a full oscillation of the field, Nt, the number of full magnetization cycles simulated, ncyc, and the number of repetitions of simulations, X. Their values were used as specified in Eq. (15.28). The class of particle properties includes all parameters characterizing the MNP, such as the (core) magnetic diameter, dM, with its log-normal distribution width, σ dM , and the absolute thickness added to the particle diameter due to MNP coating, dcoat (together with the dM this constitutes the particle hydrodynamic size, dH = dM + dcoat). It also includes, the (mean) effective uniaxial anisotropy constant, Keff, which is assumed to be dependent on the particle magnetic size due to surface anisotropy effects according to K eff = K B + d6M K S (Bodker et al.

1994). With bulk anisotropy KB = 11 kJ m−3 and surface anisotropy KS~10 μJ m−2 for magnetite (Bickford et al. 1957). Therefore, the anisotropy is simulated as log-normal distributed with distribution width, σ K eff . Furthermore, the MNP saturation magnetization MS and the phenomenological damping parameter α is included. Finally, the external parameters including the applied field with amplitude, H0 and frequency, f, as well as the ensemble MNP concentration, C, the temperature, T, and the macroscopic viscosity of the carrier medium, η are included in the input. 2) From dM and σ dM a one-dimensional array with P entries of log-normally distributed individual particle sizes, di, is generated.

Input parameters

#1

P, Nt, X, ncyc dM, dcoat, σd , Ku, σK, MS, α′ M

H0, f, T, η, C

#2

#4 Generate log-normal distributed sizes di with P entries:

Generate log-normal distr. anisotropy constants Ki with P entries: With μ = Keff and σ = σKeff (uniaxial anisotropy)

(In(di)–μ)2 (– .e 2σ2

1 σdi√2π with μ = dM and σ = σdM

p(d) =

#3 Generate magnetic and hydrodynamic volumes: VM,i = VH,i =

πdi3 6

π(di + dcoat)3 6

Randomly distribute P particles with VM,i, VH,i, Keff,i in box of length L = 3 p and average interticle

#5

c

distance ravg =

2

3

1 3

C

Assign randomly distributed directions of magnetization m ˆ i and easy axes nˆ i for each particle.

#10

#6

Eqs. (1.32), (1.33), (1.39) & (1.40)

#8 Thermalize system for Nt/5 time steps Δt= Repeat X times

Heff,i = Hk,i + Hth (+ Hpp–IA,i).

1 Nt·f

Nt / 5

Eqs. (1.29), (1.32), (1.33), (1.39) & (1.40)

#9 Evolve system for Nt time steps under applied field Heff,i = Hk,i + Hac (Δt) + Hth (+ Hpp–IA,i).

Nt

Average over z-direction projection of all magnetic

#11

Extract Mz (ΔH) = M(H).

#12

moments Mz = 1 ΣXj =1( 1 ΣPi =1mi) ˆfor each time P X step (i.e. different value of applied field ΔH (Δt)).

Figure 15.A.1 Flow diagram of Monte Carlo simulation implementation. The input parameters are marked with different colors as simulation input, particle properties, and external parameters. The steps, explained in detail in the text, are marked at the appropriate position in the flow diagram with #x, x = (1,…,12). Note that step #7 is not shown. Source: Engelmann (2019). Reprinted with permission from Infinite Science Publishing.

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15 Magnetic Nanoparticle Relaxation in Biomedical Application: Focus on Simulating Nanoparticle Heating

3) From this di another array with P entries of magnetic volumes, V M,i = π

d3i 6 , and a third array of

3

the hydrodynamic volumes, V H,i = π di + 6dcoat , is generated. 4) In the same way, a P-entry array of individual effective anisotropy values Ki is generated from the inputs for Keff and σ K eff . 5) A cubic box of length L =

3

P C is

generated, in which the individual particles are randomly dis-

tributed with VM, i, VH, i, Ki and the average interparticle distance, r avg =

3

3 . C

6) These as-described distributed particles are set with randomly oriented axes of magnetization, mi, and directions of the easy axis, ni. This step completes the static arrangement of the MNP ensemble from which the relaxation dynamics are evolved in time in the next step. 7) The number of full magnetization cycles (M(H)-loops) simulated, ncyc, is multiplied by the number of time steps, Nt, so that the new N t accounts for all time steps over ncyc cycles: N t = N t ncyc . 8) In order to account for any possible relaxation trends due to thermal activation, the system is first left to thermalize for N5t time steps with zero applied field, Hac = 0. For each time step, the magnetization and torque are calculated under thermal fluctuations from Eqs. (15.5), (15.6), (15.11), and (15.12). The magnitude of the thermal fluctuations, Hth,i and Θth,i, at each step is given by Eqs. (15.15) and (15.16) and the effective field reads: H eff,i = H K i K i + H th,i + H pp − IA,i , with the individual particle’s anisotropy field, H K i K i = 2 Ki μ0 M S ,

9)

10) 11)

12)

and, when used, the magnetic dipole–dipole interaction field, Hpp − IA,i (derived from

inserting Eq. (15.10) in Eq. (15.9)). After thermalizing, the external field, Hac Eq. (15.1), is applied and the system is evolved for Nt time steps as described in step 7 above. In other words, a full cycle of the M(H)-loop is simulated, and the effective field reads: H eff,i = H ac + H K i K i + H th,i + H pp − IA,i . Steps 5 through 9 are repeated X times to increase statistical precision. The ensemble average magnetization over X repeated MC-simulation runs with P particles each is calculated for every discretized field step, ΔH(Δt), along the direction of applied field (in z-direction), ΔMz(ΔH), according to Eq. (15.28). From ΔMz(ΔH), the M(H)-loop is extracted.

Acknowledgments Ulrich Engelmann acknowledges funding by the German Federal Fellowship Cusanuswerk e.V. and the German Ministry of Culture and Science of North Rhine-Westphalia. C.S. acknowledges funding by the US National Science Foundation Graduate Research Fellowship. This work was facilitated through the use of advanced computational, storage, and networking infrastructure provided by the Hyak supercomputer system and funded by the STF at the University of Washington. This chapter is partly reprinted from (Engelmann 2019) with kind permission of Infinite Science Publishing, Lübeck, Germany, 2019.

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355

16 Magnetic Nanoparticles in Alternative Tumors Therapy: Biocompatibility, Toxicity, and Safety Compared with Classical Methods Costica Caizer1 and Mahendra Rai2 1

Physics Faculty, Department of Physics, West University of Timisoara, Timisoara, Romania UGC - Basic Science Research Faculty, Department of Biotechnology, SGB Amravati University, Amravati, Maharashtra, India 2

16.1

Introduction

Magnentic nanoparticles are increasingly used today in biomedical applications, the most important being magnetic resonance imaging (MRI) (as contrast agents), targeted drug delivery (for magnetic targeted delivery of tumors), and magnetic/superpamagnetic hyperthermia (in thermal cancer therapy) due to their specific magnetic properties and low dimensionality. The use of modern nanobiotechnology together with the characteristics of magnetic nanoparticles allows to increases their effectiveness in applications with reduced tissue toxicity, which makes magnetic nanoparticles very versatile in the most diverse medical applications (Pankhurst et al. 2003; Lin et al. 2008; Solanki et al. 2008; Barakat 2009; Ito and Kamihira 2011; Markides et al. 2012). The toxicity and safety of the use of magnetic nanoparticles result from the type of nanoparticles, the dose used in therapy, and their biocompatibility with the biological tissue, where they are used. Safety is given below a minimum permissible toxicity to the living organism. A key parameter in applications is the size of the nanoparticles. The major benefit of magnetic nanoparticles is that due to their small size (nm – tens of nm) and their unique magnetic properties they can be nontoxic below a certain size. At the same time, they can be safely handled and directed to the target tissue/cells (Caizer et al. 2017). The magnetic nanoparticles most used in biomedical applications are those based on iron oxides, representative being not only ferrimagnetic spinel ferrites (MeFe). Fe2O4, where Me can be ions of Fe(II)/Fe(III), Ni, Zn, Mg, Mn, Co, etc. (Smit and Wijin 1961), but also some ferromagnetic metallic nanoparticles based on Fe, Co (Caizer, 2017). However, it has been shown so far that Fe-oxide nanoparticles are best suited in biomedical applications (Berry 2005; Ju et al. 2006; Bulte 2009; Kim et al. 2010; Jasmin et al. 2011; Markides et al. 2012), and in particular in magnetic hyperthermia, because iron (Fe) exists naturally in the human body as is the ferritin protein in blood red cells that contains Fe ions. Therefore, nanoparticles based on Fe oxides are biocompatible up to a certain concentration and size of nanoparticles, and also biodegradable, being adapted to the metabolism, and can be used by the body in metabolic processes. Representative ferrimagnetic nanoparticles are magnetite (Fe3O4) and maghemite (γ-Fe2O3).

Magnetic Nanoparticles in Human Health and Medicine: Current Medical Applications and Alternative Therapy of Cancer, First Edition. Costica Caizer and Mahendra Rai. © 2022 John Wiley & Sons Ltd. Published 2022 by John Wiley & Sons Ltd.

356

16 Magnetic Nanoparticles in Alternative Tumors Therapy

However, at high concentrations and/or for large nanoparticles of iron oxides a certain toxicity will exist depending on the case; therefore, it is necessary to test them in vitro and in vivo in this respect before being used in clinical trials, in order to determine the appropriate dose, concentration, and size of nanoparticles for safe use. In such cases, for safety in practice, various biocompatible agents and techniques are used for the biocompatibility of NPs, and in some cases, even their biofunctionalization or multifunctionalization for different biomedical applications (Caizer et al. 2020). Magnetic hyperthermia with magnetic nanoparticles for the thermal destruction of tumor cells (Datta et al. 2016) and noninvasively under the action of an external alternating magnetic field is seen today by researchers as a method of the future in alternative cancer therapy. This new technique has low toxicity compared to the classic chemo- and radiotherapy methods currently used in this field, which have high toxicity on the human body and in many cases, are ineffective. However, one of the most important problems in magnetic hyperthermia is the safe use of magnetic nanoparticles with as little or no toxicity as possible, and with maximum efficacy on cancer cells. This chapter focuses on the biocompatibility, toxicity, and safety of magnetic nanoparticles used in cancer therapy as noninvasive alternative therapy compared with conventional chemotherapy and radiotherapy methods.

16.2 Biocompatibility, Toxicity, and Safety of Magnetic Nanoparticles for Alternative Cancer Therapy Magnetic nanoparticles used in magnetic or superparamagnetic hyperthermia for alternative cancer therapy or targeted drug delivery are generally ferrimagnetic (oxide), the most commonly used being spinel (Caizer 2019). However, as a result of the development of advanced modern nanobiotechnology, in recent years, the idea of using ferromagnetic (metallic) nanoparticles in magnetic hyperthermia is advancing more and more (Rosensweig 2002; Caizer 2017). This is justified by the possibility of increasing the heating power of MNPs in a shorter time which does not affect healthy tissues. The size of nanoparticles is in the range of a few nanometers – tens of nanometers, corresponding to an single-domain or incipient multidomain magnetic structure (Caizer 2016), nanoparticles having a superparamagnetic behavior or low hysteresis in the external magnetic field (Caizer 2004). Superparamagnetic behavior is specific to superparamagnetic hyperthermia based on Néel–Brown magnetic relaxation phenomena, and hysteresis behavior is characteristic of magnetic hyperthermia where heat dissipation occurs through the phenomenon of hysteresis. In the case of soft magnetic materials, which are also most often used in both magnetic hyperthermia and superparamagnetic hyperthermia, the superparamagnetic behavior is generally obtained for sizes (diameters) of nanoparticles positive SPIONs > negative particles Significant toxicity on both neuronal and glial cells

2012

(Kawanishi et al. 2013)

NIH 3T3

CTAB BSAand HSACoated NPs

60 mg ml−1 (core = 7–9 nm, d = 50–70 nm)

MTT, LDH, and DCFDA

244,872 h

Cellular viability for proteincoated NPs > 95%, for CTABcoated NPs decrease to 90%, for IONPs a clear decline

2014

(Mahmoudi et al. 2012b)

hTERTBJ1

MA-PEG

0–1000 mg ml−1 (d = 50 nm)

MTT, live/dead

24 h

For 250 mg ml−1: 25–50% viable for bare SPIONs; for 1 mg ml−1: 99% viable for PEG-coated NPs

2004 (Cengelli et al. 2006)

L929

Poly(ethylene glycol)-cofumarate

0.4, 0.8, and 1.6 mg ml−1, d = 82 ± 12

MTT

24, 48 and 72 h

Lower toxicity for PEGF-coated NPs compared to bare one

2009

(Mbeh et al. 2015)

(Continued)

Table 16.4

Cell line

(Continued) Surface coating

NP concentration (average size)

Test

Exposure duration

Toxicity

Year

Refs.

L929

Bare, CESgrafted, PEGylated, APTESgrafted

(2–32 mM), d = 13.762.1, 13.862.1, 14.961.8, 17.862.6 for bare, CESgrafted, PEGylated, APTES-grafted, respectively

MTT and XTT

24 h

Very little toxicity

2012

(Kawanishi et al. 2013)

Hepa1-6

DMSA

50 and 100 μg ml−1 (core = 11 ± 1.24 nm, d = 32 nm)

GeneChip analysis

24 h

Overall significant toxicity, repression of Id3 expression

2015

(Ankamwar et al. 2010)

BRL 3A

None

0–250 mg ml−1 (d = 30, 47 nm)

LDH, MTT, GSH

24 h

EC50 > 250 mg ml−1

2005

(Lewinski et al. 2008)

Hep G2

Bare, CESgrafted, PEGylated, APTESgrafted

(2–32 mM), d = 13.762.1, 13.862.1, 14.961.8, 17.862.6 for bare, CESgrafted, PEGylated, APTES-grafted, respectively

MTT and XTT

24 h

Very little toxicity

2012

Kawanishi et al. 2013)

LLC

Poly (TMSMA-rPEGMA)

From 1 to 100 μg iron per well, core = 4–8 nm, d = 16 nm)

MTT

12 h

No toxicity even at relatively high concentrations of the SPION

2006

(Könczöl et al. 2011)

A549

Without coating

0.2–10, 2–3, 0.5–1.0 μm, 20–60 nm

DCFH-DA, mmp Comet assay, cytokinesis blockmicronucleus test

24 h

Genotoxicity of magnetite in A549 cells

2011

(Soenen and De Cuyper 2009)

A549

TEPSA, TPED

1 × 105 cells per well in to in a 12well plate. (core = 9.3 nm, d = 10.1 ± 1.3, and 10.4 ± 1.6 nm for Fe3O4@NH2, and Fe3O4@COO

DCFH-DA, MTS assay and etc.

24 h

No cell deaths, proliferation reduction is dose-dependent and highest for bare SPIONs. Negatively charged NPs are most biocompatible

2015

(Raynal et al. 2004)

A549

Bare, CESgrafted, PEGylated, APTESgrafted

(2–32 mM), d = 13.762.1, 13.862.1, 14.961.8, 17.862.6 for bare, CESgrafted, PEGylated, APTES-grafted, respectively

MTT and XTT

24 h

Significant toxicity

2012

(Kawanishi et al. 2013)

HCM

–COOH, – NH2, bare

(2–32 mmol ml−1), size of –COOH, – NH2, bare NPs, respectively, 13.8 ± 2.1, 17.8 ± 2.6, 13.7 ± 2.1

MTT

24 h

2011

(Lei et al. 2013)

HCM

Bare, CESgrafted, PEGylated, APTESgrafted

(2–32 mM), d = 13.762.1, 13.862.1, 14.961.8, 17.862.6 for bare, CESgrafted, PEGylated, APTES-grafted, respectively

MTT and XTT

24 h

Toxicity amounts: bare SPIONs > positive SPIONs > negative particles SPIONs-NH2 Very little toxicity on the human cardiac myocytes

2012

(Kawanishi et al. 2013)

Human MSCs

Resovist SPIONs, Endorem SPIONs

25–1000, and 25–2000 for resovist and endorem, respectively

MTT

24 h

No significant cytotoxicity

2012

(Nune et al. 2009)

BSA: bovine serum albumin, CTAB: cetyl trimethylammonium bromide, DMSA: dimercaptosuccinic acid, HSA: human serum albumin, poly(TMSMA-r-PEGMA): poly (trimethoxysilyl)propyl methacrylate and PEG methacrylate, TPED: N-[3-(trimethoxysilyl) propyl]ethylenediamine, TEPSA: 3-(triethoxysilyl)-propyl succinic anhydride, MSCs: mesenchymal stem cells. Id3: can be used as a nanotoxicity biomarker for iron nanoparticles. Source: Vakili-Ghartavol et al. (2020). Reprinted by permission of Taylor & Francis Ltd.

368

16 Magnetic Nanoparticles in Alternative Tumors Therapy

Table 16.5 Representative magnetic nanoparticles for magnetic nanoparticle-mediated hyperthermia. Core size

Characteristics

Refs.

Magnetite

A few μm

The first demonstration using magnetic particles

(Fortin et al. 2008)

Dextran magnetite

6 nm

The first demonstration using magnetite of nanometer sizes

(Gazeau et al. 2008)

Aminosilane-coated magnetite

15 nm

Enhances the uptake by cancer cells and prevents intracellular digestion

(Baldi et al. 2007)

Magnetite cationic liposome or cationic protein

10 nm

Enhances the uptake by cancer cells and stabilizes the colloidal solution

NPrCAP-conjugated magnetic nanoparticle

10 nm

Targets melanoma cells and exerts chemotherapeutic effects

Antibody-conjugated magnetic nanoparticle

20 nm

Targets human breast cancer and is conjugated with radioactive indium

(Gordon et al. 1979) (Guandong et al. 2010) (Hayashi et al. 2014) (Hergt et al. 1998, 2006) (Hergt and Dutz 2007) (Hilger et al. 2005)

Antibody or aptamer-conjugated magnetic nanoparticle

10 nm

Targets tumor cells and stabilizes the colloidal solution

Magnetic nanoparticle with encapsulated antitumor drug

20–30 nm

Controlled drug release

Name

(Hilger et al. 2003) (Hutten et al. 2005) (Ito et al. 2005a,b) (Ito et al. 2003, 2004)

NPrCAP: N-propionyl-cysteaminylphenol. Source: Reproduced from Kobayashi et al. (2014) with permission of Future Medicine Ltd.

(accumulation, excretion) in tissues and organs of MNPs (depending on their size) compared to functionalized MNPs with aptamers (Zamay et al. 2020). There is seen the accumulation in tumors of MNPs biofunctionalized with aptamers. Also, functionalizing of MNPs with biomolecules, including antibodies, proteins, enzymes, bovine/human serum albumin, biotin, avidin, or polypeptides, has become a good strategy for the application of MNPs in nanomedicine (Samanta et al. 2008; Xie et al. 2010; Cao et al. 2012; Iwaki et al. 2012; Okuda et al. 2012; Marcelo et al. 2013; Wu et al. 2015). However, in magnetic and superparamagnetic hyperthermia, in addition to the use of biocompatible magnetic nanoparticles most suitable for this therapy and with as low toxicity as possible (or even without toxicity), the amplitude (H) and frequency (f) parameters of the external alternating magnetic field which apply in the induction coil (Figure 16.5) (Rabias et al. 2010; www.ims.demokritos.gr; Wu et al. 2015) are equally important. They must be maintained within certain limits given by the formula (Hergt and Dutz 2007): H × f = 5 × 109 A m − 1 Hz

16 1

Table 16.6 The distribution of MNPs in organs and tissues, depending on their size. Particle size

Accumulation

Excretion

Refs.

40 nm Large superparamagnetic iron oxide nanoparticles > KV), if the temperature decreases, there is a given temperature called the blocking temperature from which the thermal energy becomes lower than the anisotropy energy. Consequently, TB can be defined as follows: TB =

KV k B ln τM

τ0

17.2.2.2 Influence of the Size and Shape on Magnetic Properties

Both size and shape influence strongly the NPs magnetic properties. First, an increase in the NPs diameter ultimately leads to an increase of the anisotropic energy, which is proportional to KV. It is also possible to change the magnetic anisotropy of a NP by modifying its shape. Thus, the magnetic anisotropy energy Ea is then called the effective energy Eeff, which is a sum of several energies: Eeff = EMC + E Sh + E s where EMC, ESh, and Es are the magneto-crystalline, shape, and surface anisotropy energies, respectively, more details can be found in ref (Palmer 1963; Skumryev et al. 1999; Gilmore et al. 2005). Briefly, ESh is related to inhomogeneous fields induced by anisotropic-shaped NPs, and will increase the anisotropy of the NP. The surface energy Es is proportional to the ratio between the surface and the volume atoms Atomssurface/Atomscore. As the NPs get bigger, this ratio decreases and so do the surface energy. Yet, this decrease of the surface energy with the size increase is generally overcome by the increase of energy due to the increase in NPs volume. Therefore, the bigger and the more anisotropic in shape the NPs are, the higher the magnetic anisotropy energy is.

17.2 Structure, Magnetic Properties and Synthesis Methods of Iron Oxide NPs

In addition to the anisotropic energy, the size influences the magnetization of the NPs. Indeed, as the size decreases, the ratio Atomssurface/Atomscore increases. The lower coordination of surface atoms generates a local increase in anisotropy, which tends to align the magnetic moment of surface iron perpendicular to the surface, rather than along the magnetic field. It is reported that these surface spins are canted and, therefore, do not contribute to the total NPs magnetization. This will cause an overall decrease in NPs magnetization. This surface layer is called “dead layer.” The smaller the size of the NPs, the greater the volume percentage of the dead layer will be, which explains why the saturation magnetization of NPs is often lower than that of the bulk phase. Second, the Fe(+II) cations at the surface of magnetite-based NP are more sensitive to oxidation due to the nanoscale. Consequently, we observe the formation of an oxidized layer on the surface of the NPs. Since the magnetization of γFe2O3 is lower than that of Fe3O4, this oxidized layer contributes also to the decrease of the NPs saturation magnetization. The formal description of NPs is no longer (FeIII)[FeIIFeIII]O4, but Fe3 − δO4 or (FeIII)[FeII1 − δFeIII1 + 2/3δ □1/3 δ]O4. The composition of NPs synthesized by thermal decomposition (Baaziz et al. 2014b) as well as those synthesized by coprecipitation (Salazar et al. 2011) was shown to evolve as a function of the mean size of NPs. The combination of several characterization techniques (XRD, Mössbauer and infrared spectroscopy…) have demonstrated that iron oxide NPs synthesized by thermal decomposition were close to maghemite with a canted layer below 8 nm (Baaziz et al. 2014b) (Figure 17.3). Above 12 nm, they have a magnetite core with an oxidized maghemite layer on the surface. Between 8 and 12 nm, there is a composition gradient along the NPs with change of stoichiometry along the volume.

17.2.2.3

Effect of Doping on Magnetic Properties of Iron Oxide NPs

Thanks to the double exchange between Fe3+ and Fe2+, spins in octahedral sites are aligned ferromagnetically and antiferromagnetically with Fe3+ in A sites in magnetite. The net magnetic moment resulting from this structure can be considered as the difference between the moments in octahedral and tetrahedral sites: μ = μoct − μtet = 5 + 4 − 5 = 4μB Due to the weak ligand field in spinel compounds, all cations could be considered as high spin. Therefore, Fe3+ ions in ferrite is a pure spin ion (with no orbital momentum) (3d5, S = 5/2, L = 0), with no spin-orbit coupling. The contribution to magnetic anisotropy is only brought by the Fe2+ γFe2O3

Surface spin canting

Fe3–xO4

Fe3–xO4

When

When

ϕ >8 nm

ϕ >12 nm

Volume&surface spin canting

Fe3O4

Surface spin canting

Figure 17.3 Evolution of the magnetite composition with the NPs size. Source: Reprinted with permission from Baaziz et al. (2014b). Copyright 2014 American Chemical Society.

385

386

17 The Size, Shape, and Composition Design of Iron Oxide Nanoparticles

cations which have their orbital moment L quenched in octahedral sites. It explains therefore the low anisotropy of magnetite. However, doping elements such as cobalt, manganese, or zinc may substitute some iron cations in the spinel phase and depending on their nature, oxidation degree, and on the site where they substitute iron cations, the magnetocrystalline anisotropy of doped ferrites is impacted. Thus, when some iron cations are substituted by Co2+ cations, the resulting cobalt ferrite exhibits strong magnetocrystalline energy (Song and Zhang 2006). This effect is attributed to the strong spin-orbit coupling of cobalt ions in octahedral sites (Slonczewski 1958; Schnettler and Gyorgy 1964; Song and Zhang 2006; Sharifi et al. 2012), which increase the anisotropy constant of the material. Lee et al. (2011) showed that doping iron oxide NPs with Mn or Co allowed the increase in SAR values compared to the same undoped NPs. The magnetocrystalline anisotropy could also be tuned by growing a layer of a material with high magnetocrystalline anisotropy on a ferrite core with low magnetocrystalline anisotropy. Those core@shell NPs have presented higher SAR values than those of homogeneous ferrite NPs with similar size (Walter et al. 2014; Kumar and Mohammad 2011; Lee et al. 2011). Here, we choose to focus on zinc doping as other doping elements such as Co and Mn were reported toxic for biomedical applications, but the difficulties of the doping at the nanoscale reported below are the same whatever the doping element (Baaziz et al. 2014b). It is possible to enhance the magnetic moment by introducing a right level of doping element in the right site. The substitution of Fe2+ (3d6, S = 2, μ = 4μB) by Mn2+ (3d5, S = 3/2, μ = 5μB) leads to an increase of the moment in octahedral sites, and so to the overall magnetic moment from 4μB to 5μB (Angadi et al. 2016) (Figure 17.4a). Moreover, the dilution with zinc in A site of the magnetite phase up to 10–15% of the tetrahedral site will increase Ms (Bárcena et al. 2008; Wan et al. 2012). Indeed, the stoichiometric zinc ferrite ZnFe2O4 is a normal spinel with Zn2+ ions being in A sites. Therefore, the stoichiometric zinc ferrite is a diamagnetic compound. However, if only a small amount of zinc is introduced, Fe3+ will migrate into B sites, and so increases μoct while μtet decreases. This effect is seen as long as the spins in B sites are ferromagnetically aligned (Bárcena et al. 2008; Jang et al. 2009) (Figure 17.4b). By considering x as the doping level, the structure can be described as (Zn2+xFe3+(1 − x))[Fe2+(1 − x) Fe3+(1 + x)]. The introduction of diamagnetic elements such as Zn in Td sites will strongly affect the net magnetization of the spinel ferrite. If we consider the previously described structure (Zn2+xFe3+(1 − x)) [Fe2+(1 − x)Fe3+(1 + x)], the resulting moment would be μ = μOh − μTd = 1 − x μFe2 + + 1 + x μFe3 + − 1 − x μFe3 + + xμZn2 + = 2xμFe3 + + 1 − x μFe2 + = 4μB + 6xμB with μFe2+ = 4μB, μFe3+ = 5μB, and 4μZn2+ = 0μB. Therefore, the magnetization of zinc-doped magnetite should increase with x. However, this is true as long as B sites stay ferromagnetically be coupled which is not verified for all x values. It is often reported that beyond x = 0.3−0.4, the B sites align antiferromagnetically, leading to a decrease of the magnetization (Bárcena et al. 2008; Jang et al. 2009). When reduced to the nanoscale, difficulties do not seen in the bulk are also encountered. First, zinc was reported to be sometime localized in B sites instead of A sites (Yao et al. 2007; Liu et al. 2016b). This is a major issue since totally inverted zinc-doped ferrite does not have the same magnetic behavior. For instance, with x = 0.3, one could expect a magnetization of 5.8μB if Zn is in A sites, while the magnetization falls to 2.8μB below the magnetization of magnetite if Zn is in B sites. Another difficulty is the higher oxidation of iron II at the nanoscale, leading to the

(a)

(b) MnFe2O4

FeFe2O4

CoFe2O4

x=0

Td

NiFe2O4

TEM image

Magnetic spin structure

Oh 110

101

99

180 x = 0.2

Fe3+

T site

O site

Magnetic moment

5

5 μB

4

4 μB

3

3 μB

M2+

2

O2–

2 μB

5μB × 2 + 4μB × 4 = 26μB x = 0.4

High T2-weighted MRI

160

140

(Znx Mn1–x)Fe2O4

120

R2

Color map

Relaxivity coefficient (I/mmol/s)

Oh

4μB × 5 = 20μB

85

Ms/emu g–1 (magnetic atom)

Mass magnetization (emu/g)

(Znx Fe1–x)Fe2O4

100

Low 400

5μB × 4 + 4μB × 3 = 32μB

300

o2–

Zn2+

200

Td site

100

Fe3+ Fe2+ (5μB) (4μB)

0.0

0.1 0.2 0.3 0.4 Zn2+ doping level (x)

0.8

Oh site

Dopant effect on Ms

0 MnMEIO

MEIO

CoMEIO

NiMEIO

CLIO

Figure 17.4 (a) Magnetization of different ferrites and its influence on transverse relaxivity. Source: Lee et al. (2007). Reprinted by permission from Springer Nature. (b) Effect of zinc doping on the magnetization of Zn doped magnetite and manganese ferrite. Source: Jang et al. (2009). Reproduced with permission from John Wiley & Sons.

388

17 The Size, Shape, and Composition Design of Iron Oxide Nanoparticles

appearance of oxygen vacancies in B sites. Therefore, a better way to describe zinc-doped iron oxide would be the use of the following formula: Zn2x+− i Fe31+− x + i

Zn2i + Fe21+− x − δ Fe3 1++ x − i + 2δ □13δ O4 3

with x ≤ 1, the doping level, i ≤ x the so-called inversion degree of the spinel, δ a parameter characteristic of the oxidation of Fe2+ into Fe3+, and □ the vacancies. In this formula, we did not consider that Fe2+ could go in A sites, since it has never been reported previously.

17.2.3

Main Chemical Synthesis Methods of Iron Oxide NPs

Many techniques have been developed to synthesize iron oxide NPs (Mornet et al. 2004; Gupta and Gupta 2005; Laurent et al. 2008; Figuerola et al. 2010; Colombo et al. 2012). The advantages and drawbacks of the most used methods are presented in Table 17.1. The synthesis by coprecipitation is the easiest and most used method. NPs are formed with the addition of a base in an acid aqueous solution of iron salts Fe2+ and Fe3+. These ions are soluble in acidic medium but precipitate when the basicity increases. The main advantage of this method is to produce a large amount of NPs in water. Nevertheless, the size dispersity is not well controlled, and the NPs tend to aggregate as they are “naked” as synthesized (no molecule on their surface to provide colloidal stability) in water. To remedy this, ligand can be added during the synthesis, but it may perturb the process, and size and shape are not well controlled (Salavati-Niasari et al. 2012). Other methods have been developed in order to improve the control of the shape and size of the NPs such as microemulsion synthesis (Lopez-Perez et al. 1997; Lu et al. 2007; Gutiérrez et al. 2015), hydrothermal synthesis (Chen and Xu 1998), and the polyol synthesis (Chakroune et al. 2003; Wan et al. 2007; Dong et al. 2015), among many other methods. Since the 2000s (Sun and Zeng 2002; Park et al. 2004; Sun et al. 2004), the synthesis by the thermal decomposition method quickly developed for the synthesis of iron oxide NPs. This method allows the synthesis of monodisperse NPs with a narrow size distribution and a good morphology control. Furthermore, the NPs are stable in organic solvents thanks to their in situ coating by surfactants during the synthesis. Therefore, this synthesis method is now widely used and developed to tune the size, composition, and shape of NPs, but the mechanisms still need to be better understood to really master these parameters (Thanh 2012; Guardia et al. 2014; Baaziz et al. 2014b; Sathya et al. 2016; Baaziz et al. 2018; Lak et al. 2018; Cotin et al. 2018a, b, 2020). Table 17.1 Size and shape control of the most reported synthesis methods of iron oxide NPs.

Method

Conditions

Size (nm)

Size dispersity

Shape control

Yield

Coprecipitation

Fast reaction time, water solvent, low T