Bone Cell Biomechanics, Mechanobiology, and Bone Diseases [1 ed.] 9780323961233

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Bone Cell Biomechanics, Mechanobiology, and Bone Diseases

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Bone Cell Biomechanics, Mechanobiology, and Bone Diseases

Edited by Airong Qian School of Life Sciences, Northwestern Polytechnical University, Xi’an, People’s Republic of China

Lifang Hu School of Life Sciences, Northwestern Polytechnical University, Xi’an, People’s Republic of China

Academic Press is an imprint of Elsevier 125 London Wall, London EC2Y 5AS, United Kingdom 525 B Street, Suite 1650, San Diego, CA 92101, United States 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom Copyright © 2024 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. ISBN 978-0-323-96123-3 For information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Stacy Masucci Acquisitions Editor: Elizabeth A. Brown Editorial Project Manager: Tracy I. Tufaga Production Project Manager: Swapna Srinivasan Cover Designer: Christian Bilbow Typeset by STRAIVE, India

Dedication The book is dedicated to all biological and biomechanical researchers, students, and clinicians. We hope they will refer to it regularly and use the information to help guide their research and study.

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Contents Contributors Preface Acknowledgments

xv xxiii xxv

Part I Basic knowledge and research methods 1.

Basic knowledge and research methods Kaiyuan Zheng, Meng Deng, Yang Yu, Jingmei Zhou, Yimei Hou, Lulu Chen, Yuwen Ma, Yonghao Chen, Hong Chen, Xiaoqin Guo, Rongping Luo, Jiamei Liao, Shan Meng, Jing Zhang, Pingping Yan, Yan Zhang, Lifang Hu, Airong Qian, and Chong Yin 1.1 1.2

1.3

1.4

1.5

Introduction Bone structure and its cellular component 1.2.1 Bone matrix 1.2.2 Bone marrow 1.2.3 Periosteum 1.2.4 Blood vessel, lymphatic vessel, and nerve innervation of bone 1.2.5 Cell components Cartilage structure and its cellular component 1.3.1 Cartilage stroma 1.3.2 Articular cartilage Bone mechanobiology 1.4.1 Physiological response of bone under mechanical stimulation 1.4.2 Physiological response of cartilage under mechanical stimulation Conclusion and perspectives Acknowledgments References

3 4 5 6 7 7 9 13 14 18 21 21 22 23 24 24

vii

viii Contents

2.

Methods and models of bone cell mechanobiology Wenjing Mao, Ying Huai, Xuehao Wang, Lifang Hu, Airong Qian, and Zhihao Chen 2.1 2.2

2.3

2.4

3.

Introduction Methods and models of bone cell mechanobiology study in vitro 2.2.1 Fluid shear stress (FSS) in bone cell mechanobiology 2.2.2 Mechanical stretch in bone cell mechanobiology 2.2.3 Hydrostatic compressive force in bone cell mechanobiology 2.2.4 Vibration in bone cell mechanobiology 2.2.5 Mechanical unloading microgravity in bone cell mechanobiology 2.2.6 Hydrogel stiffness in bone cell mechanobiology Methods and models of bone cell mechanobiology study in vivo 2.3.1 Three-point bending 2.3.2 Vibration 2.3.3 Exercise 2.3.4 Hindlimb unloading (HLU) 2.3.5 Immobilization 2.3.6 Bedrest Conclusion and perspectives Acknowledgments References

31 32 32 35 36 37 39 42 43 43 44 44 46 46 47 48 48 48

The whole bone mechanical properties and modeling study Kang Ru, Raees Fida Swati, Hanrou Zeng, Zarnaz Khan, Zhihao Chen, Airong Qian, and Lifang Hu 3.1 3.2

3.3

3.4

Introduction Mechanical properties of cortical bone 3.2.1 Basic variables and values 3.2.2 Strength of cortical bone 3.2.3 Young’s modulus/modulus of elasticity 3.2.4 Micro and nanoscale property of cortical bone Mechanical property of trabecular bone 3.3.1 Trabecular bone structure and mechanical property 3.3.2 Strength of trabecular bone 3.3.3 Young’s modulus of trabecular bone 3.3.4 Micromechanical property and structure of trabecular tissue Three-dimensional bone models and techniques in biomechanics

53 54 54 55 57 59 60 60 61 62 63 64

Contents

3.5

Finite element analysis (FEM) for bone analysis 3.5.1 Meshing 3.5.2 Boundary condition 3.5.3 Boundary condition and mesh 3.6 Methods for biomimetic study 3.6.1 Biomimetics 3.6.2 Multiscale modeling 3.6.3 Homogenization 3.6.4 Top-down method 3.6.5 Bottom-up method 3.7 Development of representative volume element 3.7.1 Honeycomb composite 3.7.2 Nacre 3.7.3 Euplectella aspergillum (sea sponge) 3.7.4 Spider silk fiber 3.7.5 Comparison of biomimetic structures 3.8 Modeling and fracture analysis of bone and applications 3.9 Femur bone modeling and meshing 3.10 Conclusion and perspectives Acknowledgments References

ix 65 66 66 68 70 70 70 71 71 71 73 73 75 77 79 81 83 85 89 90 90

Part II Bone cell mechanobiology 4.

Mechanobiology of bone marrow mesenchymal stem cells (BM-MSCs) Hua Liu, Zihan Tian, Shuyu Liu, Wenhui Yang, Airong Qian, Lifang Hu, and Zixiang Wu 4.1 4.2

4.3

4.4

4.5

Introduction Bone marrow mesenchymal stem cells (BM-MSCs) 4.2.1 BM-MSCs characteristics 4.2.2 BM-MSCs function Mechanical stimulation of BM-MSCs 4.3.1 The effect of mechanical loading on differentiation of BM-MSCs 4.3.2 The effect of mechanical unloading on differentiation of BM-MSCs Mechanism of BM-MSCs mechanotransduction 4.4.1 Extracellular matrix-integrin-cytoskeleton system 4.4.2 Ion channel 4.4.3 Primary cilia 4.4.4 Signaling pathways Conclusion and perspectives Acknowledgments References

97 98 98 98 99 99 107 108 108 110 111 112 114 115 115

x Contents

5.

Mechanobiology of osteoblast Yunxian Jia, Zarnaz Khan, Mili Ji, Wenjin Zhong, Xuehao Wang, Airong Qian, and Lifang Hu 5.1 5.2

5.3

5.4

5.5

6.

Introduction Osteoblast 5.2.1 Osteoblast characteristics 5.2.2 Osteoblast function Mechanical stimulation of osteoblast 5.3.1 The effect of mechanical loading on osteoblast 5.3.2 The effect of mechanical unloading on osteoblast Mechanism of osteoblast mechanotransduction 5.4.1 Mechanical sensitive molecules 5.4.2 Signaling pathways Conclusion and perspectives Acknowledgments References

125 126 126 127 127 128 132 133 133 137 140 141 141

Mechanobiology of osteoclast Yan Zhang, Chen-xi Di, Nai-ning Wang, Fei Chen, Fan Zhao, Pai Peng, Zi-Han Qiu, Zhihao Chen, Ling Zhang, Lifang Hu, Yan Guo, Airong Qian, and Tie-Lin Yang 6.1 6.2 6.3

6.4 6.5

7.

Introduction Osteoclast characteristics Mechanical stimuli of osteoclast 6.3.1 FSS in osteoclast mechanobiology 6.3.2 Vibration in osteoclast mechanobiology 6.3.3 Mechanical Stretch in osteoclast mechanobiology 6.3.4 Compressive force in osteoclast mechanobiology 6.3.5 Mechanical unloading microgravity in osteoclast mechanobiology Osteoclast mechanotransduction Conclusion and perspectives Acknowledgments References

151 152 152 153 154 156 157 159 161 162 163 163

Mechanobiology of osteocytes Shaopeng Pei, Murtaza Wasi, Shubo Wang, Tiankuo Chu, Rosa M. Guerra, and Liyun Wang 7.1 7.2

7.3

Introduction Osteocytes 7.2.1 Osteocyte characteristics 7.2.2 Osteocyte function Mechanical stimulation of osteocytes 7.3.1 Lacunar-canalicular system in osteocyte mechanobiology 7.3.2 In vivo stimulation of osteocyte

167 168 168 171 172 172 174

Contents

7.4

7.5

8.

Mechanisms of osteocyte mechanotransduction 7.4.1 Mechanosensing complexes 7.4.2 Temporal responses of osteocyte mechanotransduction 7.4.3 Signaling pathways in osteocyte mechanotransduction 7.4.4 Altered osteocyte mechanotransduction in various diseases Conclusions and future studies Acknowledgments References

xi 178 179 184 190 197 198 199 199

Mechanobiological crosstalk among bone cells and between bone and other organs Fan Zhao, Yan Zhang, Shaopeng Pei, Shubo Wang, Lifang Hu, Liyun Wang, Airong Qian, Tie-Lin Yang, and Yan Guo 8.1 8.2

8.3

8.4 8.5

8.6

Introduction Subcellular structural basis for mechanosensing and cell communication in bone 8.2.1 Ion channels 8.2.2 Integrins 8.2.3 Cytoskeleton 8.2.4 Focal adhesions 8.2.5 Primary cilium 8.2.6 G protein-coupled receptors 8.2.7 Osteocytes and the lacunar-canalicular network 8.2.8 Other structures for mechanosensing Mechanotransduction between adjacent osteocytes: Immobilized, but active mechanosensitive orchestrator 8.3.1 Generation of primary biochemical-coupling signals by osteocytes 8.3.2 Intercellular transmission of biochemical-coupling signals to adjacent osteocytes Mechanotransduction between osteoblasts and osteoclasts Mechanotransduction among osteocytes, osteoblasts, and osteoclasts 8.5.1 Crosstalk between osteocytes and osteoblasts 8.5.2 Crosstalk between osteocytes and osteoclasts 8.5.3 Crosstalk among osteocytes, osteoblasts, and osteoclasts Mechanotransduction between bone and other organs 8.6.1 Osteocyte signaling to kidneys in regulation of phosphate homeostasis 8.6.2 Osteocyte-muscle crosstalk 8.6.3 Osteocyte-cancer crosstalk

215 217 218 218 220 221 221 221 222 222

223 223 225 226 229 230 232 232 234 234 234 236

xii Contents 8.7

9.

Conclusion and perspectives Acknowledgment References

238 239 239

Mechanobiology of the articular chondrocyte Quanyou Zhang, Min Zhang, Nan Meng, Xiaochun Wei, and Weiyi Chen 9.1 9.2

9.3

9.4

9.5

Introduction The biomechanical microenvironment of the chondrocyte 9.2.1 The mechanical cues in the pericellular matrix 9.2.2 Recapitulation of the mechanical microenvironment 9.2.3 The implication of mechanical microenvironment in tissue engineering Biomechanical characterization of a single chondrocyte 9.3.1 Mechanical behaviors of single cells 9.3.2 Measurements of single cell mechanics 9.3.3 The mechanical behavior of the chondrocyte Mechanosensitive channels are involved in mechanotransduction 9.4.1 TRPV4/PIEZOs in chondrocytes 9.4.2 TRPV4/PIEZOs mediate mechanical strain 9.4.3 TRPV4/PIEZO mediate chondrocyte sensing matrix physical properties Conclusion and perspectives Acknowledgments References

249 251 251 254 256 257 257 259 263 268 268 271 273 277 277 277

Part III Bone biomechanics and bone diseases 10. Bone cell mechanobiology and bone disease Lifang Hu, Zixiang Wu, Kang Ru, Hua Liu, Yunxian Jia, Zarnaz Khan, Zihan Tian, Shuyu Liu, Xia Xu, Zhihao Chen, and Airong Qian 10.1 10.2

Introduction Bone cell mechanobiology and osteoporosis 10.2.1 Bone marrow mesenchymal stem cell mechanobiology and osteoporosis 10.2.2 Osteoblast mechanobiology and osteoporosis 10.2.3 Osteoclast mechanobiology and osteoporosis 10.2.4 Osteocyte mechanobiology and osteoporosis

291 292 295 296 297 298

Contents

10.3

10.4 10.5

Bone cell mechanobiology and scoliosis 10.3.1 Mechanobiology of bone marrow mesenchymal stem cells and scoliosis 10.3.2 Osteoblast mechanobiology and scoliosis 10.3.3 Osteoclast mechanobiology and scoliosis 10.3.4 Osteocyte mechanobiology and scoliosis Chondrocyte mechanobiology and osteoarthritis Conclusion and perspectives Acknowledgments References

xiii 299 300 300 301 301 301 305 305 306

11. Biomechanics in clinical application for bone diseases Yuhong Niu, Yongle Wang, Hailan Meng, Chong Yin, Kai Dang, and Airong Qian 11.1 11.2

11.3

11.4

Introduction Abnormal bone biomechanics involved in bone diseases 11.2.1 Bone fracture biomechanics 11.2.2 Spinal diseases biomechanics 11.2.3 Osteoarthritis biomechanics 11.2.4 Osteoporosis biomechanics 11.2.5 Rickets and osteomalacia biomechanics 11.2.6 Osteosclerosis biomechanics 11.2.7 Osteogenesis imperfecta biomechanics Therapeutic strategies for bone diseases by using mechanical stimuli 11.3.1 Mechanical stimuli of bone fracture 11.3.2 Vibration training 11.3.3 Ultrasound therapy 11.3.4 Extracorporeal shock wave therapy 11.3.5 Magnetic therapy 11.3.6 Massage therapy Conclusion and future perspectives Acknowledgments References

315 316 316 324 327 328 330 331 333 334 334 337 338 340 342 343 344 345 345

Part IV New technologies for bone disease 12. New technologies for bone diseases Shuo Gao, Hao Zhang, Linbin Lai, Menglei Xu, Hong Yu, Airong Qian, and Wenjuan Zhang 12.1 12.2

Introduction Artificial intelligence 12.2.1 Artificial intelligence in medical research 12.2.2 Application of AI in bone diseases

355 356 356 357

xiv Contents 12.3

12.4

12.5

Single-cell sequencing 12.3.1 Introduction of single-cell sequencing 12.3.2 Application of single-cell sequencing in bone cell 12.3.3 Application of single-cell sequencing in bone diseases Genome-wide association study 12.4.1 The introduction of genome-wide association study 12.4.2 The research of bone diseases susceptibility genes based on GWAS 12.4.3 Multiomics study for interpretation of GWAS in bone disease genes Conclusion and perspectives Acknowledgment References

Abbreviations Index

363 363 366 367 369 369 369 370 372 373 373 377 385

Contributors Numbers in parentheses indicate the pages on which the authors’ contributions begin.

Fei Chen (151), Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China Hong Chen (3), Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China Lulu Chen (3), Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong; Department of Clinical Laboratory, Zigong First People’s Hospital, Zigong, Sichuan, People’s Republic of China Weiyi Chen (249), College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan, Shanxi, People’s Republic of China Yonghao Chen (3), Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China Zhihao Chen (31,53,151,291), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Tiankuo Chu (167), Center for Biomechanical Engineering Research, Department of Mechanical Engineering, University of Delaware, Newark, DE, United States Kai Dang (315), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Meng Deng (3), Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China

xv

xvi Contributors

Chen-xi Di (151), Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China Shuo Gao (355), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Rosa M. Guerra (167), Center for Biomechanical Engineering Research, Department of Mechanical Engineering, University of Delaware, Newark, DE, United States Xiaoqin Guo (3), Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China Yan Guo (151,215), Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China Yimei Hou (3), Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China Lifang Hu (3,31,53,97,125,151,215,291), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Ying Huai (31), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Mili Ji (125), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Yunxian Jia (125,291), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China

Contributors xvii

Zarnaz Khan (53,125,291), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Linbin Lai (355), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Jiamei Liao (3), Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China Hua Liu (97,291), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Shuyu Liu (97,291), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Rongping Luo (3), Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China Yuwen Ma (3), Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China Wenjing Mao (31), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Hailan Meng (315), Department of Spine Surgery, Honghui Hospital, Xi’an Jiaotong University, Xi’an, People’s Republic of China Nan Meng (249), College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan, Shanxi, People’s Republic of China

xviii Contributors

Shan Meng (3), Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China Yuhong Niu (315), Nursing and Rehabilitation College, Xi’an Medical University, Xi’an, People’s Republic of China Shaopeng Pei (167,215), Department of Orthopedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Center for Biomechanical Engineering Research, Department of Mechanical Engineering, University of Delaware, Newark, DE, United States Pai Peng (151), Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China Airong Qian (3,31,53,97,125,151,215,291,315,355), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Zi-Han Qiu (151), Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China Kang Ru (53,291), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Raees Fida Swati (53), Institute of Space Technology, Islamabad, Pakistan Zihan Tian (97,291), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Liyun Wang (167,215), Center for Biomechanical Engineering Research, Department of Mechanical Engineering, University of Delaware, Newark, DE, United States Nai-ning Wang (151), Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China Shubo Wang (167,215), Center for Biomechanical Engineering Research, Department of Mechanical Engineering, University of Delaware, Newark, DE, United States

Contributors

xix

Xuehao Wang (31,125), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Yongle Wang (315), Nursing and Rehabilitation College, Xi’an Medical University, Xi’an, People’s Republic of China Murtaza Wasi (167), Center for Biomechanical Engineering Research, Department of Mechanical Engineering, University of Delaware, Newark, DE, United States Xiaochun Wei (249), Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Shanxi Medical University, Taiyuan, People’s Republic of China Zixiang Wu (97,291), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Menglei Xu (355), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Xia Xu (291), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Pingping Yan (3), Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China Tie-Lin Yang (151,215), Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China Wenhui Yang (97), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Chong Yin (3,315), Department of Clinical Laboratory, Academician (expert) Workstation, Lab of Epigenetics and RNA Therapy, Department of Rehabilitation

xx Contributors

Medicine, Affiliated Hospital of North Sichuan Medical College; Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan; Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Hong Yu (355), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPUUAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Yang Yu (3), Tianjin Key Laboratory on Technologies Enabling Development Clinical Therapeutics and Diagnostics (Theranostics), School of pharmacy, Tianjin Medical University, Tianjin, People’s Republic of China Hanrou Zeng (53), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Hao Zhang (355), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPUUAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Jing Zhang (3), Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China Ling Zhang (151), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Min Zhang (249), College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan, Shanxi, People’s Republic of China Quanyou Zhang (249), College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan, Shanxi; Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Shanxi Medical University, Taiyuan, People’s Republic of China Wenjuan Zhang (355), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems

Contributors

xxi

Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Yan Zhang (3,151,215), Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China Fan Zhao (151,215), Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China Kaiyuan Zheng (3), Department of Clinical Laboratory, Academician (expert) Workstation, Lab of Epigenetics and RNA Therapy, Department of Rehabilitation Medicine, Affiliated Hospital of North Sichuan Medical College; Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China Wenjin Zhong (125), Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China Jingmei Zhou (3), Department of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China

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Preface Bone, as a highly specific mechanical support structure, mineral reservoir, and endocrine organ, is characterized by its unique rigidity, hardness, and regeneration and repair ability. It provides mechanical support for the body, meets the needs of minerals in the body’s metabolism, protects other organs, supports hematopoiesis and fat storage, and regulates the function of other organs. Bone is composed of fibers, a matrix, and bone cells. There are five main types of bone cells: (1) bone marrow mesenchymal stem cells (BM-MSCs), which possess pluripotent differentiation ability and are the origin of osteoblasts; (2) osteoblasts, which are responsible for bone formation; (3) osteoclasts, which are responsible for bone absorption; (4) osteocytes, which are the major mechanosensors and orchestrators in bone; and (5) chondrocytes, which are the only type of cell in the articular cartilage and are responsible for maintaining cartilage homeostasis. As mechanical stimulus plays a key role in both bone health and bone disease, bone cells play critical roles in bone sensing and responding to mechanical stimuli via mechanotransduction. The abnormal mechanotransduction of bone cells is one critical reason for numerous bone diseases, including osteoporosis, osteoarthritis, and scoliosis. Therefore, understanding the role and mechanism of bone cell mechanobiology in both bone health and bone disease is important. This book is a comprehensive and systematic compilation of bone cell mechanobiology and bone diseases. Based on the introduction of the basic knowledge of bone, bone mechanobiology, and methods and models of bone cell mechanobiology and bone mechanics, the book summarizes recent research advances in bone cell mechanobiology, including mechanobiology of BM-MSCs, osteoblasts, osteoclasts, osteocytes, and chondrocytes, and crosstalk among bone cells and between bone and other organs. Moreover, the book discusses bone cell mechanobiology involved in bone disease and biomechanics in clinical application for bone disease. Finally, it introduces new technologies for bone disease. This volume is a useful resource for researchers, scientists, students, and clinicians working in the field of bone, biomechanics, and bone disease.

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We apologize in advance for not including all researchers’ ongoing efforts in this field due to space limitations. We truly hope that this book brings those of us working in bone, bone mechanobiology, bone disease, and related fields around the world a little closer to each other. So, let’s begin this journey together. Airong Qian Lifang Hu

Acknowledgments The successful completion of this book required a long scholastic journey and the help of numerous individuals. We appreciate the contributing authors who donated their considerable time and effort to writing the excellent chapters of this book. We also express our thanks to those who helped make this book possible: Ge Zhang and Chao Liang at Hong Kong Baptist University, Xiaoyang Wu at the University of Chicago, Hong Zhou at the University of Sydney, Cory J. Xian at the University of South Australia, Jean X. Jiang at the University of Texas Health Science Center, Xiaona Li at Taiyuan University of Technology, and Hui Li at the Xi’an Hong-hui Hospital. We thank these colleagues for their professional support and constructive suggestions. We also thank Mr. Hafiz Muhammad Umer Farooq, Ms. Xiaodan Song, Ms. Dian Li, Ms. Dan Qiao, Mr. Xupeng Fu, Mr. Fulai Zhang, and Mr. Hao Zhang at Northwestern Polytechnical University, People’s Republic of China, and Mr. Awais Madni, Mr. Khalid, Mr. Aqib, and Mr. Ali Faiz at the Institute of Space Technology, Pakistan, for their assistance in editing and reviewing the chapters. We are grateful for the support of our esteemed institution, the Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, School of Life Sciences, Northwestern Polytechnical University. We also sincerely thank the members of the Elsevier publishing team, especially Tracy Tufaga and Elizabeth Brown, for their great help throughout the publication process. This work was supported by the National Natural Science Foundation of China (82072106, 81772017, 31570940, 31370845, 30970706, 30840030, 31400725, 81700784, 81801871, 81901917, 32000924, 32101055, 11872263, 12272252), the Programs for New Century Excellent Talents in University (NCET-12-0469), the China Postdoctoral Science Foundation (2021M692582, 2020M683573, 2018T111099, 2017M610653, 2015T81051, 2014M562450, 2017M613210, 2017M623249), the Project Supported by Natural Science Basic Research Plan in Shaanxi Province of China (2023JC-YB-163, 2021JQ-128, 2018JM3040, 2015JQ3076, 2018JQ8032, 2018JQ3049, 2022JQ-808, 2022JQ-829), the Key R&D Projects in Shaanxi Province (2018KWZ-10, 2021GXLH-01-02, 2022SF-295, 2021SF-242), the Shenzhen Science and Technology Project (JCYJ20160229174320053), Young Talent Fund of University Association for Science and Technology in Shaanxi, People’s Republic of China (20170401), the Fundamental Research Funds for

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the Central Universities (JC201055, 3102014JKY15007, 3102016ZY037, 3102018zy053, D5000210746, xzy012022032), the Medical Science and Technology Project of the Health Planning Committee of Sichuan (21PJ101), “Take the Lead” Program of Affiliated Hospital of North Sichuan Medical College (2022JB007), Clinical Research Program of Affiliated Hospital of North Sichuan Medical College (2021LC008), Basic Research Program of Affiliated Hospital of North Sichuan Medical College (2022JC014), the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health (P30GM103333, R01AR054385), the Shanxi Huajin Orthopaedic Public Foundation, the research project on major theoretical and practical issues of philosophy and Social Sciences in Shaanxi Province, People’s Republic of China in 2022 ([2022] 41), and the National Program of Innovation and Entrepreneurship for Undergraduates (S202110699538, XN2021031, S202010699126).

Part I

Basic knowledge and research methods

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Chapter 1

Basic knowledge and research methods Kaiyuan Zhenga,b, Meng Dengb, Yang Yuc, Jingmei Zhoub, Yimei Houb, Lulu Chenb,d, Yuwen Mab, Yonghao Chenb, Hong Chenb, Xiaoqin Guob, Rongping Luob, Jiamei Liaob, Shan Mengb, Jing Zhangb, Pingping Yanb, Yan Zhange, Lifang Huf, Airong Qianf, and Chong Yina,b,f,* a

Department of Clinical Laboratory, Academician (expert) Workstation, Lab of Epigenetics and RNA Therapy, Department of Rehabilitation Medicine, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China, bDepartment of Laboratory Medicine, Translational Medicine Research Center, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China, cTianjin Key Laboratory on Technologies Enabling Development Clinical Therapeutics and Diagnostics (Theranostics), School of pharmacy, Tianjin Medical University, Tianjin, People’s Republic of China, dDepartment of Clinical Laboratory, Zigong First People’s Hospital, Zigong, Sichuan, People’s Republic of China, eKey Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China, fLab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China * Corresponding author.

1.1

Introduction

In the 17th century, Galileo (1638) proposed the biomechanical function of bone and described its anatomy in detail. This was the earliest description of bone in medical physiology. Bone is a dynamic, mineralized connective tissue with multiple physiological functions. Together with the skeletal muscle attached, it constitutes the motor system of the human body and carries out motor function under the control of nerves. The morphology of bones varies among the different types. Accordingly, bones are categorized as long bones, short bones, flat bones, and irregular bones. This polymorphism is adaptive to their corresponding specific functions. There are two types of bone formation in human beings: intramembranous and chondrogenic osteogenesis. Intramembranous osteogenesis refers to the process Bone Cell Biomechanics, Mechanobiology, and Bone Diseases. https://doi.org/10.1016/B978-0-323-96123-3.00001-4 Copyright © 2024 Elsevier Inc. All rights reserved.

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that occurs during the embryonic period; mesodermal mesenchymal stem cells (MSCs) aggregate and differentiate into embryonic connective tissue membranes, within which bone forms. The parietal bone, frontal bone, and clavicle of the human body are generated in this way. Others such as long bones, short bones, and part of irregular bones are transformed through chondrogenic osteogenesis, a process during which some mesodermal MSCs are first transformed into chondrogenic cartilage, which are then gradually ossified. It is the most common form of osteogenesis. Each component of bone has a complex internal and external structure and together they form the biological function of bone. Physiologically, bone functions in support, movement, protection, hematopoiesis, and storage. Furthermore, there is cartilage tissue present in the metaphyseal end of the bone, which has multiple roles such as stabilizing the joint structure, increasing the joint range movement, reducing the friction force and pressure between the joints, and absorbing the impact force on the joints. In this chapter, we summarize the basic knowledge about the structure and cellular composition of bone and cartilage as well as introduce the mechanobiology of bone.

1.2 Bone structure and its cellular component Bone is composed of bone tissue, periosteum, blood vessels, nerves, lymph, and bone marrow. Bone tissue is the hardest part in the bone structure and constitutes the main body of the bone. The microstructure of bone includes cellular and intercellular substances. Bone tissue is composed of five cell types: bone mesenchymal stem cells (BMSCs), preosteoblasts, osteoblasts (OBs), osteoclasts (OCs), and osteocytes (Ocys). The intercellular substances of bone include the matrix and fibers, with most fibers being bone collagen fibers.

FIG. 1.1 Bone structure.

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The matrix, including cortical bone and trabecular bone, contains a large amount of solid inorganic salts (Fig. 1.1).

1.2.1

Bone matrix

Histomorphologically, bone tissue consists of cortical bone and trabecular bone. Cortical bone is firm and dense, with a compact structure and mineralized components, and is composed of microstructures such as the Haversian system. The cortical bone units and plexiform sheets are arranged longitudinally with strong resistance to compression and torsion, existing in the superficial layer of the diaphysis of long bones and other types of bone. Channels of blood vessels and nerves are distributed inside, accounting for about 80% of the mass of the entire bone tissue [1]. Trabecular bone is relatively sparse, spongy, and porous, consisting of many interlaced irregularly layered or needle-like trabecular bones. It mostly exists at the end of the long bone and bone cavity as well as the middle of the laminar bones, principally responsible for energy absorption and load transfer. A study of the pelvis and its associated joints and ligaments found that the mass proportion of cancellous bones was approximately 20%, while that of the surface area was 67% [2]. Although the porosity of trabecular bone reduces the strength and load-bearing capacity of the overall bone structure, the overall weight is also largely reduced. Meanwhile, the huge surface area of the loose and porous trabecular bone provides an essential internal environment for metabolic activities including bone cell metabolism and bone marrow erythropoiesis. Therefore trabecular bone has excellent hematopoietic function [3]. At the level of microstructure, the bone tissue, regardless of the state, is composed of bone tissue cells and numerous calcified extracellular matrix (ECM) components. Bone tissue cells are located in different positions of bone and perform specific physiological functions. The ECM is the main body of the bone tissue, composed of organic matter and inorganic matter. The principal component of organic matter is bone collagen fibers, which are synthesized by OBs, accounting for about 90% [4]. Collagen fibers function as a grid in bone and cartilage tissue, which reinforces the hardness of bone and cartilage. The other category of organic matter is known as non-collagenous proteins of amorphous matrix, including osteocalcin (OCN), alkaline phosphatase (ALP), osteonectin, connexin (Cx), and bone growth regulators. These non-collagen proteins determine the specificity of the bone matrix and probably participate in modulating the synthesis, secretion, and degradation of collagen as well as the mineralization of the bone matrix. The inorganic substances in the bone matrix are usually referred to as bone salts, which account for about 65% of the dry weight of the bone tissue. The highest content in bone salts is calcium phosphate followed by calcium carbonate and calcium citrate [5]. They are distributed in the organic matter of bone in the form of hydroxyapatite (HA) crystalline. The proportion of organic matter and inorganic matter in the bone matrix varies with age. In children, both organic matter and inorganic matter account for half of the bone weight. In adults, the proportion of organic matter increases to 1/3, while that

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of inorganic matter decreases to 2/3. In the elderly, the proportion of inorganic matter is higher. Therefore, with increasing age, the bone gradually becomes hard and brittle, while the elasticity and impact resistance keep declining.

1.2.2 Bone marrow Bone marrow, located in the medullary cavity of the long bone and all trabecular bone, constitutes the largest hematopoietic tissue in the human body. It accounts for about 4%–6% of body weight. There are two kinds of bone marrow: red bone marrow and yellow bone marrow. In fetuses and infants, there is only red bone marrow. After the age of 5 years, the red bone marrow in the long bones is gradually replaced by adipose tissue and becomes yellow bone marrow. After the age of 18 years, the long bone diaphysis is almost filled with yellow bone marrow. The red bone marrow is distributed in the mesh woven by the trabecular bone. Using the reticular connective tissue as a scaffold, a large number of blood cells of different developmental stages are attached to it. The yellow bone marrow is distributed in the bone marrow cavity of the tubular bone body. The red bone marrow has hematopoietic function, while the yellow bone marrow, which is mainly composed of adipose tissue, does not. However, there is a small amount of naive hematopoietic cell clusters in the yellow bone marrow. Under some pathological conditions, it can retransform into red bone marrow and restore hematopoietic function. Red bone marrow is mainly composed of blood sinusoids and hematopoietic cells. Blood sinuses are cavities with irregular shapes and different diameters that are formed after branches of arterial capillaries entering the red bone marrow. The sinus wall is lined with endothelial cells with a basement membrane and flattened polyprocess pericytes attached outside. In addition, monocytes and macrophages around the sinus wall and cavity have the function of phagocytosing and removing foreign bodies, bacteria, and senescent and dead blood cells from the bloodstream. Hematopoietic tissue is located between the blood sinuses and is composed of reticular connective tissue and hematopoietic cells. Reticular cells and reticular fibers constitute the meshwork of hematopoietic tissue, filled with various blood cells of different developmental stages and a small amount of hematopoietic stem cells (HSCs), macrophages, adipocytes, mesenchymal cells, and so on. Therefore, in addition to hematopoiesis, red bone marrow is also fundamental in immunity, defense, wound repair, bone healing, and defect repair [6]. Studies have shown that the microenvironment on which bone marrow depends for growth and development is extremely important for maintaining normal bone marrow function. This hematopoietic microenvironment contains bone marrow neural, microvascular system, fiber, stroma, and connective tissue components composed of various stromal cells. These components jointly influence the development of hematopoietic cells, which then regulate hematopoietic homeostasis.

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Periosteum

The periosteum is a layer of dense connective tissue covering the surface of bone. It is tightly attached at the bone end and where the tendon is connected. Elsewhere, it is thick and easy to peel off. Although the tissue structure of the periosteum varies with different anatomical sites and ages, its structure is often divided into a superficial fibrous layer and a deep cambium layer. The fibrous layer, principally composed of collagen fiber bundles, is thicker with less cellular components [7]. The cambium layer is immediately adjacent to the outer surface of the bone, with abundant cells, less fiber components, and loosely arrangement. The cellular components of the cambium layer include osteoprogenitors, OBs, OCs, and vascular endothelial cells [8]. In fracture repair, an intact periosteal cuff is particularly important for rapid healing. If the periosteal cuff is damaged, the fracture hematoma may flow into the soft tissue, resulting in the spread of the local mesenchymal cells and impeding fracture healing. At the same time, the fibrous tissue will invade into the fracture site, resulting in fibrous healing. Investigations have shown that upon fracture, the periosteum, especially the cambium layer, thickened significantly. Osteoprogenitor cells in the cambium layer proliferate and differentiate into OBs, which then form periosteal callus through intramembranous osteogenesis. This process is most pronounced adjacent to injury site. With the increase in the distance on the periosteum from the fracture, the response gradually decreases [9]. Meanwhile, the periosteum contains ample blood vessels and nerves. The principal function of periosteal blood vessels is to provide nutrition for the periosteum. However, recent studies have revealed that during periosteal osteogenesis, pericytes on periosteal capillary wall can proliferate and differentiate into OBs, which constitutes a supplementary source of OBs [10–12]. The majority of nerve fibers in the periosteum are unmyelinated with free endings correlated with pain conduction. Immunohistochemistry identified substance P staining nerve plexus and vasoactive peptide-stained nerve fibers in the periosteum, substance P peptidergic nerve fibers may be related to periosteal sensory conduction, while the effect of nerve fibers containing vasoactive peptides is not clear. It is widely believed that blood vessels and nerves in the periosteum are correlated with the peri-bony soft tissue, which plays a fundamental role in the nutrition, sensation, generation, repair, and transformation of bone.

1.2.4

Blood vessel, lymphatic vessel, and nerve innervation of bone

1.2.4.1 Blood vessel of the bone As an organ, bone requires blood supply to provide nutrients and remove metabolites. The vascular network of bone consists of arteries, veins, and capillaries. Bone has abundant arteries that can be categorized into the diaphyseal trophic system, the epiphysis-metaphyseal system, and the periosteum-cortical bone

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system. The nutrient arteries penetrate into the bone through the periosteum and cortex where they divide into two branches, one for the cortex and the other for the interior of the cortex. These two branches enter the cortical capillary network and bone marrow capillary network, respectively. After the cortical blood flows through the capillary network to enable substance exchange of bone cells, it returns to the venous plexus of the outer periosteum. The blood flow that nourishes the cancellous bone and bone marrow flows into the bone marrow venous sinus system, where it converges with the central venous sinus, and finally exits the bone through the nutrient vein. The anatomical characteristics of bone blood vessels are highly adaptive to the function as a solid scaffold of the skeletal system, in that the arteries are widely anastomosed and interconnected, and the venous network has a large diameter to accommodate the arterial characteristics and facilitate the rapid discharge of blood. Bone vessels play essential roles in the process of bone growth, development, repair, and reconstruction. Angiogenesis is closely correlated with bone formation. In terms of time, angiogenesis precedes bone formation, and vascular invasion is a prerequisite for bone formation and mineralization. In terms of space, blood vessels are necessary for bone tissue in providing oxygen, nutrients, and endocrine hormones as well as eliminate metabolic wastes. Angiogenesis also acts as a bridge between bone and adjacent tissues. This tight connection between angiogenesis and bone formation is called “vascularosteogenesis coupling” [13].

1.2.4.2 Lymphatic vessel of bone In the 19th century, some scholars proposed that there are lymphatic cavities around the blood vessels in the bones, but they failed to confirm it. Neoteric studies demonstrated that the lymphatic vessels of bone existed in the periosteum. However, the existence of lymphatic vessels in the bone marrow or bone cortex had not been proved. Recently, Wang et al. [14] revealed the intrinsic relationship between bone lymphatic vessels and bone metabolism. This study found that Gorham’s syndrome was caused by the increased activity of OCs in bone tissue, which resulted from the action of vascular endothelial growth factor (VEGF) and macrophage-stimulating factor (M-CSF) secreted by lymphatic vessels, and therefore suggested the existence of lymphatic vessels in the bone as well as their involvement in bone metabolism through M-CSF secretion. However, the relationship between the lymphatic system and bone function needs to further exploration. 1.2.4.3 Nerve innervation of bone Since the 19th century, many scholars in the field of histology have demonstrated the presence of nerves in bone. Their research suggested that most nerve fibers were accompanied by blood vessels, while a few sensory fibers were also distributed in the periosteum and vascular adventitia. Early studies believed that

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intraosseous nerves were pain fibers used to perceive severe pain caused by fractures, intraosseous abscesses, and tumors. In recent years, it has been gradually recognized that receptors for certain neuropeptides exist in skeletal cells. These receptors can accept neural signals and regulate the physiological functions of cells. Therefore, the nervous system not only participates in the sensory conduction of bone but is also involved in the regulation of bone metabolism. The intraosseous nervous system is divided into sympathetic, parasympathetic, and sensory nerves. They regulate bone metabolism principally through their secreted neurotransmitters and extensive peripheral nerve synapses. The sympathetic nervous system secretes norepinephrine and epinephrine, which regulate bone metabolism through the adrenergic receptors in tissues. The parasympathetic nerves, acting on OCs through acetylcholine receptors, increase the apoptosis of OCs and inhibit bone resorption, which is opposite to the function of sympathetic nerves. Sensory nerves regulate bone metabolism through the secretion of some neuropeptides secreted by their ends, such as substance P and calcitonin gene-related peptide (CGRP). In addition, several bioactive substances synthesized by neurons in the central nervous system, such as serotonin (also known as 5-HT) and leptin, are involved in the regulation of bone metabolism through various signaling pathways. Meanwhile, some investigations revealed that bone tissue can also influence nervous system in bone, which is mainly reflected in the regulation of nerve function by various cells in bone tissue. Chen et al. [15–17] found that prostaglandin E2 (PGE2) secreted by OBs regulated the physiological function of bone by the activation of PGE2 receptor 4 in sensory nerves, which inhibited the sympathetic activity in the central nervous system. The nervous system and bone metabolism are closely linked. With the future development of neuroscience, bone science, and interdisciplinary research, the interaction between the nervous system and bone physiology and pathology will be further explored for the benefit of patients with related diseases.

1.2.5

Cell components

Five types of cells, namely, bone marrow mesenchymal stem cells (BM-MSCs), preosteoblasts, OBs, OCs, and osteocytes, are present in the bone tissue. Among these, OBs, osteocytes, and OCs are located in the cortical bone, while BM-MSCs are in the trabecular bone.

1.2.5.1 Bone marrow mesenchymal stem cells BM-MSCs are stromal stem cells derived from non-HSCs of the mesoderm. They exist in the bone marrow matrix with several unique and important characteristics. First, BM-MSCs have strong self-renewal capacity and pleiotropic differentiation potential. Their self-renewal ability is attributed to highly active telomerase, which allows cell proliferation through asymmetric division and

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maintains the number of stem cells. Meanwhile, under the induction of a specific microenvironment, BM-MSCs can differentiate into various tissue cells, including OBs, chondrocytes, adipocytes, nerve cells, myocytes. BM-MSCs have low immunogenicity, which makes them free from NK cell-mediated cytolysis. They perform an immunomodulatory function and can inhibit the function of T and B cells in vitro. They have good paracrine function and can secrete a variety of substances that function to regulate the damaged local microenvironment, reduce inflammation, and promote the repair of damaged tissues. Last, they have a homing ability. When damage occurs to the corresponding tissue or cell, BM-MSCs can migrate through endothelial cells to the target tissue of lesion injury to play their biological functions. BM-MSCs are essential during the process of bone formation, repair, and reconstruction. Under certain conditions, they first transform into bone marrow clonogenic units, which differentiate into preosteoblasts. Preosteoblasts can further differentiate into OBs, which finally differentiate into osteocytes [18]. Therefore, BM-MSCs play a significant role in maintaining homeostasis of normal bone [19]. However, there are two directions in BM-MSC differentiation, adipogenesis, and osteogenesis. Adipogenesis induction factor inhibits osteogenesis, while osteogenesis induction factor blocks adipogenesis [20,21]. The specific direction of differentiation is precisely regulated by biological, physical, and chemical factors. Mechanical factors, including mechanical strain, vibration, and hydrostatic pressure, are important for the osteogenic differentiation of BM-MSCs. Recent studies have demonstrated that several essential signaling pathways, including Wnt, TGF-β/BMPs, Notch, MAPK, and HIPPO, jointly determine the direction of BM-MSC differentiation through relevant transcription factors (e.g., Runx2, Osterix, PPARγ, C/EBPα). In addition, non-coding RNA (ncRNA) has been found to play essential roles in BM-MSC transcription and post-transcriptional gene regulation [22]. These non-coding RNAs, such as miR-204/211, miR-214, and Lnc-DIF, regulate bone metabolism by binding to downstream or target genes [23–34]. In conclusion, BM-MSCs have multidirectional differentiation ability and low immunogenicity [25]. They can differentiate into OBs, chondrocytes, adipocytes, cardiomyocytes, and nerve cells under the induction of various stimuli in vitro, which has great potential for clinical application [26–28]. In-depth investigation of BM-MSCs will lead to future potential applications in clinical treatment and other fields.

1.2.5.2 Preosteoblasts Preosteoblasts, also known as bone progenitors, are located on the inner side of the periosteum and cortical bone, beneath the outer periosteum and on the bone surface [29]. Preosteoblasts are spindle-shaped with small finger-like protrusions. The cell nuclei are oval or long. Both nuclei and cytoplasm were stained very lightly. In the cytoplasm, there are several endoplasmic reticula (ER),

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underdeveloped Golgi apparatus, more mitochondria, and free ribosomes. As a type of primitive mesenchymal cell, preosteoblasts also have multidirectional differentiation potential, which allows them to proliferate and differentiate into OBs during osteogenesis, growth, reconstruction, or repair. Preosteoblasts have different origins due to different distribution positions. Preosteoblasts in the periosteum are derived from the MSCs in the periosteum [30], while that in the bone marrow matrix are differentiated from MSCs within the bone marrow [31]. Bone marrow-derived preosteoblasts can form bone directly through periosteal osteogenesis after differentiation, without the presence of other inducers called directional preosteoblasts (DOPC). Correspondingly, preosteoblasts derived from periosteum MSCs appear in the pathological state, such as heterotopic ossification, fracture repair. They differentiate into OBs under the induction of bone induction factors such as bone morphogenetic protein (BMP). Its osteogenesis mode is also different from that of DOPC, but through the form of chondrogenic bone, which is called preosteoblasts as inducible preosteoblasts (IOPC). An investigation on the effect of aging on the osteogenic ability of preosteoblasts revealed that with increasing age, the proliferation capacity of preosteoblasts gradually diminishes. The reduced bone-forming ability in elderly persons is attributed to the reduced osteogenic potential of anterior OBs due to alterations in the individual internal environment, including sex hormones, growth hormones, and biologically active substances released locally after fracture [32].

1.2.5.3 Osteoblasts OBs, also known as bone-forming cells, are the cells that form the bone tissue. OBs have a variety of shapes; they can be cuboidal, round, flat, or columnar, with a diameter of 20–50 μm. The cell morphology is plump when functioning vigorously. The cytoplasm is basophilic, with a large number of nucleoproteosomes and coarse ER in cytosol. The nucleus is large, round, or oval and lightly stained with 1–3 nucleoli. Active OBs have ALP activity and express large amounts of type I collagen. The genes of osteocalcin and osteopontin are also expressed. They can be calcified in conditioned medium (Alizarin red and VonKossa staining positive). These are phenotype markers of OBs adopted as criteria for OB identification and the evaluation of their osteogenic effects and metabolic regulation [33,34]. OBs often exist on the surface of newly formed bone and are arranged in a monolayer, covering the newly formed bone in an epithelioid fashion. On their surface, a large number of short villus protrusions are connected with adjacent cells and penetrate the surrounding osteoid tissue to form a network. There are bundles of microfilament and microtubules in the protrusions through which OBs can transfer materials to the surrounding cells [35]. Furthermore, OBs can synthesize and secrete bone matrix, which participates in the calcification of bone and regulates the amount of calcium and phosphorus into and out of the bone.

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In the process of bone formation, OBs undergo four stages to accomplish osteogenesis: cell proliferation, ECM maturation, mineralization, and OB apoptosis. The entire differentiation process is regulated by multiple transcription factors and signaling pathways [36]. Among these, Runt-related transcription factor 2 (Runx2), Osterix (Osx), is one of the essential regulating factors. Furthermore, several signaling pathways, including PI3K/AKT, Wnt/β-catenin, BMP/TGF-β/Smad, MAPK, Notch, and Hedgehog (Hh), play dominant roles at different stages during differentiation regulation and are synergistically involved in the regulation of OB differentiation [37–40]. Therefore, research on important signaling pathways and transcription factors related to osteogenesis differentiation should be carried out to identify pathogenesis and novel therapeutic targets for bone metabolic diseases in the clinic.

1.2.5.4 Osteocytes Osteocytes are the most widely distributed cells in bone tissue. Accounting for about 90% of bone cells [41], they are derived from OBs and are terminally differentiated cells of BM-MSCs. They are located in the osseous lacuna and embedded in the mineralized extracellular bone matrix. They have a diameter of about 10–15 μm. Nascent osteocytes are connected to mature osteocytes, and then they are swallowed into the osteoid; therefore, they are called osteoid osteocytes [42]. Once the matrix surrounding osteocytes is mineralized, these osteoid osteocytes turn into mature osteocytes, which can interconnect with up to 12 adjacent osteocytes through a number of intercellular protrusions. Moreover, as the longest-lived cells in bone tissue, osteocytes have a life span of about 25 years on average [43]. The perception of mechanical stress in bone tissue is mainly by osteocytes through the high connectivity of bone matrix and the osseous lacuna-tubule network system. Osteocytes elongate their dendrites in response to mechanical signals and release soluble factors (such as PGE2, ATP, and NO) that can regulate OB function. Moreover, under certain internal environments, osteocytes can promote or inhibit the proliferation and differentiation of different cells through sending signals to BM-MSCs, OBs, or OCs, thereby promoting or inhibiting bone formation [44–46]. Meanwhile, osteocytes can regulate the peripheral environment of near-osteocytes. Osteocytes have active acid phosphatase and lysosomal hydrolase, which can digest proteins and aminoglucans. Therefore, they can determine the local biochemical environment of cells. Gluhak-Heinricd et al. [47] revealed that the ECM dentin matrix protein 1 (DMP1) changes dynamically in response to mechanical stress. Besides, osteocytes can regulate mineral balance. The expressions of three key molecules (DMP1, Pex/Phex, and FGF23) in osteocytes is crucial for maintaining phosphorus balance in vivo [48]. Osteocytes, accounting for more than 90% of bone tissue cells, play an important role in bone metabolism. Research on osteocytes will elucidate the physiological mechanism of bone metabolism-related diseases and provide potential therapeutic clues.

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1.2.5.5 Osteoclasts OCs, also known as bone-resorbing cells, are composed of multi-nuclear giant cells (MNGCs). With a diameter of around 100 μm, an OC contains 2–50 tightly packed nuclei that are irregularly round or oval with smooth nuclear membranes. The cytosol is basophilic, which gradually becomes eosinophilic with the aging of cells. OCs are distributed on the bone surface and around the intraosseous vascular channels. The isolation and culture of OCs began in the 1980s. High expression of the tartrate-resistant acid phosphatase and cathepsin K are the major markers of OCs. OCs function in bone resorption, corresponding to OBs. The two kinds of cells work in coordination and play an important role in the development and formation of bone. However, OCs also have other biological roles. Researchers have discovered that OCs regulate hematopoiesis, osteogenesis, and intra-bone angiogenesis. In addition, OCs have a special absorptive function. In some local inflammatory lesions, OCs and macrophages jointly participate in the inflammatory resorption. Just like other cells in bone tissue, OC differentiation is regulated in multiple ways. Mature OCs are differentiated from HSCs. Several early factors (such as PU1 and MITF) can transform undifferentiated HSCs into myeloid precursor cells. With the expression and activation of M-CSF, these myeloid precursors cells begin to differentiate into monocytes/macrophages. Meanwhile, they initiate the expression of RANK (NF-κB, nuclear factor κB receptor activation factor) and proceed to differentiate into OC precursors. Under the action of important transcription factors such as NF-κB and NFATc1, OC precursors are activated and modulated by RANKL (nuclear factor κB receptor-activating factor ligand). Subsequently, through the action of multiple signaling pathways and OC differentiation factors, OC precursor cells differentiate, develop, and fuse to form mature OCs [49]. Many signaling pathways, including the OPG/ RANKL/RANK signaling pathway [50], NF-κB classical signaling pathway [51], c-SRC-PI3K-Akt signaling pathway [52], and MAPK signaling pathway [53], are modulators of OC differentiation. In conclusion, OCs play important roles in skeletal system diseases. A comprehensive understanding of their function can lead to better remedies for bone diseases including osteoporosis (OP), osteoarthritis (OA), and osteonecrosis, as well as provide a new vision for the treatment of immune and metabolic diseases.

1.3

Cartilage structure and its cellular component

Cartilage is a supporting organ with a certain degree of hardness and elasticity. It is very developed in vertebrates. In the human body, it is distributed in the outer ear, nose, trachea wall, and the end of long bones. Cartilage is a specialized and dense connective tissue composed of cartilaginous and its surrounding perichondrium. The cartilaginous consists of chondrocytes, matrix, and

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collagen fibers. Chondrocytes are scattered in the cartilage matrix and constantly synthesize and degrade the cartilage matrix. The matrix protects chondrocytes, provides nutrition, and transmits signals. The chondrocytes and matrix interact with each other and are interdependent [54–59]. Cartilage is derived from the embryonic mesenchyme. During embryonic intrachondral osteogenesis, undifferentiated MSCs differentiate into cartilage tissue. From the surface to inside, the cartilage tissue can be divided into four regions: superficial, transitional, deep, and calcified cartilage regions. Each region has unique cell, collagen fiber, and ECM components. The surface area deals with shear forces, while the deep area fights against compressive forces. The special feature of cartilage is that it contains no blood vessels, lymphatic vessels, or nerves. The arteries, veins, and nerves supplying osteochondral can only reach the calcified cartilage layer of the cartilage. However, there are tiny tubes within the subchondral plate that can provide nutrients to articular cartilage (AC). Meanwhile, the cartilage matrix is rich in water, which facilitates nutrient penetration, so the chondrocytes in the deep layer can still obtain essential nutrients [60]. The subchondral bone is the deepest tissue in the osteochondral unit with strong hardness and stiffness and is composed of hydroxyapatite and type I collagen [61]. The connection of subchondral bone and cartilage tissue is called an osteochondral junction, which has both elasticity and toughness to cushion shock.

1.3.1 Cartilage stroma The cartilage tissue is dominantly composed of intercellular substances, which account for about 90% of the total volume [62]. The main components of the intercellular substances include cartilage mucin (CMP), collagen fibers (mainly type II collagen), and water. Among these, water accounts for 70%–80% of cartilage tissue, while CMP and collagen fibers account for 10%–15%. Additionally, there is a small amount of glycoprotein, fat, protein, and inorganic salts. In the cartilage stroma, the proteoglycans are mainly acidic glycosaminoglycans with strong hydrophilicity, which allows cartilage to bear greater pressure. CMP and water are the main chemical components of the ECM secreted by chondrocytes. Collagen fibers, including interstitial collagen I, II, and III, basement membrane collagen IV, and trace collagen VI, IX, and XI, are embedded in the matrix. Among these, type II collagen is a gene product of chondrocytes and can be used to determine the phenotype of chondrocytes. In addition, it has certain elasticity, which endows cartilage tissue with tensile property [63,64]. The collagen fibers in the cartilage layer gradually decrease from the surface layer to the deep layer, while the proteoglycans gradually increase. The collagen distribution pattern varies in different cartilage, while the distribution direction of fibers in cartilage usually resists the direction of tension borne by the cartilage [65]. According to the different fiber components contained, cartilage can be divided into three types: hyaline cartilage, elastic cartilage, and

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fibrocartilage. The matrix of hyaline cartilage contains water, mucin, and collagenous fibrils. Fibers are arranged in disorder. The hyaline cartilage, which is blue white or milky white and elastic, is distributed in the AC and costal cartilage and function in bearing load and reducing interarticular skeletal friction [66,67]. The structure of elastic cartilage is similar to that of hyaline cartilage. Only in stroma are there large numbers of fibers interwoven into mesh. Fibers are dense in the middle of the cartilage, while relatively rare in the peripheral part. This kind of cartilage is distributed in the auricle and respiratory tract and has good elasticity and functions in structural support [68]. The matrix of fibrocartilage is rich in thick and dense collagen fiber bundles, which are arranged in parallel or staggered. The chondrocytes are small and few, arranged in rows between the collagen fiber bundles. Fibrocartilage is distributed in the intervertebral disc, articular disc, and pubic bone symphysis [69]. Among the three cartilage tissues, hyaline cartilage is the most widely distributed, and its structure is more typical (Fig. 1.2). In the cartilage tissue, the cartilage stroma occupies the largest volume and constitutes a complex grid architecture that supports and connects the cartilage tissue. The difference of its composition determines the specificity of connective tissue. Many scholars have demonstrated that cartilage stroma can also regulate the formation of cartilage tissue and transmit various physical, chemical, and biological signals to chondrocytes, thereby regulating cell activities.

1.3.1.1 Chondrocytes Chondrocytes are the only cell type in mature cartilage tissue. Immature chondrocytes are oblate and distributed singly. Mature chondrocytes are located in the cartilage lacuna and are nearly round with oval nuclei and weakly basophilic cytoplasm. Around the lacuna, there is a layer of hyper-stained matrix called the cartilage capsule. The ultrastructure of chondrocytes is characterized by abundant rough ER, well-developed Golgi complex, some glycogen, and lipid droplets. They contain few mitochondria and therefore obtain energy through glycolysis. Chondrocytes are distributed in cartilage with certain regularity. The chondrocytes closed to the perichondrium are relatively immature and small. With the growth of cartilage, the cells gradually move to the deep part of the cartilage. The cells divide in the capsule and gradually form a cell mass with 2–8 cells, which is called a homologous cell mass. The chondrocytes can generate, secrete, and maintain cartilage matrix, and play an important role in the process of cartilage genesis, growth, repair, and remodeling [63]. Chondrocytes are derived from the differentiation of MSCs and this differentiation can be divided into four stages: differentiation induction, differentiation, terminal differentiation, and dedifferentiation. Differentiation induction refers to the process during which undifferentiated MSCs differentiate into cartilage stem cells. Differentiation refers to the process of proliferation and maturation of quiescent chondrocytes. The characteristic of this stage is that the

FIG. 1.2 Microstructure of cartilage. (Left) Hyaline cartilage. (Middle) Elastic cartilage. (Right) Fibrocartilage.

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quiescent chondrocytes that enter the rapid proliferation stage maintain strong proliferation ability, while the secretion rate of ECM is significantly reduced, and the morphology is round or oblate. At this stage, chondrocytes can synthesize a large number of ECMs such as type II collagen, type IV collagen, and cartilage-specific proteoglycans. In the terminal differentiation stage, chondrocytes mature and gradually transform into hypertrophic chondrocytes. The synthesis of proteoglycan and type II collagen is reduced, while the synthesis of ALP, active vitamin D3, and type X collagen are greatly increased, which eventually leads to the calcification of the ECM. Dedifferentiation of chondrocytes is characterized by the production of a large amount of CMP and type II collagen. However, due to the influence of the extracellular environment, chondrocytes gradually lose the biological characteristics, accompanied by a series of changes in their cell morphology, metabolism, differentiation, and proliferation. These changes are referred to as dedifferentiation of chondrocytes. Although the number of chondrocytes can increase through proliferation and differentiation, the volume and cell number of chondrocytes are precisely regulated. According to current research, the switches that initiate chondrocyte apoptosis include changes in the redox state of chondrocytes, locally secreted growth factors acting as apoptosis inducing signals (such as TNF and TGF-β), and vascularization of cartilage-bone junction. The above three pathways jointly regulate the process of apoptosis at the gene level. The proliferation and apoptosis of cartilage balance each other and jointly maintain cartilage homeostasis.

1.3.1.2 Perichondrium Perichondrium is a dense connective tissue covering the surface of cartilage, with the highest density found in infants and children. It is a thin membrane made of proteins joined together. The membrane is dense but porous with highly concentrated blood vessels, thus facilitating blood flow and oxygen transport. The main function of the perichondrium, like most connective tissues, is to provide protection for the more sensitive or vulnerable parts of the body. Furthermore, perichondrium can maintain the cartilage function by assisting in nutrient transport. In addition, when cartilage suffers from trauma, perichondrium can also promote the regeneration and growth of chondrocytes, thereby promoting cartilage tissue repair. 1.3.1.3 Chondrogenesis, growth, and degeneration Cartilage is derived from the embryonic mesenchyme. The basic process of chondrogenesis starts from the accumulation and proliferation of MSCs at the site where the cartilage is about to form. They then differentiate into bone progenitors, which further differentiate into chondroblasts. Chondroblasts synthesize and secrete ECM to embed themselves, and further transform into

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chondrocytes. The mesenchyme around the cartilage transforms into a fibrous membrane that surrounds the new cartilage, which is the perichondrium. After cartilage is formed, it continues to grow as the body develops. There are two growth patterns: appositional growth and interstitial growth. Interstitial growth, also known as endochondral growth, refers to the division of a single chondrocyte, which increases the number of chondrocytes and fills a lacuna with a population of cells formed from one cell. Meanwhile, cells produce matrix to make cells separate so that the volume of cartilage increases. Appositional growth is also known as subchondral growth. When the matrix ages, its rigidity increases, while the interstitial growth decreases rapidly. Therefore, further growth relies on the production of cartilage by perichondrium, a process during which the undifferentiated flat cells of the germinal layer differentiate into chondrocytes and produce matrix to become cartilage. The newly formed cartilage is attached to the outside of the existing cartilage. In the early stages of the embryonic development, both appositional growth and interstitial growth coexist, while relying mainly on appositional growth later. Chondrocyte senescence may be determined by two factors: stress induction (DNA damage, oxidative stress, inflammatory senescence, and epigenetic factors) and a limited in situ replication capacity [70]. It can eventually lead to a persistent proliferation arrest state of cells. Cellular senescence and age-related diseases are highly correlated. Typical features of a senescent chondrocyte include enlarged cell morphology, shortened telomeres, upregulated expression of cell cycle checkpoints such as p21 and p53, elevated levels of reactive oxygen species (ROS), and increased senescence-associated β-galactosidase (SAβ-Gal) activity [71]. Different cartilage tissues vary in their response to aging. Elastic and fibrous cartilage are often resistant well to aging, while hyaline cartilage often undergoes obvious aging. In recent studies, with the development of high-throughput proteomics, genomics, and metabolomics techniques combined with bioinformatics tools, several key molecules and biomarkers in the pathogenesis of cartilage degeneration have been identified. It is of great value to elucidate the molecular pathways driving chondrocyte aging and develop relevant targeted drugs.

1.3.2 Articular cartilage 1.3.2.1 The structure and function of articular cartilage AC, either hyaline cartilage or fibrocartilage, is a layer of bright connective tissue covering the surface of the joint. It is located at the opposite bone ends of the moving joint and has a smooth surface with a light blue color. The basic framework of AC is composed of collagen fibers. It has a semi-circular morphology, with its bottom end firmly attached to the underlying subchondral bone, while the upper end is oriented toward the articular surface. This structure enables the AC to tightly combine with the bone, while allowing for a little deformation

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FIG. 1.3 The structure and microstructure of articular cartilage.

when stressed. Between collagen fibers, there are scattered chondrocytes that are necessary for the metabolism of AC (Fig. 1.3). Under an electron microscope, normal AC shows a continuous four-layer plate laminar structure: the superficial layer (sliding layer), the intermediate layer (transition layer), the radiative layer (deep layer), and the calcified layer. In the superficial layer, the cells are spindle-shaped and the collagen fibers in the matrix cross into a network parallel to the cartilage surface. In the intermediate layer, cells are oval or round and the fibrils in the matrix are staggered, curved, and oblique. Cells in the radiative layer are large and round, often 2 or 4 aggregated. The matrix collagen fibers run diagonally toward the superficial zone. In the calcified layer, there are very few cells, some of which are degenerated. The collagen fibers in the matrix are thick. This microstructure of AC is compatible with its function. The main functions of AC include bearing mechanical loads while distributing the forces evenly, preventing joint wear, and absorbing and buffering stress. In this way, the AC allows the joints to bear the mechanical load to the maximum extent, makes the joints smooth and flexible during movement, and at the same time absorbs and buffers the vibration and impact of the connected bones during walking, jumping, and other movements, thereby protecting joints from multiple directions.

1.3.2.2 Nutrition of the articular cartilage The AC has no perichondrium, and its nutrition supply depends on synovial fluid and arterial branches around the synovial layer of the joint capsule. Synovial fluid contains hyaluronic acid, electrolyte, oxygen, glucose, and lubricating elements secreted by superficial chondrocytes. Therefore, synovial fluid not only provides nutrients required by cartilage but also plays an important role in lubricating the articular surface [72]. For the subchondral layer, the nutrients of synovial fluid may not be available. Currently, it is considered that it is mainly supplied by the nutrient diffusion from subchondral bone vessels [73]. In addition, studies have shown that joint movement plays a

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fundamental role in the acquisition of nutrients in AC and the elimination of metabolic waste. When the joint is active, the cartilage is pressed and the synovial fluid is extruded. When the pressure is reduced, the elasticity of the cartilage recovers and the synovial fluid is absorbed. Therefore, the synovial fluid of the cartilage can be renewed. If the AC is not sufficiently stressed, the synovial fluid cannot be renewed in time, and nutritional deficiency can lead to AC degeneration [74–76]. The nutrition supply for AC is restricted due to the deficiency in the directly nourishing blood vessels and nerves. Therefore, its self-repair ability is very limited when damaged.

1.3.2.3 Degeneration and repair of articular cartilage As with other cartilage in the body, AC experiences age-related changes. Degeneration of AC can be observed in normal individuals from the age of 30 years onward. At the initial stage, proteoglycans in the matrix of AC decrease, and collagen fibers on the surface of cartilage degenerate. Then, the articulation shows fissured wear and erosion and ulcers gradually form. Finally, due to repeated friction, the cartilage surface is destroyed, resulting in cartilage thinning or erosion. Further, the subchondral bone is exposed, and the joint space is narrowed, resulting in the reduced ability of the AC to withstand pressure stress. In the early stage, there may be no obvious changes in the synovial membrane and fluid of the joint. Subsequently, however, the necrotic and exfoliated cartilage can irritate the joint capsule and synovium, leading to congestion, edema, and increased synovial secretion, which can result in secondary synovitis. Joint synovial fluid becomes thinner due to synovitis, which impairs its lubrication and nutritional function to AC. Moreover, synovitis may result in synovial hyperplasia and hypertrophy, which can further develop into joint capsule fibrosis and contracture, and finally lead to joint fibrous stiffness. In addition, the degeneration of cartilage can increase the number of degenerated chondrocytes, which contain a large number of intracellular filaments and lysosome-like structures that can further aggravate this degeneration [77]. At the same time, chondrocytes can no longer secrete ECM after degeneration, which can further destroy the cartilage [78]. AC can hardly repair or regenerate owing to the deficiency in blood vessels and stem cells [79]. Investigations have demonstrated that lesions at the joint edge that are adjacent to the synovium can be repaired by the proliferation of synovial cells and the formation of fibrocartilage. However, injuries at other parts cannot be repaired by themselves because mature chondrocytes lack the ability of proliferation and division [80]. Once AC is damaged, this damage will often be gradually aggravated due to the intensification of mechanical friction and the activation of decomposition enzymes. Therefore, during the pathological process of cartilage degeneration, there are not only degenerative changes in AC but also alterations in joint morphology. Meanwhile, research has

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revealed that cartilage self-repair, redistribution of weight-bearing surface, and stability reconstruction also exist in the process of cartilage degeneration. However, the damage is much faster than the repair, so the joint surface is gradually eroded and destroyed. At present, all the clinical treatment methods for AC injury have corresponding limitations [81]. In the future, the research and development of bionic scaffold technology of stem cell engineering and tissue engineering may provide certain solutions for the clinical problems of cartilage repair and regeneration [82].

1.4

Bone mechanobiology

The mechanical properties of bone are determined by its structure and function. Bone biomechanics combines the biology of bone with mechanical principles and methods. Stress and strain are the most fundamental concepts in bone biomechanics. Stress refers to the amount of force exerted on bone tissue, while strain is the morphological changes of bone tissue due to external forces. The growth and change of bone tissue are associated with stress and strain. The relationship between bone stress and strain can be divided into two stages: the elastic stage and the plastic stage. In the elastic stage, the strain increases linearly with the stress before reaching the elastic limit of the bone. If the stress increases beyond the elastic limit, the bone tissue will enter the plastic stage. In this stage, the bone tissue has been structurally damaged, resulting in permanent deformation, also known as plastic deformation. When the stress increases to a certain extent, the bone breaks and fractures occur. The stress required to cause fractures is called the maximum stress or the strength limit of bone. The strain can in turn regulate the structure and function of bone, resulting in adaptive changes in bone. Research in this area is called bone mechanobiology. Three questions that mechanobiology research focuses on are how external force or muscle force is transmitted to bone tissue, how bone cells feel mechanical signal stimulation, and how mechanical signals stimulate cell expression and differentiation. Mechanical stimulation signals, signaling pathways, and cell response processes after stress constitute the three main research areas of bone mechanobiology.

1.4.1

Physiological response of bone under mechanical stimulation

As an important external stimulus, mechanical conditions can be converted into biological signals in vivo and regulate bone formation. It is believed that after being stressed, the deformation of bone tissue leads to the flow of interstitial fluid around the cell network of bone tissue from the high-pressure area to the low-pressure area. The flow of this fluid provides mechanical stimulation for cells. Osteocytes express abundant mechanical receptors. Therefore, they can first feel this stimulus and transmit the signal to OBs and OCs to change their activity, thereby regulating bone formation and remodeling.

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In terms of osteogenesis, after perceiving mechanical stimulation, osteocytes can regulate OB function by over-releasing soluble factors (such as NO and PGE2) through paracrine secretion. Meanwhile, osteocytes can convert mechanical stimulation into intracellular signals and regulate OB function through gap connection. In terms of bone resorption, osteocytes will signal OCs for bone resorption, while mechanical stimulation will stimulate osteocytes to produce cytokines to inhibit OC aggregation. Reduced mechanical loading attenuates the activity of osteocytes, leading to the apoptosis of osteocytes. Apoptotic osteocytes release signals to recruit OCs for bone resorption [83]. In addition, OBs and OCs can also be directly affected by mechanical stimulation. Mechanical stimulation of appropriate intensity can enhance the proliferation and differentiation of OBs, thereby promoting bone formation [84]. However, lack of mechanical stimulation results in the downregulation of multiple osteogenic genes in OBs, thereby inhibiting osteogenic differentiation. Research on the response of OCs to mechanics revealed that appropriate stress can directly inhibit the formation of OCs [85]. On the contrary, mechanical unloading can upregulate gene expression related to the maturation and activity of OCs, which promotes bone absorption [86]. Experiments in animal models showed that after immobilization in rats and hindlimb unloading (HLU) in mice, the ALP activity of OBs was significantly decreased and the osteogenesis was weakened, while appropriate mechanical loading promoted bone formation [87]. Clinical studies have shown that long-term immobilization of patients will lead to mechanical unloading of the bone, resulting in bone metabolism imbalance, which is manifested by a significant decrease in bone formation and bone mineral density [88]. Alternatively, moderate mechanical loadings, such as supine treadmill exercise and flywheel exercise, can resist bone loss caused by mechanical unloading conditions such as bed rest [89]. The reduction or absence of mechanical stimulation can lead to loss of bone mass and the decrease in bone density, which will lead to OP. OP caused in this way is called disuse osteoporosis [90], which can be either systemic or local. Localized disuse osteoporosis typically occurs in loadbearing bones such as the femur, tibia, and lumbar spine.

1.4.2 Physiological response of cartilage under mechanical stimulation As a dense connective tissue, cartilage is constantly subjected to endogenous and exogenous mechanical stimulation. These mechanical stimuli can directly or indirectly regulate the activity and behavior of chondrocytes [91]. Generally speaking, mechanical stress regulates cartilage through the following pathways. First, mechanical signals are transmitted to chondrocytes and matrix and transformed into biological signals through receptors and other ways. Then, biological signals enter the nucleus to modulate the expression of related genes,

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thereby producing a series of biological effects. In the process of chondrocyte metabolism, appropriate mechanical stimulation plays an essential role in the stability and maintenance of the internal environment of chondrocytes. Studies have shown that mechanical unloading conditions are not conducive to chondrocyte differentiation, and the level of chondrocyte proteoglycan aggregation is reduced. However, under mechanical overload, there will be an elevation in apoptosis-related gene in chondrocytes. Under moderate mechanical stimulation, chondrocyte activity increases and apoptosis levels decrease, along with increased levels of cartilage matrix synthesis. Animal experiments have demonstrated that after 11 weeks of immobilization the content of glycosaminoglycan (GAG) in dog knee AC decreased and the AC was significantly softened. Even if the biomechanical properties were restored by remobilization, the cartilage stiffness still did not reach the normal level [92]. Furthermore, running-induced overload in dogs resulted in decreased GAG content in the knee AC and altered collagen network organization and subchondral bone remodeling, which ultimately led to AC softening [93]. Clinical experiments have shown that reducing mechanical load may lead to loss of AC volume. One year after reducing joint load in paraplegic patients, their AC thickness decreased by 9%–13%, as shown by knee MRI. Meanwhile, the injury of excessive load to AC has been confirmed. A recent study on cumulative load involving 964 subjects revealed that the injury to medial tibial cartilage in overweight patients (i.e., joints were overloaded) was significantly higher than that in normal weight patients [94]. In addition, a study suggested that proper mechanical stimulation may promote cartilage growth. An MRI study of 18 adults showed that the surface area of tibial and patellar cartilage increased in athletes who engaged in high levels of physical activity throughout their lives compared with the control group of non-athletes [95]. In short, a certain range of mechanical stimulation promotes the formation of chondrocytes and ECM, and is crucial for the maintenance of the integrity of AC structure and function. Too low and high mechanical stimulation will lead to changes in the biological behaviors of chondrocytes. Therefore, it is of great significance to elucidate how the stress of various degrees affects the morphology and function of cartilage tissue for improving the clinical treatment of cartilage diseases.

1.5

Conclusion and perspectives

In this chapter, we present the basic functions and structure of bone and briefly describe the bone response to mechanical stimuli. As a dynamic connective tissue, composed of multiple cells and intercellular substances, bone performs multiple functions. It also receives multiple regulations in vivo. However, there is no doubt that mechanical stimulation is one of the most important factors. In recent years, due to the rapid development in the fields of stem cell engineering, genomics, epigenetics, and tissue engineering, some new research

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technologies as well as diagnosis and treatment methods for skeletal system diseases have become increasingly mature and have begun to be applied in clinical practice. However, there are still many scientific problems to solve on the regulation of bone and cartilage by mechanical stimulation. For example, what is the specific mechanism by which bone tissue cells respond to mechanical stimuli? At different growth stages of bone and cartilage, will mechanical stimulation affect the interaction between blood vessels and bone? What role do lymphatic vessels play in the mechanical response of bone? We believe that with the constant development of bone biology, molecular biology, and mechanobiology, the problems of bone biomechanics that we have not yet clarified will be solved and applied in clinical practice. These achievements will greatly promote the diagnosis and treatment of human motor system diseases.

Acknowledgments This work was supported by the National Natural Science Foundation of China (32000924), Medical Science and Technology Project of the Health Planning Committee of Sichuan (21PJ101), “Take the Lead” Program of Affiliated Hospital of North Sichuan Medical College (2022JB007), Clinical Research Program of Affiliated Hospital of North Sichuan Medical College (2021LC008)，Basic Research Program of Affiliated Hospital of North Sichuan Medical College (2022JC014).

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Chapter 2

Methods and models of bone cell mechanobiology Wenjing Mao, Ying Huai, Xuehao Wang, Lifang Hu, Airong Qian, and Zhihao Chen* Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China * Corresponding author.

2.1

Introduction

The skeletal system is involved in a variety of key physiological activities in mammals and is an important mechanical support framework. When bones are subjected to external force or motion, their changing laws can reflect mechanical and biological properties. In bone tissue, various cells including osteoblasts (OBs), osteoclasts (OCs), and osteocytes enable bone tissue to sense physiological stimuli and trigger related mechanical responses. Specifically, a portion of OBs can form OCs and then osteocytes act as sensor cells to receive mechanical stimuli and respond to mechanical signals. While in-depth research has been carried out on changes in bone formation and developmental factors, more attention has been paid to bone remodeling and development under different mechanical conditions [1,2]. Stretch stress, fluid shear stress (FSS), and hydrostatic compressive force are the components of mechanical forces described by Wolff’s law. Excessive action of these mechanical forces can lead to adverse outcomes for bones. Fractures always occur when the mechanical load on the bone exceeds its structural strength, which is an undesirable consequence of many bone-related diseases. With advancements in mechanical technology, various mechanical methods and models for bone research have been developed. Studies of these methods and models are necessary to evaluate the reliability, efficiency, and ergonomics of material tools and environments. Researchers are constantly developing various novel mechanical methods and models to explore the laws of bone-related mechanics. For example, Kozhevnikov et al. developed a dual-conduction integrated biosensing system based on biomechanical-related theories to study the Bone Cell Biomechanics, Mechanobiology, and Bone Diseases. https://doi.org/10.1016/B978-0-323-96123-3.00004-X Copyright © 2024 Elsevier Inc. All rights reserved.

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dynamic process of bone regeneration [3]. Zhang et al. promoted the formation of cartilage and bone from induced pluripotent stem cells by using mechanical stimulation generated by 3D rotating suspension culture [4]. This chapter summarizes in vitro and in vivo mechanical methods and models of bone cell biomechanics.

2.2 Methods and models of bone cell mechanobiology study in vitro Mechanical stimuli are important for the development and maintenance of bone. Bone is a complex tissue that adjusts its mass and structure to adapt to the mechanical environment under the force of gravity and other sources such as muscle contractions and ground response during locomotion. As the main signal sensors of bone, OCs control the conversion of mechanical signals to biological signals, thereby guiding the regulation of osteogenesis. In addition, osteocytes, OBs, and OCs work together to coordinate bone growth, maintenance, and healing after injury. However, these key cells involved in the mechanical network are also affected by other factors, thus the response of bones is altered in different situations. As such, it is essential to use novel methods and models to understand the mechanisms by which mechanical stimuli modulate bone mechanobiology. Various methods also need to be utilized to precisely analyze the mechanical behavior of bone to identify different diseases and risks [5,6]. In vitro cell cultures have been used to evaluate the influences of mechanics on the activities and functions of bone cells. For example, in vitro culture can create conditions that cause bone loss, enabling further analysis of osteocyte function. In the following sections, we introduce some necessary and practical in vitro methods and models for bone cell mechanobiology. Table 2.1 summarizes the parameters and characteristics of in vitro mechanical stimuli.

2.2.1 Fluid shear stress (FSS) in bone cell mechanobiology Blood and interstitial fluid (ISF) are two main types of fluids in bone tissue. As a vital component of the body, ISF localizes in the whole extracellular matrix (ECM), which provides cells with nutrients and facilitates the removal of metabolic waste. In addition, ISF can be found in some tissues of bones where it fills interspaces, such as cortical and cancellous bones, which bring nutrients to the cells within the bone through the movement of ISF [14]. The changes in mechanical loading generate fluid flow in bone, along with muscle contractions, leading to blood pressure. In biological fluid systems, the mechanical force caused by the friction of liquids such as blood on the apical cell membrane is shear stress, which affects cell adhesion and physiological activities. Shear stress is measured in dynes per square centimeter (dyn/cm2). Under physiological conditions, shear stress

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TABLE 2.1 Types of mechanical stimuli model. Parameter scope

Characteristics

Fluid shear stress

Physiological shear stress values range from 0.5 to 120 dyne/cm2 [7]

The range of physiological shear stress values depends on the type of blood vessel or tissue, and the size of the organism

Mechanical stretch

Stiffness range from 0.1 to 80 kPa (Flexcell system) [8]

Biochemical responses of various tissues and cells under stress can be detected

Hydrostatic compressive force

Hydrostatic pressure devices typically range from 0.05 to 12.0 MPa [9]

The direction of hydrostatic pressure is vertical and points towards the pressure surface

Vibration

Existing studies vary greatly in determining the optimal frequency, usually between 0 and 100 Hz [10–12]

Low-intensity, high-frequency mechanical stimulation can prevent bone loss [11]

Hydrogel stiffness

The hydrogel stiffness is softer at
1 kPa and stiffer at
7 kPa (depending on the cell type) [13]

Simulates the stiffness of the cytoplasmic matrix under physiological conditions

values range from 0.5 to 120 dyn/cm2 depending on the size of tissues and organisms as well as the thickness of blood vessels. In veins, shear stress is usually in the range of 1–6 dyn/cm2, while in arteries, this value is in the range of 10–70 dyn/cm2 [15]. In biological tissues, fluids are divided into different flow types, including laminar and turbulent flow. Laminar flow refers to the flow of fluids in parallel layers with no interruptions between the fluids. Among them, the unidirectional flow layer is the most common in most blood vessels, such as endothelial cells, which are often exposed to unidirectional laminar flow. The main characteristic of turbulent flow is the unpredictability of its velocity and direction. The occurrence of turbulent flow occurs mostly under pathophysiological conditions, thus it does not occur frequently [16]. FSS is one of the mechanical stimuli that bone cells experience as ISF flows across their surface. The flow of ISF is driven by the strain gradients induced by mechanical loading and bending of the bone, as shown in Fig. 2.1 [17]. The mechanical stimulus inflicted on the surface of cells can be converted into a biochemical signal to exert biological effects, such as proliferation and differentiation of some bone cells [18]. Using a numerical model, Weinbaum et al. estimated the level of FSS induced by ISF flow to be between 0.8 and 3 Pa and located in lacuna-canalicular spaces of bone tissues [19].

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FIG. 2.1 Fluid shear stress (FSS) experienced by bone cells. Mechanical loading creates a flow of interstitial fluid in the bone, and bone cells sense changes in the biomechanical environment.

In vitro models aim to recreate FSS of bone cells in a controlled cell culture platform, which contributes to an improved understanding of bone cell mechanotransduction. Compared with FSS in vivo, in vitro models can explore the impacts of different forms of flow on cell proliferation, development, and signaling mechanisms. For instance, studies of the difference between unidirectional flow and oscillating flow or changing the fluid flow rate are according to the actual situation in the study. The parallel-plate flow chamber (PPFC) is a common monolayer cell culture device that applies fluid shear forces [20]. Compared with other systems, PPFC has a very high FSS rate. FSS magnitude is measured in pascal units, and the FSS rate can be defined as Pa/mm (in the space domain). Frangos et al. originally invented this device to achieve cell growth on a glass slide sealed with a rubber ring and control fluid flow through hydrostatic pressures [20]. Over time, a more effective experimental device based on the principle of PPFC was developed. Yu et al. designed a microfluidic-based multi-shear device as a useful tool for analyzing the effects of FSS on cells. The device works by varying the length and width of the fluid flow channel, creating a low level of constant shear stress [21]. However, a limitation of this device is that the formation of air bubbles in the channel alters the mechanical environment of the cell, and the application of the flow regime is rarely exceeded for more than 24 h. Also, Anderson et al. found that although the target stress forms are comparable, the data studied in different chambers is not easily comparable [22]. In addition, the cultivation of 3D bone cells is more adapted to the natural growth of cells than in a flat environment. Therefore, a bioreactor that uses different materials to recapitulate the bone environment was created. To combine 3D bone cells with fluid flow, different kinds of bioreactors have been invented, such as spinner flasks, rotary vessels, and perfusion flow systems. Goldstein et al. discovered that the flow system was an optimal culturing method that induced high-level activity of alkaline phosphatase (ALP) in bone cells and

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FIG. 2.2 Fluid shear stress (FSS) loading system schematic diagram. This system utilizes a pump to control the flow rate and time of the medium in which the cells are placed to achieve a mechanical loading effect.

more uniform distribution of cells [23]. Fig. 2.2 shows the principle of the FSS loading system, which can control the flow rate and time.

2.2.2

Mechanical stretch in bone cell mechanobiology

When an object deforms due to changes in external conditions, internal forces can be generated between the components inside the object, and usually, the internal force per unit area on the observed section is called stress. In addition, strain, as another physical quantity, represents the change in shape and size of an object due to changes in conditions. The stress-strain curve is the basis and source of information for understanding the fundamental behavior of mechanics. Tensile stress refers to the reaction force per unit area of an object to an external force that tends to stretch the object. The effects of mechanical stretching on living organisms can be achieved through stress-strain curves. The stress and strain of the stress-strain curve of an object are generally expressed by conditional stress σ and conditional strain δ: σ ¼ P=A0 δ ¼ Δl=l0 In the formula, P is the load, Δl ¼ ll0 is the elongation of the sample, l0 is the original standard length, l is the length of the standard length corresponding to P, and A0 is the original cross-sectional area. During stretching, the length of the specimen increases and the cross-sectional area decreases [24]. Different kinds of mechanical loads can act on bone and its surrounding tissues, such as fluid shear force generated by ISF, and mechanical stretching

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acting on bone structure. In vitro models of cells that respond to different forms of mechanical loading have been established and increasingly extensively studied by scientists. The utilization of flexible-bottomed plates to investigate the influence of mechanical stimulation on cell culture was first reported in 1985 [25]. This method of mechanically stretching the device uses a computer to control the vacuum device in it and then exert negative pressure on the bottom of the membrane on the plate through the vacuum device. Cells that are firmly attached to the bottom membrane of the plate will gradually be stretched downward as the vacuum deforms the plastic petri dish, so the adhered and fixed cells can be strained. The Flexercell system is useful for studying the roles of strain on the cell population. This system can be utilized to control a variety of parameters, such as the amount and time of pressure applied. The Flexercell system has always been an excellent platform to study the effects of mechanical loads under different environmental conditions due to its relatively simple operation and ease of control over parameter variations. Strain is typically applied to silicone membranes used for a 2D culture that are coated with type 1 collagen. Sometimes, to characterize whether different ECMs affect the cells, the substance smeared on the petri dish could be replaced with the ECM of different types of cells. For example, Bhatt et al. utilized a uniaxial in vitro strain device based on the Flexcell system to create a novel model that induced OBs to mimic the molecular expression patterns observed in vivo [26]. Mechanical signals are continuously generated in the bone tissue containing osteocytes during mechanical stretching to influence cell activity. Therefore, mechanical strain is closely related to cell viability and changes cell activity in a variety of ways. For instance, strain can affect osteogenic ability in OBs, and mechanical transduction competes with the TGF-β signaling pathway to inhibit its function [27]. This technology platform was used to understand the influences of mechanotransduction on bone cells, contributing to a better understanding of the role of mechanodynamics in bone biomechanics. Mechanical stress, as an important cue of the cellular microenvironment, has a positive impact on the physiological activities of key cells leading to bone formation. However, once this mechanical signal exceeds a certain threshold, some physiological activities of cells are no longer stimulated, and even the normal viability of cells is adversely affected.

2.2.3 Hydrostatic compressive force in bone cell mechanobiology Hydrostatic pressure is the pressure exerted on an object by a uniform fluid, applied uniformly to all parts of the object’s surface from all directions. From a biological point of view, hydrostatic pressure is the pressure generated by the liquid accumulated in a certain part of the body on the surrounding tissues and

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cells, such as the pressure generated by the tissue fluid on the capillary wall. The hydrostatic pressure is represented by P, and the general calculation formula is P ¼ ρgh, where h is the liquid depth and ρ is the liquid density. In the same liquid environment, the deeper the depth, the greater the pressure. Hydrostatic pressure, as a vital mechanical microenvironment for cells, can exert uniform stress to affect various cell behaviors without deforming the cells. For example, it has been implicated in cartilage formation and can also act as a sensor to regulate the function of epithelial cells [28,29]. In addition, a recent study found that hydrostatic pressure also regulates the calcium ion response in cells [30]. As an experimental method to simulate the mechanical environment in the body, the hydrostatic pressure method is widely adopted to study the mechanical properties of cells to simulate the dynamic environment in vivo and explore the impact on endothelial cells. Ding et al. designed an in vitro experimental device with a compliance chamber as the core, using periodically changing hydrostatic pressure to simulate the systolic and diastolic pressures generated by the heart pumping blood [31]. The airbag, air cavity, purge valve, and internal liquid constitute the compliance cavity, and the liquid in it is used to generate hydraulic pressure. The compliance chamber, the afterload loading device, the flow chamber, and other devices together constitute the entire recirculating system. The afterload loading device achieves precise control of stress by controlling the flow rate of the outlet. When the liquid is pumped, the pressure of the pipeline rises, and part of the liquid enters the compliance chamber, which is utilized in the air chamber by the gas storage pressure potential; the other part of the liquid enters the follow-up device. Conversely, when the pulsating pump sucks in liquid, the stored potential energy pushes the liquid into a continuous process. Compared with the real environment in vivo, there are some differences between this experimental device and the real flow field, such as the temperature of the environment where the cells are located and the stability of the flow field. In addition, cell devices deployed in a liquid environment can detect and characterize fluid transport rates, which facilitates the study of physiological effects related to cellular fluid transport. Yang et al. designed a flow chamber system with two flow chambers to detect the fluid transport rate of the cell layer [32]. This device is applied to measure the relative velocity of cell transport fluid since the rate at which fluid is injected from the downflow chamber into the upflow chamber in the system is closely related to the rate of epithelial cell transport fluid.

2.2.4

Vibration in bone cell mechanobiology

As a ubiquitous phenomenon, vibration refers to the reciprocating change of any physical quantity near a certain value, including periodic and non-periodic

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vibrations. One of the signs of vibration is frequency. The vibration frequency F refers to the number of vibration cycles of an object per second, indicating the speed of vibration of the object. It can be used as an important basis for analyzing vibration and plays an effect in the pathogenic effect of vibration. In addition, the period T refers to the time required to complete a vibration process, which is the reciprocal of the frequency, F ¼ 1/T, and they are related to the physical properties of the vibration system itself. Biomechanics affects the process of bone regeneration. Bone cells are sensitive to mechanical stimulation, so vibration can be used as a physical stimulation method to explore the effects of mechanical stimulation on bone cells. Vibration comes in many forms, one of which is low-amplitude high-frequency vibration (LMHFV) applied to subjects standing on a vibrating platform, which has been extensively studied in recent years [33]. Generally, the amplitude of LMHFV is less than 1 mm, and the vibration frequency varies according to the experiment; it is usually between 10 and 150 Hz. The LMHFV approach promotes achieving more convenient and more cost-effective treatment of bonerelated diseases and bone regeneration. As multipotent stem cells, mesenchymal stem cells (MSCs) have the ability to differentiate [34]. Their physiological activities and functions are also strongly affected by mechanical stimulation. Therefore, studies of these cells are often tightly coupled with LMHFV and have important implications for cell regeneration. Using a low-intensity vibration method, Baskan et al. showed that this mechanical stimulation significantly reduced the expression of adipogenic markers, partially offsetting the effect of adipogenic induction on MSCs [35]. Therefore, they speculate that low-frequency vibration may be closely related to fat deposition. In this study, bone marrow mesenchymal stem cells (BM-MSCs) specialized for adipogenesis were placed in the LMHFV device for 15 min per day as the main experimental method. After a certain number of experimental days, the resting state of the cells in the experimental group and the control group were compared to determine the lipid accumulation and cell viability in the two groups. Furthermore, in addition to the study of MSCs using mechanical vibration methods, OBs derived from them can also be used as cells sensitive to mechanical stimulation. OB differentiation is regulated by transcription factors [36], and their terminal phase differentiates into long-lived osteocytes. Primary mouse OBs or OB-like cell lines allow for the evaluation of the effects of vibration on the function and behavior of these cells. In terms of vibration conditions, 0.25–0.5 g and vibration frequency of 30–60 Hz are usually selected to assess cell proliferation and mineralization. For example, Haffner-Luntzer et al. chose a vibration condition of 45 Hz and 0.3 g to perform LMHFV on pre-OB MC3T3E1 cells and primary OBs for 20 min a day to observe the presence or absence of estrogen [37]. By detecting the metabolic activity and proliferation of cells after LMHFV, it is concluded that the direct effect of LMHFV on OBs depends on estrogen receptor alpha signaling.

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The mechanical method of vibration may become an effective treatment strategy in the future. Different research literature has shown that slight changes in mechanical vibration conditions will have various effects on cell physiological processes. Therefore, more precise control and more controllable methods and devices based on LMHFV are needed. In addition, vibration is also used in in vivo experiments on bone biomechanics, which we discuss in the following subsections.

2.2.5 Mechanical unloading microgravity in bone cell mechanobiology The microgravity environment in space flight will enact certain changes in the metabolism and absorption of human nutrients. For astronauts, one of the most important problems is the impact of the space environment on bones, such as decreased bone density, which can lead to osteoporosis. It has been reported that significant bone loss was observed in the measurement of bone-related data of cosmonauts with different stay times at the Mir space station in Russia [38]. Therefore, bone loss is the most common physiological change observed in astronauts performing long-term missions. Simulating weightlessness on the ground has become a popular method to explore the effects of microgravity on the biomechanical properties of bone due to the high cost and limited opportunities of conducting experiments in space. Table 2.1 shows the comparison of the space environment and the terrestrial environment. In vitro methods have been developed to simulate gravity reduction, such as clinostats, parabolic flight, diamagnetic levitation (DL), and random positioning machines (RPMs) [39].

2.2.5.1 Superconducting magnet Superconducting magnets are ground-based simulators of gravity environments, allowing biological effects to be explored at the cellular level. Over time, a new superconducting magnet with a large-gradient, high-magnetic field (LG-HMF) was developed as a novel method to simulate weightlessness. Some diamagnetic materials such as cells and tissues can use this platform to explore the changes of biological effects in high-gravity and low-gravity environments, thereby helping us better understand the specific mechanism of the effects of weightlessness on cells in space. Superconducting magnets with LG-HMGs are widely used in weightlessness simulation because of their advantages such as a large-gradient magnetic field, long duration, and stability. However, this method of research also suffers from the inability to separate the magnetic field from gravity and the inability to pinpoint exactly which biological effects are causing it. Studies have demonstrated that the gravitational environment created by superconducting magnets can significantly affect cell morphology and proliferation by using three

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FIG. 2.3 A superconducting magnet with LG-HMF. The device offers three gravity levels (micro G, 1 G, and 2 G).

different gravity levels (μ g, 1 g, and 2 g) provided by a superconducting magnet (JMTA-16T50MF), as shown in Fig. 2.3 [40]. This finding facilitates further exploration of the specific mechanism of bone loss.

2.2.5.2 Clinostat The clinostat design has been around for a long time. The simplest clinostat consisted of a platform that rotated around a horizontal axis. With the progress of aerospace medicine, the clinostat has been used to simulate microgravity environments to explore biological physiological effects. Specifically, the creatures are subject to constant gravity on the ground, and the clinostat, due to its constant rotation, changes the direction of gravity attached to the platform. Thus, the constantly changing direction of gravity can be considered no gravity for living organisms, achieving an environment that simulates microgravity. Because of its simple operation, low cost, and repeatability, the clinostat is widely used in space biology and other fields. For instance, as a control experimental device for space biology experiments, it is an important tool to evaluate the sensitivity and influence of organisms to gravity [41]. The rotary speed setting is very important in determining whether the biological sample will feel the effect of gravity. Dedolph et al. concluded through calculation and analysis that the rotation rate of a clinostat is ω  1.38951  102 (L0t)1/3, which was considered by scholars at the time to be the optimal rotational speed, and this speed is suitable for all kinds of organisms and all kinds of cells affected by gravity [42]. In this formula, L0 refers to the distance between the sample and the clinostat axis, and t is the clinostat time. There are many differences between the simulated microgravity environment experiment of a clinostat and the real space environment. Mechanical signals are transmitted through fluid flow in bones, which affects cells through

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hydrostatic pressure and FSS. Therefore, the influence of FSS and other factors of cell samples in the clinostat experiment should be noted. In addition, other environmental factors need to be considered in the real space environment, such as radiation. Many ground and space experiments have been carried out along with the advancement of science and technology, and gyroscopes have also been improved, thus contributing to the further study of space biology.

2.2.5.3 Random position machine (RPM) The two-dimensional rotation method provided by a clinostat has been widely used in the simulation of microgravity, but it produces redundant effects on organisms. As such, 3D rotation more closely resembles real microgravity environment conditions by comparison. The 3D rotation can work in a variety of ways, including single-axis rotation, fixed-speed biaxial rotation, and random-speed biaxial rotation. As a kind of 3D rotation, the RPM (Fig. 2.4) can realize the random speed of biaxial rotation and is a vital tool to simulate weightlessness experiments. Its apparatus consists of two rotating shafts that are perpendicular to each other. Driven by the motor, the outer frame and the inner frame move at random speeds and directions so that cells and other samples can rotate in the inner frame in 3D [43]. The use of centrifugal technology to achieve a zero-sum gravity vector is the mechanical principle of RPM to simulate weightlessness. At the cellular level, RPM has been widely applied to explore the effects of microgravity on cell functions. One study found that the microgravity-simulating cellular changes were temporary, allowing normal activity to resume under the force of gravity. For example, Uva et al. observed that within a few minutes of simulated weightlessness, the cytoskeletal structure of lymphocytes, glial cells, and other cells are affected, microtubules, microfilaments and intermediate filaments are destroyed, mitochondria are damaged, cell division is blocked, and cell apoptosis occurs [44]. However, the cellular activity could resume 20 h after the end of a rotation.

FIG. 2.4 The schematics of the random positioning machine (RPM).

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In addition, it is worth noting that gravity cancellation does not eliminate the long-term stimulation of cells and other samples by gravity. Factors such as shear force in the cell will lead to displacement within the cell. At present, in the RPM cell culture system, the hydrostatic pressure of the environment in which the cells are located changes when the culture medium is filled in the conventional culture flask. Therefore, there is still room for improvement in RPM design.

2.2.6 Hydrogel stiffness in bone cell mechanobiology Hydrogel is a 3D hydrophilic polymer network that responds to environmental stimuli and swells in water. Its water content is between 90% and 99% and it facilitates the efficient exchange of oxygen with substances. The mechanical properties of hydrogels are important performance indicators, which are usually characterized by elastic modulus. The elastic modulus is the main parameter of mechanical characterization, which refers to the ratio between stress and strain. The larger the elastic modulus, the less likely the material is to deform. Research on this has gradually become popular in the biological field due to the high similarity of swollen hydrogels to biological tissues. Initially, the application of hydrogels in biomedicine was limited by the toxicity of the crosslinking agent and its self-formation under aqueous conditions [45]. Over time, biological processes have been better understood and chemical methods have been better mastered. Many studies have identified synthetic hydrogels as ideal substitute materials for biological tissues. For instance, the natural ECM used to support the adhesion, migration, and other activities of adipose stem cells has poor mechanical properties and poorly defined degradation properties. Therefore, hydrogels need to be adapted as scaffold materials to adapt to cell differentiation [46], which provides a prospect for the application of hydrogels in tissue engineering. The mechanical properties of ECM determine the various physiological functions of cells. The reason why cells perceive the mechanical cues of ECM is that the ECM is tightly connected to the cytoskeleton and affects the positioning and differentiation of cells, which involves a variety of cell surface receptors [47]. Generally, it is easier to use hydrogels to control stiffness. Therefore, stiffness is the most widely studied among the mechanical properties of ECM. The stiffness of ECM regulates a variety of physiological and pathological responses of cells. For example, this stiffness is closely related to cell differentiation. In a study by Dennis et al., researchers chose a polyacrylamide matrix as the matrix for cell culture and cultured MSCs in this matrix with different elastic moduli [48]. The mechanical stimulus induced by the constant change of the substrate stiffness led to cell differentiation, which contributes to understanding the relationship between physical stimulation and cells under microenvironmental conditions and has important implications for the therapeutic function

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of stem cells in medicine. The difference in individual tissues also changes the required stiffness, and the use of hydrogel is conducive to achieving a specific substrate stiffness that can be used to affect the physiological functions of cells. In terms of mechanism research, ECM simulation technology realized by hydrogel has revealed some mechanotransduction signal pathways in cells such as the Hippo pathway and TGF-β pathway [49,50]. Moreover, some investigations have found that the ability of human embryonic stem cells to maintain proliferation and diversity while growing in a wide range of stiffness was achieved by using a semi-interpenetrating network of polyacrylamide and reconstituted basement membrane [51].

2.3 Methods and models of bone cell mechanobiology study in vivo 2.3.1

Three-point bending

The bending test performed by the three-point bending mechanical loading device is one of the methods of mechanical loading. This test can measure the mechanical properties of a subject when subjected to a load. The device can also measure and track bone deformation in the human body, provide reference evaluation data for the physical therapy of bone-related diseases, and realize the clinical application. The three-point bending test usually places the subject at two support points within a certain distance and then applies a downward load to the test object from the upper part of the midpoint of the two support points. The three contact points of the test object form two equal moments, and three-point bending occurs. The three-point bending mechanical loading device realizes the mechanical loading of the bone on the living animal. Grimston et al. subjected mice to in vivo mechanical stress for 2 weeks, 5 days a week, generated by a threepoint bending device. Results found that the Cx43 gene attenuated the anabolic response to in vivo mechanical stress [52]. In addition, this mechanical loading device can also be combined with optical equipment. Lewis et al. used a three-point bending device to deliver mechanical loads to the bone of living mice and applied fluorescence imaging to detect the calcium response in osteocytes, finally reporting an in vivo method to explore calcium in osteocytes [53]. Furthermore, the model may also be utilized in clinical medicine. Ganse et al. used optical segmental tracking and the three-point bending test to measure the deformation of the human tibia in vivo. After local anesthesia, a threemillimeter screw was inserted into the bone and optical motion capture was performed, followed by the three-point bending test, combining optics and bone mechanics methods to measure bone deformation in vivo [54].

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2.3.2 Vibration Vibration, which can provide varying degrees of mechanical stimulus, has been extensively employed to study the impact of mechanical loads on bone. In in vivo experiments, whole-body vibration (WBV) training has been shown to increase bone mineral density (BMD) by mechanical loading [55]. The use of an oscillating plate to generate vertical acceleration is the principle of WBV training. Therefore, a person standing on the device could achieve the effect of transmitting the mechanical stimulus generated by the vibration to the whole body through the acceleration of the oscillating plate. Studies have shown that WBV can be used as a supplementary method to increase or maintain BMD, but whether the effects of this way are sustainable requires further investigation [56]. In addition, WBV training is relatively safe. Many training and data measurements involving the elderly found that this method can increase bone mass or prevent bone mass decline, suggesting that WBV is a promising alternative to prevent osteoporosis and fractures [57]. During vibration training, the response of cells in the bone tissue is evoked, and the parameters of the vibrating device affect the response of bone cells to mechanical loads such as vibration frequency (Hz), acceleration (G), and the duration of device action. For instance, Butezloff et al. explored the effect of vibration training on the femur of ovarian rats [58]. The set vibration frequency was 60 Hz, the duration was 20 min each time, and the vibration was performed three times a week. The researchers concluded that vibration therapy can improve the quality of fracture callus and bone quality of ovariectomized rats. In addition, it is necessary to combine vibration training with the measurement of biochemical markers and other technologies to obtain more detailed and reliable conclusions.

2.3.3 Exercise 2.3.3.1 Treadmill Treadmills can precisely adjust the speed and duration of exercise to study the impact of various intensities of training on the body, thus training on the treadmill is one of the common methods for preventing bone diseases. Typically, mouse models are used for treadmill training, as small animals are becoming increasingly popular models for investigating bone diseases. Before formal training, to reduce the differences between individuals and familiarize the mice with the surrounding environment, adaptive training is required. In most studies, the adaptive training option was applied approximately 1 week before the formal experiment. The specific method is to place the mice near the running equipment or choose a low-intensity mode of treadmill running training (8–15 m/min). Zhang et al. utilized a moderate-strength treadmill exercise method and found that this exercise enhanced bone formation [59]. They chose 2-month-old

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C57BL/6 mice and divided them into an exercise group and a control group. The exercise group needed to exercise 6 days per week for 5 weeks. By analyzing the bone morphology and BMD values of the exercise group and the control group, the researchers found that treadmill exercise effectively improved bone quality and enhanced the activation of the BMP-Smad signaling pathway in the body. In addition, Chen et al. used mechanical loads such as treadmill exercise to identify a mechanoresponsive microRNA (miRNA) in bone that is sensitive to bone metabolism [60]. They chose a laboratory animal treadmill and began training after grouping the mice into exercise and control groups. The mice in the exercise group exercised on the treadmill 5 days a week for 4 consecutive weeks, while the mice in the control group did not exercise on the treadmill. The speed setting was 10 m/min in the first week, and then gradually accelerated to 15 m/min in the fourth week; the length of time spent on the treadmill was also increased every week. Results showed that miR-138-5p, as a mechanically responsive miRNA, could explain the sensitivity of mechanical stimulation in bone metabolism and provide a strategy for bone metabolism to improve osteoporosis. It has been proven that exercise has a positive effect on bone health. For example, some studies have found that treadmill exercise may be good for the bones of female rats, including preventing bone loss in ovariectomized rats and increasing bone mass in adult rats [61]. Increasing bone mass and reducing bone loss after middle age are the main measures to prevent fractures and osteoporosis in women.

2.3.3.2 Swimming Exercise is a natural and simple treatment for certain conditions and diseases. The muscle contraction driven by physical exercise transmits mechanical signals into the body, exerting a certain impact on bone metabolism and other aspects [62]. Therefore, various sports training is increasingly being used to regulate bone metabolism since bone metabolism reflects the connection between bones and muscles. As a non-weight-bearing exercise, swimming can improve bone health. For example, high-intensity interval swimming training has a beneficial effect on both bone structure and strength in rats [63]. Swimming requires the coordination of the whole-body musculoskeletal system and ligaments, making it an effective form of endurance training. In rodent experiments, attention needs to be paid to the care of the mice and the control of environmental conditions. To pay attention to whether the mouse is floating in the water instead of moving, and to prevent the mouse from drowning, the water temperature in which the mouse swims is usually set at around 30°C. In addition, adaptive training is essential. The mice adapt to the swimming tank by swimming 3–7 days before the formal training, and the swimming time is no less than 15 min per day. Terada et al. allowed rats to swim under

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unloaded conditions and found that swimming induced an increase in the expression of PGC-1α protein in the soleus muscle of rats, which is beneficial to the exploration of skeletal muscle-related mechanisms [64]. For swimming training, intensity control is achieved by controlling the number and time of swims. Usually, 20–59 min a day is defined as low-intensity swimming training, 60–89 min a day is medium-intensity, and 90 min or more is high-intensity training. Therefore, it is necessary to select an appropriate training intensity based on the degree of adaptation of rats to this training method. In addition, the duration of training also needs to be considered. Many studies consider training 6 weeks or less as short-term training, and training 6 weeks or more as long-term training. Physical exercises such as swimming are beneficial to bones. For example, moderate-intensity exercise therapy improves bone strength and bone mass in mice by affecting bone formation and resorption [65]. During exercise training, it is important to tailor the corresponding exercise intensity and duration according to the subject’s fitness level. Compliance was found to be lower in studies of human exercise, while mouse models showed more controlled compliance. Therefore, it is necessary to start with mouse models to study the molecular mechanisms of bone-related diseases.

2.3.4 Hindlimb unloading (HLU) As an ideal animal model to simulate weightlessness, the tail suspension mouse model, also known as the hindlimb unloading (HLU) model, is widely used. In addition to exploring musculoskeletal changes in the space environment, it has also been effectively used to study skeletal and musculoskeletal diseases. In this model, a mouse’s tail is attached to a cage with a thin wire so that its hind legs cannot touch the ground. Usually, the angle between the hind limbs of the mouse and the ground is 30 degrees, which ensures that it can drink and eat normally (Figs. 2.2–2.5). Thus, changes in bone biomechanical properties can be detected, providing data for further research on the relationship between bonerelated diseases and weightlessness. The results of HLU model experiments showed that almost all the changes in organ systems and tissues could be measured. Studies of this model contribute to a better understanding of how the immune, cardiovascular, and nervous systems respond to mechanical stress and load. However, the HLU model also has disadvantages, such as continuous gravitational loading of the animal’s forelimbs that can have adverse systemic effects, and the effect of the model on the spine is still unclear [66].

2.3.5 Immobilization Hindlimb immobilization is another animal model method to explore the effects of mechanical load on bone. Usually, neurectomy or tenotomy is employed to

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FIG. 2.5 Schematic diagram of hindlimb unloading (HLU) mouse model.

construct this kind of animal model, followed by morphological analysis of the excised bone for further study. Usually, bone loss is caused by mechanical disuse, and one of the ways to cause mechanical disuse or lack is fixation. For instance, Weinreb et al. conducted a six-week limb-immobilization experiment on rats and found that bone loss is closely related to the reduction of bone formation [67]. They performed knee tendonectomy to immobilize the unilateral hindlimbs of the rats and then sacrificed the animals at different time periods to measure relevant data. It was concluded that the causes of bone loss include the rapid increase of bone resorption and the decrease of bone formation. Using the same method, Sakai et al. performed a sciatic neurectomy on mice tibia to assess the developmental capacity of bone marrow cells and the transformation of trabecular bone [68]. This study demonstrates the development of osteopenia after sciatic neurectomy.

2.3.6

Bedrest

Bedrest is one of the main methods for simulating the weightlessness of the body. In this method, the subject usually adopts a supine position or a headdown position. However, head fluid transfer in space may differ from horizontal bedrest, so head down tilt (HDT) bed rest with a tilt angle in the range of 2–10 degrees is often used; the recommended head tilt angle is 6 degrees [69]. This method is widely used to investigate the impact of simulated microgravity on individual physiological conditions and plays an important role in

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the study of individual bones, muscles, and cardiovascular systems [70], such as testing for bone loss and muscle atrophy. When subjects adopt this method, their activities are restricted; for example, the upper body cannot be lifted. The principle of this method is that when lying in bed, the hydrostatic effect of the fluid in the large blood vessels of the body can be partially or completely eliminated, which greatly reduces the load on the bones. This approach helps to better understand the impact of the space environment on physiological functions while keeping costs in check. Bone stress and strain reduction were simulated with bedrest by Leblanc et al. to determine the specific extent of bone loss and recovery [71]. In the study, six healthy men were selected as subjects and data on bone loss and recovery after 17 weeks of continuous bed rest and free walking for 6 months were determined. Eventually, a potential redistribution of bone minerals was observed. However, this method also has its limitations. Once a person adapts to this bedridden state, it is difficult to return to a normal state. Moreover, this method is not very reliable nor representative of the simulation results of some physiological state changes in space, such as body fluid transfer, spinal dysfunction, and radiation hazard [70].

2.4 Conclusion and perspectives Biomechanical research of bone cells has attracted increased attention, and more and various models and methods have been adopted and updated in this field. The applications of these methods are wide-ranging in both animals and humans. This chapter reviewed various in vivo and in vitro bone biomechanical research methods, which allowed the effects of mechanical stimuli on the bone to be simulated and studied. The role of mechanics in bone growth and remodeling has been elucidated and new ideas have been provided for treating bone-related diseases through these methods. It is believed that the study of the relationship between mechanics and bone can be widely used in future clinical practice.

Acknowledgments This work was funded by the Natural Science Foundation of China (grant number 82072106 and 32101055), China Postdoctoral Science Foundation (grant number 2020 M683573), Natural Science Foundation of Shaanxi Province (grant number 2021JQ-128), the Key R&D Projects in Shaanxi Province (grant number 2021SF-242), and the Fundamental Research Funds for the Central Universities (grant number D5000210746).

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[22] E.J. Anderson, T.D. Falls, A.M. Sorkin, M.L. Knothe Tate, The imperative for controlled mechanical stresses in unraveling cellular mechanisms of mechanotransduction, Biomed. Eng. Online 5 (2006) 27. [23] A.S. Goldstein, T.M. Juarez, C.D. Helmke, M.C. Gustin, A.G. Mikos, Effect of convection on osteoblastic cell growth and function in biodegradable polymer foam scaffolds, Biomaterials 22 (11) (2001) 1279–1288. [24] S. Bou Jawde, A. Takahashi, J.H.T. Bates, B. Suki, An analytical model for estimating Alveolar Wall elastic moduli from lung tissue uniaxial stress-strain curves, Front. Physiol. 11 (2020) 121. [25] A.J. Banes, J. Gilbert, D. Taylor, O. Monbureau, A new vacuum-operated stress-providing instrument that applies static or variable duration cyclic tension or compression to cells in vitro, J. Cell Sci. 75 (1985) 35–42. [26] K.A. Bhatt, E.I. Chang, S.M. Warren, S.E. Lin, N. Bastidas, S. Ghali, et al., Uniaxial mechanical strain: an in vitro correlate to distraction osteogenesis, J. Surg. Res. 143 (2) (2007) 329–336. [27] B.I. Knoll, T.L. McCarthy, M. Centrella, J. Shin, Strain-dependent control of transforming growth factor-beta function in osteoblasts in an in vitro model: biochemical events associated with distraction osteogenesis, Plast. Reconstr. Surg. 116 (1) (2005) 224–233. [28] G. Pattappa, J. Zellner, B. Johnstone, D. Docheva, P. Angele, Cells under pressure—the relationship between hydrostatic pressure and mesenchymal stem cell chondrogenesis, Eur. Cell. Mater. 37 (2019) 360–381. [29] S. Tokuda, A.S.L. Yu, Regulation of epithelial cell functions by the osmolality and hydrostatic pressure gradients: a possible role of the tight junction as a sensor, Int. J. Mol. Sci. 20 (14) (2019). [30] M. Fukuchi, K. Oyama, H. Mizuno, A. Miyagawa, K. Koumoto, G. Fukuhara, Hydrostatic pressure-regulated cellular calcium responses, Langmuir 37 (2) (2021) 820–826. [31] H. Ding, A. Qiao, L. Shen, M. Li, Z. Chen, X. Yu, et al., Design of compliance chamber and after-load in apparatus for cultured endothelial cells subjected to stresses, Cell Biol. Int. 30 (5) (2006) 439–444. [32] H. Yang, P.S. Reinach, J.P. Koniarek, Z. Wang, P. Iserovich, J. Fischbarg, Fluid transport by cultured corneal epithelial cell layers, Br. J. Ophthalmol. 84 (2) (2000) 199–204. [33] L. Steppe, A. Liedert, A. Ignatius, M. Haffner-Luntzer, Influence of low-magnitude highfrequency vibration on bone cells and bone regeneration, Front. Bioeng. Biotechnol. 8 (2020), 595139. [34] D.C. Ding, W.C. Shyu, S.Z. Lin, Mesenchymal stem cells, Cell Transplant. 20 (1) (2011) 5–14. [35] O. Baskan, G. Mese, E. Ozcivici, Low-intensity vibrations normalize adipogenesis-induced morphological and molecular changes of adult mesenchymal stem cells, Proc. Inst. Mech. Eng. H 231 (2) (2017) 160–168. [36] T. Komori, Regulation of osteoblast differentiation by transcription factors, J. Cell. Biochem. 99 (5) (2006) 1233–1239. [37] M. Haffner-Luntzer, I. Lackner, A. Liedert, V. Fischer, A. Ignatius, Effects of low-magnitude high-frequency vibration on osteoblasts are dependent on estrogen receptor α signaling and cytoskeletal remodeling, Biochem. Biophys. Res. Commun. 503 (4) (2018) 2678–2684. [38] P. Collet, D. Uebelhart, L. Vico, L. Moro, D. Hartmann, M. Roth, et al., Effects of 1- and 6-month spaceflight on bone mass and biochemistry in two humans, Bone 20 (6) (1997) 547–551. [39] Y. Arfat, W.Z. Xiao, S. Iftikhar, F. Zhao, D.J. Li, Y.L. Sun, et al., Physiological effects of microgravity on bone cells, Calcif. Tissue Int. 94 (6) (2014) 569–579. [40] A.R. Qian, W. Zhang, Y.Y. Weng, Z.C. Tian, S.M. Di, P.F. Yang, et al., Gravitational environment produced by a superconducting magnet affects osteoblast morphology and functions, Acta Astronaut. 63 (7–10) (2008) 929–946.

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[41] M. Cogoli, The fast rotating clinostat: a history of its use in gravitational biology and a comparison of ground-based and flight experiment results, ASGSB Bull. 5 (2) (1992) 59–67. [42] R.R. Dedolph, M.H. Dipert, The physical basis of gravity stimulus nullification by clinostat rotation, Plant Physiol. 47 (6) (1971) 756–764. [43] J.J.W.A. van Loon, Some history and use of the random positioning machine, RPM, in gravity related research, Adv. Space Res. 39 (7) (2007) 1161–1165. [44] B.M. Uva, F. Strollo, F. Ricci, M. Pastorino, J.I. Mason, M.A. Masini, Morpho-functional alterations in testicular and nervous cells submitted to modelled microgravity, J. Endocrinol. Invest. 28 (11 Suppl Proceedings) (2005) 84–91. [45] S.J. Buwalda, K.W. Boere, P.J. Dijkstra, J. Feijen, T. Vermonden, W.E. Hennink, Hydrogels in a historical perspective: from simple networks to smart materials, J. Control. Release 190 (2014) 254–273. [46] Q. Huang, Y. Zou, M.C. Arno, S. Chen, T. Wang, J. Gao, et al., Hydrogel scaffolds for differentiation of adipose-derived stem cells, Chem. Soc. Rev. 46 (20) (2017) 6255–6275. [47] J.D. Humphries, M.R. Chastney, J.A. Askari, M.J. Humphries, Signal transduction via integrin adhesion complexes, Curr. Opin. Cell Biol. 56 (2019) 14–21. [48] A.J. Engler, S. Sen, H.L. Sweeney, D.E. Discher, Matrix elasticity directs stem cell lineage specification, Cell 126 (4) (2006) 677–689. [49] E. Batlle, J. Massagu
e, Transforming growth factor-β signaling in immunity and cancer, Immunity 50 (4) (2019) 924–940. [50] V. Rausch, C.G. Hansen, The hippo pathway, YAP/TAZ, and the plasma membrane, Trends Cell Biol. 30 (1) (2020) 32–48. [51] A.J. Price, E.Y. Huang, V. Sebastiano, A.R. Dunn, A semi-interpenetrating network of polyacrylamide and recombinant basement membrane allows pluripotent cell culture in a soft, ligand-rich microenvironment, Biomaterials 121 (2017) 179–192. [52] S.K. Grimston, M.D. Brodt, M.J. Silva, R. Civitelli, Attenuated response to in vivo mechanical loading in mice with conditional osteoblast ablation of the connexin43 gene (Gja1), J. Bone Miner. Res. 23 (6) (2008) 879–886. [53] K.J. Lewis, D. Frikha-Benayed, J. Louie, S. Stephen, D.C. Spray, M.M. Thi, et al., Osteocyte calcium signals encode strain magnitude and loading frequency in vivo, Proc. Natl. Acad. Sci. U. S. A. 114 (44) (2017) 11775–11780. [54] B. Ganse, P.F. Yang, G.P. Br€uggemann, L.P. M€uller, J. Rittweger, T. Koy, In vivo measurements of human bone deformation using optical segment tracking: surgical approach and validation in a three-point bending test, J. Musculoskelet. Neuronal Interact. 14 (1) (2014) 95–103. [55] A. Prioreschi, T. Oosthuyse, I. Avidon, J. McVeigh, Whole body vibration increases hip bone mineral density in road cyclists, Int. J. Sports Med. 33 (8) (2012) 593–599. [56] P.Y. Liu, K. Brummel-Smith, J.Z. Ilich, Aerobic exercise and whole-body vibration in offsetting bone loss in older adults, J. Aging Res. 2011 (2011), 379674. [57] A. Go´mez-Cabello, I. Ara, A. Gonza´lez-Ag€uero, J.A. Casaju´s, G. Vicente-Rodrı´guez, Effects of training on bone mass in older adults: a systematic review, Sports Med. 42 (4) (2012) 301–325. [58] M.M. Butezloff, A. Zamarioli, G.B. Leoni, M.D. Sousa-Neto, J.B. Volpon, Whole-body vibration improves fracture healing and bone quality in rats with ovariectomy-induced osteoporosis, Acta Cir. Bras. 30 (11) (2015) 727–735. [59] L. Zhang, Y. Yuan, W. Wu, Z. Sun, L. Lei, J. Fan, et al., Medium-intensity treadmill exercise exerts beneficial effects on bone modeling through bone marrow mesenchymal stromal cells, Front. Cell Dev. Biol. 8 (2020), 600639. [60] Z. Chen, F. Zhao, C. Liang, L. Hu, D. Li, Y. Zhang, et al., Silencing of miR-138-5p sensitizes bone anabolic action to mechanical stimuli, Theranostics 10 (26) (2020) 12263–12278.

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[61] J. Iwamoto, T. Takeda, Y. Sato, Effect of treadmill exercise on bone mass in female rats, Exp. Anim. 54 (1) (2005) 1–6. [62] D.J. DiGirolamo, D.P. Kiel, K.A. Esser, Bone and skeletal muscle: neighbors with close ties, J. Bone Miner. Res. 28 (7) (2013) 1509–1518. [63] T. Oh, S. Tanaka, T. Naka, S. Igawa, Effects of high-intensity swimming training on the bones of ovariectomized rats, J. Exerc. Nutr. Biochem. 20 (3) (2016) 39–45. [64] S. Terada, I. Tabata, Effects of acute bouts of running and swimming exercise on PGC-1alpha protein expression in rat epitrochlearis and soleus muscle, Am. J. Physiol. Endocrinol. Metab. 286 (2) (2004) E208–E216. [65] L. Zhang, X. Chen, J. Wu, Y. Yuan, J. Guo, S. Biswas, et al., The effects of different intensities of exercise and active vitamin D on mouse bone mass and bone strength, J. Bone Miner. Metab. 35 (3) (2017) 265–277. [66] R.K. Globus, E. Morey-Holton, Hindlimb unloading: rodent analog for microgravity, J. Appl. Physiol. (1985) 120 (10) (2016) 1196–1206. [67] M. Weinreb, G.A. Rodan, D.D. Thompson, Osteopenia in the immobilized rat hind limb is associated with increased bone resorption and decreased bone formation, Bone 10 (3) (1989) 187–194. [68] A. Sakai, T. Nakamura, H. Tsurukami, R. Okazaki, S. Nishida, Y. Tanaka, et al., Bone marrow capacity for bone cells and trabecular bone turnover in immobilized tibia after sciatic neurectomy in mice, Bone 18 (5) (1996) 479–486. [69] B.S. Katkovskiı˘, V.S. Georgievskiı˘, G.V. Machinskiı˘, V.M. Mikhaı˘lov, D. Pometov Iu, Some physiological effects caused by 30 days of bed rest in different body positions, Kosm. Biol. Aviakosm. Med. 14 (4) (1980) 55–58. [70] A.R. Hargens, L. Vico, Long-duration bed rest as an analog to microgravity, J. Appl. Physiol. (1985) 120 (8) (2016) 891–903. [71] A.D. Leblanc, V.S. Schneider, H.J. Evans, D.A. Engelbretson, J.M. Krebs, Bone mineral loss and recovery after 17 weeks of bed rest, J. Bone Miner. Res. 5 (8) (1990) 843–850.

Chapter 3

The whole bone mechanical properties and modeling study Kang Rua, Raees Fida Swatib, Hanrou Zenga, Zarnaz Khana, Zhihao Chena, Airong Qiana, and Lifang Hua,* a

Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China, bInstitute of Space Technology, Islamabad, Pakistan * Corresponding author.

3.1

Introduction

Bone tissue is mainly composed of cortical bone and trabecular bone. Cortical bone has a special hierarchical structure, which allows it to have both the toughness of organic materials and the strength of inorganic materials, which is the fundamental reason for its excellent mechanical property. The trabecular bone is composed of many irregular lamellar or needle-like trabeculae intertwined with each other in an irregular porous structure. As a loose and porous material, the overall mechanical property of trabecular bone is closely related to the trabecular morphology, the arrangement, and the number of trabeculae. In general, the trabecular morphology varies between plate and rod shapes, and there is no uniform pattern of shapes. Trabecular bone structure is neither completely regular nor completely random. For example, the trabeculae of a particular direction corresponds to the corresponding stress direction. Since the femur bone is the main study area for biomechanical engineers, fracture analysis is an important mechanical aspect of the study. Fracture is the separation or fragmentation of a body into two or more pieces in response to imposed stresses that may be static or varying with time and at temperatures relative to the material’s melting temperature. Stresses applied in the material resulting in fracture may be compressive, tensile, shear, or torsional. There are six types of femoral fracture: femoral head fracture, femoral neck fracture, intertrochanteric fracture, sub-trochanteric fracture, femoral shaft fracture, and distal femur fracture. There are many causes of fracture/failure occurrence in engineering machines, such as stress concentrations, stress variations, and Bone Cell Biomechanics, Mechanobiology, and Bone Diseases. https://doi.org/10.1016/B978-0-323-96123-3.00012-9 Copyright © 2024 Elsevier Inc. All rights reserved.

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dislocation of joints. There are many numerical analytical techniques to study various mechanical aspects like displacements, stress variations, and so on, as well as to study biomechanical systems on 3D computational models of physical bodies. However, the finite element method (FEM) is one of the most commonly used and widely accepted techniques for biomechanical analysis of any body organ of different species of animals having complex geometries, such as human bone structure. It is also used to study structural analysis, heat transfer, fluid flow, and more on mathematical and engineering models. FEM is based on computers and programming. A special branch of FEM to study complex structural geometries and their biomechanical analysis is the extended finite element method (XFEM), which is a sub-module of FEM specially developed to treat discontinuities, cracks, and different microphenomenon structures. Specifically, the bone structure of mammals has many small discontinuities and complexities in its structure that are sometimes difficult to cater to a 3D model. Moreover, these complexities in bone structure, despite being minute in appearance, can have significant effects on biomechanical analysis of the bone and cause variations in stress due to their response to different loading conditions. For this reason, XFEM is an excellent choice for the biomechanical analysis of the bone structure of the femur bone.

3.2 Mechanical properties of cortical bone 3.2.1 Basic variables and values Cortical bone has a six-level hierarchical structure from macroscopic to microscopic, as shown in Fig. 3.1. The levels are bone tissue, bone units (scale of 10–500 μm), lamella, mineralized collagen fiber bundles (scale of 1–10 μm), mineralized collagen fiber molecules (scale of several hundred nanometers to 1 μm), and collagen fiber molecules and mineral microcrystals [1]. The laminar structure of cortical bone endows it with excellent mechanical property. The laminar structure of cortical bone with compatible mechanical property was first proposed by Katz in 1970 [2] and subsequently developed by Rho and Hoffler et al. [3], which gradually formed the correspondence between the laminar structure and the corresponding mechanical property, as shown in Table 3.1.

FIG. 3.1 Six-level hierarchical structure of cortical bone.

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TABLE 3.1 Determinants of cortical bone hierarchical structure and corresponding hierarchical property. Dimensional range

Specimen form

Main determinants of bone mechanical property

Osteopathy

Femur, tibia, vertebrae, etc.

Bone shape, cross-sectional area, porosity degree, etc.

Tissue levels

Cortical bone masses, columns, rectangular blocks, etc.

Bone density, porosity, bone unit orientation, collagen fibers, etc.

Microscopic level

Bone units, bone trabeculae

Loading direction

Submicrostructure

Bone plates, collagen fiber bundles

Optimal selection of collagen fiber molecular bundles orientation

Nanoscopic structure

Mineralized collagen fiber molecules and components

Hydroxyapatite fraction, collagen fraction

As a natural multilayered biomaterial, most of the research on bone in the field of mechanics focused on the structure of bone at different scales or the deformation, fracture, and failure behavior of the material under load, and the constitutive relation between structure and property. The mechanical property of bone can be obtained directly from the micro/macroscopic level by using conventional mechanical property of materials testing means. The equivalent material structure may be studied for composites or hybrid structures based on the engineering variables.

3.2.2

Strength of cortical bone

Strength is defined as the ultimate stress that the structure can bear before failure, which is the maximum stress in the stress-strain curve (Fig. 3.2) [4,5]. Since the main cause of fracture is the inability of the bone itself to resist the load from outside, clinical assessment of bone strength is often used to predict a patient’s fracture risk [6]. Understanding the major factors affecting bone strength is important for accurately assessing fracture risk and monitoring associated bone disease outcomes. The stress-strain relationship may be studied using Hooke’s/ generalized Hooke’s law and the trend may be compared with the equivalent proposed material. The factors affecting bone strength are complex but can be summarized into two types: geometric morphological characteristics and compositional characteristics [7]. Among the geometric morphological features are the bone’s size, shape, and structural features. An increase in bone length, cross-sectional area, and cortical bone thickness leads to an increase in overall bone size. Bone size

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FIG. 3.2 Stress-strain curves for cortical bone tested along the longitudinal direction.

and shape are important factors affecting bone strength; generally, larger-sized bones correspond to relatively greater bone strength [8]. Cortical bone thickness and porosity are important factors in determining the strength of cortical bone, and these two factors are closely related to mechanical stimulation. The crosssectional area and thickness of cortical bone in mice under mechanical unloading (hindlimb unloading [HLU]) conditions are significantly reduced (Fig. 3.3). At the same time, the increase in osteoclast resorption causes the expansion of the Haver’s canal, resulting in the formation of larger pores. As a result, the volume fraction of cortical bone is reduced, leading to a decrease in the mechanical property of cortical bone [9,10].

FIG. 3.3 Femoral cortical bone thickness in mice under mechanical unloading. Con, control; HLU, hindlimb unloading. Bar: 100 μm.

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Tensile tests can accurately describe the strength and stiffness property of bones. By performing tensile tests on bovine cortical bone, Fyhrie et al. found that the yield strength and ultimate strength of cortical bone were highly correlated with its stiffness [11]. Wahab et al. used tensile tests to analyze the anisotropic viscoelasticity of cortical bone and found that different anatomical locations had different mechanical property, with higher axial strength than transverse strength in the same anatomical location [12]. Gupta et al. performed in situ tensile mechanical tests on cortical bone specimens at the nanoscale using a ray diffraction synchrotron device and found that the heterogeneity of cortical bone deformation was composed of tensile deformation of collagen and shear deformation of the interfibrillar matrix [13].

3.2.3

Young’s modulus/modulus of elasticity

Bone materials deform elastically when a small load is applied in compression or tension, and the elastic deformation is reversible. The stress-strain curve is linear as the stress and strain approach zero, and Hooke’s law describes the relationship between stress and strain, which states that stress is proportional to strain. The scale factor is Young’s modulus (Fig. 3.2). The greater the modulus, the greater the stress required to produce the same amount of strain. The Young’s modulus of bone (human femur, 18 GPa in tension) is between that of hydroxyapatite and collagen fibers, but the material’s mechanical property is better than both. This allows it to avoid both the brittle damage of hard materials and the premature yielding of soft materials [14,15]. Since the elastic modulus of bone is affected by its porosity, many researchers have investigated the relationship between the elastic modulus of bone and its porosity. Mackenzie proposed an equation to describe the relationship between the elastic modulus of bone and its porosity [16]. The mathematical equations describing and representing the Young’s model, mineralizational degree and the respective ratios in bone mechanics are given below (Eqs. 3.1–3.4).
E ¼ E0 1  1:19P + 0:9P2 (3.1) where E is the measured Young’s modulus, E0 is Young’s modulus of dense bone without porosity, and p is the volume fraction of porosity. For dense bone with 5% porosity, Young’s modulus E0 of dense bone without porosity is 10% greater than Young’s modulus E of the measured bone. For dense bone with 10% porosity, E0 is about 22% greater than E. Jager et al. proposed a composite model of bone with interleaved mineral crystals and collagen, where the reinforcing phase is mineral crystals and collagen is used as the matrix. The mineralization degree Φ is defined as ld (3.2) Φ¼ ðb + d Þðl + aÞ

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where a is the amount of overlap between the crystal sheets, b is the transverse distance between the crystal sheets, and l and d represent the geometric dimensions of the mineral crystal sheets. The modulus of elasticity is considered a combination of four different regions: tensile regions A and B, and shear regions C and D (Fig. 3.4) [17]. Considering these four regions, the relative Young’s modulus can be expressed as: E0 ¼ E=EC ¼ E1 + E2 + E3 + E4

(3.3)

where, EC is Young’s modulus of collagen, E1–E4 are regions A–D’s contribution to the overall modulus. This leads to: E d ð l + aÞ + ¼ EC ab

  l γ ðl  aÞðl + aÞ γaðl + aÞ 1+ + + 2 2a 2bð2b + aÞ 4b

(3.4)

In the formula, γ is the relationship between the shear modulus and Young’s modulus. Because the axial period size of the collagen fiber structure is 67 nm, given below as Eq. (3.5). γ ¼ ða + lÞ=2 ¼ 67 (3.5)

FIG. 3.4 Two adjacent elementary cells of the staggered model showing the regions of tensile (regions A and B) and shear (regions C and D). (A) the amount of overlap between the crystal sheets, (B) the transverse distance between the crystal sheets, l and d: the geometric dimensions of the mineral crystal sheets, A and B: tensile regions, C and D: shear regions.

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Assuming a typical thickness of the mineral crystal sheet d ¼ 3.5 nm and a fixed degree of mineralization Φ, Young’s modulus of collagen Ec ¼ 50 MPa can predict the relative Young’s modulus E0 . The elastic modulus of cortical bone under tensile and compressive loading is different [18,19]. The compressive strength of cortical bone is usually greater than its tensile strength [20]. Cortical bone can dissipate more energy through permanent and viscoelastic deformation under compressive loading than under tensile loading [21]. Nyman et al. used a three-point bending test to investigate the mechanism of the effect of water on cortical bone strength and toughness and found that water loss in collagen fibers decreased cortical bone toughness, while mineral water loss decreased cortical bone strength and toughness [22]. Keller et al. conducted experiments and found a strong correlation between human cortical bone flexural strength and bone tissue’s apparent density [23]. Steele et al. measured the flexural stiffness and bone mineral content of monkey tibiae and found that their tibial flexural strength correlated with their mineral content in cross-section, with flexural strength decreasing by 12%–22% when mineral content decreased by 17%–24% [24].

3.2.4

Micro and nanoscale property of cortical bone

With the advancement of experimental techniques and research tools, the study of bone mechanics has gradually advanced from the macroscopic level to the micron and nanoscale levels. Ortiz et al. used the nanoindentation technique to investigate individual mineralized collagen fiber molecules and found that stiffness changes were associated with local structural and component changes and that nanoscale inhomogeneities promoted energy dissipation in cortical bone [25]. Wagner et al. performed a nanoindentation probe of the elastic modulus variation of different bone plates of a single bone unit and showed that the bone plates close to the Haver’s canal in the longitudinal plane had a greater elastic modulus and no significant elastic modulus variation was found between different bone plates in the transverse plane. Asymmetry was found in the relative positions of the Haversian canal, thus demonstrating the structural anisotropy of the bone plate [26]. Gupta et al. performed in situ tensile mechanical tests on cortical bone specimens at the nanoscale using a ray diffraction synchrotron device. It was found that the inhomogeneity of cortical bone deformation was caused by the tensile deformation of collagen and the shear deformation of the interfibrillar matrix [13]. It can be found that the structural and mechanical property of bone at all scale levels from macroscopic to microscopic levels have been extensively and carefully investigated using mechanical means. It would be more appropriate to integrate both clinical and biomechanical approaches to study the mechanical property of bone and the effects of osteoporosis on bone mechanics.

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3.3 Mechanical property of trabecular bone 3.3.1 Trabecular bone structure and mechanical property Trabecular bone is composed of many irregularly interwoven trabecular bones with irregular porous structures. Due to this porous structure, the surface area of trabecular bone is 10 times larger than that of dense bone, although the weight of trabecular bone is only 20% of the total weight of bone. The simplest form of trabecular bone can be divided into three categories. The simplest form of trabecular bone is a mesh structure made of many small rods (trabeculae or columns) with a diameter of about 0.1 mm and a length of 1 mm arranged according to a certain pattern. It can be changed into a second structural form, that is, a part of the small rods are replaced by small plates, forming a trabecular bone mainly of small plates. In the third type of trabecular bone, its small plates are longer and can reach several millimeters and its arrangement is somewhat directional, with some parallel bone plates linked by small rods whose direction is perpendicular to them. There are also other trabecular bones composed entirely of bone plates. Under light microscope, trabecular bone consists of several parallel layers of bone plates and osteoblasts (OBs) that form a thin lamellar structure. The bone trabeculae are covered with endosteum formed by OBs, and the bone marrow cavity between the trabeculae is filled with blood cells, bone marrow stromal cells, and adipocytes. The bone traps occupied by osteocytes were distributed within and between the bone plates, and the nuclei of osteocytes were visible in the bone traps. Trabecular bone is structurally characterized by many interconnected trabecular networks; therefore, the geometric parameters, chemical composition, and mechanical property of individual trabeculae must be known before the overall structural-mechanical property of trabecular bone can be assessed. The geometric parameters of bone trabeculae include thickness, gap, specific surface area, connectivity, structural model index, and anisotropy of bone trabeculae [27]. The advancement of imaging techniques such as micro computed tomography (micro-CT) enriches the geometric parameters of bone trabecular structures. In micro-CT, the measurement method is extended from 2D images to 3D space, and the parameter analysis is transformed from qualitative description to quantitative measurement [28]. The use of morphological parameters to quantitatively describe the structure of bone trabeculae facilitates the analysis of the structural characteristics of bone trabeculae. Hildebrand et al. proposed the calculation of the structural model index to describe the changes in trabecular structure and concluded that the structural model index changes significantly when the plate beam is transformed into a columnar beam, which makes it more prone to fractures and other diseases [29]. In addition to the objectives of quantitative representation of the structural state of bone trabeculae such as thickness and gap, the structural orientation and

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fluid flow of bone trabeculae also need to be measured, thus introducing the calculation of connectivity and anisotropy measurements. Compston proposes an alternative method of “skeletonization” that does not take into account the thickness of the trabeculae, but rather only shows the connectivity, resulting in a change in the connectivity of the trabeculae within the bone [30]. Hahn et al. used the pattern factor method to measure the connectivity of trabeculae bone, but with the in-depth study of the connectivity of bone trabecular structures, it was found that the pattern factor method was more suitable for histomorphometry measurements of 2D images and could not establish the relationship with 3D structural changes [31]. With the development of 3D somatotopic techniques, the topological tree model with Euler number as the variable was proposed and applied to the quantitative analysis of bone trabecular connectivity. In addition, anisotropy is informative in determining the decrease in mechanical property of bone tissue due to structural changes in bone trabeculae. Lenthe et al. used mean intercept length (MIL) algorithm to measure the degree of anisotropy of bone trabeculae based on 2D images [32]. Tabor et al. used a 3D MIL algorithm to calculate and measure the degree of anisotropy of trabecular structures, providing a basis for studying the directionality of trabecular structures and the design of implant structures [33].

3.3.2

Strength of trabecular bone

Strength is defined as the ultimate stress that the structure can bear before failure, which is the maximum stress in the stress-strain curve. Studying the strength of trabecular bone is important since it can be related to bone fracture and damage [4]. Bone strength is determined by “bone volume” (generally reflected by bone mineral density [BMD]) and “bone quality.” Bone quality includes both bone metabolism and microarchitecture [34]. With the widespread application of 2D and 3D image morphometrics in micro-CT, numerous new quantitative parameters for bone mass and bone microarchitecture have been introduced [35]. For example, the values of BV/TV and bone trabecular thickness (Tb.th) decrease under mechanical unloading [36]. The structure model index (SMI) is used to define whether the trabecular shape is close to a plate shape or a rod shape. The SMI value is defined as 0 for plate-like structures and 3 for rod-like structures and usually varies between 0 and 3 for trabecular bone in selected areas. There is a tendency for the SMI to increase, for the bone resorption rate to become higher, and for the plate-like trabeculae to change to rod-like trabeculae under constant conditions [29]. The trabecular bone score (TBS) is a recently developed parameter for characterizing bone microstructure, which uses the average fluctuation of the gray scale of a 2D planar projection image to characterize the quality of bone microstructure. TBS has been proposed to be synergistic with BMD to improve the diagnostic accuracy of osteoporosis [37]. In addition, there are parameters characterizing the microstructure such as specific surface area

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FIG. 3.5 Changes in bone microstructure of mouse femur under mechanical unloading conditions. Con, control; HLU, hindlimb unloading. Bar: 100 μm.

(BS/BV), bone trabecular spacing (Tb.Sp), and so on [38]. Fig. 3.5 represents the changes in trabecular bone microstructural parameters in mice under mechanical unloading.

3.3.3 Young’s modulus of trabecular bone Young’s modulus or modulus of elasticity (E) of trabecular bone, a typical porous material, can be predicted by the law of proportionality proposed by Gibson and Ashby with the following in Eq. (3.6) [39]: E=ES ¼ CE ðρ=ρs Þ2

(3.6)

Here, E is the overall modulus of elasticity of the material and ρ/ρs is the relative density. CE is a dimensionless factor usually influenced by the material’s morphology, anisotropy degree, topological property, and so on. Young’s modulus can vary up to 100 times within a single epiphysis, and strength can vary up to 5 times [40]. These changes in density and structure lead to heterogeneity in the apparent elastic and strength property of trabecular bone [41]. The yield strain of trabecular bone exhibited only a weak dependence on apparent density and volume fraction. For human vertebral trabecular bone, the compressive yield strain increases slightly with increasing density, and for denser trabecular bone, the compressive yield strain does not depend on density. Thus, describing the yield property of trabecular bone in terms of strain rather than stress can provide a greatly simplified picture of tissue damage since strain-based damage criteria may not need to account for interspecies differences in apparent density. Trabecular bone has creep property similar to those of cortical bone. It exhibits an initial rapid increase in strain, followed by a steady state with a constant creep rate, and finally another rapid increase in strain before creep fracture [42].

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Micromechanical property and structure of trabecular tissue

Due to the development of high-precision μCT scanning technology, various characteristic parameters of trabecular bone microstructure can be easily obtained. The combination of μCT scanning technology with traditional methods of mechanics provides a powerful tool for the study of the “microstructuremechanical property” of trabecular bone. Through analysis of μCT data and mechanical testing techniques of materials, Ciarelli et al. comparatively studied the property of trabecular bone at the anterior femoral segment in women with a history of hip fracture, respectively. They found that the experimental group with hip fracture had a lower modulus of elasticity compared to the healthy control group [43]. In addition, the combination of μCT scanning technology and the finite element methods (FEM) provides a more convenient and powerful tool for studying the “microstructural-mechanical property” of bone. Biomechanical modeling simulation combining μCT scanning technology with FEM is also accepted and adopted in orthopedic clinics and is slowly becoming one of the most popular research areas today [44,45]. Stauber et al. used basic unit classification to divide the bone trabecular composition into basic rod units and plate units and then performed finite element computational analysis [46]. By comparing 328 sets of clinical CT data, it was concluded that in the part of trabecular bone dominated by plate units, the strength of the bone was mainly related to the property of the plate units. In the part of bone dominated by rod units, the combination of rod units determines the overall mechanical property of the bone. Liu et al. also used scanning combined with FEM to systematically investigate the local microstructure of trabecular bone [47,48]. It was found that the proportion and orientation of rod-like trabeculae in trabecular bone significantly affect the overall mechanical property of the bone. This finding corrects the previous study that rod-like trabeculae, which are usually considered to account for a relatively small volume in many parts of the bone tissue, are among the structures that have less influence on the overall mechanical property of bone. By combining clinical data from the human spine, the transverse and axial rod trabeculae determine the overall modulus of the bone, while the axial rod trabeculae only affect the axial modulus of the bone. Wang et al. studied the effect of metabolic behaviors such as bone remodeling on trabecular bone microstructure and mechanical property by simulation [49,50]. The combination of μCT scanning technology and mechanical research test methods allows for a clearer and more intuitive study of the mechanical property of bone. In addition, OC-dominated bone resorption can occur on the trabeculae’s surface, resulting in numerous bone resorption pockets. In cases of severe bone resorption, penetration holes may also form. Bone resorption fossae are usually described as deep, discrete, rounded fossae, or sometimes as long, hollow grooves. These resorption foci often extend in the direction of collagen fibers. In those uninterconnected trabeculae bones, OC-dominated bone resorption does not cause bone formation, even if it occurs. Therefore, if the connectivity of the trabecular network structure is lost, bone loss, in this case, would be irreversible.

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3.4 Three-dimensional bone models and techniques in biomechanics This section analyzes the semi-crystalline advanced polymers polyetheretherketone (PEEK) and hydroxyapatite-polyetheretherketone (HA-PEEK) using ANSYS static structural module. The femur bone is expected to have isotropic direct versatile material property. The property of PEEK, HA-PEEK, and human femur bone as shown in Table 3.2. The materials used in all biomimetic structures are silicon carbide and graphite, often used in synthetic composite materials. The human femur bone framework is initiated by taking CT images from a literature review and using Creo (computer-aided design software) to design a 3D solid model, as shown in Fig. 3.6. The model is hence imported into a finite element analysis (FEA) software package through a mechanical workbench to perform an FEA and sectioned the bone in the design modular interface, as shown in Fig. 3.7. For the sake of better visualization of the model it is very clear for the type of loading applied in Fig. 3.7A stance configuration, for the other side as Fig. 3.7B trochanter configuration, and Fig. 3.7C sideways. The modeling is conducted using a different approach and another bone model. A procedure for the high-resolution model for the femur is obtained

TABLE 3.2 Mechanical property exhibited by human bone, PEEK, and HA-PEEK. Property

Human bone

PEEK

HA-PEEK

Young’s modulus (GPA)

2.13

3.2

6.8

Poisson’s ratio

0.3

0.42

0.38

2000

1291

1851

3

Density (kg/m )

FIG. 3.6 Femur model for FEM evaluation in FEM analysis package ANSYS 16.0.

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FIG. 3.7 Loading applied in (A) stance configuration, (B) trochanter configuration, and (C) sideways.

from different optimized models [51,52] developed from CT images as discussed in previous sections. The geometry needs to be cleaned in CATIA V5 which finally is converted into a solid body using SpaceClaim, as shown in Figs. 3.8 and 3.9 as a solid model.

3.5

Finite element analysis (FEM) for bone analysis

FEM is used tonumerically analyze structures of complex geometries with different loadings and boundary conditions . In these methods, the basic purpose is to simulate the actual process by utilizing a mathematical equations and techniques. It is very helpful for engineers because they can apply FEM to minimize

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424.223 mm

FIG. 3.8 Surface geometry of the femur model for solid shape generation.

FIG. 3.9 Volumetric solid bone model and initial modeling scheme.

the count of actual design models and perform indirect investigations to improve their designs. It proves to be the prime technique in which complex mathematical equations are involved. In FEA, the problems related to structures interconnected with aerospace and mechanical engineering can be modeled very efficiently. Finite element modeling is considered a very effective tool for vibrational analysis because it considers both static and dynamic loading conditions. Before performing the stress analysis of the human femur bone, it has been presumed that the femur is an isotropic and homogenous material. A middle-aged person 40 years of age weighing 85 kg is discussed and examined here for the analysis. The homogenized values from the literature for femur property is characterized by a Young’s modulus of 2.13 GPA, a Poisson’s ratio of 0.3, and a density of 2000 kg/m3.

3.5.1 Meshing Before meshing, there are some settings in the FEM software package to obtain the required mesh and optimized values for better computation. The geometry of the femur is meshed with an element size of 5 mm and the element order to be kept quadratic. The total number of nodes and elements after meshing are 19,876 and 11,206, respectively (see Fig. 3.10).

3.5.2 Boundary condition After meshing the bone model, the next step is to apply the necessary boundary conditions. First, the lower end of the femur bone is taken as a fixed support.

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ANSYS

R19.2

X Z 0.00

200.00 (mm)

100.00 50.00

150.00

FIG. 3.10 Meshed geometry of 3D bone model.

A: Static Structural Fixed Support Time: 1. s 26/04/2021 6:58 am Fixed Support

Z X

0.00

300.00 (mm)

150.00 75.00

Y

225.00

FIG. 3.11 Bone model with fixed support.

Then, any value of pressure (e.g., 750 Pa) [24] that is a compressive load and uniformly distributed is applied at an angle of 30 degrees (see Figs. 3.11 and 3.12). The application of boundary conditions and load calculation is already explain in previous sections. The elastic property is orthotropic, changing along the radial, circumferential, and longitudinal directions (see Fig. 3.12). It is thus necessary to define the element coordinates as cylindrical instead of Cartesian as shown. For this analysis, the bone is modeled as a single homogeneous orthotropic mass, with the property of cortical bone tissue as shown in Fig. 3.13 adjusted in software interface.

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A: Static Structural Pressure Time: 1. s 26/04/2021 6:49 am

X

Z

Y

Pressure: 7.5e-004 MPa Components: 0.,0.,-7.5e-004 MPa

0.00

150.00 75.00

300.00 (mm) 225.00

FIG. 3.12 Bone model with pressure load applied at femur head with a magnitude of 750 Pa.

FIG. 3.13 Properties of orthotropic homogeneous bone in FEM software package interface.

3.5.3 Boundary condition and mesh A simplified muscle profile was developed in different studies [53–56] for understanding the method. For the initial study, the bone profile is applied with three forces and displacements as boundary conditions, primarily added up from 46 muscle forces, making up the in vivo hip loading that occurs during walking. The coordinate system has been modified according to the one established by Bergmann. The modeled structure of bone with boundary conditions are shown for the sake of better idea, as fixed supports and structure is shown for types of coordinate systems (see Fig. 3.14).

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FIG. 3.14 Coordinate systems in modeling the 3D model global (Cartesian) and local coordinate systems.

FIG. 3.15 Representation of 3D mesh characteristics and elements

In the following example of 3D modeling and design for the sake of understanding, the value of mesh is quadratic with a 6-mm element size, and finer 3-mm elements near the head and similar mesh may be applied accordingly as shown in Fig. 3.15.

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3.6 Methods for biomimetic study 3.6.1 Biomimetics Generally, nature solves its problems not by conscious decision-making to meet functional requirements as a scientist might but by evolving structures with extraordinary capabilities and unique functions that perfectly fit the task at hand. These structures are flawlessly built to specification with very limited and seemingly mundane materials, in ambient temperature and pressure, and are then “market tested” quite extensively over millions of years. The methods and principles behind biological materials can be extracted and applied to the design and optimization of engineering materials [57]. This is a fruitful area of research and can pave the path to creative and cost-effective solutions to many problems. There are three main areas of biomimetics engineering: (1) structural materials that support loads and transmit forces and have properties such as strength, toughness, and stiffness (e.g., bone, nacre, etc.); (2) functional materials have certain unique functions or features such as self-cleaning, self-healing, and stressresponsive materials; (3) the processes and procedures by which these materials are fabricated. This research focuses on structural biomimetic materials. Structural materials found in nature have excellent mechanical property. This is not due to the processes that form them, but rather to their unique microstructures. Some examples are bone, enamel in teeth, spider silk, and so on. The structures of biological materials are different from industrial ones, mainly in that they are multiscale. This means that they are constructed at different organized scale levels, with each scale exhibiting a distinct, translatable property. The overall interaction of characteristics at every length scale produces the final material property. The multiple hierarchical levels activate different strengthening and toughening mechanisms at each length scale, from nano to macro, dramatically enhancing damage resistance.

3.6.2 Multiscale modeling Multiscale modeling helps us explain the upper-scale behavior of materials based on lower-scale physics. Complex lower-scale processes have nonlinear effects, which propagate through the scales. However, conventional multiscale approaches require heavy computational resources. For this purpose, we use multiscale algorithms that accurately introduce coupling between the macro and microscales, without having to model each level physically. There are two approaches to multiscale modeling using FEA. The first is the top-down or “global-to-local” approach [58]. In this method, the body’s structure is analyzed and the critical damage regions are identified. Refined analyses of these regions are then carried out using smaller, more detailed, usually phenomenological models. The FEA of the structure provides the driving boundary conditions for the next models, but the property of the materials need to be known.

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The other approach is more novel and is known as the bottom-up approach. The start here is to model a representative volume element (RVE) representing the smallest repeatable unit cell that builds up the entire microarchitecture. Fiber and matrix/phase property are known through experiments. This analysis is built upwards to component levels.

3.6.3

Homogenization

The underlying principle in multiscale infrastructure is information being translated coherently between each length scale. However, assembling the microstructure to the component level is impossible in most cases. Homogenization provides us with a way to bypass this. Through homogenization, the actual heterogeneous microstructure is replaced by an equivalent continuum, a material in which matter is uniformly distributed, greatly simplifying the analysis [59]. Thus, with homogenized data only the macroscopic scale needs to be simulated. For this technique, an RVE is considered. The RVE is a unit cell uniformly repeated over the domain of an entire structure. It is the smallest volume representative of the structure at a particular scale, and the constitutive property of this volume can characterize the whole domain. The goal is to determine the effective elastic property of the RVE, which can then be used as a material property in larger structures.

3.6.4

Top-down method

There are two main approaches to multiscale modeling. The global-local approach begins with the macrostructure and moves down to smaller components. For example, the earlier heterogeneous femur model is used to analyze an artificial femur model constructed of a standard honeycombswashplate structure. The results of that analysis would provide the boundary conditions to be used for subsequent, smaller-scale models. Following the simulation results of the bone, an area of high stress, where damage is likely to occur, can be extracted for analysis as a separate gauge length (see Fig. 3.16). There are limitations to this approach. For one, the phenomenological models used in the top-down approach lack accuracy and may not depict some aspects of material failure. This also limits the use of any results in further studies. Also, for this approach, the full material constituency for the component and part-level structure is needed before analysis can be performed. In terms of meshing, mesh generation is a difficult process and geometry sometimes needs to be simplified to reduce computational requirements, at the expense of accuracy.

3.6.5

Bottom-up method

The bottom-up method is a more novel approach with different computational advantages. Multiscale modeling is carried out by homogenizing constitutive

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FIG. 3.16 A honeycomb material applied to a gauge length of the femur diaphysis.

property from the RVEs of individual components at their relevant length scales and building up the simulation to determine behavior at larger scales. The homogenized material is assumed orthotropic, implying that there is no interaction between the normal stresses σ x, σ y, σ z and the shear strains εxy, εyz, εzx. Thus, the nine elastic constants of an orthotropic stiffness matrix need to be found. These are the three Young’s moduli Ex, Ey, Ez, the three Poisson’s ratios νxy, νyz, νzx, and the three-shear moduli Gxy, Gyz, Gzx. To determine the nine independent coefficients, six independent load cases are required. These consist of three mutually perpendicular tension/compression tests, and three mutually perpendicular pure shear tests, both performed in the XY, YZ, and ZX planes. After applying loads using an FEA package, the directional stress is found from forces and the directional strains are found from deformation. These are then used to calculate the orthotropic coefficients using the following equations (Eqs. 3.7–3.9): σ ii Fii =A ¼ εii Δxi =li εii νj ¼ εij

Ej ¼

(3.7) (3.8)

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Gj ¼

τij T ij =A ¼ γ ij Δxi =lj

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73

(3.9)

where Fii is the normal force, Tij is the shear force, γ is shear strain, A is the projected area, Δx is elongation, and l is the reference length. Thus, the bottom-up approach is a well-established method that represents an effective strategy for simulating engineering materials’ structure, property, and performance. It can capture, in turn, the different failure micromechanisms that occur at every level and their complex interactions. This method is easier to carry out and is significantly less computation and memory intensive than its counterpart. Only the fiber and matrix phase properties are required for homogenization, which are easily obtainable. Furthermore, studies are being done to improve efficiency further. This approach is utilized in the rest of this section for its convenience and effectiveness.

3.7

Development of representative volume element

The biomimetic theory has long been applied to optimize structural designs and propose new ones. In this section, we investigate different biomimetic materials. It is essential to understand and identify structure-property relationships when learning from natural materials. The features that cause certain desirable properties can then be abstracted from the natural model and successfully implemented into engineering design. Desirable properties for high-performance structural materials include strengthening, stiffening, and toughening mechanisms, energy dissipation, and structural features that allow light weight. In this section, several structure-property models with pertinent biological design features have been homogenized and applied to the heterogeneous femur model for analysis. A parametric study was carried out. RVE dimensions are all kept in mm to keep the designs manufacturable. For comparison, the matrix phases are all defined as graphite, and the reinforcement phases are silicon carbide (SiC). SiC is hard and provides excellent wear resistance, whereas graphite is softer and used for lubrication, flexibility, and toughness. These materials have been used frequently in synthetic composites [60]. The RVs have been altered in scale, and volume fractions where appropriate, to see the effect of scale on results. All meshing on RVs is periodic and conformal.

3.7.1

Honeycomb composite

Honeycombs make very efficient use of space in the construction of materials. Reinforced materials have considerably enhanced robustness while keeping the weight at a premium. Honeycomb lattices have low density and low stiffness and large deformation under pressure, making them good energy absorbers when applied to components like car bumpers. As the hexagon cells collapse under great loads, either by buckling or fracture, they dissipate energy,

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protecting the vehicle. Thus, metal honeycomb structures are frequently used in the automotive industry. They are also widely used in the aerospace and civil aviation industries. It has been shown that desirable properties can be introduced into lattice structures by altering unit cells or adding structural hierarchies at different length scales. The structure of honeycombs resembles the porous structure of spongy bone tissue.

3.7.1.1 Honeycomb-swashplate model Honeycomb-swashplate model: Synthetic honeycomb structural materials commonly have a honeycomb material sandwiched between two thin, stiff face sheets that provide strength in tension. This layered configuration of stiff plates with a viscoelastic material provides high energy absorption capability [61]. The sandwich plate model consists of two SiC layers with a thickness of 0.1 mm surrounded by a crushable graphite core, as shown in Figs. 3.17 and 3.18. The mesh model for Fig. 3.17A as RVE of the honeycomb-swashplate model and Fig. 3.17B for dimensions of the honeycomb-swashplate model. Table 3.3 shows the density and elastic property of the models described previously. 3.7.1.2 Spherical honeycomb Alternate honeycomb material spherical voids instead of hexagonal ones to figure out the comparative stress analysis. No plate stiffeners have been used. The RVE is a face-centered cubic cell with a graphite matrix and SiC spherical particles. The particles are hollow with a 1-mm diameter and 0.5-mm wall thickness. The volume fraction of the particles is altered to obtain different RVE properties and mesh, as shown in Fig. 3.19. Table 3.4 shows the density and elastic property of the models. a

b 1mm

Y 1.932mm Z

X

0.1mm

3.173mm

0.1mm

FIG. 3.17 (A) RVE of the honeycomb-swashplate model, (B) dimensions of the honeycombswashplate model.

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FIG. 3.18 Mesh of the model using 0.045-mm elements.

TABLE 3.3 Density and elastic property of the models. Scaling 3

Density (kg/m )

1×

0.8 ×

0.6 ×

838.75

838.75

838.75

E–X direction (GPA)

90.297

90.299

90.302

E–Y direction (GPA)

90.246

90.248

90.251

E–Z direction (GPA)

2.4553

2.4558

2.4565

ν–XY

0.16191

0.16191

0.16191

ν–YZ

0.10303

0.10327

0.10363

ν–XZ

0.10933

0.10964

0.10998

G–XY (GPA)

38.86

38.861

38.862

G–YZ (GPA)

0.50723

0.5075

0.50791

G–XZ (GPA)

0.57097

0.57124

0.5716

3.7.2

Nacre

Nacre is a biological ceramic found in the inner lining of the shells of many mollusks. It is a strong and resilient material with a pearlescent appearance that protects softer inner tissue. Supportive or protective structural materials in nature usually acquire their stiffness by incorporating mineral crystals into their soft organic matrices.

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FIG. 3.19 Mesh of the spherical honeycomb of volume fraction 0.4.

TABLE 3.4 Density and elastic property of the models. Property Volume fraction 3

Density (kg/m ) E–X, Y, Z direction (GPA)

Case 1

Case II

0.4

0.5

0.6

1578.5

1460.7

1342.7

24.169

ν–XY, YZ, XZ

0.22319

G–XY, YZ, XZ (GPA)

9.879

27.021 0.22951 10.967

Case III

31.448 0.228 12.125

Similarly, nacre consists of 95% of aragonite, a fragile bioceramic. Aragonite, a form of calcium carbonate, provides stiffness but is also very brittle. However, the nacre microstructure is arranged so that its toughness is around a thousand times greater than that of aragonite. Nacre is a laminate composite, structured like a brick-and-mortar arrangement, with roughly 0.5-μm thick aragonite platelet layers separated by 30-nm layers of a soft protein polymer. The roughness of the laminates, coupled with a natural waviness in their structure, allows the layers to interlock and induces adhesion between them, which affords the overall strength and flexibility of the structure. It is stiff (60–70 GPA) with high work to fracture (about 1.3 kJ/m2) and fracture toughness of 3–5 MN/m3/2.

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The brickwork structure and interlocking mechanism give nacre some impressive features, such as its ability to spread damage laterally and inhibit transverse crack propagation as well as being insensitive to internal defects. If strains are large enough, the interlocking of individual laminates causes them to respond to strain as a single continuous material. In addition, other strengthening mechanisms such as mineral bridging have also been proposed. The biopolymeric layer between platelets is soft, which provides flexibility and slows crack propagation while acting as a viscoelastic glue [62]. Nacre-like materials are useful in applications where protection or shielding is required, such as on ship hulls, as they can provide high impact resistance and enhanced energy dissipation to protect inner cargo from collision or shock and reduce fragment penetration. Another potential application of a translucent nacreous material is for supersonic aircraft canopies, where it can provide resistance to small objects or water droplets flying faster than sound without shattering. Nano roughness or nano asperities on the interface between layers of many laminate materials including nacre tablets provides another mechanism for strengthening and interlaminar locking. This prevents interfacial debonding, and sliding along the interface can account for a great deal of resistance to deformation in the overall structure, as shown in Figs. 3.20 and 3.21 where Fig. 3.21A shows the RVE of the interfacial interlocking model and Fig. 3.21B is a section of the interfacial interlocking model. Table 3.5 shows the density and elastic property of the models.

3.7.3

Euplectella aspergillum (sea sponge)

E. aspergillum is a sea sponge of great interest in materials engineering. It has a skeleton structure almost wholly made of silica, which is brittle, but it is arranged in a way that makes it a very tough material. Tiny structures called

FIG. 3.20 A transparent model showing nano asperities on the surface of nacre tablets.

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FIG. 3.21 (A) RVE of the interfacial interlocking model, (B) a section of the interfacial interlocking model.

TABLE 3.5 Density and elastic property of the models. Scaling 3

Density (kg/m )

1×

0.8 ×

0.6 ×

2964.4

2964.4

2964.4

E–X direction (GPA)

225.72

225.89

226.09

E–Y direction (GPA)

253.43

253.55

253.72

E–Z direction (GPA)

84.53

84.577

84.627

ν–XY

0.10922

0.10927

0.10933

ν–YZ

0.16137

0.161

0.16062

ν–XZ

0.15867

0.15843

0.15807

G–XY (GPA)

81.712

81.774

81.867

G–YZ (GPA)

34.342

34.359

34.389

G–XZ (GPA)

33.782

33.808

33.854

siliceous spicules are made of layered silica and organic phases. These spicules weave together into a very fine mesh, which provides tremendous rigidity to the nearly pure glass structure, allowing sea sponges to survive at great depths underwater. The interface material between silica layers arrests crack growth and gives the structure flexibility and toughness not found in glass rods of the length scale. A first RVE is made of SiC and graphite layers to simulate the silica-organic laminate.

3.7.3.1 Stiff walled model The RVE is made as a box-like construction, with crisscrossing walls acting as stiffeners for the design, as shown in Fig. 3.22 where Fig. 3.22A is RVE and Fig. 3.22B is sectioned model. Table 3.6 shows the density and elastic property of the models.

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a

0.06mm

3

79

b

0.025mm Y

Z

2mm

X

1mm

FIG. 3.22 RVE and dimensions of stiffness model. (A) RVE and (B) sectioned model.

TABLE 3.6 Density and elastic property of the models. Scaling 3

Density (kg/m ) E–X direction (GPA) E–Y direction (GPA) E–Z direction (GPA)

1×

0.8 ×

0.6 ×

849.4

849.4

849.4

36.928 6.3988 58.723

36.992 6.4068 58.766

37.08 6.4182 58.816

ν–XY

0.28677

0.28695

0.2871

ν–YZ

0.013916

0.013939

0.013967

ν–XZ

0.058454

0.058668

0.058842

G–XY (GPA)

2.6373

2.6408

2.646

G–YZ (GPA)

2.5292

2.5322

2.5369

G–XZ (GPA)

8.1833

8.2066

8.2428

3.7.3.2 Cubic lattice Another sea sponge-inspired material is a lattice structure. The RVE is cubic with side diagonal supports, as shown in Fig. 3.23. Table 3.7 shows the density and elastic property of the models and messed structure with listed parameters. 3.7.4

Spider silk fiber

Spider silk has tensile strength five times greater than steel and toughness around two to three times greater than synthetic polymers like nylon or

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FIG. 3.23 Mesh of cubic lattice model of volume fraction 0.1.

TABLE 3.7 Density and elastic property of the models. Volume fraction

0.3

0.2

0.1

Density (kg/m3)

789.75

526.5

263.25

E–X direction (GPA)

20.299

11.305

4.7442

E–Y direction (GPA)

19.052

10.339

4.2229

E–Z direction (GPA)

18.82

10.174

4.1422

ν–XY

0.022224

0.046966

0.076377

ν–YZ

0.26391

0.30795

0.34608

ν–XZ

0.28119

0.3367

0.3888

G–XY, YZ, XZ (GPA)

1.2442

0.69974

0.29219

Kevlar, while still being nearly as elastic as rubber (up to 300%). These outstanding properties render it a perfect model for high-performance fibers. In addition, the high resilience of spider silk allows spider webs to withstand massive impacts relative to size and completely dissipate impact energy [63].

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Spider silk, like other natural composites, has a hierarchical structure. At the macroscale, it exists as a fiber with weak skin holding circular filaments. The filaments are stuck together and aligned with the fiber axis. At the nanoscale, these filaments consist of strong peptide crystals acting as reinforcements, suspended in an amorphous mesh of softer spidroin protein chains. The amorphous chains are made of helical protein strands that can uncoil under tensile load, which is how the material gets its great extensibility. This interaction between hard crystalline segments and elastic semi-amorphous regions allows spider silk to have a perfect balance of high strength and high toughness, which is not found in even the most advanced engineering fibers [64]. The nanofilaments in the silk are bundled together. There is no slippage between the fibers due to protrusions along their lengths. However, under high shear stress, slipping between filaments occurs and dissipates energy, preventing bulk fracturing of the entire material. The RVEs were modeled as unidirectional composite materials with a graphite matrix and SiC fibers, as shown in Fig. 3.24 as meshed structure. The fiber volume fraction is kept at 0.9 because silk fibers should be bundled together without gaps. Material symmetry has been used in the YZ plane. Table 3.8 shows the density and elastic property of the models.

3.7.5

Comparison of biomimetic structures

In this section, we compare all the biomimetic structures used and analyzed so far (see Figs. 3.25 and 3.26). There is a statistical analysis of average equivalent

FIG. 3.24 Mesh of spider silk model.

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TABLE 3.8 Density and elastic property of the models. Fiber diameter (mm) 3

Density (kg/m )

0.5

0.3

0.1

3098.5

3098.5

3098.5

E–X direction (GPA)

404.89

404.77

404.92

E–Y direction (GPA)

222.95

223.66

223.72

E–Z direction (GPA)

222.89

223.63

223.69

ν–XY

0.16102

0.16131

0.16118

ν–YZ

0.19636

0.19503

0.19566

ν–XZ

0.1639

0.16257

0.16314

G–XY (GPA) G–YZ (GPA) G–XZ (GPA)

105.71 94.205 105.71

105.95 93.836 105.95

106.15 94.207 106.15

FIG. 3.25 Graph depicting equivalent stress on each model vs the scaling increase of each RVE.

stresses versus the scales for all the types we discussed. Every type exhibits particular application with respect to the size and strength which is shown and discussed. The average equivalent stress depends on the object’s geometry and the magnitude and direction of the forces applied. It does not, however, depend on the material property. As the geometry of the femur and load is constant across all models, the average stress is understandably very close for all. The microstructures of the individual RVE may account for slight differences. In

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FIG. 3.26 Graph depicting the correlation between average deformations due to applied stress, and the scaling factors of each RVE.

Fig. 3.25, stress values lie within a range of 12.5–13.5 MPa for five models. However, for the honeycomb-swashplate RVE, the stress value is 19 MPa. This is an outlier, possibly because the geometry of the honeycomb structure has a lot of corners and thus high-stress regions. There is little effect of scaling change on average stress, as structures are different only at the micro level. Average deformation is inversely proportional to the stiffness of each model. In Fig. 3.26, it can be seen that the spider silk model is by far the stiffest, closely followed by the interlocking and stiff-walled models, all having deformations less than 1 mm. This is due to their structure-strengthening mechanisms and perhaps also due to a higher concentration of SiC. Less stiff is the cubic lattice model, and the least stiff is the honeycomb-swashplate model, which is expected because honeycombs are meant to deform and dissipate impact energy. It is clear from the graph that simply scaling the model up or down, or changing fiber diameter in the case of spider silk, has a much smaller effect on its mechanical property than changing the volume fractions of subcomponents. However, volume fraction changes are very effective, as seen by the spherical honeycomb and cubic lattice trends.

3.8

Modeling and fracture analysis of bone and applications

Biomechanics is the study of the structure, function and motion of the mechanical aspects of biological system from molecules, proteins to cells and organs using the methods of mechanics. As we can see, the human body experiences different forces and stresses when performing different tasks or when confronted with injuries. Almost every field is interconnected, so biomechanic engineers study the human body for different fractures/injuries [65].

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The femur bone is the largest and strongest bone in the human body and thus is one of the major concerns and fields of study for biomechanic engineers to observe various mechanical phenomena (stress analysis, strain variations, etc.). The femur bone is divided into three parts: the upper extremity of the femur containing the head, neck, and two trochanters, the shaft, and the lower extremity. Its body is almost cylindrical. The lower extremity is somewhat cuboid in form and larger than the upper extremity. The femur structure consists of two layers: a dense outer layer also called cortical or compact bone, which prevents bending, and the inner portion, which is spongy and mainly resists compression. The major part of the bone is called the diaphysis, which is the shaft of the bone. Both ends of the bone surrounding the diaphysis are called epiphyses. The upper end, which is connected to the hip joint, is called the proximal epiphysis. The lower end, connected to the knee joint, is called the distal epiphysis. The layer separating epiphysis and diaphysis is called the epiphyseal line. The outer connective tissue around the cortical bone is called the periosteum, except for the joint sections, and the inner portion is called the endosteum. Bone marrow is stored in the central part of the bone, along the shaft of the bone, and is called the medullar cavity. The whole bone is covered with cartilage [66]. Since the femur bone is one of the main study areas for biomechanic engineers, fracture analysis is an important mechanical aspect of this study. Fracture is the separation or fragmentation of a body into two or more pieces in response to imposed stresses that may be static or varying with time and at low temperatures relative to the material’s melting temperature. Stresses applied to the material resulting in fracture may be compressive, tensile, shear, or torsional. There are six types of femoral bone fracture: femoral head fracture, femoral neck fracture, intertrochanteric fracture, sub-trochanteric fracture, femoral shaft fracture, and distal femur fracture. There are many causes of fracture/failure in engineering machines, such as stress concentrations, stress variations, and dislocation of joints [26,67–69]. There are many numerical/analytical techniques to study various mechanical aspects like displacements, stress variations, and biomechanical systems on 3D computational models of physical bodies. However, FEM is the most commonly used and widely accepted technique for biomechanical analysis of any body organ of different species of animals having complex geometries, such as human bone structure. It is also used in mathematical and engineering models to study structural analysis, heat transfer, fluid flow, and so on. FEM is based on computer-based programming [70]. A special branch of FEM called XFEM is used to study complex structural geometries and their biomechanical analysis. XFEM is a sub-branch of FEM that is specially developed to treat discontinuities in biomechanical structure [71,72]. The bone structure of mammals has many small discontinuities and complexities in its structure that are sometimes difficult to cater to in a 3D model. Moreover, these complexities in bone structure, despite being minute in appearance, can have big effects on the biomechanical analysis of the bone

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and cause variations in stress due to their response to different loading conditions. For this reason, the XFEM technique is a good choice for the biomechanical analysis of femur bone structure. The femur bone shows nonlinear behavior, meaning its properties do not remain the same at all positions. Femur bone properties vary at different locations under different loading conditions. Due to this, the choice of applying loads is taken to be those points where fracture probability is considerably high [70,73,74]. Hip fractures are one of the main problems of bone failure in the human body. Low-impact falls cause hip fractures, and the mechanical analysis of the proximal femoral part may predict hip behavior during a fall. In one study of femoral fracture, analyses were carried out in tensed, relaxed, and slap conditions. In this work, we carried out fracture analysis of the femur bone via the XFEM technique under different fall configurations. We studied the fracture by defining fracture onset on the proximal femur and conducting mechanical analysis. We modeled the femur using CT images and then conducted mechanical analysis [43,75–77].

3.9

Femur bone modeling and meshing

The dimensions of the femur bone vary from person to person based on differences in age group, gender, health, and so on. A study has shown a rough estimate of the dimensions of different parts of the femur bone. Many researchers have used different methods to model the femur bone. One study [78] used digital image correlation (DIC) for bone modeling and strain measurements on the bone’s surface. Another study [71] used CT images to model the femur bone through voxels in Hounsfield units. In this study, we collected CT images of femur bone through an extensive literature review (DICOM files) and imported them into Materialize Mimics software. Fig. 3.27 shows individual CT images of cross-sectional views of parts of the femur bone in different planes.

FIG. 3.27 Femur bone view along the axial plane.

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Fig. 3.27, shows a CT image of the femur bone along its axial direction (viewed from above). The yellow region shows the distal femur. Fig. 3.28 shows a CT image of the femoral head and distal femur in the coronal (frontal) plane. Fig. 3.29 shows a CT image of the femur diaphysis, also called the shaft, in the coronal plane. Some steps are performed to create a 3D model of the femur bone using these CT images (see Fig. 3.30) where Fig. 3.30A shows CT image in coronal view, Fig. 3.30B axial view, Fig. 3.30C sagittal view, and Fig. 3.30D shows overall 3D bone model.

FIG. 3.28 Distal femur and head in the coronal plane.

FIG. 3.29 Femur diaphysis in the coronal plane.

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FIG. 3.30 (A) CT image in coronal view, (B) axial view, (C) sagittal view, (D) 3D bone model.

The analysis may be studied precisely by selecting the respective orientation with respect to the type of load over the bone structure, extra surfaces, volumes, and edges have been removed by using the icon “New Mask” then defined the upper and lower threshold ranges, divided the segment, removed floating pixels from the region, and created a rough model or uncleaned surfaces (see Fig. 3.31).

FIG. 3.31 Rough 3D model after cutting edges.

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The non-linear elements and errors are further removed using Materialize 3-Matic Medical software. Fig. 3.32 shows a refined 3D model of the femur bone. The wrap option in the fix design menu can close any hole on the surface of your part and smooth it out. It can also be used to remove any of the internal shells in your model, thus making a smoother bone. By selected the smallest detail (7.5 mm), indicating the smallest element of size to make the smooth bone (see Fig. 3.33) the outputs are explained as well. After creating a smooth 3D model, the next step is to apply meshing using the Materialize 3-Matic Medical software. At first, the surface meshing is to be performed on the bone model to generate a fine mesh for precise analysis. Then, applied volume meshing and tetrahedral elements is done in software. Fig. 3.34 shows a sliced view of the volume mesh generated.

FIG. 3.32 Refined 3D model of the femur bone.

FIG. 3.33 Smooth 3D model of the femur bone.

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FIG. 3.34 Volume mesh cut view.

3.10 Conclusion and perspectives The special structure of bone determines its mechanical properties. In this chapter, we introduced the structure of cortical bone and trabecular bone. From macroscopic to microscopic, cortical bone has a six-level hierarchical structure, and the different hierarchical structures determine the different mechanical properties of cortical bone. The spongy bone is composed of bone trabeculae, which exhibits an irregular porous structure. Due to this porous structure, the Young’s modulus of trabecular bone can vary up to 100 times and the strength can vary up to 5 times when external forces are applied to the bone. The structure of bone also changes in response to the mechanical environment. Next, we described the procedure and complexity of bone modeling using different software packages, such as image processing software for 3D design and modeling. WE used FEM for stress and deformation analysis to deal with the problems in bone biomechanics. We accurately modeled bone by collecting CT images and 3D models prepared in Materialize Medical software. Material properties, assigning the variables and meshing must be performed in different compatible software packages, such as Materialize 3-Matic. FEM analysis allows predicting the strain values over time under the XFEM fracture technique. It is important to note that FEM analysis may also vary due to changes in mechanical property (Young’s modulus and critical energy). The stress levels

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found in the fracture analysis results compared to other values in the literature can be aware of the significance for proper characterization of the bone and material assignment. This chapter discusses the initial stages of crack propagation only because fracture modeling of whole bone and covering the final stages of crack propagation is a difficult task and may include local defects in the model. Further advancement in this field can include fracture analysis of femur bone at the micro level, which studies the changes in femoral structure at the micro level (tissues, nerves) and their behavior to different configurations and loading conditions. Also, the methods of material assignment to the femoral structure at the tissue level can be observed in a better way. The heterogeneous behavior of human bone can also be considered. These studies will better help us understand the relationship between the mechanical properties of the bone and environmental changes as well as provide insights into bone-related diseases.

Acknowledgments This work was supported by the National Natural Science Foundation of China (81772017, 82072106, 31570940), the Project Supported by Natural Science Basic Research Plan in Shaanxi Province of China (2023-JC-YB-163), and Young Talent Fund of University Association for Science and Technology in Shaanxi, People’s Republic of China (20170401).

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Part II

Bone cell mechanobiology

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Chapter 4

Mechanobiology of bone marrow mesenchymal stem cells (BM-MSCs) Hua Liu, Zihan Tian, Shuyu Liu, Wenhui Yang, Airong Qian, Lifang Hu, and Zixiang Wu* Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China * Corresponding author.

4.1

Introduction

Bone marrow mesenchymal stem cells (BM-MSCs) are characterized by fiberadherent growth and multidirectional differentiation in vitro. The consensus was reached through multiple studies that pluripotent BM-MSCs are common precursors of osteoblasts [1]. BM-MSCs not only have pluripotent differentiation potential but also show therapeutic potential in wound healing, such as cutaneous regeneration [2], therapy for lung injury [3], and tooth development [4]. Thus, these strategies are reflected in regenerative medicine for drug development and tissue engineering [5]. Some studies have shown that BM-MSCs are associated with osteogenic and adipogenic differentiation, which contribute to bone formation and repair [6,7]. In particular, BM-MSCs mediate the induction of osteogenic differentiation in cell commitment and could be used in the treatment of osteoporosis [8]. The differentiation ability of BM-MSCs is regulated by various factors, among which mechanical stimuli play a critical role in determining the osteogenic differentiation of BM-MSCs [9]. BM-MSC properties in terms of differentiation are modulated via physical stimulation and are associated with therapeutic strategies to maintain bone metabolic homeostasis [10]. Mechanoreceptors, components from the interior of living cells, are mechanosensitive to mechanical stimuli from the extracellular environment with the extracellular matrix (ECM) accompanied by a series of changes in osteogenesis. BM-MSCs receive mechanical stimulation through mechanoreceptors and convert mechanical signals into biochemical signals, Bone Cell Biomechanics, Mechanobiology, and Bone Diseases. https://doi.org/10.1016/B978-0-323-96123-3.00003-8 Copyright © 2024 Elsevier Inc. All rights reserved.

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thus affecting bone formation [11]. It is known that osteogenic and adipogenic differentiation of BM-MSCs are the opposite process, which means that the increase in osteoblasts is accompanied by a decrease in adipocytes in most instances. Compared to adipogenic differentiation and chondrogenic differentiation, change in osteogenic differentiation is the most obvious phenomenon under mechanical stimulation. Therefore, this chapter focuses on osteogenic differentiation and adipogenic differentiation of BM-MSCs. In this chapter, we summarize recent research of various mechanical stimuli on osteoblast differentiation and adipocyte differentiation of BM-MSCs. Physical properties of the microenvironment, including compressive, fluid shear stress (FSS), tensile strains, hydrostatic pressure (HP), vibration, and substrate stiffness (SS), are all involved in regulating differentiation of BM-MSCs. Based on these mechanical models, we also summarize the molecular mechanisms by which mechanotransduction promotes osteoblast differentiation. The chapter highlights the biomolecular mechanism of mechanically stimulated osteogenic differentiation in BM-MCSs and provides a reference for bone research based on BM-MSCs to improve their application in clinical settings.

4.2 Bone marrow mesenchymal stem cells (BM-MSCs) 4.2.1 BM-MSCs characteristics In 1976, Friedenstein et al. isolated a long fusiform, fibroblast-like cell population from bone marrow, which grew adherently and could form colonies, namely, a fibroblast-like colony-forming unit [12,13]. Bone marrow primordial mesenchymal stem cells are bone marrow stromal stem cells that can selfreplicate and differentiate into bone, cartilage, fat, nerve, and myoblasts [14]. In 1987, Friedenstein et al. found that adherent bone marrow monocytes cultured in plastic Petri dishes could differentiate into osteoblasts, chondroblasts, adipocytes, myoblasts, and other cell types under specific conditions and that these cells maintained their multi-direction differentiation potential after 20–30 generations of amplification [15]. Under specific conditions, BM-MSCs can differentiate into mesodermal cells, such as adipocytes, osteoblasts, muscle cells, endothelial cells, chondrocytes, cardiomyocytes, muscle cells, and even into ectodermal cells, such as nerve cells. In addition, they have immunomodulatory activity and may contribute to immunosuppression and tissue healing.

4.2.2 BM-MSCs function Bone tissue undergoes a constant process of bone remodeling in which old bone is absorbed and new bone is formed. Osteoblasts are mainly responsible for the formation of new bone. The maintenance of bone formation depends on the balance between osteogenic and adipogenic differentiation of BM-MSCs.

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Any weakening or inhibition of BM-MSCs’ osteogenic differentiation will upset this balance, leading to disrupted bone remodeling and bone loss. In addition, BM-MSCs are generally in a static state. Still, under a specific induction environment, BM-MSCs are activated and continuously differentiated into preosteoblasts through self-renewal to promote bone formation.

4.3

Mechanical stimulation of BM-MSCs

It is believed that BM-MSCs can sense different biomechanical signals during the growth process. The differentiation ability of BM-MSCs is regulated by various factors, among which mechanical stimuli play a critical role in determining the osteogenic differentiation of BM-MSCs [9]. Different forces have different effects on the proliferation and differentiation of BM-MSCs. The differentiation characteristics of BM-MSCs are adjusted by physical stimulation and are associated with therapeutic strategies for maintaining bone metabolic homeostasis [10]. Mechanoreceptors are the internal components of living cells and are mechanically sensitive to the mechanical stimulation of the extracellular environment. The ECM undergoes a series of changes during osteogenesis. BM-MSCs use mechanoreceptors to sense mechanical stimulation and respond to cell differentiation ability [11]. It is well known that osteogenic and adipogenic differentiation are opposite processes, that is, in most cases, an increase in osteoblasts is accompanied by a decrease in adipocytes. Compared to adipogenic and chondrogenic differentiation, osteogenic differentiation was most obvious under mechanical stimulation. Diverse mechanical stimulation is extensively involved in determining the osteogenic differentiation of BM-MSCs. To better understand the process of mechanical stimulation-induced changes in the cellular microenvironment, we summarize the findings of various mechanical models and a series of changes in osteogenic differentiation and adipogenic differentiation in BM-MSCs.

4.3.1 The effect of mechanical loading on differentiation of BM-MSCs (1) Compression and tension forces Compression and tension affect the proliferation and differentiation of BM-MSCs [16]. BM-MSCs can change by stretching back and forth in response to compression and tension forces and gradually exhibit the tendency to diverge in different directions. In addition, the Flexcell Tension System applies compressive and tensile forces to membrane tension, with precise adjustment of the loading period, mechanical size, frequency, and duration of the stretching force. These are key factors in response to the osteogenic differentiation of BM-MSCs. There are several models of the Flexcell system, including

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FX-3000, FX-4000T, and FX-5000. Previous studies have shown that BMMSCs respond positively to compressive and tensile strains (Table 4.1). In a study by Chen et al., researchers reported that human jawbone marrow mesenchymal stem cells (hJBM-MSCs) were mechanically stretched and showed potential for osteogenic differentiation by the Flexcell Tension System. Results showed mineral deposition and a 2.4-fold increase in calcium deposition after 21 days of mechanical stretching treatments. The mRNA expression level of osteogenic markers ALP, Runx2, and Osterix were also significantly upregulated through the continuous activation of NF-κB [17], suggesting that mechanical stretching facilitates osteogenic differentiation of hJBM-MSCs. Importantly, cyclic tension plays a crucial role in osteogenic differentiation from various MSCs. For example, Jiang et al. cultured BM-MSCs under cyclic tensile strains of 0%, 3%, 6%, and 9% with a Flexcell 5000 mechanical tension system. The researchers verified that 6% tensile strain was the optimal mechanical stimulation to promote osteogenic differentiation. The high expression evidenced this through a VEC-mediated paracrine effect on BM-MSCs, a process in which the VEGF-R inhibitor tivozanib [18]. Another study demonstrated that the frequency of cyclic tensile strains was positively correlated with osteogenic differentiation, accompanied by the upregulation of alkaline phosphatase (ALP) activity [19]. A study by Zhang et al. found that a 10% cycle mechanical strain can stimulate high levels of ALP and calcium deposition by activating receptor activator of nuclear factor-kappa B ligand (RNAKL), thus promoting bone formation [23]. In a study by Hu et al., mechanical stretching significantly induced osteogenic differentiation of BM-MSCs in the control group, with increased ALP activity and increased expressions of RUNX2/RUNX2 and ALP [62]. The silencing of Fak inhibits the osteogenic differentiation of rat BM-MSCs induced by mechanical stretching in vitro through the integrin signaling pathway [62]. Jia et al. analyzed 5%–15% of cells at different stages of the cell cycle after 24 h of stretching. Mechanical stretching promotes cell proliferation by promoting cell cycle progression [63] (Table 4.1). In addition, BM-MSCs can differentiate in the direction of adipocyte differentiation, as previously described. Cyclic stretch inhibited differential adipogenesis by inhibiting BMP4 and upregulating ERK but not through the downregulation of Smad or p38RK with the system using 10% strain and 0.25 Hz for 120 min/day [20,21]. In addition, cyclic mechanical stretch using a Flexcell Tension System (3% elongation at 0.1 Hz) can accelerate ALP activity and mineralize matrix deposition by adding various ECM proteins at the bottom of the substrates. The cyclic mechanical stretch worked via activating FAK and upregulating transcription and phosphorylation of Cbfa1 in this process [22]. These findings suggest an effective role for mechanical stimulation using the Flexcell Tension System to promote osteogenic differentiation and reduce lipogenic differentiation of BM-MSCs (Table 4.1).

TABLE 4.1 Effects of diverse mechanical stimuli on osteogenic differentiation of BM-MSCs. Mechanical stimuli

BM-MSCs source

Osteogenic differentiation ability of BM-MSCs

Key mechanism

Reference

Compression and stretch

hjBM-MSCs

Promote osteogenic differentiation

Inhibit NF-κB activity

[17]

Bone marrow stromal cells

Promote osteogenic differentiation

A VEC-mediated paracrine effect of VEGF

[18]

MSCs

Promote osteogenic differentiation; inhibit adipogenesis

Through HIF-1α-TWIST signaling pathway; suppress the BMP4 and upregulate ERK; activate TGFβ1/Smad2

[19–21]

HMSCs

Accelerate ALP activity and mineralized matrix deposition

Activate the phosphorylation of FAK, upregulate transcription, and phosphorylation of Cbfa1

[22]

Rat dental mesenchymal stem cells

Trigger the accumulation of calcium deposition

Activate RANKL gene expression

[23]

2T3 preosteoblasts

Inhibit osteogenic differentiation

Enhance BMP4 and block BMP antagonist noggin

[24,25]

Mouse primary osteoblasts

Inhibit osteogenic differentiation

Overexpression of β-catenin and BMP signaling

[26]

Human bone marrow stromal cells

Promote osteogenic differentiation

Unknown

[27]

Continued

TABLE 4.1 Effects of diverse mechanical stimuli on osteogenic differentiation of BM-MSCs—cont’d Mechanical stimuli

BM-MSCs source

Osteogenic differentiation ability of BM-MSCs

Hydrostatic pressure (HP)

BM-MSCs

Hindlimb unloading (HLU)

Modified lowintensity ultrasound stimulation

Key mechanism

Reference

Promote osteogenic/chondrogenic differentiation

Increase RhoA activity and Rac1 activity

[28]

MSCs

Promote osteogenic differentiation

Controlled by Piezo1 and BMP2

[29,30]

hBM-MSCs

Promote osteogenic differentiation

Unknown

[31,32]

9-month- old and 28month-old male rats

Promote bone loss

Unknown

[33]

Bone marrow stem cells

Promote osteogenic differentiation

Regulate Dnmt3b and block the binding of SHHR gene promoter

[34]

hMSCs

Enhance osteogenic differentiation

Unknown

[35]

Low-magnitude high-frequency vibration (LMHFV)

Substrate stiffness (SS)

hBM-MSCs

Promote osteogenic differentiation

Unknown

[36]

BM-MSCs

Promote osteogenic differentiation, induce BM-MSCs osteogenic lineage commitment

Enhance miRNA-335-5P expression; activate ERK1/2; through miR-378a-3p/Grb2 signaling pathway and Inhibit p38 MAPK signaling pathway

[37–40]

MC3T3-E1 cells and primary osteoblasts

Promote osteogenic differentiation

Enhance ERα signaling and cytoskeletal remodeling; Activation of β-catenin

[41–43]

MSCs

Promote adipogenic and osteogenic differentiation

Interaction with β-catenin; silence ITGB1 and stimulation of α5β1 integrin signaling

[44–49]

Human dental pulp stem cells

Promote osteogenic differentiation

Activation of the WNT signaling pathway

[50]

MC3T3-E1 cells

Induce the formation and rearrangement of actin stress fiber, promote osteogenic differentiation and mineralization

Collaboration of BMP2 and integrin β1 pathways; reduced miRNA expression

[51,52]

hMSCs

Promote osteogenic differentiation

Activation of ERK1/2 and FAK

[53–56]

MSCs

Promote osteoid nodules formation; promote osteogenic differentiation

Through the mechanosensitive TRPM7-osterix axis; cytoskeletal remodeling activity

[57–60]

Rat marrow stem cells

Facilitate the three-dimensional osteoblastic differentiation

Unknown

[61]

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(2) Substrate stiffness (SS) Whether the differentiation is mechanical transduction of stiffness initiated by a mechanosensory or is related to cytoskeletal arrangement due to the balance of intracellular tension needs further elucidation. The substrate stiffness (SS) usually determines the shape of the cell. Substrate elasticity can be considered as a special mechanosensory force that acts directly on the osteogenic direction of BM-MSCs by interacting directly with β-catenin through FAK and paxillin [44,45]. Stiff substrates are also more conducive to osteoblast differentiation, whereas soft substrates are usually accompanied by the differentiation of adipocytes and chondrocytes [9,64,65]. Therefore, the application of 3D printing hydrogel technology to alter the morphological structure and accelerate SS can promote the adipocyte and osteogenic differentiation of BM-MSCs [46,47]. Furthermore, the positive response of SS to osteoblast and chondrocyte differentiation is regulated by silencing integrin subunit beta 1 (ITGB1) [48]. α5β1 integrin signaling is also involved in promoting osteogenic differentiation of human mesenchymal stem cells (hMSCs) of different substrate sizes by binding peptide hydrogels [49] (Table 4.1). The selection of stem cell fate depends on the coregulation of SS and culture time duration [66]. Studies have shown that substrate, an important mediator of osteogenesis with varying stiffness, mainly affects early mesendoderm differentiation compared with other softer substrates in embryonic stem cells [67]. Similarly, compared with the soft substrates, SS enhanced the osteogenic differentiation of umbilical cord stem cells [68]. Furthermore, a novel mechanism was found that SS played a promising role in promoting osteogenic differentiation in adipose-derived stem cell differentiation [50,69] (Table 4.1). (3) Fluid shear stress (FSS) Physiologically, the fluid flow derived from blood flow and interstitial FSS, as a mechanical loading of bones, has also been shown to induce osteogenic differentiation of hMSCs via MAPK, NO/cGMP/PKG, and Ca2+ signaling pathways [70]. The ability of osteogenic differentiation of equine AMSCs was enhanced by FSS through a certain independent mechanism and combined with composite macromolecule biomaterials [71,72]. Integrin β1 plays a pivotal role under single-short duration FSS application in osteogenic differentiation through the collaboration of BMP2 and integrin β1 pathways [51]. One study showed that intermittent FSS was more effective than continuous FSS by detecting the phosphorylation levels of ERK1/2 and FAK in the osteogenic differentiation of hMSCs [53]. Analogously, integrin β1 is conducive to osteogenesis under FSS through activating ERK1/2 and FAK, followed by high feedback expression through activation of nuclear factor kappa-B [54,55]. FSS is sufficient to promote osteoid nodule formation of hPDLCs through the activation of ERK1/2 and p38 MAPK signaling pathways [73]. Intermittent fluid shear stress (IFSS) is an efficient method to modulate the osteogenic differentiation of MSCs through

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the mechanosensitive TRPM7-Osterix axis [57]. Short-term and appropriate FSS induces formation and promotes osteogenic differentiation and mineralization with the reduction of miRNA expression [52]. To investigate the function of FSS on osteogenic differentiation of periodontal ligament (PDL) cells at different times, diverse time points with the same flow rate and 6 dyn/cm2 were set to induce osteogenic differentiation. Then, the expression levels of osteogenic key genes and growth factors in PDL cells were examined. The results showed that osteogenic gene and protein level markers were upregulated time relatedly [74]. Additionally, ECM and FSS can facilitate 3D osteoblastic differentiation, which is good for bone tissue engineering [61]. Biological experiments have proven that flow rates had different effects on osteogenic differentiation of hMSCs, with FSS enhancing osteogenic differentiation and completely inhibiting the amount of ECM mineralization [56]. Similarly, the osteogenic differentiation genes, ALP were upregulated to varying degrees in MSCs after generation by a multimodal bioreactor system [58]. Consequently, these findings suggest that osteogenic differentiation of MSCs is related to oscillatory fluid flow (OFF) rates, frequency, and duration. The process elicited a significant increase in collagen and mineral deposition, suggesting that the OFF benefits osteogenic differentiation [59]. Interestingly, it was verified that the vibration or OFF rather than only FSS induced the osteogenic lineage commitment of BM-MSCs through cytoskeletal remodeling [60]. This surprising finding is inconsistent with previous studies. Whether vibration or oscillation is necessary for osteogenic differentiation of BM-MSCs remains controversial. In addition, the study found DNA methylation levels were reduced after 24 h of FSS applied on osteocyte (Ocy)-conditioned medium (CM), indicating that it facilitated osteogenic differentiation of BM-MSCs while reducing lipogenic gene expression [75]. Therefore, we expected that FSS would effectively reduce preadipocytes and inhibit adipocyte maturation and differentiation [76]. Li et al. investigated the regulating effect of pulse FSS on humans [77]. In the presence of osteoblast induction factor, the researchers continued to load FSS at 1 Hz and a maximum of 2.0 Pa and found that calcium precipitation significantly increased after 3 min. After loading FSS at 1 Hz and a maximum of 1.0 Pa for 2 h, they found that cell proliferation of osteoblast-related genes such as OP increased by 57%. The expression of OSTC was significantly increased, while the activity of ALP was significantly decreased, presenting a more mature osteoblast morphology [77]. Pulsed FSS can promote osteoblast differentiation in the presence of osteoblast induction factor [77] (Table 4.1). (4) Hydrostatic pressure (HP) Hydrostatic pressure (HP) is considered a non-negligible factor, especially in the bone marrow cavity and the joint synovium. Cyclic hydrostatic force stimulates mechanical responses that enhance bone development and regeneration in vitro [78]. It has been demonstrated that HP mainly facilitates the differentiation of BM-MSCs into osteoblasts and chondrocytes through the

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upregulation of RhoA and Rac1 activity and the proliferation of BM-MSCs [28]. Sugimoto et al. revealed that HP was mainly controlled by Piezo1, which promoted osteogenic differentiation of BM-MSCs, and BMP2 determined their fate in this process [29,30]. HP is beneficial to osteoblasts’ survival, differentiation, and maturation, and may be related to the high expression of mechanotransductive molecule integrin β5 [31]. Liu et al. stimulated rat BM-MSCs isolated and cultured in vitro by applying static or dynamic compressive stress and quantitatively detected and analyzed mRNA levels of RANKL and osteoprotegerin (OPG) in the cells [79]. The results showed that exposure to static or dynamic compressive stress at the early stage of BM-MSCs promoted an osteoclastic effect [79]. Research from Reinwald et al. showed that hBM-MSCs were treated with static culture or HP, and the expressions of collagen-I, ALP, and Runx2 were upregulated via fiber orientation under intermittent mechanical stimulation, which can influence cell morphology and calcium deposition patterns [32]. The results indicated that HP plays an important role in bone generation (Table 4.1). Disuse osteoporosis is a significant type of human osteoporosis and refers to bone loss during prolonged bed rest [80]. Thus, we can regard disuse osteoporosis as a special mechanical stimulus that leads to skeletal mechanical unloading. Numerous studies have found that prolonged bed rest, hindlimb unloading (HLU), and space flight all belong to the special mechanical stimulus. They inhibit bone formation and lead to massive bone loss [33,81]. A study by Uddin pointed out that disuse can lead to the lack of mechanical signals that inhibit the osteogenic differentiation of BM-MSCs [35]. In addition, the study revealed that lying in bed for a long time may be caused by brain and spinal cord injuries, and space flight is one of the causes of osteoporosis, which is ultimately caused by a decrease in the number of osteoblasts in BM-MSCs [35]. Research from Hu showed that disuse osteopenia could be rescued by targeting and silencing miRNA-132-3p [82]. Thus, miRNA-132-3p may be an effective target for preventing and treating osteoporosis of prolonged flight in pilots and bed rest in patients [82]. Another study demonstrated that mechanical unloading-induced disuse osteoporosis could promote osteogenic differentiation of BM-MSCs via directly regulating Dnmt3b and blocking the binding of the SHHR gene promoter [34] (Table 4.1). (5) Vibration Vibration also plays a pivotal role in the osteogenic differentiation of BM-MSCs. Low-magnitude high-frequency vibration (LMHFV) is the most common model, and researchers have observed its induction of osteogenic differentiation originating from BM-MSCs. It has been shown that LMHFV also mediates the distribution of bone structures and cytoskeletal rearrangements. Moreover, LMHFV promotes bone formation and positively affects osteogenic and adipogenic differentiation of BM-MSCs [37,41,42,83]. However, the experimental result demonstrated that high-frequency vibration promoted the

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mineralization, maturation, and differentiation of osteoblasts to bone tissue [36]. A report by Zhao et al. revealed that the osteogenic differentiation induced by LMHFV was enhanced by miRNA-335-5P expression [38]. Similarly, another report also illustrated that the miR-378a-3p/Grb2 pathway promoted osteogenesis in senescent rats under LMHFV [39]. Haffner-Luntzer et al. showed that LMHFV promoted osteogenic differentiation of pre-osteoblastic MC3T3-E1 cells by cytoskeletal remodeling [41]. In addition, suppression of p38 MAPK with SB203580 (a p38 MAPK inhibitor) suggested a strong increase in ALP activity and osteogenic markers by LMHFV, and that the activation of ERK1/2 promoted osteogenic differentiation capacity and induced osteogenic lineage commitment of BM-MSCs [37,40]. LMLF vibrations can also be used to enhance osteogenic differentiation potential of hMSCs [83]. Zhang et al. established LMHF mechanical vibration at 0.14–0.49 g facilitated cell survival and promoted osteogenic differentiation [43]. Interestingly, primary cilia are involved in osteogenesis, mineralization, and maturation. Chloral hydrate (CH) can chemically remove primary cilia and inhibit LMHFV-induced osteogenic differentiation [84] (Table 4.1).

4.3.2 The effect of mechanical unloading on differentiation of BM-MSCs (1) Random positioning machine (RPM) Numerous observational studies have found that preventing bone loss is crucial for astronauts during space flight [85]. RPM is a model to simulate microgravity for cell culture, providing a new strategy to study the ground-based microgravity environment of osteogenic differentiation [86,87]. The device contains two frames, an outer frame and an inner frame, with two separate axes to ensure that 3D rotation is possible. As a result, RPM provides a microgravity environment close to the space flight environment with zero resultant force. Microgravity has been identified as a major contributing factor to the decline of bone loss in astronauts and new hints for research and development in space medicine [27] (Table 4.1). It has been demonstrated that the differentiation and mineralization of rat cranial calvarial osteoblasts were significantly suppressed after treating with RPM for 6 h with cytochalasin D [87]. The mineralized nodular formation initially inhibited MC3T3-E1 pre-osteoblasts with an RPM-simulated microgravity condition, where p-ERK protein was reduced. This suggests that the reduction of osteogenic differentiation under microgravity may be regulated by ERK signaling [88]. Gene expression profiles of 2T3 pre-osteoblasts were examined using RPM for up to 9 days, and the results indicated that microgravity downregulated mRNA levels of ALP, Runx2, OMD, and PTH1R [24]. Another study found that mechanical loading rescued RPM-induced reduction of bone formation responses in 2T3 pre-osteoblasts, along with increased gene

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expression of ALP, Runx2, OMD, and PTH1R. This process improved the expression of BMP4 and blocked the expression of the BMP antagonist noggin [25]. In addition, recombinant irisin reduces osteogenic differentiation under RPM-simulated microgravity, and it may rescue bone loss in microgravity by overexpressing β-catenin and BMP signaling, which could be used to prevent astronauts from osteoporosis after prolonged space flight [26,89]. Li et al. showed that microgravity inhibits proliferation and differentiation into osteoblasts but promotes adipogenesis, and SMG also selects high tumorigenic cells to survive with prolonged SMG [90]. Yan et al. studied a simulated microgravity model that reduced the proliferation and differentiation of BM-MSCs after 48 h of exposure to simulated microgravity [91]. In contrast, the inhibition of differentiation was due to a decrease in BM-MSCs SATB2 expression induced by simulated microgravity [91]. Zayzafoon et al. cultured the isolated human in an osteogenic differentiation medium. After successfully inducing human osteoblast differentiation, inoculated these cells into microcarriers and cultured them in a rotary bioreactor for 7 days [91]. We found that the expression of osteogenic genes Cbfα1, ALP, and collagen I decreased, while the expression of adipocyte differentiation genes PPARr2, adipsin, leptin, and GLUT4 increased and did not return to pre-treatment expression levels 35 days after normal gravity was restored [91]. These outcomes suggested that osteogenic differentiation was inhibited by simulating microgravity under RPM. However, in contrast to these studies, another study reported that culture of human BM-MSCs in the RPM conditions facilitated Runx2, Osterix, and COL1A1 in the presence of an osteogenic cocktail [27]. In conclusion, the general answer is that microgravity inhibits osteogenic differentiation (Table 4.1).

4.4 Mechanism of BM-MSCs mechanotransduction The cell senses mechanical signals and influences gene expression and protein synthesis through signal transduction pathways. Mechanical stimulation influences the expression of integrin, which converts mechanical stimulation into biomechanical signals and regulates osteogenic differentiation of BM-MSCs. The expression levels of integrin α2β1, α5β1, and αVβ3 in BM-MSCs were increased after different mechanical stimulation. Meanwhile, integrin-based FAK was involved in initiating multiple signaling pathways and promoted the expression of genes related to osteogenic differentiation by regulating different signaling pathways. Therefore, multiple cellular components are involved in signal transduction, such as the cytoskeleton, integrin, ion channel, primary cilia, and other aspects involved in mechanical signal transduction.

4.4.1 Extracellular matrix-integrin-cytoskeleton system ECM, a macromolecular substance secreted by cells into the intercellular substance, such as collagen, elastin, proteoglycan, and so on, affects various

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physiological activities of cells through the signal transduction system. Numerous experimental studies and computer models have demonstrated that cells can generate biomechanics, and the physical characteristics of ECM are relevant to the field of mechanobiology [92]. Apart from this, which components mediate the mutual recognition and adhesion between cells to ECM? Integrins, also known as transmembrane proteins, respond primarily to interactions with ECM. Integrins also initiate signaling pathways that regulate the migration, growth, and survival of cellular structures inside and outside the cell [93,94]. It is well known that the cytoskeleton maintains cell morphology, cell spreading, cell migration, bearing external forces, cell spreading, and determining cell fate [95,96]. Together they form the ECM-integrin-cytoskeleton system (Fig. 4.1). MSC/ECM complexes (C-MSCs) are effective in bone regenerative cell therapy under 3D floating culture. It has been demonstrated that C-MSCs cultured under 3D floating conditions can lose actin cytoskeleton and thus downregulate YAP/TAZ activity, which directs to the production of adipocytes and chondrocytes concomitant with the formation of integrin β1-dependent actin fiber [97]. This process is accompanied by an increase in COL1 and Runx2

FIG. 4.1 Effects of diverse mechanical stimuli on osteogenic differentiation of BM-MSCs. FAK, Focal adhesion kinase; TRPV4/TRPV8, Transient receptor potential vanilloid 4/Transient receptor potential vanilloid 8; TREK1, TWIK-related K+ channel 1; PGE2, Prostaglandin E2; YAP1/TAZ, yes-associated protein/transcriptional co-activator with PDZ-binding motif Wnt, MAPK, and AMPK signaling pathways regulate the differentiation of BM-MSCs into osteoblasts and adipocytes by promoting or inhibiting their respective transcription factors.

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[97]. At the same time, the activation of mechanically sensitive channels is mainly dependent on changes in the ECM-integrin-cytoskeleton system, cell volume, and membrane relaxation, resulting in elevated Ca2+ levels in the cytoplasm that trigger a series of secondary reactions in mechanical mechanics [98]. Research showed that the ECM-integrin-cytoskeleton system (integrins connect the ECM to the cytoskeleton) consists of actin, transmembrane proteins of the βintegrin type, and vitronectin-like proteins in the ECM, which are critical as a pivotal composite system in polar axis formation during the early stages of postfertilization development [99]. The review concluded that integrin activates its downstream pathway and mediates bone formation via the ECM-integrincytoskeleton signaling axis [100]. However, what is the role of the ECM-integrin-cytoskeleton system in BM-MSCs under the mechanotransduction mechanism of TRPV4? Studies have revealed that by optimizing the compression amplitude, ECM deposition can be enhanced and the differentiation of BM-MSCs can be promoted. Furthermore, low-intensity compression can promote an anabolic response, while high-intensity compression can induce the catabolic response of 3D-cultured BM-MSCs by inhibiting TRPV4. The results showed that low-intensity compression promoted 3D-cultured BM-MSCs to disc formation [101] (Fig. 4.1).

4.4.2 Ion channel The ion channel is a crucial protein structure that constitutes a cell membrane component located on the diversified cell membrane, which can be found to be involved in mechanotransduction of cell proliferation and osteogenic differentiation of BM-MSCs [102–104]. Some studies indicate that the appearance of multiple ion channel proteins in the cell membranes of BM-MSCs and ion channels become important components of BM-MSCs to respond to various mechanical stimuli. Ion channels in cells are mainly force sensitive [105], temperature sensitive [106], and voltage sensitive [107]. Mechanosensitive ion channel expression was significantly increased under mechanical cyclic tensile strain and evaluated with ALP and matrix mineralization, thus activation of mechanosensitive ion channels is a pivotal mechanism to process osteogenic differentiation under mechanical stretch [108]. For example, KATP channels are effective for osteogenic differentiation through significantly upregulating the subunits of Kir6.2 in vitro and help distinguish the metabolic stages of mesenchymal stromal stem cells [109]. So, what is the relationship between the different types of ion channels? It was shown that in most hMSCs, the way Ca2+ entered into the plasma membrane was not mediated by voltage-operated calcium channels and that no matter how the L-type Ca2+ channel was blocked, it would not affect the early osteogenic differentiation of hMSCs [110]. Li et al. found that mechanical stress stimulation significantly increased osteogenic differentiation of BM-MSCs, during which pannexin1 (Px1) protein channels inhibitor CBX inhibited the Px1 protein channel [111]. Henstock et al. found

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that activating magnetic ion channel protein TREK1 expressed on hMSCs can improve differentiation into skeletal muscle cell types and enhance osteogenic differentiation in surrounding cells through superparamagnetic nanoparticles conjugated with targeting antibodies [112]. According to a study by Lu et al., a moderate non-physiological rate of FSS (0-2’) triggers a large influx from the BM-MSCs, which can rescue osteoporosis [113]. Panx3 ER Ca2+ channel is actively involved in osteogenic differentiation through phosphorylation of serine 68 residue [114]. TRPV4 ion channel and TRPM8 channel promote osteogenic differentiation in 3D microenvironments of hBM-MSCs. TRPV4 is the reciprocal feedback of volume expansion and is sensitive to substrate viscoelasticity [115,116] (Fig. 4.1).

4.4.3

Primary cilia

Primary cilia are ubiquitously expressed on diverse BM-MSCs and are microtubule and sensory organelles located on the cell membrane [117,118]. There are nine microtubules in both the primary cilia and motile secondary cilia, which originate from a basal body of the microtubule-organizing center [119]. Recent studies have revealed that primary cilia show mechanical sensitivity in BM-MSCs derived from bone marrow and are partly involved in mechanotransduction. It has been discovered that primary cilia act as a control center and play a pivotal role in BM-MSCs’ commitment [120]. Primary cilia can determine the differentiation direction of MSCs depending on various characteristics of primary cilia, including length, structure, and frequency. Data suggest that stable cilia can prolong the differentiation period by coordinating signals and dynamic changes [121]. Similarly, primary cilia are significant in engineering adipose-derived stem cells [122]. As mentioned, the formation of primary cilia is removed after using CH, and osteogenic differentiation is negatively regulated and unbalanced [84]. Experimental results showed that the primary cilia were part of the mechanosensitive structures in adiposederived stem cells to cyclic tensile strain. Primary cilium mediates fluid flow mechanotransduction in hMSCs and plays a pro-osteogenic mechanosensory role under OFF [123,124]. Primary cilia is a positive mediator for inhibiting OFF-induced mineral deposition via reducing the expression of PGE2 in MLO-A5 murine osteoblasts [125]. Research has shown that primary cilia act as mechanosensory during osteoblastic differentiation, and this conclusion has also been demonstrated in adult mice models [126]. However, TGF-β 1 can distort primary cilia and impair this mechanosensation. Further studies found that HDAC6 inhibitor Tubacin could reverse the damage to primary cilia of human osteoblasts and reduce sensitivity caused by TGF-β 1 [127,128]. Some studies have revealed that primary cilia are involved in mechanical stimulation to promote osteogenic differentiation in BM-MSCs by a novel paracrine signaling mechanism. Interestingly, osteogenic genes were not upregulated in BM-MSCs if the formation of BM-MSCs, and the present study explains that

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osteogenic differentiation of BM-MSCs on mechanically stimulated Ocyconditioned medium is dependent on primary cilia of osteocytes (Ocys) [129]. After adding the cilia-related siRNAs separately to the osteo-induced medium, chondro-induced medium, and adipo-induced medium, respectively, another study found that both types of cells, osteoblasts and adipocytes. However, chondrogenic differentiation was not affected in this process [130] (Fig. 4.1).

4.4.4 Signaling pathways (1) Wnt signaling pathway The Wnt/β-catenin signaling pathway has become a key pathway for mechanical stimulation to mediate osteogenic differentiation in BM-MSCs. The Wnt/βcatenin signaling pathway is involved in osteoporosis induced by long-term bedrest or microgravity during spaceflight [131]. Reverse transcriptionquantitative polymerase chain reaction (RT qPCR) and Western blotting analyses revealed the molecular mechanisms involved in osteogenesis by activating Wnt/β-catenin signaling with low-magnitude and high-frequency mechanical vibration [132,133]. Studies have revealed that the internal forces generated during the migration of BM-MSCs can more easily facilitate osteogenic differentiation by effectively activating the Wnt/β-catenin signaling pathway and significantly upregulating the expression of Runx2, ALP, and OCN [134,135]. This new finding indicates that LRP5 is an important protein in the Wnt signaling pathway and/or LRP6-mediated mechanotransduction and maintains a balance between normal bone formation and resorption [136]. Downregulating LRP5/6 expression can block the Wnt/β-catenin pathway and inhibit osteoblast differentiation in BM-MSCs [135]. Pulsating fluid flow (PFF) induces osteoblasts’ differentiation by activating the Wnt/β-catenin signaling pathway in a 3D cell culture system accompanied by low-density LRP5, Wnt3a, and β-catenin [137] (Fig. 4.2). In the non-canonical Wnt signaling pathway, Wnt5a is upregulated with the transfer of β-catenin during mechanical stimulation, leading to osteogenic differentiation of BM-MSCs in mice. Interestingly, inhibition of Wnt5a did not affect the β-catenin transfer. Thus, cyclic compressive is used to accelerate the differentiation of osteoclasts through the Wnt/β-catenin signaling pathway under multiple sinusoidal wave magnitudes, and phosphorylated-β-catenin is increased with dickkopf-related protein 1 (DKK-1) treatment, while the protein expression levels of DVL2 and Wnt1 are not affected [138]. Stretch experiments also suggest that the Wnt/β-catenin signaling was significantly attenuated after a 40-h stretch duration, indicating that the biphasic effect of mechanical load on β-catenin in mineralized human differentiated osteoblasts is independent of the ERK pathway [139]. Similarly, uniaxial mechanical stretch can enhance the protein levels of β-catenin and Runx2 and stimulate osteogenic

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FIG. 4.2 Schematic diagram of the role of mechanical stimuli on differentiation of BM-MSCs and potential regulatory mechanisms. FAK, Focal adhesion kinase; PI3K, Phosphatidylinositol 3-kinase; ERK1/2, Extracellular regulated MAP kinase; AKT, Protein kinase B; SIRT1, Silent information regulator type 1; AMPK, Adenosine 50 -monophosphate-activated protein kinase; PGC1, peroxisome proliferator-activated receptor γ coactivator alpha. BM-MSCs sense mechanical stimuli through ECM-integrin-cytoskeleton system, ion channels, and primary cilia. Mechanical loading promoted bone marrow mesenchymal stem cells to differentiate into osteoblasts by promoting or inhibiting their respective transcription factors, while mechanical loading inhibited the differentiation of bone marrow mesenchymal stem cells to adipocytes or chondrocytes by inhibiting their respective transcription factors.

differentiation by activating the Wnt/β-catenin signaling [140]. Mechanical strain activates β-catenin signal transduction in the cytoplasm and transfers it to the nucleus [141]. Interestingly, the inhibition of Wnt by DKK1 is associated with a change in the RANKL/OPG ratio under force treatment for 1 h [142]. All these studies indicate that the positive response of Wnt to mechanical stimuli is associated with osteogenic differentiation of BM-MSCs (Fig. 4.2). (2) MAPK signaling pathway The latest research has also identified the MAPK signaling pathway as an important signaling pathway of mechanotransduction in BM-MSCs. Results show that CBX pretreatment was associated with aberrant regulation of p38 MAPK phosphorylation, resulting in progressive inhibition of MSCs-induced mechanical stress osteoblasts [111]. It has also been found that a novel MAPK,

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JAK2-STAT3, and PI3K/Akt signaling pathway offers new guidance to promote osteogenic differentiation under mechanical stress via a Flexcell Tension System [143]. The MAPK/ERK signal pathway was also activated by applying equal biaxial cyclic strain to calcifying vascular cells (CVCs) effects or hPDLCs, in which the MAPK/ERK signaling pathway played an important role in regulating osteogenic differentiation [144,145]. The shear stress distribution in different fluid flow-induced has important effects on the gene expression of the MAPK signaling pathway in human MSCs. Among them, MAP3K8 induction activates different MAPK signaling pathways, and different shear stresses can induce consistent upregulation of MAP3K8 and IL1B. Therefore, MAP3K8 is a critical mediator of mechanotransduction in human MSCs [146]. Experimental results showed that mechanical stress-treated stem cells from apical papilla (SCAPs) promoted osteogenic differentiation capacity by activating ERK and JNK signaling pathways [147]. Hydrogen sulfide (H2S) could stimulate osteogenic differentiation of hPDLCs by activating p38-MAPK and ERK signaling pathways in response to cycle tension force [148] (Fig. 4.2). (3) Other signaling pathways Osteogenic differentiation was also promoted by activating the silent information regulator type 1 and AMP-activated protein kinase (SIRT1-AMPK) signaling pathway under mechanical stretch in hMSCs. Interestingly, the effect of 10% mechanical stretching was superior to 5% mechanical stretching with increased SIRT1 phosphorylation of AMPK gene expression. Moreover, decreasing SIRT1 or AMPK expression also inhibited osteogenic differentiation under mechanical stretch [149]. Tian et al. outlined the IGF-1 signaling, which played a critical role in mediating cell-specific response to mechanical stimuli [150]. Subsequently, another study pointed out that the ERK signaling pathway, which participates in early osteogenic differentiation, played an active role in the hydrostatic stress process, but not a critical one. Surprisingly, the p38 MAPK signaling pathway was not involved in this process [151]. Therefore, it is hypothesized that mechanical stimulation induces an increase in FAK expression, which activates the ERK, JNK, and p38-MAPK pathways to activate the FAK-MAPK pathway, thereby promoting osteogenic differentiation [152]. The circulating strain that enhances matrix mineralization via the ERK1/2 signaling pathway also promotes osteogenic differentiation in adult hMSCs [153] (Fig. 4.2).

4.5 Conclusion and perspectives In this chapter, we summarized diverse mechanical stimuli and their effects on function of BM-MSCs uncovered by studies from various mechanical simulation models, such as FSS, RPM, vibration, and SS. In addition, we discussed the molecular mechanism of mechanical regulation on the differentiation of BM-MSCs, including the ECM-integrin-cytoskeleton system, ion channels,

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primary cilia, and some signaling pathways. The key signaling pathways of Wnt and MAPK are both involved in the mechanical regulation of BM-MSCs’ function. Most studies provide strong evidence that mechanical stimuli are involved in osteoblast differentiation and bone loss. These potential mechanisms will promote a deeper understanding of the process of bone reconstruction caused by mechanical stimulation. In addition, our summary of the latest advances helps provide potential treatment options for health problems caused by specific mechanical environments and even osteoporosis due to prolonged bed rest or space flight. Numerous pieces of evidence have demonstrated the critical role of mechanical stimuli in determining the differentiation of BM-MSCs. However, there are still many questions to be addressed for a better understanding of the function and mechanism of mechanical stimuli in regulating the osteogenic differentiation of BM-MSCs. For example, which kind of mechanical stimuli is dominant in adjusting the osteogenic differentiation of BM-MSCs? What molecules play key roles in sensing and transducing mechanical signals to biochemical signals to adjust the differentiation of BM-MSCs? Is there any specific mechanoreceptor or mechanosensor of BM-MSCs responding to specific mechanical stimulus? Answering these questions will provide a deeper understanding of the regulation of mechanical stimuli on differentiation of BM-MSCs. In addition, it will provide a new therapeutic strategy for bone diseases caused by abnormal BM-MSC function.

Acknowledgments This work was supported by the Natural Science Foundation of China (82072106, 81772017, and 31400725), the Project Supported by Natural Science Basic Research Plan in Shaanxi Province of China (2023-JC-YB-163, 2018JM3040 and 2015JQ3076), the Young Talent Fund of University Association for Science and Technology in Shaanxi, People’s Republic of China (20170401), the China Postdoctoral Science Foundation (2018T111099, 2017M610653, 2015T81051, 2014M562450), and the Shaanxi Postdoctoral Science Foundation.

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Chapter 5

Mechanobiology of osteoblast Yunxian Jia, Zarnaz Khan, Mili Ji, Wenjin Zhong, Xuehao Wang, Airong Qian, and Lifang Hu* Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China * Corresponding author.

5.1

Introduction

The mechanosensitivity of osteoblasts (OBs) is fundamental to skeletal physiology [1–5]. OBs are critical in the bone multicellular unit (BMU) and play an indispensable role in bone formation [2,6]. As mechanical sensors of bone tissue, OBs ensure bone metabolism and bone homeostasis, regulate bone mass, and perform various pluripotent functions [1,2,7–9]. Because they are mechanosensitive [10], OBs detect bone matrix deformation caused by mechanical stimulation and send signals to neighboring bone cells [6,11,12]. The external mechanical signals can be transduced into intracellular biological signals through the mechanically sensitive structure in OBs [13,14]. OBs experience constantly changing mechanical stimulation, such as gravity, compression, vibration, fluid shear stress (FSS), and stretch, which promotes their osteogenic differentiation [10,14–17]. These mechanical stimuli affect various cellular processes of OBs and thus influence bone tissues. Lack of mechanical load will damage the osteogenesis of OBs, such as space flight and prolonged bed rest, consequently reducing bone formation and increasing bone resorption [18,19]. Therefore, mechanical loading is critical for the function of OBs. Evidence suggests that OBs are regulated by some signal pathways and mediated by many key genes and factors [11,20], which serve vital functions and effects in different mechanical conditions or models. Hence, it is necessary to further understand the property and mechanism of diverse mechanical stimuli regulating OBs. This chapter examines mechanisms of mechanobiological functions in OBs and provides scientific references in clinical application. Bone Cell Biomechanics, Mechanobiology, and Bone Diseases. https://doi.org/10.1016/B978-0-323-96123-3.00007-5 Copyright © 2024 Elsevier Inc. All rights reserved.

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5.2 Osteoblast 5.2.1 Osteoblast characteristics OBs originate from multipotent bone marrow mesenchymal stem cells (BM-MSCs), mostly derived from bone marrow stroma and mesenchymal progenitor cells [20,21]. Some transcription factors guide the BM-MSCs along the osteoblastic lineage and inhibit their development into adipocytes and chondrocytes. Meanwhile, other transcription factors inhibit OBs from developing into osteocytes (Ocys), keeping them active in bone tissues [21]. Mesenchymal progenitor cells develop along the OB lineage under specific transcription activators, guaranteeing the four phases of OB formation [20]. The OB is one of the most multifunctional cells in bone formation and remolding [9,22,23] (Fig. 5.1). OBs have various shapes, such as cubic, round, flat, or columnar. They are often arranged in a single layer and cover the new bone, and their morphology is related to function [12]. When the function of the OB is static, they are flat and stick to the bone surface. The active OBs are cubic, round, or cylindrical, and the cytoplasm is basophilic. Mechanical stimulation is correlated with OB morphology. There are numerous mechanical sensitive structures and molecules in OBs, such as cilia, ion channels, cytoskeleton, micro-tubulin actin cross-linking factor 1 (MACF1), CX34, noncoding RNA, and so on. They are indispensable in the mechanical signal transduction of OBs [14,24–28]. OBs receive various internal and external mechanical stimulations at any time. Mechanical stimulation is of great significance to OBs. Different mechanical stimulation has different effects on their function.

Runx2 / OSX

Pre-osteoblast BM-MSC

Immature osteoblast ALP /Collal/ OPN/BSP2

Osteoblast Osteocyte

FIG. 5.1 Mesenchymal stem cells develop along the osteoblast lineage. Some transcription factors and signal pathways promote their development and differentiation into pre-osteoblasts rather than adipocytes and chondrocytes. They continue to develop and differentiate into osteoblasts and further develop into osteocytes.

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Osteoblast function

The OB is responsible for the maintenance of skeletal structure, homeostasis, and metabolism [13]. OBs are also mechanical sensors and involve some mechanical signaling pathways [29–31]. Mechanical stimulation, hormones, and transcription factors direct the function of OBs, and the OBs connect with mechanical signaling networks [31]. Mechanical stimuli show an indispensable role in determining osteogenic differentiation [12]. The process of bone remodeling requires coordination between bone formation and bone absorption, which involves interaction between OBs and osteoclasts (OCs). When bone formation is greater than bone absorption, bone remodeling can be completed. OBs participate in the regulation of the OC bone absorption function and regulate the attachment and differentiation of OCs on bone surface, leading to OC apoptosis and inhibiting OC bone absorption. Bone tissue has a mechanical sensing device. After bone tissue receives external mechanical stimulation, Ocys detect bone matrix deformation resulting from mechanical loading and send signals to neighboring bone cells to guide OBs to where bone strength needs to be increased most. The mechanical load can transduce extracellular physical signals into intracellular biological signals through ion channels on the membrane of OBs, promote OB proliferation and extracellular matrix (ECM) secretion, and maintain normal homeostasis. Studies have shown that mechanical stimulation promotes the level of osteogenic differentiation markers, such as runtrelated transcription factor 2 (Runx2), alkaline phosphatase (ALP), collagen 2 (COL2), and others [10,32,33]. Mechanical stimulation has also been shown to activate some classical mechanical sensitive pathways, such as bone morphogenetic protein 2 (BMP2), Wnt-β-catenin, and Notch pathways, among others [34,35]. Substantial studies showed that OBs secrete some mechanically sensitive cytokines when exposed to mechanical stimulation, such as FSS, stretch, vibration, and so on [36,37]. Strengthening exercise in osteoporosis patients has proven to increase bone mineral density [38]. The OB is a promising candidate for biomechanical therapeutic strategies for osteodegenerative diseases [13].

5.3

Mechanical stimulation of osteoblast

The mechanical loading borne by bone is very important for bone growth, development, and maintenance [1]. Mechanical stimuli are critical in determining osteogenic differentiation of OBs [13,31]. Diverse mechanical stimulation is extensively involved in determining the osteogenic differentiation of OBs. To better understand the process of mechanical stimulation-induced changes in the cellular microenvironment of OBs, we summarize the findings of various mechanical models and a series of changes in OBs (Table 5.1).

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TABLE 5.1 Effects of diverse mechanical stimuli on osteoblasts. Type

influence

Mechanical pathway

Reference

FSS

Promotes the proliferation of osteoblasts

FSS induces osteogenesis gene expression (such as Runx2, OPN, and Cox2. In addition, the AKT/GSK-3β/ β-catenin pathway was activated

[1,7,32,39]

Vibration

Enhances bone formation in the intact skeleton and during fracture healing

Promotes the expression of osteogenic markers and ERα, and transfers ERα to the nucleus in ovariectomy (OVX) rats

[15,40]

Stretch

Increases human osteoblast proliferation and gap junctional communication between osteoblasts

Activates the opening of calcium channel or TRPV6, induces the rapid increase of intracellular Ca2+, and then causes cell response

[41,42]

CF

Inhibits osteogenic differentiation and cell proliferation

Inhibits the level of Alp, Runx2, and Dancr in osteoblasts and increases the levels of miRNAs

[16,43]

5.3.1 The effect of mechanical loading on osteoblast (1) The effect of fluid flow strain (FSS) on osteoblast FSS is the mechanical stimulation in the cellular microenvironment of OBs, which generated by the flow of extracellular fluid [44]. FSS can activate many essential signaling pathways in OBs as well as guide their proliferation, growth activity, and apoptosis [45–47]. Many studies indicate that FSS activates the βcatenin signaling pathway and promotes the level of osteogenic-related marker. For example, FSS stimulates the expression of Runx2 by activating the Piezo1 ion channel, thus promoting the expression of Runx2 [7,39]. Song et al. showed that FSS increased Piezo1 expression and key osteoblastic gene expression, such as Runx2, cyclooxygenase 2 (COX2), and osteopontin (OPN). Furthermore, they showed that MC3T3-E1 OBs must require Piezo1 in FSS mechanical situations [39]. Stavenschi et al. demonstrated that FSS can promote the expression of collagen and the formation of mineral deposition compared with the static environment [1,32]. Zhang et al. demonstrated that FSS activated the proliferation of OBs and suppressed the apoptosis of OBs, which is mediated by mitochondria. OBs are particularly sensitive to FSS, which leads to remarkable

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morphological change. This change may result from the changes in the extracellular adhesion matrix caused by FSS [48]. FSS regulates the expression of various microRNA (miRNA) in OBs. For example, FSS inhibits the level of miR-214-3p, miR-140-5p, and miR-34a. MiR-214-3p, miR-140-5p, and miR-34a are negative regulators of OBs that influence the proliferation activity of OBs and lead to OB apoptosis. Activating transcription factor (ATF4) is the target of miR-214-3p. FSS can promote OBs through the miR-214-3p-ATF4 signaling pathway [49]. Vascular endothelial growth factor A (VEGFA) is the target of miR-140-5p. FSS promotes OBs via the miR-140-5p-VEGFA signaling pathway [49,50]. If the expression of miR-34a is upregulated, the proliferation, promotion, and apoptosis inhibition of osteogenesis induced by FSS will be influenced. FGFR1 is a target gene of miR-34a. Fibroblast growth factor receptor 1 (FGFR1) regulates the function of OBs related to miR-34a. Long noncoding RNAs (LncRNA), taurine upregulated gene 1 (TUG1), and miR-34a are competitive endogenous RNAs (ceRNAs) that inhibit and influence each other. TUG1 promotes OBs through the miR-34a/FGFR1/lncRNA TUG1 signaling pathway [45]. MiR-20a, a sensitive microRNA, is increasingly expressed in FSS and promotes OB differentiation through the BMP2 signaling pathway [51]. Ding et al. proved that FSS upregulated the expression of nuclear factor of activated T cells 1 (NFATc1). NFATc1 activated the phosphorylation of extracellular regulated protein kinases (ERK5) and then activated the levels of osteogenic genes such as cyclin E1 and E2F2 [52]. Studies showed that FSS can regulate OB differentiation through the ERK5 signaling pathway. When ERK5 expression is inhibited, the function of FSS stimulating OBs to upregulate COX-2, OPN, and other osteogenic regulatory factors is arrested. Applying 1.3 Pa FSS to rat osteoblasts promoted OB proliferation and increased cell activity [53]. The study showed that FSS-induced OB proliferation is influenced by calcium transients, which activate various metabolism signaling pathways in OBs [46]. Gαq and ERK5 are indispensable in FSS mechanical stimulation; knockdown of Gαq or inhibition of the level of ERK5 will attenuate OB promotion [47,54,55]. The current study found that FSS increased ALP activity as well as mRNA and protein expression of osteocalcin (OCN), collagen type I, and Runx2, whereas it decreased DNA synthesis and stopped the cell cycle at the G0/G1 phase. The increase in Runx2 and ALP activity was followed by activation of calcium/calmodulin-dependent protein kinase type II (CaMK II) and ERK1/2, both of which were fully inhibited by KN93 and U0126, respectively [56]. In addition, inhibiting ERK1/2 but not CaMK II reduced p21Cip/Kip activity, resulting in an increase in cell number and S phase re-entry. The current study found that in the G0/G1 phase, FSS enhanced OB development via the CaMK II and ERK1/2 signaling pathways while blocking the cell cycle via the ERK1/2 route solely. The current findings contribute to a better knowledge of OB mechanobiology [56].

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(2) The effect of vibration on osteoblast It has been reported that low-magnitude high-frequency vibration (LMHFV) promotes OB proliferation and differentiation [57,58]. Many experimental studies demonstrated that LMHFV upregulated the expression of osteoblastic regulatory genes such as COX-2, OPN, and BMP-2, and that LMHFV is critical in promoting healing of fractures and other related skeleton diseases [59] [40]. One study found that LMHFV promoted fracture healing, and intermittent LMHFV was better in sheep animal experiment [60]. Estrogen receptor α (ERα) is important in therapy during fracture healing in the LMHFV process. Research shows that LMHFV can improve the expression of osteogenic markers and ERα [40]. If ERα is downregulated, the level of osteogenesisrelated genes will be correspondingly arrested [15]. LMHFV induces OB mineralization, maturation, differentiation, and primary cilia, which play acritical role in this process [14]. High glucose (HG) has a certain inhibitory effect on OB activity. In the mechanical stimulation environment of LMHFV, LMHFV activates the GSK3β/β-catenin pathway signaling pathway, which could alleviate the inhibitory effect of HG [57]. And the damaged skeleton microstructure and biomechanical properties caused by diabetes have been improved. Applying LMHFV to OBs promotes the expression of osteogenesis-related genes and various cytokines, increases the deposition of ECM calcium, and produces a cascade amplification reaction to osteoblastic differentiation and mineralization through autocrine and paracrine pathways [61,62]. Like FSS, LMHFV can also participate in activating various signal pathways. LMHFV acted as an effective therapy in osteoporotic fracture healing, bone disorders, and regeneration [58]. A study found that mechanical vibration stimulation (0.5 gn, 45 Hz) positively controlled the biological processes of OBs, as evidenced by changes in cytoskeletal microstructure, increased cellular proliferation, and increased bone matrix mineralization [63]. Furthermore, the findings showed that mechanical vibration increased the expression of osteogenesis-related genes and proteins while also activating the canonical Wnt signaling pathway. Low-level mechanical vibration increased osteogenic genes via a putative canonical Wnt signaling-associated pathway. The study advances basic understanding of the osteogenic activity of whole-body vibration (WBV) and may lead to a more efficient and scientific therapeutic application of WBV in promoting osteogenesis and inhibiting diseases such as osteoporosis [63]. (3) The effect of stretch on osteoblast Dynamic cell stretching increases OB proliferation [33,64,65]. However, some studies show that stretch will lead to the apoptosis of OB-like cells [41,64]. Mechanical factors influence the gap junctions between OBs. Studies have shown that cyclic stretch increases gap junctional communication between OBs [42]. High-level cyclic stretch influences the activity of MG-63 osteoblastic cells. OBs undergo extensive apoptosis when exposed to the mechanical

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stimulation of high-level cyclic stretch [41]. After low-intensity distraction, OBs can change the intracellular and extracellular Ca2+ concentration through transient receptor potential melastatin 3 (TRPM3) and transient receptor potential vanilloid 4 (TRPV4) channels, resulting in the enhancement of nuclear factor kappa-B (NF-κB), receptor activator nuclear factor kappa B ligand (RANKL), and NFATc1 activities and the acceleration of bone resorption. Stretch activates the calcium channel or TRPV6, induces the rapid increase of intracellular Ca2+. Mechanical cyclical stretch (MCS) is involved in bone formation. Studies show that mechanical stretch can induce osteogenesis of human adipose tissue multipotent street cells (hAT-MSCs). Mechanical stretching can activate some cytokines and some signal pathways to promote proliferation of OBs [66]. The mechanical cyclic strain increases cell density and protein expression [67]. Mechanical stretch also stimulates and accelerates OB differentiation and promotes skeleton regeneration. Wang et al. demonstrated that the differentiation-related genes increase when OBs are exposed to mechanical stretching. They also found that stretch activated the phosphorylation of mammalian target of rapamycin (mTOR) and NF-κβ p65, and the location of nuclear transferred [68,69]. The Akt/mTOR/p70s6k pathway regulates the osteoblastic energy metabolism and responds to stretch stimulation [70]. Zeng et al. showed MCS metabolism in OBs via the Akt/mTOR/p70s6k signaling pathway [70]. Yu et al. demonstrated that high-level mechanical stretch could induce the apoptosis of MG-63 OB cells and that periostin could attenuate this influence [41]. Cyclic stretch not only promotes the expression of osteogenic-related genes but also regulates cofilins, which modulate cytoskeleton rearrangement in OBs [10]. In one study, lower levels of strain (2.5% elongation at 0.1 Hz) stimulated the proliferation of human primary OBs for 48 h without boosting ALP activity or the release of type I collagen or osteoprotegerin (OPG), implying that the cells were kept in a dormant condition. A study that tested the effects of strain over a range of 0%–9% elongation for 8 h at 1 Hz discovered that normal human OB proliferation was magnitude dependent, with the highest strain yielding the greatest level of proliferation [71]. In summary, the evidence suggests that stretch signals have a beneficial influence on OB proliferation and this effect is magnitude dependent [72]. (4) The effect of compressive force on osteoblast It has been demonstrated that compressive stress influences the activity of OBs and osteogenic differentiation. When the OBs are exposed to compressive stress mechanical stimulation, the osteogenic-related markers such as ALP,Runx2, and Dancr are also inhibited. At the same time, the NF-κβ signaling pathway is activated, and the activity of OBs is affected [16]. Some miRNAs are mechanically sensitive. When OBs are exposed to stress, the level of some miRNAs changes. For example, miR-494-3p is an inhibitor of OB proliferation. In the

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pressure environment, the level of miR-494-3p increases, so the growth rate slows and thus cell proliferation is inhibited [43]. Studies have shown that compressive force (CF) promoted the expression of prostaglandin (E2PGE2) and Ep2 and/or Ep4 receptors in OBs and then regulated bone formation. However, as the CF increased gradually, COX-2, macrophage-stimulating factor (M-CSF), and RANKL increased, but OPG expression decreased [73]. Goga et al. demonstrated that CF can induce apoptosis in OB-like MG-63 cells via the caspase-8 signaling cascade [74]. A study was conducted to assess the influence of continuous CF on specific molecules involved in bone remodeling by human alveolar bone-derived osteoblasts (HOBs). The findings demonstrated that CF increased ALP and Col I mRNA and protein expression but had no effect on OPN and OCN mRNA expression. CF suppressed Runx2 mRNA expression while simultaneously altering the expression of molecules involved in osteoclastogenesis by increasing RANKL expression and decreasing OPG expression. The expression of RANKL and PGE2 was considerably increased at 4.0 g cm2 of CF. The findings imply that the initial application of CF to HOBs can influence the expression of markers associated with both osteogenesis and osteoclastogenesis [75].

5.3.2 The effect of mechanical unloading on osteoblast Mechanical stimulation is necessary for the homeostasis of OBs. Thus, mechanical unloading is a threat to this homeostasis [76].The reduction of mechanical load caused by space flight, prolonged bed rest, aging, and injury will reduce bone mineral density and strength [2]. Mechanical stimulation promotes bone development, and load reduction has an obvious correlation with bone loss and bone tissue fragility [2]. Lack of mechanical load will damage the osteogenesis of OBs, reduce bone formation, and increase bone loss. Moderate mechanical loading can lead to increased bone size, density, and strength, while the lack of mechanical stimulation leads to damaged bone microstructure and increased fracture risk. The impaired bone resulting from the mechanical unloading is related to the imbalance between OBs and OCs. During space flight, astronauts’ bone density significantly decreases. As such, it is urgent to study how to resist bone loss in a weightless environment [18,19]. Unloading mechanical stimulation can affect the expression of some sensitive mechanical factors in OBs, activate or inhibit some related pathways, and affect the function of OBs. Our previous research showed that unloading mechanical stimulation can affect the expression of cyclin in OBs, inhibit the level of MACF1 and β-catenin, and arrest osteogenic differentiation ability. Yin et al. investigated the effects of mechanical unloading on MACF1 expression levels in cultured MC3T3-E1 osteoblastic cells and in femurs of mice with hind limb unloading (HLU). They also examined the role and potential action mechanisms of MACF1 in OB proliferation in MACF1-knockdown, overexpressed, or control MC3T3-E1 cells treated with or without the

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mechanical unloading condition [76]. Results showed that the mechanical unloading condition inhibited OB proliferation and MACF1 expression in MC3T3-E1 osteoblastic cells and mouse femurs. MACF1 knockdown decreased OB proliferation, while MACF1 overexpression increased it. The inhibitory effect of mechanical unloading on OB proliferation also changed with MACF1 expression levels. Furthermore, MACF1 was found to enhance β-catenin expression and activity, and mechanical unloading decreased β-catenin expression through MACF1 [76]. Taken together, mechanical unloading decreases MACF1 expression, and MACF1 upregulates OB proliferation through enhancing β-catenin signaling. This study provides a mechanism for mechanical unloading-induced inhibited OB proliferation [76].

5.4 5.4.1

Mechanism of osteoblast mechanotransduction Mechanical sensitive molecules

(1) Pizeo Mechanical stimulation can activate some mechanically sensitive ion channels on the cell membrane; Pizeo1 is one of these channels. It can sense the external mechanical force and guarantee mechanical transmission. Experimental knockout of Pizeo in mice OBs promoted bone resorption of OCs and caused osteoporosis in mice [27,77]. Studies have shown that Piezo1, a key mechanical sensor and a receptor for external mechanical loading, makes osteogenesis mechanically sensitive [7,77]. Experiments showed that after knockout of Piezo1 in mouse OBs, bone formation was inhibited and bone mass and bone strength decreased [7]. Sun et al. proved that if Pizeo is knocked down, the sensitivity of OBs to external stimuli will be affected. A study shows that Piezo1fl/fl mice are more susceptible to mechanical unloading than Piezo1Ocn/Ocn mice. It shows that Pizeo is responsible for mechanical perception and conduction [7]. Song et al. have shown that FSS promoted the level of Pizeo in osteogenic cells and increased key osteoblastic gene expression, such as Runx2. In this process, the AKT/GSK-3β/βcatenin pathway was activated. FSS promoted Akt phosphorylation, the following GSK-3β phosphorylation, which are companied by increasing Runx2 level via the role of Pizeo1 (Fig. 5.2). The researchers showed that MC3T3-E1 OB require Pizeo in FSS mechanical situation. The silencing of Pizeo influences the AKT/GSK-3β/β-catenin pathway mechanically. FSS plays a role in the proliferation of MC3T3-E1 OBs through the Piezo1 ion channel. Pizeo can also stimulate the YAP signal pathway, regulate the expression of type II and IX collagen, and further promote OB differentiation. Pizeo1, an activator of the Ca2+ ion channel, promotes Ca2+ influx and activates Yes-associated protein 1 (YAP1), Activator protein 1 (AP1), β-catenin and NFATc1 [1,39] (Fig. 5.2). In conclusion, Pizeo is expected to become an effective therapeutic target for bone-related diseases such as osteoporosis [7].

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FIG. 5.2 Mechanosensitive molecules and structures involved in mechanical stimulation. Many mechanosensitive molecules and structures are involved in mechanical stimulation in osteoblasts, such as Cx43, MACF1, Pizeo1, and cilia. When the osteoblasts are stimulated by mechanical force, they will start relevant response, as shown here.

(2) MACF1 The cytoskeleton is composed of actin and intermediate filament and has a microtubule structure, which is responsible for modulating OB cellular shape and regulating mechanical properties [5,10]. The cytoskeleton is the earliest structure sensing and transducing signal in mechanotransduction [10,28]. The cytoskeleton is an intertwined and interacting structure that connects all mechanosensitive components. Destroying the cytoskeleton can significantly reduce the expression of genes related to mechanical stress in OBs. MACF1 is a mechanosensitive cytoskeleton. MACF1 can isolate osteogenic gene related inhibitors in the cytoplasm, avoid entering the nucleus, and enable osteogenic genes to be transcribed procedurally [78]. Knocking down MACFI will cause the inhibitor of the OB gene to enter the nucleus and affect the normal differentiation of OBs. The cytoskeleton has been proven to be involved in OB differentiation and partake in various classic signaling pathways. MACF1 activates the Wnt/β-catenin signaling pathway by sensing external or internal mechanical signals of cells, thereby affecting the function of OBs [79,80]. Under the condition of mechanical unloading, the expression of MACF1 decreases. Knockdown of MACF1 expression reduces OB osteogenic differentiation ability [76]. Hu et al. identified that MACF1 protects β-catenin from phosphorylation and promotes β-catenin nuclear translocation. Knocking down MACF1 significantly inhibits this function as well as the subsequent activation of genes such as TCF1, LEF1, and Runx2 [80]. Axin is an inhibitor of bone

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formation. MACF1 combines with Axin to activate the degradation of Axin (Fig. 5.2). Further study has demonstrated that MACF1 inhibits the activity of GSK-3β, which is also an essential regulatory for β-catenin. Chen et al. showed that MACF1 is the target gene of miR-138-5p and HLU reduces bone anabolism. If the expression of miR-138-5p is inhibited, the deterioration effect of mechanical unloading on the skeleton will be alleviated [81]. Chen et al. confirmed that miR-138-5p is negatively related to the osteogenic gene and the bone mineral density of mice [82]. In conclusion, MACF1, as a prominent mechanical sensitive structure, plays a vital role in OB sensing of mechanical stimulation. (3) Connexin 43 The gap junction is a common method of signal transmission between cells. Studies have found that there are some connexins between bone cells, which enable bone cells to connect and transmit signals to each other. Some common connexins include Cx37, Cx43, Cx45, and so on [83,84].. Connexin 43(Cx43) is the most abundantly expressed in bone among the connexin subtypes [85]. Cx43 allows molecules less than 1200 Da to pass through [86]. Cx43 participates in mechanotransduction in OBs, which controls bone mass. Numerous experimental studies have demonstrated that Cx43 is indispensable in bone remodeling. Animal experiments showed that after knocking down Cx43, mice lost significant bone mass and the length of long bones was significantly shortened; sometimes even death occurred [87–89]. The cortical bone cells of mice with Cx43 knockdown are severely apoptotic [90] and bone resorption of OCs increased, whereas bone density was seriously lost [24,87]. The role of Cx43 in OBs is complex. OBs lacking Cx43 increase the anabolic reaction during mechanical loading and weaken the anabolic reaction during unloading [25]. Studies have shown that Cx43 is not only a connexin but also can actively participate in the signal pathway network and participate in the regulation of cell homeostasis [86]. Mechanical stimulation opens Cx43 channels and promotes the release of PGE2 in OBs. PGE2 stimulates gap junction function and Cx43 expression in an autocrine manner. PGE2 acts on corresponding receptors of target cells through autocrine and paracrine pathways. PGE2 can also activate adenylate cyclase to increase the level of intracellular cyclic adenosine monophosphate (cAMP) as well as activate phospholipase C (PLC). PLC can decompose PIP2 into inositol triphosphate (IP3) and DAG. The increase of IP3 concentration will lead to a large release of intracellular Ca2+. DAG can activate PKC with the help of Ca2+. The increase of intracellular Ca2+ and cAMP and the activation of protein kinase C (PKC) further affect the functional response of OBs (Fig. 5.2). Mechanical stretching promotes the phosphorylation of Cx43. However, the phosphorylation level does not influence the mRNA level of OB-like cells. Grimston et al. confirmed that Col1-cre leads to Cx43 deletion, which further results in decreased anabolic activity in the mechanical environment.

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(4) Cilium Cilium is a microtubule and derived from centrioles. It is a mechanically sensitive structure on the cell membrane. It exists on the membrane of most mammalian cells. There are many signal receptors on cilia, which can sense chemical, mechanical, and temperature stimuli [91–94]. Cilium is an antenna-like structure that plays an important role in transmitting mechanical signals [95]. The cilia extend outward from the OB membrane and sense dynamic mechanical stimulus [96,97]. The cilia regulate OB proliferation, differentiation, and apoptosis via the Hedgehog (Hh) signaling pathway (Fig. 5.2). A study has shown that the removal of primary cilia in MC3T3E1 OBs reduces the osteogenic promotion response to FSS [98,99]. Other studies have shown that cilium are needed in responding mechanical forces to increasing bone formation [100]. Continuous application of 0.036 Pa FSS stimulation can cause deflection of OB primary cilia, indicating that cilia can sense low-intensity mechanical stimulation [98]. We also confirmed that the primary cilia of OBs can sense vibration stress, transmit mechanical signals, and promote OB differentiation and mineralization [14]. Malone et al. observed that when the primary cilia formation of MC3T3-E1 was inhibited, the increasing effect of extracellular PGE2 caused by FSS loading would stop [98]. PGE2 is an important osteogenic regulator. As the synthesis and secretion of PGE2 increase when OB are mechanically stimulated in vivo and in vitro, PGE2 plays an important role in regulating bone dynamic balance [101]. Li et al. showed that using chloral hydrate (CH) to remove cilia inhibited the induction of OB in the LMHFV condition. Compared with normal OBs, the OBs treated with CH have lower ALP activity, mineralization, and differentiation in the LMHFV situation [14]. Primary cilia can sense different mechanical stimuli and may adjust their sensitivity through morphological changes. (5) Noncoding RNAs Noncoding RNAs (ncRNAs), which include miRNAs, lncRNAs, and tRNAs, do not translate into proteins,. Numerous studies have proven that lncRNAs and microRNAs play critical roles in OB [45]. MiRNA is a single-stranded ncRNA that targets targeted mRNA and then silences the targeted genes. Increasingly, studies have shown that miRNA has mechanical sensitivity and regulates OB function. In one study, after OBs were mechanically stimulated, the mechanosensitive miRNA changed correspondingly. Several miRNAs are proven to activate and involve in the Wnt/β-catenin, BMP, and other signaling pathways and then partake in OB differentiation [20]. miR-140-5p is significantly downregulated when OBs are exposed to FSS mechanical stimulation [50]. One study found that MiR-20a is also a mechanically sensitive miRNA. When OBs are exposed to the mechanical environment of FSS, the osteogenic differentiation ability is enhanced. miR-2861 [102] and

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miR-3960 [103] have been proven to guide the Runx2-related pathways. miRNA can be a promising and novel therapeutic target, as the roles of miRNAs are influenced by mechanical stimulation [51]. FSS also activate miR-214-3P via the ATF4 signaling pathway and promote osteogenic differentiation and arrest apoptosis [49]. ncRNAs play essential roles in bone remodeling by molecular pathways.

5.4.2

Signaling pathways

(1) Wnt/β-catenin signaling pathway The Wnt/β-catenin signaling pathway is a canonical and extensively studied signaling pathway that is necessary to regulate the functions of OBs [104,105]. Wnt/β-catenin signaling plays a crucial role in promoting OB differentiation. The activity of Wnt signaling is activated in mechanical loading situations (e.g., FSS, cyclic compression, vibration, etc.) and the activity of Wnt signaling is inhibited in mechanical unloading condition [35,106–108]. The Wnt signaling pathway is activated by the binding of Wnt protein and Lrp5/ Lrp6 and the Frizzled protein. Glycogen synthase kinase-3β (GSK-3β) induced β-catenin phosphorylation is inhibited, and then β-catenin are accumulated [109]. Subsequently, the dephosphorylated β-catenin translocates into the nucleus, inducing the transcription of LEF/TCF-responsive genes. Substantial studies have shown that mechanical stress can activate the Wnt/ β-catenin signal pathway. Simulated microgravity (SMG) can inhibit OB differentiation by influencing the Wnt/β-catenin signaling pathway. MC3T3-E1 cells cultured under SMG conditions experience characteristic changes, which reduces focal adhesion and changes cytoskeleton structure. The Wnt/β-catenin protein and its related molecules are also downregulated under SMG. In an animal model, the tibia trabecular bone of mice was significantly affected after HLU of mice in simulated weightlessness [110]. Yin et al. showed that the Wnt/β-catenin pathway is affected by cytoskeletal protein MACF1, which can activate β-catenin signaling and promote OB proliferation. MACF1 is a mechanically sensitive molecule and overexpression of MACF1 can promote osteogenesis. Mechanical unloading conditions will inhibit the expression of MACF1, and mechanical unloading can reduce β-catenin through MACF1 and affect the proliferation of OBs [76]. Chen et al. demonstrated that compression loading increased the Wnt/β-catenin signaling pathway component, mRNA expression level of Lrp5, Wnt1, β-catenin and disheveled segment polarity protein 2 (DVL2) protein level (Fig. 5.3). Compression also activated the OB differentiation-related genes via Wnt signaling, including ALP, Runx2, and OCN [108]. Intermittent cyclic compression induces adenosine triphosphate (ATP) synthesis in OBs and promotes OB differentiation via activating Wnt/β-catenin signaling [111] At the same time, this mechanical loading promotes Wnt3A mRNA expression, β-catenin nuclear translocation, and the expression of osteogenesis-related genes.

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FIG. 5.3 Wnt, BMP2, and MAPK signaling pathways are involved in mechanotransduction. Many signaling pathways are involved in the mechanical stimulation of osteoblasts, such as Wnt, BMP2, and MAPK. When osteoblasts are mechanically stimulated, they activate relevant signaling pathways, which affects the proliferation and differentiation of osteoblasts.

In conclusion, numerous studies have shown that the Wnt signaling pathway is an important signal transduction pathway in OBs and plays a critical role in the response and adaptation of OBs to mechanical stimulation. (2) BMP2 signaling pathway BMPs have more than 40 family members, with most research conducted on bone metabolism [112]. BMP2, a member of the transforming growth factor β(TGF-β) family, partakes in many biological processes such as bone formation and differentiation [113,114]. BMP2 is an important regulatory protein in OBs and plays an important role in the transcription process of OB differentiation [115]. Yang et al. found that BMP-2 phosphorylated c-Jun N-terminal kinase (JNK) to promote OB differentiation [116]. Animal experiments and clinical experiments show that BMP2 is an effective and indispensable target for the treatment of bone-related diseases [51,117]. BMP2 signaling activated by binding with BMPR type I and type II receptor. Smad1, Smad5, and Smad8 gather together with activating BMP transmembrane receptors I (BMPR-IA) and then phosphorylate to transmit signals. These Smads combine with Smad4 to form a

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complex and subsequently transfer into the nucleus to target the osteogenic gene [118–121]. In addition, studies have shown that mechanical stimulation activated the phosphorylation of SMAD1/5 and promoted the differentiation of OBs [122,123]. Mechanical stretch can promote the phosphorylation of Smads and promote osteogenic differentiation via BMP2 signaling [122,123] (Fig. 5.3). Liu et al. proved that FSS can increase the expression of BMP2 and activate the BMP2 signal pathway [124]. Wang et al. found that mechanical force enhanced the expression of ALP in MC3T3-E1 OBs and activated BMPs/ Smad signaling pathway. Knock down Smad4 level with siRNA, and the function of mechanical stimulation promoting ALP expression will be affected. Mechanical force can downregulate Smuf1 to inhibit the degradation of Smad1 and Smad5 proteins [123]. Peng et al. showed that miR-20a can promote osteogenic differentiation when MC3T3-E1 OBs are exposed to FSS via activating BMP2 signaling [51]. FSS promotes the phosphorylation of SMAD1/5 and SMAD2/3, and this increase in phosphorylation affects different target genes [125]. These findings indicate that BMP2 signaling partakes in OB mechanotransduction responding and adapting the dynamic stimulation force. (3) MAPK signaling pathway Mitogen-activated protein kinases (MAPKs) are a varied and evolutionarily conserved family of protein serine/threonine kinases critical in mechanotransduction and involved in almost all cellular physiological functions, such as cell proliferation, differentiation, and signaling transformation [126]. The signaling pathway families include ERK, c- JNK, and P38MAPK signaling. Studies show that MAPKs are extensively involved in bone mechanotransduction via phosphorylation cascades [127,128]. The MAPK signaling pathway is a cascade phosphorylation process, and its key members include MAP kinase kinase (MAPKKK), MAP kinase kinase (MAPKK) and MAP kinase (MAPK). Extracellular growth factors act as ligands to activate the receptor of L-arginine kinase, connect growth factor receptor bound protein 2 (GRB2), and recruit Son of Sevenless (SOS). SOS activates rat sarcoma (Ras) by consuming guanosine triphosphate (GTP) to form Ras-GTP. The activated Ras combines with the downstream protein Raf to phosphorylate a variety of other kinases. Phosphorylated ERK continues to phosphorylate related kinases in cells and induce gene expression related to cell cycle and cell proliferation (Fig. 5.3). Studies have demonstrated the importance of the MAPK-AP-1 axis in the response of stress-sensitive cells to mechanical loading [129–135]. The strong relationship between mechanical loading and MAPK activation is also highlighted by studies on cultured OB-like cells (ROS 17/2.8), which show mechano-induced enhancement of ERK1/2 via various mechanisms [131]. Yan et al. demonstrated the expression of 1992 genes changed in compressive stress, 41 of which are involved in the MAPK signaling pathway. The study indicated that the MAPK signaling pathway plays an important role in OB

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differentiation and proliferation [136]. Hoshi et al. found that connective tissue growth factor 2 upregulated in OBs upon compressive stress, the increased gene activated the ERK1/2 signaling pathway and induced apoptotic [137]. However, the result of Yan’s study is opposite, indicating that the function of compressive stress on OBs is still controversial. Song et al. further showed that periodic compressive stress may affect the differentiation and proliferation of OBs through the MAPK and PI3K Akt signaling pathways, and the impact is related to the magnitude of compressive stress [138]. Yuge et al. found that SMG arrests OB differentiation by inhibiting the p38 signaling activity [139]. Studies show that ERK and p38 guide osteogenic differentiation via phosphorylating and activating runx2 [140]. In vivo tests have showed greater expression and activation of JNK/ERK signaling pathways on OBs of young Wistar rat temporomandibular joints (TMJ) with changing functional mastication loads, correlating with in vitro findings [132]. Similar investigations have shown that mechanical stimulation enhances the expression of the primary JNK/ERK MAPK substrate, the transcription factor AP-1 [133]. According to one study, mechanical stress activates the p38 pathway by sensitizing Ca2+ channels in ROS-A 17/2.8 OB-like cells [141]. Runx2, a transcription factor with a runt domain, is a key regulator of osteoblastic differentiation. A substantial body of evidence demonstrates that Runx2 is important in skeletal mechanotransduction [142–144]. Cell culture investigations, for example, have revealed that mechanical stimulation causes Runx2 overexpression and activation, which promotes osteoblastic differentiation via Ras/rat fibrosarcoma serin/threonine protein kinase (Raf)-dependent ERK1/2 activation [135,145]. In line with this discovery, research on rat TMJ has demonstrated that changing mechanical loading increases Runx2 expression, again via the JNK and ERK axes [131].

5.5 Conclusion and perspectives In this chapter, we discussed recent advances in OB mechanobiology. OBs play a critical role in the mechanical mechanotransduction of bone tissue. Mechanical loading conditions such as FSS, vibration, stretch, and compression force exhibit promotion effects on OB proliferation and differentiation, whereas mechanical unloading conditions such as simulated microgravity condition by RPM exhibit inhibitory effects on OB proliferation and differentiation. Some mechanosensitive molecules and structures play a necessary role in OB signal mechanotransduction, including Piezo, MACF1, Cx43, cilium, and noncoding RNAs. Some classical signaling pathways are also involved in OB mechanical signal transduction, such as Wnt/β-catenin, BMP2, MAPK, and others. Some molecules promote the proliferation and differentiation of OBs, such as BMP2, Runx2, OSX, and so on. Proper mechanical stimulation can also promote the proliferation and differentiation of OBs. Some of these molecules have

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been shown to be mechanically sensitive, such as MACF and Cx34. It is not known whether there are other mechanically sensitive molecules. Thus, future research can explore more mechanosensitive molecules and determine their influence on mechanotransduction. Targeting these sensitive molecules, knocking down target genes, or overexpressing target genes is expected to promote bone formation. In addition, many signaling pathways are involved in mechanical transmission in OBs. Exploring their interaction mechanisms is expected to provide a deeper understanding of the biomechanical mechanism of OB mechanobiology.

Acknowledgments This work was supported by the Natural Science Foundation of China (81772017, 82072106, 31400725, 31570940, 30970706, 30840030, 31370845), the Project Supported by Natural Science Basic Research Plan in Shaanxi Province of China (2023-JC-YB-163, 2018JM3040 and 2015JQ3076), Young Talent Fund of University Association for Science and Technology in Shaanxi, People’s Republic of China (20170401), the China Postdoctoral Science Foundation (2018T111099, 2017M610653, 2015T81051, 2014M562450), and the Shaanxi Postdoctoral Science Foundation.

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[120] Z. Zhou, J. Xie, D. Lee, Y. Liu, J. Jung, L. Zhou, et al., Neogenin regulation of bmp-induced canonical smad signaling and endochondral bone formation, Dev. Cell 19 (1) (2010) 90–102. [121] Q. Wei, A. Holle, J. Li, F. Posa, F. Biagioni, O. Croci, et al., Bmp-2 signaling and mechanotransduction synergize to drive osteogenic differentiation via yap/taz, Adv. Sci. (Weinheim, Baden-Wurttemberg, Germany) 7 (15) (2020) 1902931. [122] B. Rath, J. Nam, J. Deschner, J. Schaumburger, M. Tingart, S. Gr€assel, et al., Biomechanical forces exert anabolic effects on osteoblasts by activation of smad 1/5/8 through type 1 bmp receptor, Biorheology 48 (1) (2011) 37–48. [123] L. Wang, X. Zhang, Y. Guo, X. Chen, R. Li, L. Liu, et al., Involvement of bmps/smad signaling pathway in mechanical response in osteoblasts, Cell. Physiol. Biochem. 26 (6) (2010) 1093–1102. [124] L. Liu, L. Shao, B. Li, C. Zong, J. Li, Q. Zheng, et al., Extracellular signal-regulated kinase1/2 activated by fluid shear stress promotes osteogenic differentiation of human bone marrowderived mesenchymal stem cells through novel signaling pathways, Int. J. Biochem. Cell Biol. 43 (11) (2011) 1591–1601. [125] M. Reichenbach, P.L. Mendez, C. da Silva Madaleno, V. Ugorets, P. Rikeit, S. Boerno, et al., Differential impact of fluid shear stress and yap/taz on bmp/tgf-β induced osteogenic target genes, Adv. Biol. 5 (2) (2021), e2000051. [126] L. Chang, M. Karin, Mammalian map kinase signalling cascades, Nature 410 (6824) (2001) 37–40. [127] E.K. Kim, E.J. Choi, Compromised mapk signaling in human diseases: an update, Arch. Toxicol. 89 (6) (2015) 867–882. [128] C. Thouverey, J. Caverzasio, Focus on the p38 MAPK signaling pathway in bone development and maintenance, Bonekey Rep. 4 (2015) 711. [129] F.A. Peverali, E.K. Basdra, A.G. Papavassiliou, Stretch-mediated activation of selective mapk subtypes and potentiation of ap-1 binding in human osteoblastic cells, Mol. Med. 7 (1) (2001) 68–78. [130] D. Kletsas, E.K. Basdra, A.G. Papavassiliou, Effect of protein kinase inhibitors on the stretch-elicited c-fos and c-jun up-regulation in human pdl osteoblast-like cells, J. Cell. Physiol. 190 (3) (2002) 313–321. [131] H. Jessop, S. Rawlinson, A. Pitsillides, L. Lanyon, Mechanical strain and fluid movement both activate extracellular regulated kinase (erk) in osteoblast-like cells but via different signaling pathways, Bone 31 (1) (2002) 186–194. [132] D.J. Papachristou, P. Pirttiniemi, T. Kantomaa, A.G. Papavassiliou, E.K. Basdra, JNK/ ERK-AP-1/Runx2 induction “paves the way” to cartilage load-ignited chondroblastic differentiation, Histochem. Cell Biol. 124 (3) (2005) 215–223. [133] D. Papachristou, P. Pirttiniemi, T. Kantomaa, N. Agnantis, E.K. Basdra, FOS-and JUNrelated transcription factors are involved in the signal transduction pathway of mechanical loading in condylar chondrocytes, Eur. J. Orthodontics 28 (1) (2006) 20–26. [134] M. Wong, D. Carter, Articular cartilage functional histomorphology and mechanobiology: a research perspective, Bone 33 (1) (2003) 1–13. [135] P.G. Ziros, A.-P.R. Gil, T. Georgakopoulos, I. Habeos, D. Kletsas, E.K. Basdra, et al., The bone-specific transcriptional regulator cbfa1 is a target of mechanical signals in osteoblastic cells, J. Biol. Chem. 277 (26) (2002) 23934–23941. [136] Y.X. Yan, Y.W. Gong, Y. Guo, Q. Lv, C. Guo, Y. Zhuang, et al., Mechanical strain regulates osteoblast proliferation through integrin-mediated erk activation, PLoS One 7 (4) (2012), e35709.

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Chapter 6

Mechanobiology of osteoclast Yan Zhanga, Chen-xi Dia, Nai-ning Wanga, Fei Chena, Fan Zhaoa, Pai Penga, Zi-Han Qiua, Zhihao Chenb, Ling Zhangb, Lifang Hub, Yan Guoa, Airong Qianb, and Tie-Lin Yanga,* a

Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China, bLab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China * Corresponding author.

6.1

Introduction

Bone tissue is always undergoing dynamic changes and experiencing constantly changing mechanical stimuli, such as gravity, fluid shear stress (FSS) in the bloodstream, transmural pressure, mechanical stretching, differing extracellular matrix (ECM) stiffness, and more [1]. These mechanical forces affect bone tissues not only by instructing cell shape changes but also by influencing various cellular processes. Abnormalities in the process of bone reconstruction regulate bone metabolism, leading to changes in bone internal structure and homeostasis, which in turn affect bone mechanical properties. Osteoclasts (OCs) are the only cells that perform bone resorption during bone remodeling, which is also stimulated by many different mechanical forces to regulate their formation and differentiation processes [2]. OCs are terminally differentiated cells in bone [3]. Mouse primary pre-OCs and the RAW264.7 pre-OC cell line, which are widely used in the study of OC mechanobiology, are treated with receptor activator for nuclear factor-κB ligand (RANKL) to mimic the physiological processes of mature OCs. Growing evidence suggested that OCs are regulated by some key genes or proteins and have vital functions and effects in different mechanical conditions or models [4–6]. Hence, it is necessary to further understand the property and mechanism of diverse mechanical stimuli regulating OCs. Here, we summarize the effects and mechanisms of mechanobiology on OC formation, differentiation, and physiological functions to provide new insight into mechanobiology research. Bone Cell Biomechanics, Mechanobiology, and Bone Diseases. https://doi.org/10.1016/B978-0-323-96123-3.00009-9 Copyright © 2024 Elsevier Inc. All rights reserved.

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6.2 Osteoclast characteristics OCs originate from mononuclear precursors of the hematopoietic lineage cell (Fig. 6.1), form active multinucleated large cells after fusion and differentiation, and further secrete a variety of enzymes to dissolve minerals in bone tissue. They are the only cells with bone resorption function [3]. OCs attached to the bone matrix form the ruffled border, which is developed by mixing secreted lysosomes with plasma membrane resulting in a curled cell membrane. The actin filament ring of OCs surrounds the fold boundary of the sealed area, isolating the acidified microenvironment in the cell from the rest of the extracellular space, allowing for better dissolution of the minerals in the bone and destroying bone organic matrix [7]. The formation and differentiation of OCs are regulated by two key OC factors: macrophage-stimulating factor (M-CSF) and RANKL [7]. Moreover, OCs are mechanosensitive cells, and a series of stimulation factors participate in the process of their activation, including bone morphogenetic protein (BMP), tumor necrosis factor (TNF), interferon-γ (IFN-γ), transforming factor-β (TGF-β), and interleukin (IL)-1β, -6, -11, and -17 [8]. Disorders of OC formation, activation, and differentiation may cause many diseases, for example, osteoporosis, osteosclerosis, osteoarthritis, osteogenesis imperfecta, rheumatoid arthritis, periodontitis, bone metastasis of cancer, Paget’s bone disease, and marble bone disease. Thus, it is important to understand the osteoclastogenesis process and OC function.

6.3 Mechanical stimuli of osteoclast Mechanical stimulation is vital for bone tissue growth and development, and different types and intensities of mechanical stress constantly adjust metabolic homeostasis of bone. OCs respond to mechanical stimulation including FSS, vibration, connective tissue stretching and compression, hydrostatic pressure (HP), unloading, and other stimuli. This mechanosensing has a critical effect

FIG. 6.1 Osteoclast differentiation.

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on bone resorption and bone remodeling, which may prove helpful in developing treatment strategies for related diseases [2].

6.3.1

FSS in osteoclast mechanobiology

FSS produced by the flow of pericellular fluid inevitably transduces mechanical stimulation to mechanosensitive cells, such as marrow-derived cells [9]. Previous studies have shown that OC differentiation can be accelerated by FSS in a variety of ways [10]. For example, FSS enhances OC function through the extracellular signal-regulated kinase 5 (ERK5) signaling pathway, [10] calcium oscillation, and more [11,12]. Cyclic FSS for RAW264.7 cells was applied in parallel-plate flow chambers for 30 minutes per day to investigate the influence of various types of FSS on OC functions. The study found that FSS had no effect on the proliferation and death of RAW264.7 cells, also had no cytotoxic to RAW264.7 cells induced by RANKL [10]. In addition, FSS (12 dyn/cm2) for 30 min/day significantly suppressed OC differentiation via the ERK5 pathway by reducing the expression of nuclear factor of activated T cells 1 (NFATc1) and its downstream marker genes, for example, matrix metallopeptidase-9 (MMP9), tartrate-resistant acid phosphatase-5b (TRAcP-5b), and cathepsin K (CTSK) [10]. Furthermore, the migration and differentiation progress of monocytes (OC precursors) also rely on FSS gradients. To detect the magnitude of a gradient FSS flow field by a fluid chamber device, and to investigate the effects of gradient FSS on cell migrations, cell aggregations, and cell fusion in RAW264.7, finite element analysis of FSS and particle image velocimetry measurements were carried out [13]. When exposed to gradient FSS after 40 min, OC precursor RAW264.7 cells radially moved toward the area of decreased FSS but did not follow the direction of fluid flow [13]. RAW264.7 cell migration to the lower FSS area was markedly impeded when the calcium signaling pathway was suppressed via thioprostane and gadolinium [13]. RAW264.7 cells also exhibited remarkably greater cell density and proportion of mature OCs in the low FSS area than that in the high FSS area after culturing for 6 days under gradient FSS stimulation [13]. Thus, OC precursor cells may be regulated by calcium signaling pathways, which exhibit a notable capability to respond to FSS gradients, and have the tendency to exhibit active migration to low FSS areas [13]. Additionally, the induction of OC formation can be controlled via the combination of high shear stress amplitude and extended stimulation duration in hematopoietic progenitor cells [14]. Mouse hematopoietic progenitor cells originated from mouse bone marrow can respond to an active fluid flow stimulation for 2 min through a precisely controlled FSS [14]. It is noteworthy that the effect of the peak wall shear stress rate on the sensitivity of OC precursor cells to FSS is not apparent [14]. In general, it indicated that hematopoietic progenitor cells respond to FSS because of a cooperation of high shear stress amplitudes and

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extended duty cycles required to induce the bone destruction response [14]. Moreover, high-load amplitude lead to bone damage, and the severity of bone damage would increase with the duration of high-load amplitude [14]. Bratengeier et al. also found that the mechanical responsive protein, Piezo-type mechanosensitive ion channel component 1 (Piezo1), could explain this phenomenon. Piezo1 can induce OC differentiation leading to bone destruction response and modify OC differentiation via being regulated by amplitude and duration of external mechanical stimulation [15]. Low stimulation amplitude results in the change of Piezo1 and SERCA2 (the potential inhibitor of Piezo1), low concentration of extracellular adenosine triphosphate (ATP), enhanced Ca2+ concentration in the sarcoplasmic and cell endoplasmic reticulum, and suppression of OC formation and absorption, whereas high amplitude usually causes a bone destruction response [14]. Under a certain amplitude of 3 Pa and square waveform, individual stimulation duration (duty cycle) significantly affects the release of ATP, the number of OCs, and the area of bone resorption [14]. In conclusion, the magnitude and duration of FSS stimulation can affect the differentiation of OCs and the resorption of the bone. Moreover, migration of OC precursors is also dependent on the FSS gradient.

6.3.2 Vibration in osteoclast mechanobiology Vibration stimulates the formation of alveolar bone through high-frequency acceleration (HFA) under physiological conditions and during the healing process after tooth extraction. In vivo, the maxillary first molars of rats were treated with HFA for 5 min per day over 28 or 56 days [16]. The alveolar bone mass in the osteoporosis-ovariectomized (OVX) rat can be restored to a level of the sham (control)-OVX rat by vibration, which did not remove the ovaries but underwent surgery. Furthermore, HFA-treated rats showed greater osteoblast (OB) activity and lesser OC activity [16], suggesting that HFA could improve bone density in osteoporosis and restore alveolar bone. The expressions of Runx2, Osterix, Foxo1, and Wnt signaling pathway-related factors were increased after vibration, and RANKL/RANK and sclerostin expressions were simultaneously inhibited. HFA did not influence the serum levels of TRAcP-5b and C-terminal telopeptide-1 (CTX-1) [16]. When the vibration gradients were locally applied to the alveolar bone of osteoporotic rats, anabolism increased and catabolism decreased [16]. In summary, the therapeutic influence on the alveolar bone of osteoporotic rats induced through local vibration indicated that HFA could be used to prevent the reduction of alveolar bone in osteoporotic patients. Low-amplitude high-frequency vibration (LMHFV) of < 1 g acceleration and g ¼ 9.81 m/s2 at 20–90 Hz applied to OC precursors reduced OC formation[17,18]. RAW264.7 cells were subjected to LMHFV at 0.3 g at 45 Hz for 15 min/day, which reduced formation of TRAP+ multinucleated cells and actin

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ring as well as marker gene expression, such as CTSK, TCP5, matrix metallopeptidase 9 (MMP9), and c-Fos [17]. In addition, vibration enhanced the movement of orthodontic tooth via promoting alveolar bone absorption [19]. Micropulse vibration could expedite the speed of tooth movement in the process of orthodontic treatment [20]. The vibration applied to the RAW264.7 cells promoted cell proliferation, however, it did not impact cell differentiation into mature OCs [19]. Osteocytes can sense various frequencies of LMHF vibrations (0.3 g at 30, 60, and 90 Hz for 1 h) and react by synthesizing soluble factors that suppress OC formation [18]. Micro-pulse vibration on bone cells at 30 Hz increased generation of soluble factors that inhibit osteoclastogenesis, thereby increasing bone density [20]. In general, osteocytes respond to mechanical stimuli such as LMHFV and micro-pulse vibration to produce soluble factors that inhibit osteoclastogenesis and reduce OC size. The mechanical vibration for OC-like cells represses osteoclastogenesis. In one study, RAW264.7 cells were treated with mechanical vibration with a displacement of 20 μm at 4 Hz for 1 h continuously for 3 days. At day 5, the RAW264.7 cell line was induced with 20 ng/mL RANKL. Results show that the gene and protein expression of the dendritic cell-specific transmembrane protein (DC-STAMP) was markedly reduced and P2X7R gene expression was unchanged [21]. In addition, using DC-STAMP antibody decreased osteoclastogenesis without vibration, indicating that mechanical vibration suppressed osteoclastogenesis by decreasing the expression of DC-STAMP receptors [21]. Takano-Yamamoto et al. developed a novel vibration device made of bent 0.014-in. nickel-titanium (Ni-Ti) wires for accelerating the model of tooth movement in rats and found that the most effective vibration level treated with a sustaining static force is 3 g at 70 Hz for 3 min/week [22]. Continuously applying static force to the teeth under this optimal amplitude, high-frequency vibration can activate the NF-κB signal to promote OC formation and function, enhance alveolar resorption of bone, and ultimately accelerate the movement of tooth [22]. Nishimura et al. moved the first molars of male rats to the buccal side for 21 days using an expansion spring and measured the degree of tooth movements [23]. Simultaneously, during the orthodontic tooth movements (OTMs), additional vibrations (60 Hz, 1.0 m/s2) were implemented to the rat first molar through the load vibration system on days 0, 7, and 14 [23]. Vibration accelerated the movement of the rat teeth [23]. It also increased RANKL expression of periodontal ligament fibroblasts and OCs on day 3 and the quantity of OCs on day 8 [23]. Histologically, pathological findings and apparent difference in the amount of root resorption were not found between the vibration and control groups [23]. To decrease bone loss in disabled children and osteoporotic women, lowintensity vibration (LIV) has been proposed. Spinal cord injury (SCI) is a potential cause of rapid bone loss [24]. In female rats with moderately severe

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contusion of the mid-thoracic spinal cord, the effects of LIV were detected on day 28 after SCI and treated 15 min twice/day, 5 days per week for 35 days. LIV did not change the bone mineral density (BMD) of distal femurs and proximal tibia, but it did prevent a decrease in serum osteocalcin after SCI [24]. Moreover, LIV significantly inhibited the OC formation capacity of bone marrow precursors but did not alter the C-terminal telopeptide (CTX) content in serum [24]. These findings indicate that LIV could improve bone turnover and reduce OC formation. Furthermore, LIV initiated earlier and/or for a longer duration after SCI may promote bone mass [24]. These results suggest that osteoclastogenesis and bone resorption are regulated by vibration.

6.3.3 Mechanical Stretch in osteoclast mechanobiology OCs can perceive their mechanical micro-environment and dynamically regulate bone matrix absorption. Our current study used mouse RAW264.7 cells treated with RANKL to explore the role of mechanical stretching in OC properties and bone-resorbing activity [25]. To explore the role of cyclic tension stress in OC apoptosis in vitro, RAW264.7 cells with RANKL were cultured in the load carrier and stimulated with periodic cyclic tensile micro-strain. Activated OCs were treated with 0%, 5%, 10%, and 15% stretch micro-strain for 1 h/day for 3 days [26]. Tensile micro-strains of 10% and 15% resulted in an increase for osteoclastogenesis and the resorption area [26]. In addition, 5%, 10%, and 15% tensile microstrains reduced early cell apoptosis rate through annexin V binding experiments. Tensile micro-strains of 5%, 10%, and 15% increased the ratio of Bcl-2/Bax mRNA expression and reduced the expression of caspase-3 in induced RAW264.7 cells [26]. Tensile micro-strains of 10% and 15% significantly inhibited cytochrome C; however, 5% tensile strain had no obvious effect on the expression of cytochrome C in OCs [26]. In general, cyclic tension stress (10% and 15% stretch micro-strain) may suppress OC apoptosis by promoting the expression ratio of Bcl-2/Bax, inhibiting the expression of caspase-3, and downregulating cytochrome C expression [26]. Kurata et al. developed a mechanical stretching apparatus to culture cells on an ivory slice/plastic plate assembly [25]. Under intermittent tensile strain, mature and activated OCs were seeded on the ivory/plate assembly for 2, 12, and 24 h [25]. The mechanical stretching promoted the mRNA expression of TRAP and CTSK, and increased formation of resorption pits, indicating that mechanical stretching enhanced bone absorption activity of OCs [25]. In addition, stretch-activated cationic (SA-cat) channel blocker gadolinium remarkably decreased pit formation after 24 h of stretching [25]. This research showed that activated OCs may respond to mechanical stretching by modulating the SA-cat channel, therefore enhancing bone resorption activity [25]. Moreover, in vitro, mechanical load suppressed the osteoclastogenesis of

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RAW264.7 cells by 1000 μstrain (μs) for 30 min of cyclic mechanical stretch at 1 Hz (twice per day) [27]. Further, this mechanical implementation inhibited antitartrate acid phosphatase activity secreted by RAW264.7 cells, decreased the number of multinucleated OCs, and reduced the level of MMP9 and the ability of extracellular calcium solvency [27]. Tsuzuki et al. studied the effect of membrane stretching caused by the swelling of osmotic cells on cytoplasmic Ca2+ and the bone resorption activity of freshly isolated rat OCs to evaluate the impact of mechanical stress for the function of OCs. They found that mechanical stress may be caused by an increase in the activation of nonselective cation channels by stretching to inhibit OC bone resorption [28]. In addition, Wiltink et al. found that OC membrane stretch triggered the self-reinforcing Ca2+ entry pathways [29]. Moreover, mechanical stretching could regulate the movement of OCs through nitric oxide (NO) [30]. NO stimulated guanylate cyclase and activated cGMP-dependent protein kinase 1 (PKG1), which could dynamically stop degradation of the cell matrix and OC attachment and initiate OC movement [30]. The movement of OCs induced by NO regulated the release of Ca2+ and activation of mμ-Calpain through Ins(1, 4, 5) P3R1 [30]. These studies show that different mechanical tensile strengths and durations significantly affect OC formation, apoptosis, and bone resorption activities. It is worth noting that they may also lead to completely opposite functions of OCs.

6.3.4

Compressive force in osteoclast mechanobiology

Compression force participates in various physiological processes in the body and has a crucial effect during bone remodeling. Bone-related cells are also constantly subjected to compression force, which affects the physiological function of cells. To study the effect of compression force on OCs, several models and apparatuses have been utilized. For example, RAW264.7 was induced by RANKL and cells were continuously stimulated by increasing the amount of culture medium with a compressive force of 0.3, 0.6, and 1.1 g/cm2 [31]. With RANKL, the number of mature multinucleated cells and the mRNA levels of DC-STAMP and OC-STAMP were significantly increased under the compression forces of 0.6 and 1.1 g/cm2 compared with the compression force of 0.3 g/cm2 [31]. When lacking RANKL, 0.6 and 1.1 g/cm2 compression forces inhibited expression level of another RANKL receptor-LGR4 mRNA compared with 0.3 g/cm2. With RANKL, compressive force of 0.6 and 1.1 g/cm2 promoted the nuclear translocation ratio of activated NFATc1 [31]. On day 4 of RAW264.7 cell culture, 3-, 5-, 7-, 9-, or 14-layer glass coverslips were used to apply compressive force to the cells to explore the role of compressive force in the formation of OCs. OCs generally formed rapidly on days 4 and 5 of induction [32]. The study found that when seven slips forces are applied, which is the optimal

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compressive force for the RWA264.7 cells, the number of multinucleated (>8 nuclei) OCs is the greatest [32]. The differentiation and fusion of RWA264.7 cells in response to compressive force are linked to the changes in the expression of OC marker genes [32]. When the optimal compression force lasts for 3 h, the mRNA expression of OC marker genes is remarkably promoted. Macrophages could accelerate the formation of OCs when the optimal compressive force is employed [32]. For primary cells, mechanical force promotes OC differentiation in bone marrow monocytes or macrophages (BMMs) without the presence of other mechanically sensitive cells [33]. TNF-α-induced osteoclastogenesis of BMMs was accelerated when a compression mechanical force of 10–200 g/cm2 for a duration of 1 h was applied to BMMs; anti-TNF-α and anti-TNF-α receptors could inhibit this increase [33]. Moreover, TNF-α could directly stimulate c-Fms-mediated signaling and partly activate the role of RANKL in regulating OC formation and bone resorption, which are promoted via compressive forces [33]. Li et al. found that growth differentiation factor 15 (GDF15), as a new compressive force-responsive gene, promoted macrophage line RAW264.7 cells differentiated into OCs. In addition, the M1-like macrophage polarization of RAW264.7 cells was stimulated by the recombinant GDF15 protein [34]. After suppressing GDF15 expression when compressive force was applied, nuclear translocation of NF-κB and phosphorylation of ERK were blocked, suggesting that GDF15 played an essential part in the response to compression forces of OC precursor cells [34]. Forkhead box protein M1 (FOXM1) is also a new mechanical stress response gene. Inhibition of FOXM1 promotes the differentiation of RAW264.7 cells into activated multinucleated OCs by compressive force [35]. There are new insights for the molecular mechanism of mechanotransduction during OTM [34,35]. To accelerate tooth rearrangement, mechanical force is usually taken to teeth during orthodontic treatment, and this mechanical force accelerates the maturation and fusion of OC precursors, thereby forming multinucleated OCs [36]. Orthodontic forces include tensile, compressive, and other complex forces, however, the effect of direct compressive forces on OCs remains unclear. Mechanical tension was implemented to RAW267.4 cells spread on a force loading plate through a force four-point bending strength device with frequency of 0.5 Hz and cyclic uniaxial tension stimulation of 0, 2000, 4000, and 6000 μs for 6 h per day [36]. Compressive forces increased OC maturation by TRAP staining and invasive pseudopodia formation by F-actin immunofluorescence staining [36]. Furthermore, in RAW264.7 cells, the compressive forces increased the expression of ETS-1 and TKS5 genes and increased ETS-1 activation [36]. In addition, ETS-1 mediated the effect of compressive forces on TKS5 elevation, invasive pseudopodia formation, and OC fusion [36]. All current studies indicated that compressive force could obviously promote invasive pseudopodia formation and OC formation (Fig. 6.2), maturation, and fusion.

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FIG. 6.2 Compressive force promoted osteoclastogenesis and bone resorption.

6.3.5 Mechanical unloading microgravity in osteoclast mechanobiology Mechanical forces are vital for maintaining bone integrity, but exposure to microgravity can cause bone loss. In the space microgravity environment or bed rest, mechanical unloading can suppress the formation of bone and stimulate the resorption of bone. It is crucial to prevent bone loss triggered by longterm mechanical unloading to cope with the challenges posed by long-term stays in space and the upcoming super-aging society. Due to the limitation of the frequency and payload of space flight, it is necessary to establish in vitro or in vivo systems that simulate different conditions of microgravity. Mechanical unloading can cause disused muscle atrophy and bone loss. Current studies have demonstrated that OCs play an essential role in responding to different gravity environment [37–39]. The modeled microgravity (MMG) system is used to investigate the change of OC precursors in vitro [37]. MMG itself could not induce OC precursors to differentiate into mature OCs, but MMG treatment for 24 h could activate signal molecules related to OC formation, such as ERK, p38, PLCγ2, and NFATc1 [37]. RANKL stimulation for 3–4 days (with or without M-CSF) and 24 h of MMG treatment promoted OC multinucleated cell activation, as well as the expression of TRAP and CTSK [37]. A 5-day space flight on the COSMOS 1514 biological satellite promoted the quantity of TRAP+ OCs per square millimeter of the thoracic and lumbar spine, and a 14-day flight shuttle on COSMOS 2044 promoted the tibia metaphysis of male Wistar rat OC number and bone resorption activity [38,39]. The hindlimb unloading (HLU) system was used to simulate the microgravity environment (Fig. 6.3). It was found that the HLU of BALB/c mice resulted

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FIG. 6.3 Mechanical unloading increased osteoclastogenesis and bone resorption.

in the reduction of femoral BMD and the deficiency of the 3D micro-structure of cortical bones and trabecular bones [37]. OC precursor cells removed from the tibia of mice 28 days after HLU were stimulated by RANKL to promote OC formation [37]. Contrary to the previously reported findings, Saxena et al. did not observe any histomorphological changes in bone formation parameters [37]. Further, the bone deficiency triggered by mechanical unloading could be prevented by interference with NF-κB1. Mechanical stimulation and inflammatory cytokines also activated the transcription factor NF-κB [40]. Two weeks after eight-week-old mice underwent HLU, the bone mass of tibia and femur of WT mice was significantly reduced, but the bone mass of NF-κB1 deficiency mice did not change [40]. Loss of NF-κB1 can be inhibited by unloadinginduced bone loss through suppressing RANK downstream signaling in OC precursors [40]. Therefore, NF-κB1 may have an essential effect on the rapid reduction of bone mass triggered by space or bed rest disuse osteoporosis [40]. In addition, HLU treatment for 14 days increased the amount of OC in the proximal tibia of mice, and the lack of muscle-specific RING finger-1 (MURF1) inhibited the increase of OCs after unloading, indicating that MURF1 regulated disuse bone loss in OC bone resorption [41]. An HLU model and a random positioning machine (RPM) was used by Lin et al. to explore the functions of microgravity on mouse primary pre-OCs and the RAW264.7 pre-OC cell line. Results demonstrated that the signaling mechanism of microtubule actin crosslinking factor 1 (MACF1) in affecting pre-OC migration and cytoskeleton mimics the arrangement under different microgravity. MACF1 responded to microgravity simulation thereby promoting RhoA/ROCK1 expression, leading to increased actin and microtubule organization and enhanced pre-OC migration [2]. Eight-week-old mice were first executed to HLU for 4 weeks. Then, the mice were reloaded under the geomagnetic field (GMF) and static magnetic fields (SMFs) 0.2–0.4 T for 4 weeks. The number

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of OCs in trabecular bone and serum level of TRAP-5b in the reloaded group of mice were significantly reduced, indicating that SMF of 0.2–0.4 T promoted the restoration of bone loss caused by unloading via suppressing the increase of bone resorption in reloaded group mice [42]. These results show that number of OCs increased significantly after unloading, and the internal structure of the cells also changed. Bone can adjust to mechanical stimuli via bone remodeling and OCs approaching microdamage can likely trigger the resorption of bone. For example, OCs in the bone surrounding an implant are mechanically loaded during exercise or chewing. In addition, there are other different forces that also affect the formation and differentiation of OCs, which are critical for maintaining bone homeostasis.

6.4

Osteoclast mechanotransduction

Mechanotransduction, which regulates the fate of biological cells by physical forces, has been proven to occur in every process in biological cell growth and development, and its mechanisms are extremely complex and diverse. Living cells are usually continuously subjected to mechanical stimuli mediated by the surrounding ECM or by neighboring cells. Mechanotransduction is extremely important in mediating the timely adaptation of cells to constant dynamic changes in the microenvironment. The response and transmission of OCs to different mechanical stimuli is mediated by cytoskeletal elements, such as actin, microfilaments and microtubules, integrins on the membrane and other intracellular adhesion molecules, as well as cell membrane and nuclear mechanical sensors [3,43]. This complex mechanotransduction also involves cell extension kinases, gravity-sensing organelles, and thermal convection, and triggers various signaling pathways to regulated downstream gene expression. The reorganization of the actin cytoskeleton plays a key role in the movement, proliferation, and bone resorption of OCs [3,44]. A pivotal feature of OCs in the activation process is the F-actin rings around the cell induced by the remodeling of the actin cytoskeleton [45]. L-caldesmon can change the mechanical properties and cell surface adhesion of OCs induced by RANKL and promotes cell-cell fusion into multinucleated OCs during the process of osteoclastogenesis [45]. The bone matrix adheres to the surface of cells and regulates the interaction between the cells and its peripheral ECM and regulates the physiological functions of OCs, such as cell formation, proliferation, growth, division, migration, adhesion, differentiation, and autophagy. Vinculin is the main regulatory protein in the process of cell adhesion; meanwhile, it is stuck to the cell surface via interacting with specific phospholipids in the adhesion complex [1]. It has become an important trait of neonatal cell matrix adhesion and serves as a scaffold for maintaining some actin tissue proteins. The distribution of vinculin in OCs is mainly concentrated around clustered nuclei. As the expression of

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vinculin in the soft substrate is significantly decreased, the response intensity of OCs to soft substrates also decreases [1]. In mature focal adhesions, vinculin also controls the transfer of mechanical forces from OC membrane-bound integrin to cytoplasmic F-actin [1]. Cell-matrix adhesion is a significant part for many cells to perform their physiological functions. OCs can change their cell-matrix connection to regulate their response to external stimuli. Integrins are a prerequisite for mediating cell-matrix and cell-cell interactions in OCs [44,46]. They respond to a variety of extracellular physical stimuli and interact with different ECM proteins. When OCs are subjected to some mechanical stimulation, the integrins are activated and widely expressed, recruiting cytoskeletal molecules such as F-actin, vinculin, paxillin, and gelsolin to the adhesion contact area [46]. All these results demonstrate that integrins have a key effect on regulating OC adhesion and bone matrix, reorganizing the cytoskeleton, and controlling calcium homeostasis in response to mechanical stimuli. Notably, many cytokines (e.g., IL-1, IL-6, IL-12, TNF-α, and IFN-γ) play important roles in the mechanical regulation of the formation of OCs and bone resorption via triggering different intracellular signaling pathways [47]. NF-κB kinase inhibitor (IKK), c-Jun N-terminal kinase (JNK), p38, ERK, and Srcmediated signal cascades are activated in the process of OC formation and activation [48]. TNF-α triggers c-Fms-mediated signaling pathways and triggers the role of RANKL in regulating osteoclastogenesis and bone resorption, which are facilitated by compressive forces [33]. The reduction of NF-κB1 inhibits the increase of bone resorption induced by unloading because it prevents the intracellular signal transduction process of the RANKL receptor activator in the OC precursor [40]. Microgravity simulation induced the RhoA/ROCK1 signaling pathway, leading to a rearrangement of the cytoskeleton of OCs, and promoted the migration of pre-OCs [2]. Centrifugal force inhibited osteoclastogenesis through ERK signal activation [49]. In addition, OCs can migrate to regions with low FSS stimulation in response to FSS gradients changes, and this process is regulated by calcium signaling pathway [13]. Thus, mechanical stimulation can regulate different signaling pathways to control the function of OCs and maintain the balance of bone metabolism.

6.5 Conclusion and perspectives Moderate mechanical stress stimulation is critical for maintaining bone homeostasis [1]. OCs, as mechanosensitive cells, are some of the key regulators in maintaining bone homeostasis [2,4–6]. Mechanical stimuli such as FSS, mechanical vibration, mechanical tension stress, compression force, and gravity have different effects on OC formation, differentiation, and apoptosis [1]. OC cytoskeletal elements, membrane integrins, intracellular adhesion molecules, and membrane and nuclear mechanosensors respond to various mechanical stimuli that trigger calcium channels and NF-κB, ERK, and RhoA/ROCK1

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signaling. This signaling further leads to changes in downstream gene expression that regulates OC morphology and function [1,2,46,49]. Multinucleated OCs are formed from mononuclear OC precursor cells through cell-cell fusion [50]. In addition, mature OCs can separate themselves into smaller functional multinucleated cells via fission [50,51]. OC fusion and fission during the formation and performance of bone resorption fully demonstrates that OCs can flexibly regulate population and property to rapidly adjust to changing environments [50–52]. These studies provide some new insights into the dynamics of cell-cell interaction in osteoclastogenesis and shed new light on the study of OC responses to mechanical stimuli. However, the mechanism of mechanical stimulation in OC fission remains unclear and thus requires further in-depth investigation. At present, many studies on OCs and mechanics are in vitro studies. Thus, the real situation of OC responses to mechanical stimulation during bone resorption in vivo needs to be further explored. With the update of advanced imaging systems, two-photon microscopy has been used to observe the behaviors of mature OCs and their precursor cells in the bone marrow cavities during inflammatory bone destruction in vivo [53]. This will provide insight into how OCs respond to mechanical stimuli in vivo. In this chapter, we summarized the role and mechanism of OCs in mechanobiology, demonstrating that OCs are mechanosensitive cells that play an important role in mechanobiology. This information promotes better understanding of the physiological function and mechanism of bone mechanobiology as well as bone-related disease.

Acknowledgments The work of this chapter was supported by the China Postdoctoral Science Foundation (2021M692582), Natural Science Basic Research Program of Shaanxi Province (2022JQ808) and the Fundamental Research Funds for the Central Universities (xzy012022032).

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Chapter 7

Mechanobiology of osteocytes Shaopeng Peia, Murtaza Wasib, Shubo Wangb, Tiankuo Chub, Rosa M. Guerrab, and Liyun Wangb,* a

Department of Orthopedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States, bCenter for Biomechanical Engineering Research, Department of Mechanical Engineering, University of Delaware, Newark, DE, United States * Corresponding author.

7.1

Introduction

The question of how bone cells detect and respond to external mechanical stimuli is fundamentally important in skeletal physiology. This capability, at least partially, defines bones as being “living” and “adaptive” in contrast to being purely mineralized objects like rocks. The journey of finding answers to this question has led to our improved understanding of bone biology and effective treatments for osteoporosis. The subject of this chapter is osteocytes (Ocy), the major mechanosensing cells in bone. They are the terminally differentiated cells of the osteogenic lineage including mesenchymal stromal (stem) cells and bone-forming osteoblasts (OBs). Both topics are discussed in other chapters of this book. Osteocytes, the most abundant cells in adult bone tissue, account for approximately 90%–95% of the total bone cell population. Because they are dispersed in bone matrix and spatially positioned away from bone surfaces where bone formation and/or bone resorption occur, osteocytes had been viewed as “passive placeholders.” However, data accumulated during the past three decades reveal the crucial regulatory roles that osteocytes play in bone growth, repair, and maintenance under biochemical and mechanical cues. This chapter examines how osteocytes sense and respond to mechanical stimulations at the cellular and molecular levels, as well as the signaling pathways by which osteocytes orchestrate osteoblastic bone formation and osteoclastic bone resorption driven by external mechanical cues. This choice is justified by the mechanical capacity of the skeleton in weight bearing, locomotion, and shielding and protecting internal organs. The impacts of hormonal and biochemical cues on osteocytes function have been reviewed elsewhere in the literature [1] and will not be detailed herein. Bone Cell Biomechanics, Mechanobiology, and Bone Diseases. https://doi.org/10.1016/B978-0-323-96123-3.00010-5 Copyright © 2024 Elsevier Inc. All rights reserved.

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We aim to balance the biological and engineering contents in this overview of osteocyte mechanosensing and mechanotransduction. Our intended audience include engineering students with limited bone biology background as well as biology students or medical trainees without prior exposure of biomechanics. Please note that only selected primary and review literatures are referenced for brevity. We apologize in advance to the many authors whose studies have moved the field but are not discussed herein due to space limitation. The readers are also referred to several excellent reviews for in-depth discussion of osteocyte viability, signaling, and crosstalk (Bonewald [2]; Dallas et al. [1], Schaffler et al. [3], Robling and Bonewald [4]). First, we first introduce the characteristics of osteocytes and the osteocytic network (Section 7.2), as well as the lacunar-canalicular pore system (LCS) and load-induced fluid flow in osteocyte mechanosensing and mechanotransduction (Section 7.3). We then review the molecular entities of the sensing complex, the temporal responses and intracellular signaling pathways involved in osteocyte mechanotransduction, and altered osteocyte mechanotransduction in disease conditions (Section 7.4). The chapter concludes with a short summary and prospective for future studies (Section 7.5).

7.2 Osteocytes 7.2.1 Osteocyte characteristics When one examines a piece of mineralized bone under a microscope, they would be amazed by the “star-like” osteocytes (Fig. 7.1). The cell bodies are prolate spheroids with a major diameter of
10–20 μm and the other two orthogonal minor diameters of
8–10 μm (Fig. 7.1A,B). Prominently, the dendritic cell processes (
50–100) emanating from individual osteocytes perforate the matrix in such a high frequency that the distance between any point of bone matrix to the nearest cell process is within a couples of microns (Fig. 7.1A,B). The osteocytes, with a typical cell-cell spacing of 30–50 μm, are dispersed within concentric lamella (Fig. 7.1C). One can appreciate the extensiveness of this cellular network, which consists of osteocytes embedded in the bone matrix, blood vessels in the vascular pores, and OBs and osteoclasts (OCs) on the bone surface. Although the size and shape of osteocytic cell bodies may vary with species (human vs. murine), bone sites (trabecular vs. cortical), or bone types (calvarial vs. long bone), the conserved feature of osteocytes is their extensive cellular connectivity. Thus, the functions of osteocytes should not be viewed individually but in the context of a cellular network. All things connected—Osteocytes as the “brain” of the skeleton: The osteocytic network in bone shows high morphological and functional similarities to the neural network in the brain. Buenzli and Sims [5] estimated that, for a human body, there are similar tissue volume of bone (1.75 L) and brain (1.2 L). The bone contains 42 billion osteocytes, 23 trillion OC connections,

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FIG. 7.1 Confocal fluorescent imaging of osteocyte (Ocy) network embedded in collagen bone matrix. (A) The star-shaped Ocy with extensive dendritic cell processes (P) were labeled with sodium fluorescein (green) and shown to form an interconnecting cellular network within a cross-section of tibial cortex of adult mice. (B) A longitudinal section shows the connection between the blood vessel (BV, red arrow) and Ocy. The cell nuclei (blue) were labeled with Hoechst 33342. (C) The Ocy are well distributed in concentric bone lamella consisting of collagen bundles (purple, second harmonic imaging).

and 175,000 km of total dendritic process length, while the brain contains 86 billion neurons, 150 trillion neural cortex synapses, and 150,000–180,000 km of neuron dendrites. Besides these topological features, there are other functional similarities between osteocytic and neural networks. First, signaling molecules are propagated in the osteocytic network through the gap junctions between opposing dendrites and the extracellular fluid space along the dendrites [6], which is similar to the biochemical signaling and electric potentials that propagate over synapses and axons in a neural network. Second, osteocytes, like neurons, are terminally differentiated cells with a long life span up to 50 years in humans [7]. Third, both osteocytic and neural networks show topological

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stability at the network level. Neural dendrites and synapses remain very stable after the postnatal explosive growth. Osteocytic dendrites are rich in actin cytoskeleton and gap junctions, two prerequisites for stable connectivity. In adult mice, we find that despite large variations of osteocyte size and spacing, the number density of canaliculi housing the cell processes per unit surface area of lacuna housing the cell body is conserved (one canaliculus every 5 μm2 lacunar surface area) in several transgenic mice including wildtype, diabetic, and perlecan-deficient mutants regardless of trabecular or cortical bone compartments [8]. The osteocytic network also differs from the neural network, in that osteocytes are fully encased in mineralized matrix and the signaling molecules are constrained within the pericellular fluid space in the LCS (detailed in Section 7.3). Such physical constraint is not seen in brain. However, one can appreciate the large exchange area due to the number of dendrites (and canaliculi), which is almost sevenfold of that in the gastrointestinal tract. Taken together, osteocytes in mineralized bone tissue form a neural-like network, which contains extensive and stable intracellular and extracellular communication conduits. Such a network enables the propagation of signaling molecules, triggers cellular responses of effective cells at the edge of the network, and eventually leads to bone’s adaptation under external mechanical cues. Origin and maturation of an osteocyte: Osteocytes arise from matrixproducing OBs, as some of the OBs become buried in the newly formed osteoid. Based on histological observations, Bonewald et al. suggested that the osteocyte goes through four differentiation stages: OB, osteoid osteocyte, mineralizing osteocyte, and mature osteocyte (figure 1 in reference [2]). The transition from OBs to osteocytes is more dynamic than the 2D histological section suggests. A series of real-time confocal imaging of living osteocytes in cultured calvarial explants by Dallas et al. demonstrated that newly embedded osteocytes can change their cell body and dendrites while actively modify their surrounding collagens (reviewed in [9,10]). Using dentin matrix protein 1 (DMP1) reporter mice, the team further showed that upon turning on DMP1 expression in osteocytes, matrix mineralization proceeds, leading to the formation of a hydroxyapatite cave of lacunae and many tinny tunnels of canaliculi to house the cell body and dendrites [11]. Eventually, the mineralizing osteocyte becomes a functional part of the osteocyte network, although the exact mechanisms are still elusive. In addition to different morphological features, the cells express differentially expressed markers, such as keratocan (KTN) for OBs, E11/ gp38 (E11) for early embedding osteocytes, DMP1 for an early osteocyte marker responsible for mineralization, neuropeptide Y (NPY; a neurotransmitter) for maturing osteocytes, and matrix extracellular phosphoglycoprotein (MEPE) and sclerostin-encoding gene (SOST) for mature osteocytes (figure 1 in reference [4]). Do mechanical factors affect the formation (birth) of osteocytes? The answer is likely yes. The rapidly formed woven bone under overloading or during endochondral bone formation in fracture healing contains irregularly shaped osteocytes and dendrites compared with lamellar bone

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[12–14]. Mechanical loading also regulates the many factors involved in osteocyte formation and differentiation. The molecular control of osteocyte dendrite formation: The mechanisms that drive the dramatic transformation from a polygonal OB to a star-like osteocyte have been poorly understood until now. Insights into this mystery come from several transgenic mice showing distinct defective phenotypes of osteocytic dendrites and osteocytic network. The mice harbored mutations in OBs and osteocytes including the deletion of matrix metalloproteinases MT-MMP1 (also MMP14) [15] or MMP13 [16], Bcl-2 overexpression [17], and the deletion of SHP2 [18] or Sp7 [19]. The finding of reduced osteocytic dendrite number and length in mice with deficient MMPs reinforces the notion that the formation and maintenance of osteocyte phenotype and network requires continuous cleavage of collagens [15,16]. In 2021, Yang et al. [18] showed severely disrupted osteocytic dendrite formation in mice after deleting SHP2 protein tyrosine phosphatases in bone gamma-carboxyglutamate protein-expressing (Bglap+) bone cells. They also found that SHP2 promotes Runx2/Osterix signaling [18]. Interestingly, Wein et al. [19] further discovered that deletion of the Osterix-encoding Sp7 gene in mature OBs and osteocytes also caused osteocytic dendrite defects, and these defects could be rescued using the Sp7-targeting osteocrin, a factor secreted by OBs and early embedding osteocytes and increased by mechanical loading [20]. As these studies demonstrate, defective osteocytic dendrite and network formation lead to the death of osteocytes and impaired ability of osteocytes to regulate osteoblastic bone formation and osteoclastic bone resorption.

7.2.2

Osteocyte function

Life dedicated to sensing and signaling: During the long life span, osteocytes regulate mineral homeostasis and the structural integrity of the bone. The regular distribution of osteocytes in bone matrix, their extensive dendrite connections, and the intimate contact between osteocytes and the extracellular fluid space, a continuous conduit for transport, make them the ideal candidate to sense the mechanical load and relay the information to OBs and OCs on the bone surface, the major players in charge of bone remodeling. Although all bone cells are sensitive to mechanical loading [21], osteocytes show the greatest sensitivity to mechanical strains and are long believed to serve as the mechanical sensors in vivo [22,23]. Subsequent experimental studies provide strong support that osteocytes respond to mechanical stimulation at the cellular, molecular, and gene expression levels in a dose-dependent manner [4]. The application of Biot poroelasticity in porous bone matrix [24] showed that physiological loading associated with locomotion and exercise deforms the bone matrix, pressurizes interstitial fluid, and drives the fluid flow in the LCS [25]. The pericellular fluid flow interacts with various components of the osteocyte mechanosensing complex and results in the cellular and molecular responses in osteocytes. Meanwhile, mechanical loading also enhances solute transport in the LCS [26],

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facilitating the signaling between osteocytes with cells inside and outside of bone such as OBs and OCs. Not surprisingly, viable osteocytes are critical for optimizing the osteocyte network and ensuring bone homeostasis, as demonstrated by the development of severe osteoporosis after osteocytes were ablated by Tatsumi et al. [27]. There are many insults that can negatively impact the viability of osteocytes, including fatigue, micro-damage, immobilization, aging, chronic inflammation, elevated reactive oxidized stress, excess glucocorticoid, estrogen deficiency, and cancers [28]. As the long-living bone cells, osteocytes have evolved and developed defensive mechanisms, including the upregulation of hypoxia inducible factor (HIF) and antiapoptotic and autophagy pathways [29]. Autophagy is a “self-devouring” process that allows long-lived cells to preserve vitality and function in stressful conditions by degrading and recycling damaged organelles and macromolecules. Emerging data [29] support that physiological mechanical loading increases nutrient supplies and fluid flow stimulations, leading to potent anti-apoptotic and protective autophagy effects on osteocytes [30–32]. Thus, mechanical loading is not only the sensing target of the osteocyte network, but also a powerful “self-care” mechanism for a healthy osteocyte network. Dying is also a signal: Current consensus is that the apoptotic osteocytes signal to neighboring viable osteocytes, which produce cytokines like receptor activator of nuclear factor kappa-Β ligand (RANKL) and vascular endothelial growth factor (VEGF) for osteoclastogenesis and bone matrix remodeling, as demonstrated by Schaffler et al [3]. Not only healthy osteocytes but also dying ones can signal to fulfill physiological function (such as targeted repair of damaged matrix). However, widespread cell death could lead to the demise of the bone organ, as demonstrated in glucocorticoid-induced osteonecrosis and rapid bone loss when viable osteocytes were ablated [27,33]. The consequences of osteocyte death may depend on the connectivity of the LCS, as suggested by Komori [34–36]. Because osteocytes are fully encased in mineralized matrix, dead osteocytes cannot be easily removed by immune cells. Thus, in the case of a less connected LCS, as in Bcl-2 transgenic mice, the release of immunestimulatory molecules could be reduced, resulting in decreased OC activation [17]. Similarly, Komori argued that massive cell death in osteocyte ablation mice led to enhanced osteoclastogenesis [27] because the release of immunostimulatory signals was through the normal LCS. Osteocyte death leaves behind empty lacunae that can eventually fill in with minerals (micropetrosis), a process more commonly seen in aged bone and a possible compensatory mechanism to remove stress concentrator and thus reduce the risk of crack formation in bone matrix [4].

7.3 Mechanical stimulation of osteocytes 7.3.1 Lacunar-canalicular system in osteocyte mechanobiology The preceding section presents the key features of osteocytes, especially in the form of a cellular network. Before we discuss how osteocytes sense and respond

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to mechanical signals, a brief introduction of their physical dwelling is warranted. As mentioned earlier, one characteristic of mature osteocyte networks is the interconnected dendrites and ellipsoidal cell bodies, all of which are fully encased within but not in direct contact with the surrounding mineralized bone matrix. The mineralized walls surrounding the lacunae and canaliculi thus form a continuous system of channels and caves called the LCS. Within the LCS, the osteocytes are imbibed in the interstitial fluid, and the thickness of the fluid space between the cell and the mineralized wall, measured under transmission electron microscopy, is about 1 μm in lacunae and about 100 nm in canaliculi [8,37]. The overall architecture of the LCS has been visualized in undecalcified bone samples under confocal microscopy (Fig. 7.1) by perfusing basic fuchsin, fluorescein, or dextran, while the osteocyte cellular network can be visualized using reporter mice such as DMP-1creGFP mice or mT/mG mice or by staining the actin filaments of the cell body and processes, as shown by Dallas et al [10]. Everything that osteocytes need to survive and function has to go through the extracellular LCS pores [26] or intracellular gap junctions between opposing cell processes [6]. The transport characteristics have been revealed using semiquantitative tracer perfusion methods or quantitative imaging approaches (Wang [26]). Perfusion of various sized molecules in intact bone tissues revealed a cutoff size of 70 kDa in the LCS, highlighting the presence of a molecular sieve in the LCS, which is called the pericellular matrix (PCM) [26]. Molecular diffusivity and convection were further quantified using a method based on fluorescence recovery after photobleaching (FRAP). These results validated the theoretical prediction by Piekarski and Munro [38] that mechanical loading enhances nutrient exchange between bone and vasculature [39]. Thus, blood vessels penetrating the bone matrix serve as the transport highway for nutrient delivery, waste removal, and signaling with distant cells, while the LCS acts as the local routes that cover the last stretch of transport between the osteocytes and blood vessels (less than 0.2 mm). Although FRAP in live and postmortem bone did not show blood pressure itself being a major enhancer of convection inside LCS [40], the presence of the blood vessels and the intravascular transport are key to maintain proper metabolism in bone tissues. Weinbaum and Cowin pioneered the mathematical framework to analyze LCS permeability as a function of LCS porosity, pore size, and PCM density. The PCM fiber spacing is found to be the dominant determinant of the LCS permeability (Zeng et al. [25]; Lai et al. [41]). Our group further developed a hydraulic sieving model of the reflection coefficient based on the steric exclusion between the solute and the PCM fibers [39]. We subsequently predicted the enhanced transport as a possible response to the increased demand of calcium in lactating female skeleton where the LCS pores are enlarged and PCM is degraded to various degrees [41]. Besides the direct fluid-solid interactions between the PCM and fluid, Lemaire et al. [42] and their subsequent studies showed the negative charges of the PCM and their hydroelectrochemical effects, which increased the hydraulic resistance to fluid flow. These studies demonstrate that the PCM should be taken into account in LCS permeability

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when analyzing the fluid and solute transport fluxes in the LCS [41,43,44]. The integrity of the LCS is thus essential for osteocyte survival and functioning. The LCS anatomical features such as porosity, fluid gap, and PCM fiber spacing determine the LCS permeability, fluid pressure, and fluid flow. The physical signals (pressure and/or force) act on the various molecular sensors in osteocytes, leading to activation of mechanotransduction pathways and bone adaptation [45]. Some molecules associated in the osteocyte-matrix contacts have been identified. For example, Schaffler et al. discovered the tethering elements in the canaliculi as well as αvβ3 integrins along cell processes [37,46]. They and Jiang et al. further found that osteocyte dendrites are more sensitive to mechanical loading than the osteocytic cell body [47,48]. More recent studies showed that αvβ3 integrins are clustered with other known mechanical sensors such as Pannexin1, the purinergic receptor P2X7R and the T-type calcium channel CaV3.2-1, while knockdown αv integrins in vivo impairs the opening of Cx43 hemichannels and diminishes bone formation induced by loading [49,50]. Cx43 proteins not only “glue” the cell processes of neighboring osteocytes to form the cell network, but also serve as mechanical sensitive “windows” to connect the plasma domain with the extracellular conduits for autocrine and paracrine signaling [51]. Despite advances in identifying and studying the membrane mechanosensors (Qin et al. [52]), our understanding of the PCM remains quite limited due to technical challenges of preserving the fragile PCM in mineralized tissues. Taking advantage of the perfusion fixatives developed by Schaffler et al., Farach-Carson et al. identified perlecan, a large linear proteoglycan, as one major component of the PCM. Their single molecule measurements using AFM revealed that perlecan is long (100–200 nm) and strong enough (71 MPa elastic modulus, 150 nN break force) to serve as a flow sensor in bone [53,54]. The osteocyte LCS serves as an ideal site to amplify tissue-level mechanical loading and integrate mechanosensing through interactions between fluid flow and the intrinsic sensing complex.

7.3.2 In vivo stimulation of osteocyte To understand mechanotransduction (the conversion of biophysical forces into cellular response), an essential process for living organisms to respond to mechanical environments [21], we need to investigate the types and magnitudes of various mechanical stimuli experienced by bone cells. There are earlier outstanding reviews on the variety of stimulations focusing on in vivo [55–58] or in vitro aspects [21,59,60]. In this section, we discuss mechanical stimulation at the whole bone and tissue level, followed by major forces experienced by osteocytes. In vivo physiological strains at whole bone and tissue level: Wolff [61] hypothesized that mechanical stress determines the architecture of bone. Later, this hypothesis was referred to as “Wolff’s law,” describing the well-accepted

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observations that bone adapts its mass and structure to obtain a higher efficiency of load bearing. In tennis players, mechanical loading induces asymmetry with increased bone volume in their dominant arm compared to the nondominant arm [62,63]. Conversely, deficiency of mechanical stimuli such as during long-term bed rest and space flight decreases bone mass in the lower limbs [64]. Strain gauges attached to bone mid-diaphysis allowed 12-h recordings of strain history during the daily activities of live animals [65]. The occurrence and magnitude of the strain events were found to show a consistent pattern, in which the strain magnitude decreases with the number of occurrences. Similarly, strain gauge measurements in humans showed that peak tension or compression strains on human tibiae are typically lower than 1000 or 2000 με (0.1%–0.2%), even under extraneous exercises [66]. The spatial distribution of mechanical strains can also be measured using imaging correlation methods [67–69], or predicted using finite element analysis [70]. In the former method, surface speckle patterns could be recognized and tracked to yield the displacement and strain fields on the bone surfaces. In the latter method (as shown in figure 3 of reference [58]), microCT images could be used to generate anatomically accurate models, and the load-induced strain field obtained in commercially available software such as ABAQUS and ANSYS or an open-source package like FEBio [70]. The measurements from different approaches can complement each other, as reviewed by Main [58]. Bone’s responses to loading depend not only on the magnitude but also temporal characteristics (strain rate, rest period, number of cycles, and duration) of the mechanical stains [58]. Notably, static loads do not induce bone formation in vivo [71–73], while dynamic loading increases bone formation significantly [73,74]. As the strain level progressively increases to
3000 με, newly formed bone in mice transits from lamellar to woven like [12]. Loading induced fluid flow: Several types of mechanical stimuli have been proposed to activate osteocytes, and comprehensive reviews on this topic can be found elsewhere [3,75,76]. Among possible stimulations such as direct deformation of the cells or hydrostatic pressure, load-induced fluid flow is well accepted to transmit mechanical stimulation from whole bone to cellular level. As discussed, bone is a hydrated porous tissue, containing three levels of porosity: the vascular pores (
10–50 μm), the lacuna-canalicular pores (
0.1–1 μm), and the collagen-hydroxyapatite pores (
10 nm) [24]. Due to the rapid pressure relaxation in bone marrow (seconds), the pressure within the vascular porosity remains low as bone marrow and fluid flow is negligible; while water in the collagen-hydroxyapatite is thought to be bound and cannot move. Piekarski et al. [38] first hypothesized that locomotion-induced matrix deformations force fluid to move in the lacunar-canalicular pores. In the 1980s, strain-generated potentials as the results of fluid flow through charged bone surface were actively studied as a mechanism to excite osteocytes [77–79]. The size of the conduits was found to be on the order of 10 nm, which was in consitent with Piekarski and Munro’s bound water assumption in the matrix pores [76]. This

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conflict was later resolved by Weinbaum et al. [25], who introduced the concept that a PCM fills the fluid space in the LCS and load-induced fluid shear stress (FSS) acts on the osteocyte processes for cellular excitation. The shear stress was estimated to be on the order of several pascals and was further validated with osteocyte in vitro experiments [80]. Later, refined models from Weinbaum et al. showed that fluid flow drag forces that fluid flows act on the transverse tethers were at least one order greater than the shearing forces on the cell membrane, and the resulting deformation on actin cytoskeleton via tethers or collagen-bound integrin complex was 20- to 100-fold greater compared to the tissue level strain [81,82]. Fluid flow can also interact with other possible sensing molecules such as primary cilia [83], mechanosensitive ion channels such as T-type calcium channels [84,85], Cx43 hemichannel [86], and the newly discovered Piezo1 channel [87]. Although fluid flow and hydraulic pressure are intrinsically connected, the former is believed to act as the physical mediator for cellular responses to mechanical loading. Experimental measurements of bone fluid flow in LCS: The first experimental evidence of fluid flow in the LCS was obtained in intact bone in 2011 using a novel imaging method in combination with mathematical modeling [88]. FRAP may be an old technique [89], but it is versatile in biological research. We first adopted FRAP to measure solute diffusion in 2005 [88]. In a typical FRAP experiment (Fig. 7.2A), fluorescent tracer molecules in an osteocytic lacuna at equilibrium were irreversibly photobleached under intense laser illumination. The following fluorescence recovery phase of the photobleached lacuna due to tracer transport from neighboring lacunae was recorded with a confocal microscope. The time-serial changes of the fluorescent intensity with the targeted osteocyte lacuna were modeled and analyzed to derive the tracer diffusion coefficient. The diffusion coefficient of sodium fluorescein (376 Da) was reported to be
330 μm2/s in bone LCS, 60% of its diffusion coefficient in aqueous solution [88]. We recognized the potential of using FRAP to measure convection in addition to diffusion in the LCS. However, we needed to connect the fluorescence measurements on the lacuna level, which was visible under confocal microscopy with the fluid flow in the canaliculi, which was not revealed. To this end, we simulated FRAP under mechanical loading in a one-dimensional transport model that incorporated the FRAP site, the neighboring lacunae, and the canalicular channels that connected the photobleached and surrounding lacunae (Fig. 7.2B). The time course of tracer concentration within the photobleached lacuna was solved as a function of canalicular fluid velocity using a modified diffusion-convection equation subjected to the boundary and initial conditions. Hence, the tracer fluorescent recovery rate in the photobleached lacuna could be readily obtained from the tracer concentration profile. The simulation results showed that the recovery rate increased with increasing loading magnitude and increasing diffusion coefficient [90]. This simple model provided the tool to analyze FRAP data obtained in loaded bone.

FIG. 7.2 Measurement of bone fluid flow in LCS. (A) FRAP principles: A fluorescent tracer (sodium fluorescein) was injected in vivo to a mouse to allow for its uniform perfusion throughout the entire LCS. One lacuna was rapidly (s) photobleached with a high-intensity laser. With time, the fluorescence of the bleached lacuna recovered due to the influx of tracers from surrounding lacunae through canaliculi. (B) A model was developed to describe the enhancement FRAP in the lacuna as a function of the canalicular flow rate, which was used to fit the below experiment. (C) Experimental setup: The freshly harvested tibia samples were imaged and an Ocy lacuna underneath the region of interest (yellow area) on the tibial surface was chosen for FRAP without loading applied. Then, the same lacuna was subjected to FRAP with loading (3 N peak, 2 s/cycle, 4 s resting period). Note, loading and imaging were alternated in sequence. (D) Prebleach image of the region of interest and the timelapse recordings under nonloaded and loaded conditions. (E) Data analysis of the two FRAP series showed faster recovery under loading. (F) Transport enhancement, defined as the ratio of FRAP recovery rate, was used to compare with those from a computational model of the LCS to find the canalicular fluid velocity that best fit the experimental results. (B–F) modified from Zhou et al. [90], and Price et al. [91] with permission. .

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The challenge of performing FRAP in loaded bone samples was the out-offocus artifacts during imaging a moving target. To overcome this challenge, we integrated the confocal microscope and the loading system so that images were timed to be captured during the resting (no loading) periods between loading cycles [91]. The dissected tibiae with fluorescent tracer were loaded under force control during the periodic, cyclic loading cycles and imaged under displacement control during the resting periods to ensure good image quality. The FRAP image sequences were broken down to one obtained immediately after photobleach, while the remaining images were acquired during the resting periods (Fig. 7.2C). For one target lacuna, two trials of FRAP, first without loading (diffusion alone) and then with applied loading (convection plus diffusion), were performed. The time-lapse recording showed excellent image quality using this method (Fig. 7.2D). Analysis of the FRAP data (Fig. 7.2E) showed that moderate tibia loading (-3N peak load,
400 με) enhanced sodium fluorescein (376 Da) transport rate in the LCS by 31% [91]. Comparing this transport enhancement with the three-compartment model predictions allowed us to conclude that the peak fluid velocity in the loaded bone was 60 μm/s (Fig. 7.2F) [91]. Further studies found that the transport enhancement increased with larger loading magnitude (4.8 N vs. 2.8 N). Loading at 0.5, 1, and 2 Hz all showed solute transport enhancement, and 0.5 Hz showed significantly greater enhancement compared to the other loading frequencies [39]. Taken together, combining a perturbation method (FRAP) and mathematical modeling, bone fluid flow could be visualized and quantified in situ with intact LCS structure and in vivo with living cells and functional vasculature. An historical review of the modeling development of load-induced bone fluid flow, including the incompatibility of the strain-generated potential measurements with the predicted faster relaxation in the LCS pores has been published [76]. Weinbaum et al. [25] was a groundbreaking study because of its novel assumption of glycosaminoglycan (GAG)-like fiber matrix and the theoretical framework of multiscale modeling of the permeability of the LCS from the fiber spacing level to the tissue porosity level. They adopted the Biot poroelasticity theory to calculate the fluid pressurization and pressure gradients in a piece of bone slice under bending as performed in streaming potential experiments. The same strategy was later expanded to study fluid and solute transport in one osteon under cyclic compression, a cortical bone shell under blood pressure [40,92], and an entire tibia [90]. Mathematical and computational modeling offers a versatile approach to study bone fluid flow, complementary with the above experimental approaches.

7.4 Mechanisms of osteocyte mechanotransduction In this section, we summarize the molecules implicated in the osteocyte mechanosensing complex, the temporal cellular responses and downstream molecular pathways activated in osteocytes by mechanical stimuli. Finally,

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we discuss alterations of the osteocyte mechanotransduction in various disease conditions.

7.4.1

Mechanosensing complexes

The molecular entities underlying osteocyte mechanosensing have been reviewed in several excellent reviews [2,3,52,59,83,93,94]. The consensus in the field is that these mechanosensors (Fig. 7.3) probably formulate a functional complex to sense varying mechanical environmental cues and integrate them into robust biological responses. In this section, we focus on integrins, calcium ion channels, connexins, primary cilia, and PCM. Please note that the components of the osteocyte mechanosensing complexes, although discussed individually, are believed to function collaboratively. Integrins: Cells attach to the extracellular matrix (ECM) via membranespanning integrins [95,96] and integrins connect with the actin cytoskeleton through actin-associated proteins including vinculin, talin, tensin, and α-actinin [21]. There are two subunits of integrins, denoted as α and β subunits. Using immunohistochemistry, a punctate pattern of β3 along the canalicular wall was found in the pericellular space, while β1 integrin subunit was found overwhelmingly concentrated on osteocyte cell body [46]. The group further

FIG. 7.3 Mechanosensors enable the Ocy to sense mechanical stimuli in the forms of hydraulic pressure (P) and fluid flow (v) due to the amplification of direct strains (με) of bone matrix in the fluid-filled LCS PCM. The presumed sensor molecules include integrins, ion channels (VGCC, Piezo1), connexins (Cx43 hemichannels and gap junctions), Lrp5/6 receptors, primary cilia, and pericellular PCM. Secondary messengers include calcium ions (in extracellular fluid and ER), and ATP and PGE2, which act on P2X7 and EP receptors. Wnts and sclerostin are agonist and antagonist of Lrp5/6 for Ocy.

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visualized the β3 integrins in situ using structured illumination super resolution microscopy and the attachment foci under transmission electron microscopy (TEM), as shown in figure 1 of reference [49]. Functionally, inhibition of αvβ3 integrin attachment sites with an antagonist (IntegriSense 750) compromises osteocyte intracellular calcium response under probe stimulation [47]. Furthermore, when β1 integrin subunit was conditionally deleted from osteocytes in mature (16-week-old) mice, bone formation after three consecutive days of cyclic loading was significantly reduced at the ulnar midshaft of the mutant mice compared to control mice [97]. At this time, there has been no report on the in vivo effects of osteocyte-specific β3 integrin knockdown, although no skeletal defects were found in global integrin-deficient mice [98]. Cytoskeletons: There are three types of cytoskeleton: microfilaments (actin), intermediate filaments (lamins), and microtubules (α-, β-Tubulin). All are present in the osteocyte cell body, while actin is the major cytoskeleton in osteocyte dendrites [99]. Cytoskeleton defines the cell shape and stiffness and serves as a force transmission linkage from cell exterior to interior. Under direct substrate stretching and vibration, the cells respond with formation of focal adhesions, which induce signal transduction through a cascade of activation of Akt ! GSK3β ! β-catenin [94]. Microtubles’ stabilization also affects FSS-induced Ca2+ influx, CaMKII activation, and sclerostin abundance [100]. Studies from Guo et al. demonstrated that calcium influx due to fluid flow stimulation or mechanical loading was followed with actin contraction within osteocytes in both in vitro and in vivo, which was believed to increase cell tension and the release of extracellular vesicles [101]. A recent review [102] summarized the literature showing the considerable variations in the shape of osteocytes and their lacunae and noted the trend of osteocyte lacunae becoming more spherical in disuse. The effects of these aging-related changes in osteocyte shape and size on its mechanotransduction remain to be studied. Connexins: Gap junctions formed by hemichannels from two adjacent cells allow the movement of small molecules ( > 1+ e < FðtÞ ¼ 3ð1  νÞ τε
 > τσ  τε > > : E0 ¼ ER 1 + , μ ¼ ER ð τ σ  τ ε Þ τε where τσ and τε reflect a relaxation time under constant load and deformation, respectively. In recent years, AFM has mainly been used to measure the realtime mechanobiological response of chondrocytes to the abnormal mechanical microenvironment, drug stimulation, and disease development.

9.3.2.2 Micropipette aspiration technique In 1954, Mitchison and Swann invented the first MA apparatus, which was utilized to study cell membrane tension [94]. Similar to AFM, MA can be used to assess local or entire cell viscoelasticity. However, the application scope of MA tests is less versatile in cell mechanics. Thus, MA is mainly used to characterize time-dependent creep experiments, in which a micropipette is placed in contact with a suspended cell membrane at the central region, and a step suction pressure is applied to induce a spherical cell membrane to deform to a certain extent and then reach equilibrium. By analyzing the geometry changes of the cell, elastic and viscoelastic properties can be determined according to the existing formula (Fig. 9.3) [95–97]. The sucking pressure will usually hold to a constant value between 0.3 and 0.4 kPa. In an MA experiment, cell creep lasts approximately 200 s. MA has been extensively used to explore the elastic or viscoelastic properties of single chondrocytes and their PCM [69,98–101]. All living tissues, including all kinds of cells, have been found to have viscoelastic characteristics. Under mechanical loading, viscoelastic materials represent an instant flexible deformation similar to a completely elastic solid,

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FIG. 9.5 The analysis of viscoelastic properties of chondrocytes. (A). Schematic diagram of a theoretical model. (B). Normal chondrocyte creep under aspiration [97].

immediately exhibit the characteristic of liquids, namely time-dependent deformation and energy dissipation. Viscoelastic materials will exhibit creep in a time-dependent manner by external step load and experience stress relaxation in a time-related manner under a step constant deformation. In cell mechanics, a standard linear solid model was used to model aspiration-creep curves of the specific cells under a step negative pressure in MA experiments, as earlier theoretical study has described [96] (Fig. 9.5). The following equations determined how aspirated lengths (L) increase with time (t):
  8  t  3aΔp k1 > > < LðtÞ ¼ πE  1 + k + k  1 exp  τ ∞ 1 2 > μ ð k + k Þ 3 3 1 2 > :τ ¼ , E0 ¼ ðk1 + k2 Þ, E∞ ¼ k1 k1 k2 2 2 In recent years, researchers have focused on the biomechanical microenvironment of chondrocytes and mechanoresponsive material design. Therefore, it is of more physiological significance to study the mechanobiological behavior of chondrocyte sensing and response to 2D or 3D matrixes. The instrument and mechanical theory of MA technology are usually only suitable for studying the mechanical behavior of suspended chondrocytes. Thus, MA technology has shown certain limitations in determining the active mechanical properties of chondrocytes during perceiving chemical and mechanical cues in the matrix environment. The MA can also be used to understand molecular functions in time-lapse studies. The extended application of MA method employs two micropipettes for testing specific ligand-receptor dynamics.

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The mechanical behavior of the chondrocyte

The deformability of chondrocytes plays a critical role in perceiving the mechanical stimuli induced by the ECM. The mechanical behavior of chondrocytes in the process of normal growth, development, and degenerative lesions of AC has been a focus of scientific research. Growing evidence in recent years has suggested a correlation between chondrocyte mechanical behaviors (elastic and viscoelastic properties) and physiological states (healthy or OA condition) [69,89,97,102,103]. The mechanical properties of chondrocytes, as mechanical biomarkers, are essential for understanding their mechanosensing and mechanoregulating processes.

9.3.3.1 The viscoelastic properties of normal and osteoarthritic chondrocytes The chondrocytes from normal and osteoarthritic cartilage have similar elastic property. However, the volume regulation capabilities of chondrocytes from osteoarthritic cartilage are abnormal in response to mechanical stimuli [99]. Interestingly, previous studies have indicated that normal and osteoarthritic chondrocytes exhibit completely different viscoelastic behaviors [69]. Chondrocytes isolated from osteoarthritic cartilage exhibited higher viscoelastic parameters than normal chondrocytes. Our previous study indicated that osteoarthritic cartilage degeneration significantly weakens the viscoelastic properties of chondrocytes [97]. These differing results may be caused by individual differences of patients (age, sex, disease status, etc.). For example, the viscoelastic parameters of chondrocytes from aging cartilage were significantly attenuated compared with chondrocytes from young and adult cartilage [104]. The cytoskeleton, as a major cellular component in cell mechanosensing, is an important factor that causes changes in the viscoelastic properties of chondrocytes [100]. Our previous study indicated that the alteration in the viscoelastic behaviors of chondrocytes were associated with cytoskeletal organization [104]. The osmotic environment of tissue regulates the homeostasis of chondrocytes in AC. Although it is not clear how osmotic loading regulates cell function, cell membrane or cytoskeletal structure may be involved in this process. Recent studies have demonstrated that the viscoelasticity and morphology of chondrocytes are vulnerable to sharp variations in the osmotic loading environment [98]. Therefore, alterations in the osmotic loading in situ microenvironment may affect the chondrocyte mechanical behavior. Furthermore, evidence also indicates that a higher rate of hypo-osmotic loading can increase chondrocyte viscoelasticity, whereas a lower rate of hypo-osmotic loading had no such effect [105]. Although MA provides a convenient experimental method for characterizing the rheological properties of nonadherent cells, this method may not be suitable for some types of cell, such as adherent cells, collective cells, and cells

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embedded in the ECM. At present, AFM is considered an ideal technology for analyzing cell mechanical properties in physiological-related contexts since the small tip of the cantilever during indentation can be placed in contact with adherent cells. Thus, AFM has been widely used to study chondrocyte mechanics in recent years. AFM can characterize the mechanical state of chondrocytes under a physiological state. Thus, the cell mechanical properties analyzed based on AFM technology are more convincing. Based on AFM configuration, contact mechanics provide useful analytical theories for obtaining elastic and viscoelastic parameters. Previous work directly suggested that the viscoelastic properties of chondrocytes are zone related. For example, the chondrocytes in the superficial zone exhibited more stiffness than chondrocytes from other zones [106]. Darling et al., using AFM stress-relaxation and MA creep, also demonstrated that chondrocytes from distinct cartilage zones behave differently [89].

9.3.3.2 Matrix stiffness regulates the biomechanical properties of chondrocytes The behavior of chondrocytes is regulated by multiple biomechanical cues in the matrix microenvironment. Focal adhesion, traction stresses, cytoskeleton reorganization, and phenotype can be significantly influenced by substrate stiffness [75,76,107–112]. During AC development and degeneration, the chondrocyte ECM/PCM stiffness varies. Additionally, the in vivo chondrocytes’ function and fate, to some extent, may depend on the matrix stiffness-related mechanical behavior [113]. However, the main concern in previous works is the passive mechanical behaviors of chondrocytes, not the active mechanoresponsiveness during perceiving the matrix microenvironment. These studies seem to ignore the active response of chondrocytes to physiologically related stiffness. Chondrocytes have physical connection with cell-supporting biomaterial or the matrix microenvironment through focal adhesion structures [103]. Thus, it may be useful to study how the physical cues in the matrix microenvironment are transduced into active mechanical behavior of chondrocytes. For example, the mechanical behaviors of native chondrocytes in a 3D matrix are significantly different compared with that of in vitro chondrocytes [114]. Utilizing cell-supporting and physiologically related substrates combined with AFM technique, our study demonstrated that substrate stiffness regulates the active mechanical behavior and F-actin distribution of chondrocytes during sensing of different substrate stiffness [115] (Fig. 9.6). Our results show that a stiff substrate improves the spreading area and mechanical parameters of chondrocytes (Fig. 9.6C–F) [31]. Deep understanding of substrate stiffnessregulated biomechanical behaviors has far-reaching significance for designing cell-instructive biomaterial and improving treatment for cartilage destruction.

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FIG. 9.6 Substrate stiffness affects chondrocyte mechanical behaviors. (A). PDMS surface roughness. (B). AFM indentation of chondrocyte. (C–F). The statistical analysis of viscoelastic parameters from substrates with varying stiffness. n.s., not significant (P > 0.05). *P < 0.05 [31].

9.3.3.3 Geometry regulates the mechanical properties of chondrocytes Geometry, as extrinsic physical signals of matrix geometric confinement, control various cellular behaviors and functions [116]. Based on AFM stressrelaxation experiments, previous study demonstrated that the ellipsoidal confinement significantly enhanced the elastic and viscoelastic properties of chondrocytes compared with other geometries (Fig. 9.7). The morphology of chondrocytes confined by ellipsoidal geometry is similar to the chondrocytes in the superficial zone. Evidence has shown that the chondrocytes isolated from the superficial zone exhibit significantly more stiffness than that obtained from other zones [106]. A possible explanation may be that ellipsoidal micronicheinduced cytoskeletal reorganization makes the chondrocyte stiffer. Since geometric confinement is physiologically relevant to the matrix microenvironment of chondrocytes, engineering geometric confinement is essential for revealing the mechanobiological behavior of chondrocyte perception of mechanical signals from the matrix microenvironment. 9.3.3.4 Hypo-osmotic loading regulates the mechanical behavior of chondrocytes The RVD induced by hypotonic stress regulates many biological functions of chondrocytes. Chondrocyte RVD dysfunction usually results in cell death

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FIG. 9.7 The mechanical analysis of chondrocytes from varying geometries. (A). AFM experiment of a single chondrocyte in spheroidal confinement. (B). Stress-relaxation process from a chondrocyte. (C). Fitting the relaxation portion of the curve. (D–G). The statistical analysis of viscoelastic parameters in different geometric confinement. n.s., not significant. *P < 0.05, **P < 0.01, and ***P < 0.001 [38].

and cartilage degeneration [117,118]. The deformability of chondrocytes influences cell phenotype and matrix synthesis [119,120]. Previous findings emphasized that matrix stiffness determines the RVD response of chondrocytes. For example, chondrocyte volume swelling and Ca2+ signaling are regulated by the variation of PCM stiffness [39]. Although these investigations have revealed the swelling process during RVD response, the corresponding volume-recovery process of chondrocytes remains unknown. To date, no theoretical and experimental research has been utilized to explore the effect of substrate stiffness on chondrocyte swelling and recovery processes during RVD response. Our results demonstrated that the two processes of cell swell and recovery during RVD response exhibit significantly different deformational features that depend on the substrate stiffness. The robust swelling of chondrocytes usually presents on soft substrate, but stiff substrate causes a faster recovery process (Fig. 9.8) [121]. In addition, soft substrate markedly improves chondrocyte spreading rate (Vd) during cell swelling, but stiff substrate increases Vd when the cell recovers [121]. The reason for this result is that stiff substrate-induced higher cell elasticity made it difficult for chondrocytes to swell during the RVD

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FIG. 9.8 Substrate stiffness induces different RVD of chondrocytes. (A). Chondrocyte RVD. (B). Chondrocyte non-dimensional diameter (d/d0). (C). Chondrocyte swelling time (TS). (D). Chondrocyte recovery time (TR). (E). Chondrocyte RVD responding time (TRes). (F). Chondrocyte diameter rate. (G). Chondrocyte diameter rate. n.s. denotes insignificant (P > 0.05). *P < 0.05, **P < 0.01, and ***P < 0.001.

response [31]. In contrast, chondrocytes exhibit lower elasticity on the soft substrate and can rapidly swell. However, it is not clear why stiff substrate makes chondrocytes recover soft substrates more quickly. Cytoskeletal stiffening induced by stiff substrate enhances cell elasticity [34,105,122]. Thus, chondrocyte stiffening induced by stiff substrate may store more cytoskeletal tension and recovery energy, which would promote chondrocytes to recover but inhibit them swelling. Previous study indicated that cell elasticity decreases with volume increasing when cells are cultured on stiffness-unchanged substrates [98]. However, our results have shown that the elasticity of chondrocytes on substrates with varying stiffness is enhanced when cells swell. The cytoskeletal organization may result in the differences. Thus, future research should explore how substrate stiffness regulates the cell membrane in chondrocytes [123]. At present, it is almost impossible to speculate the in vivo processes of cell perceiving and responding to the matrix environment through similar in vitro scientific investigations. Cells embedded in engineered biomaterial scaffolds often produce distinct mechanical behaviors with inappropriate biochemical and mechanical cues.

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9.4 Mechanosensitive channels are involved in mechanotransduction 9.4.1 TRPV4/PIEZOs in chondrocytes Mechanosensitive ion channels, as important transducers, can transduce mechanical stimuli into biochemical signals that affect signaling pathways and cell behavior [124,125]. In vivo, chondrocytes undergo diverse types of mechanical stimuli within the PCM microenvironment, which play a pivotal role in transducing biophysical cues from the ECM [126,127]. The variations of mechanical stimuli in chondrocyte PCM can significantly regulate mechanotransduction, which is carried out by ion channels, receptors, membrane proteins, and subcellular structural components. Chondrocytes perceive alterations in the matrix microenvironment through specialized mechanosensing mechanisms, by which physical cues can be transduced into biochemical signals. The calcium signaling and changes in mitochondrial function are involved in the earliest responses in chondrocyte mechanotransduction, which includes an integrated set of signaling pathways that transmit external mechanical cues to the cell through mechanosensors. Recently, mechanosensitive ion channels have emerged as critical mechanical sensors in perceiving external forces. Mechanosensitive ion channels can rapidly transduce mechanical force into cellular responses by triggering calcium signaling [128]. Although mechanosensitive ion channels have long been considered mechanosensors, the electrophysiological characteristics and mechanotransduction mechanism of these channels remain unclear. This hinders our full understanding of the physiological significance of mechanosensitive ion channels in vivo. Chondrocytes have diverse types of mechanosensors, such as TRPV4/PIEZO channels, integrins, and primary cilia [20]. TRPV4/PIEZO channels are involved in modulating tissue development, matrix remodeling, and homeostasis balance of AC. The entry of extracellular Ca2+ influx into cells is crucial for cells to respond to external mechanical loads [129]. Calcium channels on the membrane control variations in Ca2+ concentration. It is well known that many processes in chondrocytes are modulated by Ca2+ signaling, such as cell division, migration, and differentiation [130]. Many conditions influence the activity of Ca2+ signaling during mechanotransduction. Diverse mechanical stimuli, such as static or dynamic strain, can regulate calcium signaling and influence cellular homeostasis. Physical and chemical stimulation can significantly increase the concentration of cytoplasmic Ca2+ [128,131]. Additionally, chondrocyte Ca2+ signals induced by cartilage traumatic injury influence the cytoskeleton, homeostasis, apoptosis, and inflammation [124,132–135]. While chondrocytes express several ion channels that could modulate calcium signaling, the TRPV4/PIEZO channels of articular chondrocytes, as two identified mechanosensitive ion channels, preferentially regulate calcium signaling [136] and functionally express to improve matrix synthesis, cartilage formation, and mechanical properties [25,137].

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9.4.1.1 Activation mechanisms for TRPV4/PIEZO channels Mechanosensitive ion channels regulate diverse cellular and organismic mechanical sensations. TRPV4/PIEZO channels have been involved in various mechanotransduction processes at the cellular or tissue scale of AC. However, how PIEZO/TRPV4 converts a mechanical stimulus into channel gating is not clear. Interaction between ion channels and mechanical forces is required to perform the activation of the TRPV4/PIEZO channel, which can lead to local deformation-induced ion channel conformational change. Two classic models reveal the mechanism of ion channel activation: force from lipid (FFL) and force from filament (FFF) (Fig. 9.9) [138]. In the FFL

FIG. 9.9 Mechanical stimuli-induced channel gating models. (A). The force from lipid model. (B). The force from filament model. Figure based on work by Christensen et al. [138].

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model, the membrane surface tension transmits the mechanical force to the channel, and the membrane interacting with the channel causes a hydrophobic mismatch that favors channel opening. In the FFF model, the tether generates the gating force. In addition, other mechanisms have been proposed, such as dual tethering where tethers connect with structural components on both membrane sides. At present, there are still disputes whether or how the gating of TRPV4 is controlled by mechanical stimuli. But mechanical force or deformation can undoubtedly directly activate PIEZOs channels. Mechanical force directly gates the channel from a resting closed state to an activated open state. It is worth mentioning that direct gating of channel makes the channel activate on microsecond time scales, providing the fastest mechanotransduction. Thus, mechanosensitive ion channels can immediately respond to external forces. PIEZO channels play important pathophysiological roles in many kinds of mechanotransduction processes. PIEZO1 and PIEZO2 are mechanically activated ion channels that permeate calcium cation and can be rapidly inactivated [139,140]. PIEZO1 is expressed in many types of cells and endows them with mechanosensitivity [141]. PIEZO channels can even be activated by cell membrane deformation alone, demonstrating their intrinsic ability as mechanical transducers [139–143]. It is increasingly confirmed that PIEZO channels play a critical role in many kinds of physiological processes. The TRPV4 channel is involved in many kinds of mechanotransduction processes [144,145]. Various external forces can activate TRPV4, such as matrix stiffness, membrane deformation, and stretch strain [146,147]. Growing evidence demonstrates that TRPV4, as an osmotic transducer, regulates the mechanotransduction processes of osmotic loading in various cell types. Although many scientists have extensively studied the involvement of TRPV4 in mediating diverse external forces on many kinds of cell [148], the mechanism by which osmotic loading activates TRPV4 is unclear. Articular chondrocytes, as physiologically non-excitable cells, functionally express TRPV4/PIEZOs channels [149], which mediate the mechanosensitivity and physiology of chondrocytes through intracellular Ca2+ signaling [142,150]. Despite TRPV4/PIEZO1 existing in several kinds of mechanically sensitive cells [151,152], it is challenging to understand how TRPV4/PIEZO1 mediates the underlying downstream signal transduction pathways. It may be directly involved in mechanical activation or osmotic activation rather than the matrix mechanical microenvironment. However, it has also been proposed that some other mechanosensors may interact with TRPV4 and activate this channel [153]. The Ca2+ influx mediated by TRPV4/PIEZO channels can permeate across a large region of cells. Thus, mechanosensitive channels regulate different kinds of biochemical events and cellular behaviors through calcium signaling.

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TRPV4/PIEZOs mediate mechanical strain

Mechanotransduction is essential for cell perceiving of exogenous and endogenous biomechanical cues of the matrix environment, which reflects the physiological and pathological conditions of the AC. Chondrocytes are sensitive to various mechanical stimuli induced by the mechanical loading of cartilage, such as ECM/PCM strain, fluid sheer stress, and hydrostatic stress [154]. It is an indisputable fact that the mechanotransduction of the chondrocytes regulates their many mechanical and biological processes. The key process of these cellular behaviors is the continuous transducing of mechanical forces into chemical signals, which is mediated partially by TRPV4/PIEZOs via calcium signaling. TRPV4/PIEZO channels synergistically function through mediating Ca2+ influx of chondrocytes in response to injurious stress [137,155,156]. SOX9 is, as a chondrogenic marker, is involved in contributing to rapid chondrocyte proliferation and maintaining cartilage matrix synthesis. It is reported that SOX9 expression of chondrocytes is regulated by TRPV4-mediated Ca2+ influx [157]. The cartilage construct with primary articular chondrocytes exhibits high collagen content and tensile stiffness when the constructs are treated by TRPV4 agonist [158]. In addition, the morphological and biochemical properties of new cartilage constructs also influence TRPV4-mediated biological response [159]. Interestingly, the mechanoresponsive cartilage construct can instruct endogenous mechanosensitive TRPV4 channel to contribute synthetic genetic circuits, which transduce mechanical cues into a therapeutic transgenic expression [160]. This innovative research sheds light on the promising drug targeting treatment for cartilage destruction. TRPV4 channel mechanosensitivity, to a large extent, depends on the form of mechanical loading [161]. It is reported that cyclic stretch strain and membrane deformation distinctively regulate the TRPV4 activation [161–163]. TRPV4 also plays a key role in the antiinflammatory mechanism. Recent study has demonstrated that proinflammatory interleukin 1β (IL-1β) signaling and cartilage degradation can be inhibited by mechanically or pharmaceutically activated TRPV4, which regulates the HDAC6 and cilium [162]. Subsequent work indicates that the effects of traumatic loading on chondrocyte mechanical sensitivity is also influenced by IL-1α signaling through PIEZO1-modulated Ca2+ flux [164]. However, there is no report that TRPV4 is involved in regulating inflammatory signaling. Recent studies have also indicated that actin and microtubules may be related to membrane expression of TRPV4 channels and functional interaction between TRPV4 channels and the cytoskeleton [165–167]. A recent report suggested that TRPV4-mediated Ca2+ flux is regulated by IGF-1 in chondrocytes through cytoskeletal reorganization in the presence of osmotic loading [168]. Additionally, chondrocyte apoptosis might be induced by TRPV4-mediated Ca2+ signaling; yet high mechanical stress upregulated TRPV4 expression [169]. Thus, reducing TRPV4 activity may be beneficial for cartilage regeneration.

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In AC, PIEZO channels are responsible for mediating calcium signaling and ECM synthesis. PIEZO1 is activated by diverse external forces, including touching, stretch stress, fluid stress, and matrix deformation [139,161,170]. PIEZO channels are involved in different mechanoregulating pathways in many kinds of tissues and cells [141]. PIEZO1 and PIEZO2 are involved in mediating calcium signaling in porcine chondrocytes subject to hypertrophic compression by AFM [137]. Both PIEZO1 and TRPV4 together regulate current activation of chondrocytes through deformation disturbance of the interface between cell and matrix, but stretch-activated currents are only regulated by PIEZO1 [161]. The membrane stiffness determined by cytoskeletal proteins modulates PIEZO activity. Recent study has indicated that the variations in dynamininduced membrane stiffness alter PIEZO1 activity in chondrocytes [137]. It is well known that the crucial mechanism resulting in joint injury is chondrocyte death [171–173]. Fortunately, TRPV4/PIEZO channels could reduce cell death and alleviate cartilage degeneration induced by injury. However, further clinical study is necessary to reveal the molecular targeting mechanism by which TRPV4/PIEZO channels induce protective or restorative signaling pathways. A seminal study discovered that TRPV4 channel inactivation can initiate a protective role in reducing aging-related but not injury-related osteoarthritic degeneration [25]. Our recent study also indicated that the TRPV4-mediated Ca2+ influx regulates chondrocytes sensitive to physiological strain, while PIEZO2-mediated Ca2+ influx determines chondrocytes sensitive to traumatic strain [174] (Fig. 9.10). In short, previous studies suggest that targeting TRPV4/ PIEZO-mediated mechanoregulating improve cartilage matrix synthesis and osteoarthritic therapy.

9.4.2.1 TRPV4/PIEZOs are involved in osteoarthritic pathogenesis Inflammatory mediators and IL-1 cause inflammation and play a crucial role in cartilage pathogenesis [175,176]. TRPV4/PIEZO channels are involved in OA etiopathogenesis by regulating the inflammatory responses of chondrocytes. The release of chondrocyte pro-inflammatory factors induced by IL-1β

FIG. 9.10 TRPV4/PIEZOs synergistically regulate calcium signaling in chondrocytes during mechanical stimuli.

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enhances the expression of inflammatory catabolic genes and further alters cell functions, resulting in the degeneration of cartilage matrix [177,178]. Growing evidence suggests a proinflammatory role of TRPV4/PIEZO channels in response to mechanical cues. TRPV4 knockout in chondrocytes reduced severity of age-related OA [179]. Interestingly, TRPV4 activation contributes to chondroprotective effects by activating CaMKK/AMPK and inhibiting the NF-κB pathway [180]. Deficiency of TRPV4 leads to severe inflammatory response and interrupts AC homeostasis [181]. TRPV4 activation inhibits the lipopolysaccharide (LPS)-induced nitric oxide (NO) release of chondrocytes, whereas suppressing TRPV4 exacerbates LPS-induced inflammation [182]. In addition, proinflammatory IL-1β signaling and cartilage degradation can be inhibited by mechanically or biochemically activated TRPV4 through modulating HDAC6 and primary cilia [162]. Furthermore, intraflagellar transport and associated signaling are also regulated by TRPV4 activation through ciliary tubulin [162]. A study showed that IL-1α upregulated PIEZO1 expression, which make chondrocytes sensitive to superphysiological loading through mediating calcium signaling [164]. This study provided a molecular mechanism linking IL-1α with resulting hyper mechanotransduction through enhanced PIEZO1 expression and function in chondrocytes [164].

9.4.3 TRPV4/PIEZO mediate chondrocyte sensing matrix physical properties Chondrocytes perceive substrate stiffness through TRPV4/PIEZO1 and activation of downstream signaling pathways [41,126]. In recent decades, bioengineers have developed several advanced techniques [183] that can be used to recreate various mechanical cues in the matrix microenvironment experienced by chondrocytes in vivo. The cellular microenvironment has been engineered to investigate the molecular mechanism of cells perceiving matrix physical properties, including osmotic loading [119], physical properties [41], and mechanical loading. Matrix stiffness and geometric confinement, as important physical properties of the matrix environment, have been extensively investigated [34,41,184]. Thus, the recreation of these physical properties of the matrix microenvironment is essential to reveal the mediating mechanism of TRPV4/ PIEZO channels in chondrocytes.

9.4.3.1 Chondrocytes sense substrate stiffness Accumulating evidence has demonstrated that TRPV4/PIEZO channels mediate chondrocyte perception of mechanical microenvironmental cues. It is clear that chondrocytes perceive matrix stiffness through calcium signaling. Suppressing TRPV4-modulated Ca2+ influx results in normal chondrocytes insensitive to substrate stiffness [185]. The notably deficiency of osteoarthritic

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FIG. 9.11 Substrate stiffness affects the Ca2+ oscillations in chondrocytes. (A). Ca2+ oscillations in chondrocytes. (B–D). Ca2+ oscillation amplitude in chondrocytes. (E–G). Ca2+ oscillation frequency in chondrocytes. n.s. denotes the insignificant (P > 0.05). *P < 0.05, **P < 0.01, ***P < 0.001, P < 0.05 denotes significant difference.

chondrocytes in perceiving matrix mechanical properties renders them incapable of mechanically maintaining homeostasis and results in inadequate remodeling of damaged cartilage [186]. Recent results suggested that stiff substrate significantly enhanced calcium signaling in chondrocytes (Fig. 9.11A, B, and E) [121]. Furthermore, when treated with 4αPDD, a TRPV4 selective agonist, stiff substrate induces the strongest Ca2+ oscillations in chondrocytes (Fig. 9.11C and F). Additionally, stiff substrate significantly attenuates the Ca2+ oscillations in chondrocytes through the application of TRPV4 antagonist (Fig. 9.11D and G). Thus, the TRPV4 channel mediates how chondrocytes perceive substrate stiffness through controlling Ca2+ influx. The TRPV4 channel mediates Ca2+ oscillations in a stiffness-dependent manner in both cell swelling and recovery progress during chondrocyte RVD response (Fig. 9.12) [121]. Soft substrate increases TRPV4-mediated calcium signaling during cell swelling. Stiff substrate increases TRPV4-mediated calcium signaling during cell recovery. The effect of substrate stiffness on hypo-osmotic loading-induced calcium signaling of chondrocytes is completely different from calcium signaling induced by isoosmotic loading.

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FIG. 9.12 The calcium signaling of chondrocytes on different substrates under hypo-osmotic loading. (A). Single-cell calcium signaling in chondrocytes on substrate with varying stiffness. (B). Calcium signaling in chondrocytes on substrate with varying stiffness. (C,D). Calcium signaling during cell swelling. (E,F). Calcium signaling during cell recovery. [121]. n.s. denotes insignificant (P > 0.05). *P < 0.05, **P < 0.01, ***P < 0.001, P < 0.05 denotes significant difference.

9.4.3.2 Chondrocytes sense matrix geometry Geometry presents the diverse cell morphology determined by the matrix microenvironment. Previous study has demonstrated that the effect of matrix 3D geometric confinement on the calcium signaling of chondrocytes is entirely distinct from that of a 2D matrix system (Fig. 9.13) [38]. The ellipsoidal geometry, similar to chondrocytes in the superficial zone, significantly improved the amplitude of calcium signaling while attenuating its frequency compared with spheroidal geometry [38]. In a 2D substrate system, stiff substrate-induced cell stiffening enhances calcium signaling [121]. Noting that all ion channels are closely related to the calcium signaling. Thus, matrix 3D geometric confinement is a crucial mechanical signal in regulating Ca2+ influx, which may be mediated by TRPV4/PIEZO channels and induce corresponding mechanoregulating mechanisms in the biomechanical microenvironment of chondrocytes. With the development of biomaterials, nanotechnology, and photolithography, it is easier to understand the molecular mechanism of cell perception of the matrix microenvironment. Recently, engineered polydimethylsiloxane (PDMS) pillar arrays combined with a whole-cell patch-clamp technique was used to

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FIG. 9.13 The effects of geometric confinement on the Ca2+ oscillations of chondrocytes. (A). Geometric confinement, i.e., spheroidal, ellipsoidal, and flatter. (B). Single cell Ca2+ oscillations in different geometric confinement. (C–E). Comparison of Ca2+ oscillations of chondrocytes from varying microniche geometries. n.s. denotes insignificant difference. **P < 0.01, ***P < 0.001, P < 0.05 denotes significant difference [38].

characterize the mechanoelectrical transduction mediated by TRPV4/PIEZO1 activity in chondrocytes [161]. Furthermore, the regulatory mechanism presented by TRPV4 is closely related with mechanical stimulus modes, but PIEZO1 does not have such experimental phenomenon [187]. Thus, the substrate stiffness modulated by pillar arrays and destruction of cytoskeletal components did not regulate TRPV4-mediated currents. However, substrate stiffness and actomyosin traction forces promote the activation of PIEZO1 by forces generated by the cell [188,189]. Recent findings regarding TRPV4/PIEZO channels shed a light on various types of TRPV4/PIEZO-mediated mechanotransduction while chondrocytes sense the complex matrix microenvironment. Despite TRPV4/PIEZO channels

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playing a critical role in chondrocytes through calcium signaling, identifying other types of cytokine (inflammatory cytokines, TNF-α, and IL-1β) stimuliregulated mechanotransduction will improve understanding of the pathogenesis of OA. For example, inflammatory signaling makes articular chondrocytes sensitive to traumatic mechanical loading. In addition, recent studies have confirmed that TRPV4/PIEZO mediated-calcium signaling influences many kinds of downstream signaling pathways that are relevant for OA [49]. Understanding of the functions of TRPV4/PIEZO channels in the AC is incomplete and thus engineering physiology-related biomaterial scaffolds to characterize the gating of TRPV4/PIEZO channels is necessary.

9.5

Conclusion and perspectives

With the development of mechanobiology, it is entirely possible to unveil the mechanism that diverse mechanical stimuli use to instruct chondrocyte behavior and function. Despite remarkable research progress, many questions remain. Many mechanosensitive signaling pathways regulate cellular behavior during chondrocyte sensing of the mechanical environment. Although investigations into the roles of TRPV4/PIEZO channels in chondrocytes perceiving mechanical cues have led to major breakthroughs, the exact signaling pathway of TRPV4/PIEZOs-mediated mechanotransduction and its association with OA remain elusive. In future studies, it will be essential to precisely characterize the role of TRPV4/PIEZO channels in calcium-mediated catabolic responses through engineering physiology and pathology-related matrix microenvironment, which will provide therapeutic targeting of mechanoinflammation and calcium-dependent signaling pathways for OA.

Acknowledgments This work was supported from the National Natural Science Foundation of China (12272252, 11872263) and the Shanxi Huajin Orthopedic Public Foundation.

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[158] S.V. Eleswarapu, K.A. Athanasiou, TRPV4 channel activation improves the tensile properties of self-assembled articular cartilage constructs, Acta Biomater. 9 (3) (2013) 5554–5561. [159] G.A. Otarola, J.C. Hu, K.A. Athanasiou, Intracellular calcium and sodium modulation of selfassembled neocartilage using costal chondrocytes, Tissue Eng. Part A 28 (13–14) (2022) 595–605. [160] R.J. Nims, L. Pferdehirt, F. Guilak, Mechanogenetics: harnessing mechanobiology for cellular engineering, Curr. Opin. Biotechnol. 73 (2022) 374–379. [161] M.R. Servin-Vences, M. Moroni, G.R. Lewin, K. Poole, Direct measurement of TRPV4 and PIEZO1 activity reveals multiple mechanotransduction pathways in chondrocytes, Elife 6 (2017) e21074. [162] S. Fu, H. Meng, S. Inamdar, B. Das, H. Gupta, W. Wang, et al., Activation of TRPV4 by mechanical, osmotic or pharmaceutical stimulation is anti-inflammatory blocking IL-1β mediated articular cartilage matrix destruction, Osteoarthr. Cartil. 29 (1) (2021) 89–99. [163] J. Vriens, H. Watanabe, A. Janssens, G. Droogmans, T. Voets, B. Nilius, Cell swelling, heat, and chemical agonists use distinct pathways for the activation of the cation channel TRPV4, Proc. Natl. Acad. Sci. U. S. A. 101 (1) (2004) 396–401. [164] W. Lee, R.J. Nims, A. Savadipour, Q.J. Zhang, H.A. Leddy, F. Liu, et al., Inflammatory signaling sensitizes Piezo1 mechanotransduction in articular chondrocytes as a pathogenic feedforward mechanism in osteoarthritis, Proc. Natl. Acad. Sci. U. S. A. 118 (13) (2021) e2001611118. [165] M. Suzuki, A. Hirao, A. Mizuno, Microtubule-associated protein 7 increases the membrane expression of transient receptor potential vanilloid 4 (TRPV4), J. Biol. Chem. 278 (51) (2003) 51448–51453. [166] D. Becker, J. Bereiter-Hahn, M. Jendrach, Functional interaction of the cation channel transient receptor potential vanilloid 4 (TRPV4) and actin in volume regulation, Eur. J. Cell Biol. 88 (3) (2009) 141–152. [167] C. Goswami, J. Kuhn, P.A. Heppenstall, T. Hucho, Importance of non-selective cation channel TRPV4 interaction with cytoskeleton and their reciprocal regulations in cultured cells, PloS One 5 (7) (2010) e11654. [168] N. Trompeter, J.D. Gardinier, V. DeBarros, M. Boggs, V. Gangadharan, W.J. Cain, et al., Insulin-like growth factor-1 regulates the mechanosensitivity of chondrocytes by modulating TRPV4, Cell Calcium 99 (2021) 102467. [169] B. Xu, R.L. Xing, Z.Q. Huang, S.J. Yin, X.C. Li, L. Zhang, et al., Excessive mechanical stress induces chondrocyte apoptosis through TRPV4 in an anterior cruciate ligament-transected rat osteoarthritis model, Life Sci. 228 (2019) 158–166. [170] A.H. Lewis, J. Grandl, Mechanical sensitivity of Piezo1 ion channels can be tuned by cellular membrane tension, Elife 4 (2015) e12088. [171] J.A. Stolberg-Stolberg, B.D. Furman, N.W. Garrigues, J. Lee, D.S. Pisetsky, N.A. Stearns, et al., Effects of cartilage impact with and without fracture on chondrocyte viability and the release of inflammatory markers, J. Orthop. Res. 31 (8) (2013) 1283–1292. [172] E. Sauter, J.A. Buckwalter, T.O. McKinley, J.A. Martin, Cytoskeletal dissolution blocks oxidant release and cell death in injured cartilage, J. Orthop. Res. 30 (4) (2012) 593–598. [173] D.M. Phillips, R.C. Haut, The use of a non-ionic surfactant (P188) to save chondrocytes from necrosis following impact loading of chondral explants, J. Orthop. Res. 22 (5) (2004) 1135–1142. [174] G.L. Du, L. Li, X.W. Zhang, J.B. Liu, J.Q. Hao, J.J. Zhu, et al., Roles of TRPV4 and piezo channels in stretch-evoked Ca2+ response in chondrocytes, Exp. Biol. Med. (Maywood) 245 (3) (2020) 180–189.

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[175] M.D. Smith, S. Triantafillou, A. Parker, P.P. Youssef, M. Coleman, Synovial membrane inflammation and cytokine production in patients with early osteoarthritis, J. Rheumatol. 24 (2) (1997) 365–371. [176] J. Bondeson, S.D. Wainwright, S. Lauder, N. Amos, C.E. Hughes, The role of synovial macrophages and macrophage-produced cytokines in driving aggrecanases, matrix metalloproteinases, and other destructive and inflammatory responses in osteoarthritis, Arthritis Res. Ther. 8 (6) (2006) R187. [177] R. Liu-Bryan, R. Terkeltaub, Emerging regulators of the inflammatory process in osteoarthritis, Nat. Rev. Rheumatol. 11 (1) (2015) 35–44. [178] R.F. Loeser, S.R. Goldring, C.R. Scanzello, M.B. Goldring, Osteoarthritis: a disease of the joint as an organ, Arthritis Rheum. 64 (6) (2012) 1697–1707. [179] C.J. O’Conor, S. Ramalingam, N.A. Zelenski, H.C. Benefield, I. Rigo, D. Little, et al., Cartilage-specific knockout of the mechanosensory ion channel trpv4 decreases age-related osteoarthritis, Sci. Rep. 6 (2016) 29053. [180] K. Hattori, N. Takahashi, K. Terabe, Y. Ohashi, K. Kishimoto, Y. Yokota, et al., Activation of transient receptor potential vanilloid 4 protects articular cartilage against inflammatory responses via CaMKK/AMPK/NF-κB signaling pathway, Sci. Rep. 11 (1) (2021) 15508. [181] A.L. Clark, B.J. Votta, S. Kumar, W. Liedtke, F. Guilak, Chondroprotective role of the osmotically sensitive ion channel transient receptor potential vanilloid 4 age- and sex-dependent progression of osteoarthritis in Trpv4-deficient mice, Arthritis Rheum. 62 (10) (2010) 2973–2983. [182] F. Hu, W. Zhu, L. Wang, MicroRNA-203 up-regulates nitric oxide expression in temporomandibular joint chondrocytes via targeting TRPV4, Arch. Oral Biol. 58 (2) (2013) 192–199. [183] M. Urbanczyk, S.L. Layland, K. Schenke-Layland, The role of extracellular matrix in biomechanics and its impact on bioengineering of cells and 3D tissues, Matrix Biol. 85–86 (2020) 1–14. [184] S. Kim, M. Uroz, J.L. Bays, C.S. Chen, Harnessing mechanobiology for tissue engineering, Dev. Cell 56 (2) (2021) 180–191. [185] P. Agarwal, H.P. Lee, P. Smeriglio, F. Grandi, S. Goodman, O. Chaudhuri, et al., A dysfunctional TRPV4-GSK3β pathway prevents osteoarthritic chondrocytes from sensing changes in extracellular matrix viscoelasticity, Nat. Biomed. Eng. 5 (12) (2021) 1472–1484. [186] M.L. Delco, L.J. Bonassar, Targeting calcium-related mechanotransduction in early OA, Nat. Rev. Rheumatol. 17 (8) (2021) 445–446. [187] S. Sianati, L. Schroeter, J. Richardson, A. Tay, S.R. Lamande, K. Poole, Modulating the mechanical activation of trpv4 at the cell-substrate interface, Front. Bioeng. Biotechnol. 8 (2021) 608951. [188] M.M. Pathak, J.L. Nourse, T. Tran, J. Hwe, J. Arulmoli, D.T.T. Le, et al., Stretch-activated ion channel Piezo1 directs lineage choice in human neural stem cells, Proc. Natl. Acad. Sci. U. S. A. 111 (45) (2014) 16148–16153. [189] K.L. Ellefsen, J.R. Holt, A.C. Chang, J.L. Nourse, J. Arulmoli, A.H. Mekhdjian, et al., Myosin-II mediated traction forces evoke localized Piezo1-dependent Ca2+ flickers, Commun. Biol. 2 (2019) 298.

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Part III

Bone biomechanics and bone diseases

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Chapter 10

Bone cell mechanobiology and bone disease Lifang Hu, Zixiang Wu, Kang Ru, Hua Liu, Yunxian Jia, Zarnaz Khan, Zihan Tian, Shuyu Liu, Xia Xu, Zhihao Chen, and Airong Qian* Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China * Corresponding author.

10.1 Introduction In vertebrates, bone is a dynamic, adaptive, self-repairing structure that performs various vital physiological activities such as locomotion, body support, organ protection, hematological function, mineral storage, and endocrine function. In addition, bone is a highly mechanosensitive organ and constantly changes its shape and structure in response to mechanical stimuli. Bone homeostasis is maintained by different types of cells, including bone marrow mesenchymal stem cells (BM-MSCs), osteoblasts (OBs), osteoclasts (OCs), and osteocytes (Ocys). BM-MSCs are the multipotential stem cells located in bone marrow [1]. BM-MSCs can differentiate into different cells, such as OBs, adipocytes, and chondrocytes. BM-MSC-derived OBs are functional cells of bone formation [2]. OBs can differentiate into Ocys by embedding themselves into the bone matrix. OCs are responsible for bone resorption [3], which is closely connected to bone formation conducted by OBs through bone remodeling. In healthy adults, bone formation and bone resorption are in balance to maintain bone health. Ocys are terminally differentiated OBs found in the bone lacuna and are the most abundant cells in bone tissue. Ocys have been shown to be multifunctional cells and mechanosensors of bone [4,5]. They sense and transmit mechanical signals to effector cells (e.g., OBs and OCs) to coordinate their functions to maintain bone homeostasis. In addition, cartilage, which consists of only one cell type, chondrocyte, is also affected by mechanical stimuli. The importance of mechanical stimuli for the maintenance of bone and cartilage health through bone cells’ mechanotransduction is becoming increasingly Bone Cell Biomechanics, Mechanobiology, and Bone Diseases. https://doi.org/10.1016/B978-0-323-96123-3.00013-0 Copyright © 2024 Elsevier Inc. All rights reserved.

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apparent. Therefore, alterations of bone cells’ mechanotransduction process lead to the abnormal cellular function of bone cells, which results in bone diseases. This chapter summarizes the current understanding of and recent advances in bone cells’ mechanotransduction and its involvement in bone diseases, with a focus on osteoporosis (OP), scoliosis, and osteoarthritis (OA).

10.2 Bone cell mechanobiology and osteoporosis OP is a metabolic bone disease characterized by decreased bone mass and deterioration of bone microarchitecture, leading to increased bone fragility and increased fracture risk [6]. OP is a common bone disease in elderly people, postmenopausal women, long-term bedridden patients, and astronauts who perform space missions. Evidence has shown the key involvement of mechanical factors (e.g., mechanical unloading, mechanical loading) in bone health and bone disease (e.g., osteoporosis), which is conducted via bone cells’ mechanotransduction [7,8] (Table 10.1, Fig. 10.1).

TABLE 10.1 Bone cell mechanotransduction involved in osteoporosis. Mechanical stimuli

Cell type

Phenomenon

Reference

Simulated microgravity

BM-MSC

Inhibition on cell proliferation and osteogenic differentiation of BM-MSCs

[9–11]

Simulated microgravity

BM-MSC

Inhibition on osteogenic differentiation and promotion on adipogenic differentiation of BM-MSCs

[12–14]

Hypergravity

BM-MSC

Promotion on osteogenic differentiation and inhibition on adipogenic differentiation of BM-MSCs

[12]

Low-magnitude high-frequency vibration (LMHFV)

BM-MSC

Promotion on proliferation and osteogenic differentiation of BM-MSCs

[15,16]

Acousticfrequency vibration

BM-MSC

Acoustic-frequency vibration at 800 Hz promotes osteogenic differentiation and suppresses adipogenesis

[17]

Nanovibration

MSC

Promotion on osteogenesis, induction of therapeutic reactive oxygen species, and inflammation for three-dimensional bone tissue engineering

[18]

Hydrostatic pressure (HP)

BM-MSC

Promotion on osteogenic differentiation while inhibition on adipocyte differentiation of BM-MSCs

[19]

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TABLE 10.1 Bone cell mechanotransduction involved in osteoporosis—cont’d Mechanical stimuli

Cell type

Phenomenon

Reference

Tensile strain

BM-MSC

Promotion on osteogenic differentiation while suppression on adipogenic differentiation of BM-MSCs

[20]

Simulated microgravity/ mechanical unloading

Osteoblast

Inhibition on osteoblast proliferation and differentiation

[21–24]

Reduced mechanical stimuli (bedridden or aging)

Osteoblast

Inhibition on osteoblast differentiation

[24]

Whole-body vibration (WBV)

Osteoblast

Promotion on the differentiation of osteoblasts

[25]

Low-magnitude vibration (LMV)

Osteoblast

Promotion on osteogenic genes expression in osteoblasts of OVX rats with osteoporosis

[26]

Simulated microgravity

FLG29.1 osteoclastic precursor cell

Increase of osteoclastogenesis

[27]

Simulated microgravity

RAW264.7 cell

Increase of osteoclast differentiation

[28]

LMHFV

RAW264.7 cell

Inhibition on osteoclast differentiation

[29]

Tensile force

RAW264.7 cell

Inhibition on osteoclastogenesis

[30]

Mechanical vibration

RAW264.7 cell

Inhibition on osteoclast formation

[31]

Compressive force combined with vibration

Osteoclast

Promotion on osteoclast differentiation

[32]

Compressive force

Osteoclast

Increase of osteoclast differentiation

[33]

Simulated microgravity

Osteocyte

Osteocyte apoptosis in both trabecular and cortical bone with reduced bone mineral density

[34]

LMHFV

Osteocyte

Upregulation of E11, DMP1, and FGF23 but downregulation of sclerostin in osteocytes; promotion on bone formation in osteoporotic rats

[35,36]

FIG. 10.1 Schematic illustration of the main effects of mechanical unloading and mechanical loading on bone via regulating bone cells’ function.

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10.2.1 Bone marrow mesenchymal stem cell mechanobiology and osteoporosis BM-MSCs are the origin of OB cell lineage with multidirectional differentiation potential [37]. It has been demonstrated that BM-MSCs are mechanosensitive and their differentiation capacity is affected by mechanical stimuli [38,39], which are related to OP development and treatment (Fig. 10.1). Most evidence suggests that mechanical unloading primarily inhibits osteogenic differentiation of BM-MSCs, whereas it promotes adipogenic differentiation. According to research by Li et al., simulated microgravity prevents BM-MSCs from proliferating and differentiating into OBs, which is one factor contributing to bone loss [9,12]. Yamazaki et al. have also investigated the influence of simulated microgravity on BM-MSCs by using twoaxis rotation culture [10]. They found that two-axis rotation culture also inhibited the osteogenic differentiation of BM-MSCs [10]. Shi et al. used a large gradient high magnetic field to simulate microgravity and study how it affected the osteogenic differentiation of human BM-MSCs [11]. They discovered that osteogenesis of human BM-MSCs was reduced by mimicked microgravity. The findings suggest that simulated microgravity predominantly suppresses the start of osteogenesis of human BM-MSCs [11]. Additional investigations have shown that simulated microgravity enhances adipogenic differentiation of BM-MSCs, whereas it inhibits osteogenic differentiation [13,14]. Pan et al. studied the effects of simulated microgravity by hindlimb unloading (HLU) on the growth and osteogenic potential of BM-MSCs from rat femur ex vivo [13]. According to the findings, simulated microgravity increased adipogenic differentiation, while it decreased osteogenic differentiation in BM-MSCs [13]. Zayzafoon et al. adopted the rotary cell culture system to model microgravity and observed a significant suppression of MSCs differentiation into OBs, but an induction of adipocyte differentiation of MSCs under modeled microgravity [14]. All these findings demonstrate that mechanical unloading mainly inhibits osteogenic differentiation, which results in bone loss or OP. In contrast, most studies have shown that mechanical loading (e.g., exercise, vibration) induces osteogenic differentiation of BM-MSCs, thereby improving OP [39–42]. Menuki et al. found that climbing exercise dramatically increased bone mass and OB number, whereas it decreasesd the volume and number of adipocytes in the bone marrow of mice, which is due to the promotion effect on OB differentiation and inhibitory effect on adipocyte differentiation of BM-MSCs by climbing exercise [41]. Moreover, most studies show that vibration, a surrogate for exercise, promotes osteogenic differentiation while it inhibits adipogenic differentiation of BM-MSCs. Treatment with lowmagnitude high-frequency vibration (LMHFV) for 1 week (15 min/day)

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promotes osteoblastic differentiation and inhibits adipogenic differentiation of BM-MSCs by increasing runt-related transcription factor 2 (Runx2) expression and reducing peroxisome proliferator activated receptor γ (PPARγ) and CCAAT/enhancer-binding protein α (C/EBPα) expression [15,16]. Chen et al. found that acoustic-frequency vibrations at 800 Hz induced the highest levels of calcium deposition and significantly increased the expression of osteogenic genes (type I collagen α 1 (ColIα1), alkaline phosphatase (ALP), and Runx2), while it downregulated lipid accumulation and the expression of adipogenic genes (PPARγ, C/EBPα) [17]. This study shows that acousticfrequency vibration promotes osteogenic differentiation but inhibits adipogenesis of BM-MSCs [17]. Recently, Orapiriyakul et al. have also shown that nano vibration with an amplitude of 90 nm at 1000 Hz promotes osteogenesis of MSCs [18]. They also found that nanovibration induces therapeutic reactive oxygen species and inflammatory responses in MSCs for three-dimensional bone tissue engineering [18], suggesting the potential therapeutic application of vibration. Additionally, Sugimoto et al. reported that optimum hydrostatic pressure (HP) promoted osteogenic differentiation but inhibited adipocyte differentiation of MSCs [19]. They proved that Piezo 1, a component of the Piezo mechanosensitive ion channel, controls the expression of bone morphogenetic protein 2 (BMP2), which was necessary for the promotion effect of HP on osteogenic differentiation of MSCs [19]. Zhu et al. also reported that appropriate tensile strain promoted osteogenic differentiation but inhibited adipogenic differentiation of BM-MSCs [20]. All these findings provide theoretical basis for proper physical exercise and appropriate mechanical loading to improve the prevention and treatment of OP.

10.2.2 Osteoblast mechanobiology and osteoporosis OBs, the cells responsible for bone formation, are also mechanosensitive. Bone homeostasis and bone health are maintained by a balance between the production of new bone by OBs and the absorption of existing bone by OCs. To maintain bone homeostasis, mechanical forces play a crucial role in controlling OB activity and bone formation. Therefore, lack of mechanical stimuli (e.g., mechanical unloading) will cause dysfunction of OBs, which results in OP (Fig. 10.1). Studies show that spaceflight or long-term lack of exercise reduces bone mineral density, leads to bone loss, and may result in OP and bone fracture [43]. Microgravity prevents OB development and bone formation, according to research conducted in space and in a lab setting [44,45]. In one study, there was a significant decrease in bone mineral density in the hip and lumbar spine after 45 days of
6-degree head-down tilt bed rest, as well as decreased production of osteocalcin and procollagen type I carboxy-terminal propeptide [46]. Animal studies show that HLU inhibits bone formation [47]. Our studies also reveal that simulated microgravity/mechanical unloading inhibits OB

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proliferation and differentiation, and bone formation both in vivo and in vitro, leading to OP [21–24]. Two main mechanosensitive molecules, microtubule actin cross-linking factor 1 (MACF1) and microRNA-138-5p (miR-138-5p) have been identified to play key roles in OB responses to mechanical stimuli and in the regulation of OB differentiation and bone formation [23,24]. MACF1, a cytoskeletal protein, was reduced by mechanical unloading in association with decreased cell proliferation [23]. It was demonstrated that mechanical unloading suppresses OB proliferation by decreasing the expression of MACF1 via β-catenin signaling [23]. Furthermore, miR-138-5p has been demonstrated as a mechanosensitive molecule and participates in OB responding to mechanical stimuli [24]. In bone samples from bedridden and elderly patients, there were higher levels of miR-138-5p in association with decreased bone formation. Under different mechanical conditions, miR-138-5p inhibits OB differentiation by directly targeting MACF1. Further study showed that bonetargeted inhibition of miR-138-5p attenuated the decrease in the mechanical bone anabolic response in HLU mice and sensitized the bone anabolic response to mechanical loading in both miR-138-5p transgenic mice and aged mice to promote bone formation [24]. This study provids a novel target for ameliorating disuse or senile OP [24]. In contrast, most studies have demonstrated that mechanical loading promotes OB differentiation and bone formation. Wei et al. reported that whole body vibration (WBV) prevents ovariectomized (OVX)-induced bone loss [25], suggesting that mechanical loading can attenuate OP. Low-magnitude vibration may be adopted to prevent and treat postmenopausal OP, according to research by Zhu et al. [26]. They found that low-magnitude vibration promotes the osteogenic differentiation of OBs from OVX rats with OP [26]. Furthermore, the osteogenesis inhibitor sclerostin, which is primarily secreted by Ocys, suppresses bone formation primarily by inhibiting the Wnt/β-catenin signaling pathway [48]. Robling et al. found that mechanical loading significantly inhibits sclerostin expression [49]. As sclerostin is a target for treating OP [50], mechanical loading may improve OP by inhibiting sclerostin. The mechanotransduction of OBs is important for mechanical stimuli regulating bone formation and bone health. Mechanical unloading mainly shows an inhibitory effect on OB proliferation and differentiation and bone formation, resulting in OP. Alternatively, mechanical loading appears to improve OP by enhancing OB differentiation and bone formation. Therefore, appropriate exercise and proper mechanical loading may prove beneficial in OP.

10.2.3 Osteoclast mechanobiology and osteoporosis OCs are the bone-resorbing cells that play a critical role in maintaining bone health [3]. Their function is also modulated by mechanical stimuli. Evidence show that mechanical unloading, such as microgravity, increases OC activity and bone resorption ability and results in bone loss [51]. After

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spending 12 days in space, mice showed reduced bone mass and bone mineral density as well as increased bone resorption [52]. Moreover, medaka fish kept on the International Space Station for 56 days showed increased OCs and decreased pharyngeal bone mineral density [53]. In addition to the studies conducted in real microgravity, some ground-based studies using simulated microgravity have obtained similar findings. Di et al. reported that a simulated microgravity condition increases osteoclastogenesis of human FLG29.1 osteoclastic precursor cells [27]. Furthermore, Saxena et al. found that simulated microgravity made the OC precursor RAW264.7 more susceptible to RANKL-mediated osteoclastogenesis and promoted OC differentiation [28]. Normally, mechanical loading (e.g., exercise) inhibits bone resorption conducted by OCs and exhibits a therapeutic effect on OP [54]. In vitro studies also show that mechanical loading, including LMHFV, tensile force, and mechanical vibration, suppresses osteoclastogenesis [29–31], suggesting appropriate mechanical loading as a potential treatment for OP. Interestingly, some studies reveal that mechanical loading promotes OC differentiation and bone resorption. Hayakawa et al. found that compressive force increased TRAP-positive OCs and OC-associated genes expression in RAW264.7 cells, demonstrating their promotion effect of mechanical loading on osteoclastogenesis [55]. Matsuike et al. also reported similar findings [56]. In addition, Changkhaokham et al. found that the combination of compressive force and mechanical vibration significantly increased the number of tartrate-resistant acid phosphatase (TRAP)-positive cells and increased the expression of OC marker genes such as nuclear factor of activated T cells, cytoplasmic 1 (NFATc1), dendritic cell-specific transmembrane protein (DC-STAMP), and cathepsin K (CTSK) [32]. These findings reveal that mechanical loading promotes osteoclastogenesis by directly acting on OC precursor cells. Furthermore, other studies have demonstrated an indirect promotion effect of mechanical loading on OCs. Zhou et al. reported that orthodontic force activated OCs and promoted external root resorption by increasing the expression of RANKL in periodontal ligament stem cells (PDLSCs) [57]. Huang et al. found that mechanical force increased OC differentiation by promoting exosome PDLSC biogenesis [33]. Taken together, mechanical unloading increases OC differentiation and bone resorption, which results in OP, whereas mechanical loading suppresses OC activity and bone resorption and shows therapeutic potential in OP (Fig. 10.1). However, there are conflicting results regarding the effects of mechanical loading on OCs and bone resorption, which may be due to different types or patterns of mechanical loading. This requires further investigation.

10.2.4 Osteocyte mechanobiology and osteoporosis About 90%–95% of the bone cells in bone tissue are Ocys, long-living and abundant bone cells. Ocys are the terminally differentiated OBs and they are located within the calcified bone matrix. They have been identified as the main

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mechanosensors and coordinators in bone to maintain bone homeostasis by coordinating bone formation and bone resorption [7]. Through mechanotransduction processes, Ocys sense, respond, and transduce mechanical signals into biochemical signals to elicit cellular responses and regulate the function of other bone cells (e.g., OBs, OCs) [58]. Therefore, the abnormal mechanotransduction of Ocys will result in bone disorders such as OP [7]. Studies show that mechanical unloading (e.g., simulated microgravity) alters Ocy function and results in bone loss. Simulated microgravity by HLU induces apoptosis of Ocys in both trabecular and cortical bone. This is followed by increase of OC number, reduction of trabecular and cortical width, and a decrease of bone mineral density [34]. According to this study, the diminished mechanical forces eliminate signals that maintain Ocy viability, thus resulting in Ocy apoptosis. The dying Ocys further recruit OCs, which leads to increased bone resorption and bone loss, highlighting the importance of Ocy mechanotransduction in OP [34]. The importance of Ocys in bone mechanical conduction and bone homeostasis was demonstrated by Tatsumi et al., who adopted a diphtheria toxin receptor (DTR)-9.6 kb transgenic mouse model for Ocyspecific and -inducible ablation [59]. The researchers discovered that the mice with Ocys removed developed OP and showed resistance to the bone loss induced by HLU [59], demonstrating the contribution of Ocy mechanotransduction to bone health and bone disease. Thus, it is not surprising that changes in Ocy size and density may be associated with worsening of biomechanical properties of bone tissue, hence contributing to OP [60]. Furthermore, it is found that disruption of osteocytic canalicular networks reduces the connectivity between Ocys and osteons/interstitial tissue, which diminishes Ocys mechanosensitivity and contributes to increased bone fragility in the elderly [61]. As the morphology of Ocys is changed in OP or osteoporotic fracture condition, Cheung et al. investigated the effects of mechanical loading via LMHFV on Ocy morphology and osteoporotic fracture healing [35,36]. They found that LMHFV upregulated E11, dentin matrix protein 1 (DMP1), and fibroblast growth factor 23 (FGF23) but downregulated sclerostin in Ocys [35]. Moreover, they found that LMHFV promoted mineralization, mineral apposition rate, and bone mineral density in OP rats. These results reveal the therapeutic effect of LMHFV on osteoporotic fracture healing by enhancing the Ocy morphology and functions [35]. These studies demonstrate that Ocys are mechanosensitive and their mechanotransduction is important for maintaining bone health.

10.3 Bone cell mechanobiology and scoliosis Scoliosis, in which deformity refers to a deviation in the coronal position, is a curve in the spine caused by the midline of one or more spine segments turning outwards [62]. Severe curvature of the spine can cause difficulty in sitting and requires surgical correction. Adolescent idiopathic scoliosis (AIS) is frequently

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occurring and causes abnormal bone growth and decreased bone density, as well as bone metabolism disorders and spine malformation in three dimensions and axial planes [63]. Congenital scoliosis is an important classification of scoliosis, a vertebral deformity caused by abnormal development of the embryonic body segments leading to spinal deformity [64]. Alteration in biomechanics is an important characteristic of scoliosis [65,66]. Here we summarize the relationship between mechanical transduction of bone cells and the development of scoliosis.

10.3.1 Mechanobiology of bone marrow mesenchymal stem cells and scoliosis BM-MSCs have been determined to be involved in scoliosis. In scoliosis patients, the osteogenic capacity of BM-MSCs is reduced, and bone thickness is decreased, suggesting that BM-MSCs may control bone mass generation in AIS patients and contribute to the development of AIS [67–69]. Because low bone mass and osteopenia have been observed in AIS, Park et al. determined the association between MSC osteogenic/adipogenic potential and bone mass by comparing 16 patients with lower leg fracture to 19 age- and gendermatched AIS patients [69]. They found that the bone mineral thickness of AIS patients was lower than that of the control group, and that the osteogenic differentiation potential of MSCs from AIS patients was lower than that of the control group, indicating that the reduced osteogenic differentiation capacity of MSCs may be one cause of low bone mass in AIS [69]. Although BM-MSCs are involved in AIS development, the relationship between mechanotransduction of BM-MSCs and AIS is still not clear. As mechanical factora play key role in maintaining bone health, it is important to investigate mechanotransduction of BM-MSCs in scoliosis development and their application in scoliosis treatment.

10.3.2 Osteoblast mechanobiology and scoliosis Asymmetric degeneration of the intervertebral disc directly leads to an uneven load distribution on both sides of the intervertebral disc, causing the asymmetric loss of intervertebral disc height and a series of asymmetric changes in the intervertebral space of scoliosis segments, including the apical region, which eventually leads to the occurrence and continuous progression of scoliosis [70,71]. Scoliosis in teenagers is one of the foremost common spinal deformations. In AIS OBs, the molecular mechanosensory response is reported to be changed. Oliazadeh et al. reported that the cilia length dynamics in response to flow of AIS OBs differs from that of normal OBs [72]. Furthermore, primary OBs isolated from patients with idiopathic scoliosis (IS) show significantly enlarged primary cilia [73]. In primary OBs cultured from IS patients, the average

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primary cilium length was approximately 2.6 μm, compared to about 1.9 μm in healthy donors [73]. Furthermore, primary OBs from IS patients showed significant less response to mechanical loading than cells from controls when they were subjected to physiologically appropriate shear stress (1 Hz, 1 Pa) [73]. Moreover, there is a relationship between OP and scoliosis, as OP contributes to the deformity observed in degenerative scoliosis. DeWald et al. found that the wedge-shaped change of the vertebral body caused by OP promotes the development of scoliosis [70]. Furthermore, Velis et al. reported that the prevalence and severity of OP were increased in people with preexisting IS [74]. Because the dysfunction of OBs is one main cause of OP, these findings suggest the involvement of mechanotransduction of OBs in scoliosis.

10.3.3 Osteoclast mechanobiology and scoliosis Because there is relationship between osteopenia and AIS and osteopenia is considered as one cause of scoliosis curvature progression and curve severity [75–79], OCs have been demonstrated to be involved in scoliosis [80]. However, to our knowledge, there are very few reports on the relationship between OC mechanotransduction and scoliosis.

10.3.4 Osteocyte mechanobiology and scoliosis Ocys are considered the primary mechanosensors of bone and their mechanotransduction plays a key role in skeletal growth and function [81]. There is a reduced number of Ocys in the bone of AIS patients and the Ocys are less active with shortening dendritic length and abnormal canaliculi network [82–84]. Ocys react to mechanical stimuli by producing a variety of biological factors that regulate bone homeostasis. Sclerostin secreted by Ocys is encoded by the SOST gene and is a mechanosensitive molecule [85]. Sclerostin has been demonstrated to be involved in scoliosis [84]. Zhang et al. found a decrease in SOST gene expression and sclerostin secretion in the primary Ocys from AIS patients [86]. These results demonstrate an important role of Ocys and Ocy-derived sclerostin in AIS. Because Ocys are the primary mechanosensors of bone and orchestrators of bone remodeling, their mechanotransduction plays a key role in regulating bone development and homeostasis. Therefore, it is essential to study the role of Ocy mechanotransduction in scoliosis.

10.4 Chondrocyte mechanobiology and osteoarthritis OA is a bone disease that occurs worldwide [87,88]. It is characterized by cartilage destruction with inflammation and degradation that leads to pain and disability [89]. The main pathological features of OA are a decrease in articular

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chondrocytes, increase in degradation of the extracellular matrix (ECM), osteophyte formation, bone remodeling, and subchondral bone sclerosis [87,90]. OA seriously affects people’s health and quality of life and increases socioeconomic burden [87]. In recent decades, OA has become a hot topic of research worldwide for better understanding its development mechanism and finding effective therapeutic strategies and methods. The chondrocyte is the sole cell type in articular cartilage (AC) and plays a critical role in maintaining AC homeostasis [91]. In adult AC, chondrocytes make up only 2%–5% of the total tissue; most of the components are ECM and water [92]. Inside the cartilage ECM, chondrocytes are surrounded by collagen type VI rich pericellular matrix (PCM), which functions as a “channel” to regulate and transmit extracellular biomechanical and biochemical signals to chondrocytes [93]. In addition, numerous mechanosensors in chondrocytes, such as primary cilia, mechanosensitive ion channels, integrins, and cytoskeleton, can also detect these signals [94]. As AC is exposed to a changing mechanical loading environment, chondrocytes sense and respond to various extracellular mechanical signals to control cartilage homeostasis and OA development [95,96]. Over the last few decades, chondrocyte mechanobiology has been extensively studied. Chondrocytes live in a dynamic mechanical environment that incorporates compression, HP, shear stress, osmotic stress, and tensile strain [97]. Chondrocytes are sensitive and responsive to mechanical stimuli [98]. They sense and convert various mechanical signals into biochemical signals through mechanoreceptors on the cell membrane and transduce these signals through signaling pathways, which ultimately translate these signals into different biological effects [99]. Therefore, the response of chondrocytes to mechanical stimuli is important for both the maintenance of cartilage homeostasis and the development of OA [99] (Fig. 10.2). Physiological loading promotes proliferation, differentiation, and matrix synthesis of chondrocytes, whereas abnormal loading conditions (e.g., mechanical overloading, reduced loading) cause destruction and degradation of the cartilage and trigger OA [100–103] (Fig. 10.2). Mechanical overloading is considered one of the main causes of OA [104]. Destabilization of medial meniscus (DMM) and anterior cruciate ligament transection (ACLT) have been revealed to cause overloading of mechanical stress and result in OA [105,106]. In addition, studies have shown that mechanical overloading increases chondrocyte apoptosis and induces damage of the collagen network to contribute to OA. Loening et al. reported that injurious mechanical compression induced chondrocyte apoptosis and degradation of the collagen fibril network [107]. Additionally, Clements et al. discovered that cyclic mechanical loading increased collagen denaturation in bovine articular cartilage in a dose-dependent manner [108]. In addition, mechanical overloading accelerates chondrocyte senescence and ferroptosis,

FIG. 10.2 Schematic illustration of main effects of mechanical stimuli on articular cartilage via regulating chondrocyte’s function.

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which contributes to the development of OA [109–112]. Mechanical overloading also increases matrix metalloproteinases (MMPs) and the proinflammatory cytokines (e.g., interleukin 6 (IL-6), IL-1β, prostaglandin 2 (PGE2)) [113–117], and induces matrix degradation and chondrocyte cell death, contributing to OA. Lack of mechanical stimulation (reduced loading) causes cartilage thinning and softening. In patients with spinal cord injury, the AC thickness is significantly decreased following 1 year of reduced loading [118]. Moreover, reduced loading caused by immobilization in animals (e.g., dogs, rats) results in the reduction of glycosaminoglycans (GAG) content and proteoglycan content and AC softening [119,120]. However, the real aggrecanase II (ADAMTS5), a disintegrin and metalloproteinase with thrombospondin motifs 5, and matrix metalloproteinases (MMPs) such as MMP1 and MMP3 are increased by reduced loading with immobilization [113,120]. Because abnormal mechanical loading impairs chondrocyte function, induces cartilage damage, and leads to OA, optimal mechanical loading is important for chondrocytes to function normally to maintain AC integrity and health, and even for treating OA. Moderate mechanical loading (pressure-induced strain at 0.33 Hz) of human articular chondrocytes induced the integrin-regulated secretion of IL-4 with subsequent autocrine/paracrine activity, which is important in maintaining AC structure and function [121]. Because IL-4 exhibits an antiinflammatory effect, increases aggrecan expression, and decreases MMP3 expression [122,123], the above findings suggest that moderate mechanical loading may have potential to treat OA. Leong et al. found that moderate mechanical loading suppressed the increase of MMP3 and ADAMTS5 as well as diminished the reduction of proteoglycan content that was induced by reduced loading [120]. Musumeci et al. investigated the effects of exercise on aging cartilage to see if OA might be avoided through exercise [124]. They found that treadmill exercise in elderly rats promoted the synthesis of lubricin, a chondroprotective glycoprotein, improved lubrication, and prevented cartilage degradation [124]. This study suggests that moderate physical exercise, normal joint loading, and mechanical stimulation can be applied to treat cartilage diseases to prevent OA during aging. Helmark et al. reported that acute resistance exercise increases IL-10, an antiinflammatory factor, in OA patients, suggesting a positive effect of exercise on a chondroprotective antiinflammatory cytokine and the beneficial effect of exercise on OA [125]. These findings suggest the potential of moderate mechanical loading for combating cartilage destruction and treating OA. Physiological loading is important for normal chondrocyte function and maintenance of cartilage health, while abnormal mechanical loading induces cartilage destruction and degeneration and triggers OA. However, moderate mechanical loading (e.g., physical activity) has been shown to be a potential therapeutic method to combat cartilage destruction and to treat OA.

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10.5 Conclusion and perspectives As a specific mechanical support structure of body, bone grows and develops under mechanical stimulation. Mechanical stimulus is critical for maintaining bone homeostasis and health and is also involved in bone disease development by affecting function of bone cells. During these processes, mechanotransduction of bone cells plays important roles. Under abnormal mechanical stimuli (e.g., mechanical unloading, mechanical overloading), bone cells sense and respond to abnormal mechanical stimuli and change their functions, which results in bone diseases. This chapter summarizes research in mechanotransduction of bone cells involved in bone diseases, focusing on OP, scoliosis, and OA. The importance of mechanical stimuli in regulating bone homeostasis and diseases through bone cell mechanotransduction has been confirmed. Moreover, proper mechanical loading has been suggested as a potential therapeutic method for OP and OA. However, there are still many questions to be answered. By uncovering the effects of mechanical stimuli on bone cells during bone homeostasis and bone disease development, how do we design proper exercise regimes or mechanical treatment methods or devices? As several types of mechanical loading, such as LMHFV, acoustic-frequency vibration, and WBV, show therapeutic effects on OP by regulating the function of BM-MSCs, OBs, OCs, and Ocys, is there a best type of mechanical loading? Which kind of bone cell is the primary functional cell in responding to mechanical stimuli and during mechanical loading treating OP? How do the bone cells interact with each other to respond to mechanical stimuli? Because exercise (physical activity) and moderate mechanical loading are beneficial for treating OA, which kind of exercise and what frequency is best? Further research is needed to answer these questions to gain a better understanding of bone cell mechanotransduction in bone homeostasis and bone diseases. Additionally, more suitable mechanical methods for preventing and treating bone diseases will be established by answering these questions. Finally, more clinical trials of mechanical loading for the treatment of bone diseases are needed.

Acknowledgments This work was supported by the Natural Science Foundation of China (82072106, 81772017, 31400725, 31570940, 30970706, 30840030, 31370845), the Project Supported by Natural Science Basic Research Plan in Shaanxi Province of China (2023-JC-YB-163, 2018JM3040 and 2015JQ3076), Young Talent Fund of University Association for Science and Technology in Shaanxi, China (20170401), the China Postdoctoral Science Foundation (2018T111099, 2017M610653, 2015T81051, 2014M562450), and the Shaanxi Postdoctoral Science Foundation.

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Chapter 11

Biomechanics in clinical application for bone diseases Yuhong Niua, Yongle Wanga, Hailan Mengb, Chong Yinc,d, Kai Dangc, and Airong Qianc,* a

Nursing and Rehabilitation College, Xi’an Medical University, Xi’an, People’s Republic of China, Department of Spine Surgery, Honghui Hospital, Xi’an Jiaotong University, Xi’an, People’s Republic of China, cLab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China, dDepartment of Clinical Laboratory, Academician (expert) workstation, Lab of Epigenetics and RNA Therapy, Department of Rehabilitation Medicine, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China * Corresponding author. b

11.1 Introduction Bone is a biomaterial composed of organic and inorganic matter. It not only exhibits elasticity and toughness but it also displays hardness. If the bone inorganic matter (mineral) content increases, bone stiffness will also increase [1]. The proportion and content of bone organic matter and inorganic matter are in constant dynamic change throughout one’s life. Although this change is affected by many factors such as age, hormones, nutrition, and heredity, mechanical stimuli are some of the most important factors affecting bone metabolism. In daily life, every bone of the human body bears a load (external force). The load’s size, direction, and form directly affect the bone’s structure and function. Osteocytes (Ocy) play a leading role in sensing and regulating the mechanical signals of bone [2]. Ocy can sense the physical changes caused by mechanical strain and regulate their bone effector cells, such as osteoblasts (OBs) and osteoclasts (OCs), to affect bone resorption or bone formation [3]. Biomechanics in the study of bone has been carried out from two aspects: material mechanics and structural mechanics. The characteristics of bone material mechanics include a series of reactions in the bone under external forces, including stress, strain, stress-strain relationship (stress-strain curve), elastic modulus, and other mechanical parameters. The physical properties (elasticity, Bone Cell Biomechanics, Mechanobiology, and Bone Diseases. https://doi.org/10.1016/B978-0-323-96123-3.00006-3 Copyright © 2024 Elsevier Inc. All rights reserved.

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toughness, hardness, brittleness, etc.) of organic matter and inorganic matter that constitute bone materials determine the mechanical properties of bone materials. The characteristics of bone structural mechanics are the lamellar structure dense substance and the distribution of cancellous reticular structure in bone, which determines the strength, stiffness, and stability of the bone. The biomechanical characteristics of bone are not only related to its interior (material and structure) but also affected by its exterior (shape, size). Abnormal bone biomechanics will lead to changes in the total amount of bone, imbalance of bone proportion, and changes in bone structure, and then cause various bone diseases such as osteoporosis (OP), bone fracture, osteoarthritis (OA), hyperosteogeny, and so on. In recent years, mechanical stimuli in treating bone diseases have become the focus of scientific research and clinical application [4,5]. Its advantages include less trauma, fewer side effects, good curative effect, and high patient compliance. This chapter reviews abnormal bone biomechanics involved in bone disease development and the treatment of bone diseases by mechanical stimuli.

11.2 Abnormal bone biomechanics involved in bone diseases Bone is a sensitive mechanical organ. An appropriate load can induce an increase in bone mass and improve the structure of bone. Within the load-borne limit, there is a physiological balance between mechanical stress and bone tissue. In this equilibrium, the activities of OBs and OCs in bone tissue are the same. When the load increases, bone stress, the activity of OBs, bone formation, and the bearing area of bone also increase. A new balance will be established between mechanical stress and bone tissue. On the contrary, when the load decreases, the activity of OCs and bone resorption function increases and bone mass decreases. However, when the mechanical stress is too large and exceeds the bearing range of bone, the structure of the bone will be damaged, most commonly resulting in a bone fracture. There may also be OA, hyperosteogeny, and other diseases at the joints. When the mechanical stress is too small or insufficient, bone metabolism disorder, bone tissue structure degradation, and bone loss, such as OP, may result. In addition, malnutrition, gene mutation, and other factors will lead to rickets, osteosclerosis (OC), osteogenesis imperfecta (OI), and other bone diseases.

11.2.1 Bone fracture biomechanics Bone fracture is a partial or complete fracture of bone integrity and continuity. If the load exceeds the ultimate strength or acts on the bone for a long time, it will lead to bone fracture characterized by angulation, displacement, crack, and so on. Bone fracture is one of the most prone injuries in the motor system, and thousands of fractures occur every week worldwide [6]. Throughout most of life, the load borne by bone matches its bearing capacity and thus bone can function fully. If the load is too large, the strain of bone will also be too large. Once the load exceeds the bearing capacity of bone, bone tissue will be damaged. This

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phenomenon is common in accidents. If the load is too small, the strain is also small, resulting in bone loss, such as what occurs during long-term bed rest, immobilization, and weightlessness. According to the different stress directions and bone deformation, bone load forms include tensile load, compressive load, bending load, shear load, torsional load, and composite load. This section describes different types of fractures caused by abnormal load.

11.2.1.1 Bone fracture under tensile load Tensile load is an external force of equal magnitude and opposite direction applied along the long axis of the bone, resulting in tensile stress and strain in the bone, such as in the upper limb when carrying heavy objects or in the vertebrae during spinal traction treatment. The continuing large tensile load will lengthen the bone, especially in the limb’s long bones. The tensile strength limit of a long bone is 122.9–155.5 MPa, the elongation is 1.41%–1.59%, and the elastic modulus is 17.5–18.9 GPa [7]. Bone diseases caused by abnormal tensile load are common in the femoral neck (tension side), patella, anterior tibia, medial malleolus, talus, the proximal end of the fifth metatarsal, and so on [8]. The injury shows that the osteon and interstitial bone are stretched and stripped at the adhesive layer. The shaft is mainly bone dense, with low elongation and high elastic modulus. Therefore, the bone fracture surface presents a transverse shape and short oblique sawtooth shape (Fig. 11.1). The reason for the injury is that these parts are more prone to high tensile load. For example, the Achilles tendon or peroneal brevis tendon contracts strongly in a concise time during strenuous exercise, and stretching the calcaneus or the fifth metatarsal

FIG. 11.1 Tensile bone fracture of the fifth metatarsal base. (A) Transverse bone fracture. (B) Short oblique serrated bone fracture.

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base leads to fractures in these parts (Fig. 11.1). Bone damage caused by the tensile load is common in violent sports, especially football [9].

11.2.1.2 Bone fracture under compressive load Compressive load is an external force of equal magnitude and opposite direction applied along the long axis of the bone, resulting in compressive stress and compressive strain in the bone. Compressive load is the most common form of load borne by bone. In most cases, gravity and supporting force become the compressive load of bone, especially when the human body is upright or lying flat. A certain amount of compression load can stimulate the proliferation of bone cells, maintain the normal metabolism of bone, and promote the healing of bone fractures. The compressive strength limit of a long bone is 117.0–170.0 MPa, the compression ratio is 1.80%– 2.10%, and the elastic modulus is 14.7–19.8 GPa [7]. Bone diseases caused by high-strength compressive load are common in the spine and joints, destroying bone trabeculae in cancellous bone and destroying weak dense bone. In addition, compression load shortens and thickens the bone. Most fracture are 30- to 45-degree oblique or vertical compression fractures (Fig. 11.2). The lower thoracic vertebrae and the upper lumbar vertebrae are common sites for spinal compression injury, mostly caused by trauma. For example, if the human body falls upright or is injured by heavy objects from the vertical direction, this will likely cause vertebral compression and bone fracture. In addition, patients with OP will also experience lumbar compression fractures due to decreased bone stiffness and strength.

FIG. 11.2 Vertebral compression bone fracture. (A) Oblique bone fracture. (B) Vertical compression bone fracture.

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Compressive injuries of long bones and joints are common in high-altitude falling, mechanical sprain, heavy injury, traffic accidents, and so on.

11.2.1.3 Bone fracture under bending load Bending load is when both ends of the bone are subjected to transverse or lateral pressure to bend the bone along its axis. At the end of the bone, the tensile stress and compressive stress are the largest and gradually decrease to the center. Bending loads occurs when bones move in the form of levers, such as the lower limbs when riding a bicycle and the upper limbs when lifting weights. The ultimate bending strength of long bone is 212.0–232.0 MPa; the maximum deflection is 10.0–16.2 mm, and the elastic modulus is 10.2–18.7 GPa [7]. High-strength bending load is common in the bending failure of ribs and limb bones under high-strength axial pressure or lateral impact manifested as a bone fracture at the maximum bending moment. The bone fracture surface presents short, oblique, serrated shear and transverse tensile fractures (Fig. 11.3). Bending loads are categorized into three-point bending, four-point bending, and eccentric bending. The three-point bending load bone is subjected to three external forces located at both ends and in the middle of the bone (Fig. 11.3A). The force direction of the force points at both ends is different from that in the middle. Abnormal three-point bending load can be seen in fractures caused by antagonistic injuries in the middle of limbs, such as illegal trampling in football matches. In four-point bending load, the bone is subjected to four external forces, located at both ends and inside of the bone. The force direction at both

FIG. 11.3 Bending load of the femur. (A) Three-point bending bone fracture. (B) Four-point bending load. (C) Eccentric bending bone fracture.

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ends is different from that of the internal force points. Plate internal fixation after long bone fracture is a typical four-point bending load (Fig. 11.3B). Eccentric bending load is when the bone is subjected to compression load, the stress action point deviates from the axis, the stress on the bone cross-section is uneven, and there is large compression deformation on one side and small compression deformation on the other side (Fig. 11.3C). Abnormal eccentric bending load will cause bone bending deformation, common in the compression deformation of the femur and tibia in patients with rickets or chondropathy.

11.2.1.4 Bone fracture under shear load A shear load is an external force of the same size, opposite direction, and close to the action line on the bone, resulting in shear strain in the bone. For example, when the lower leg suddenly brakes during running, the inertial sliding of the lower femur on the plane of the upper tibia. The bearing capacity of bone under shear load is lower than that under bending load, and the shear strength perpendicular to the long axis of bone is significantly greater than that parallel to the long axis of bone. The shear strength limit of long bone perpendicular to the long axis of bone is 72.3–85.8 MPa and the shear limit deformation is 0.59–0.71 mm [7]. Large shear loads often cause the shear failure of the calcaneus, femoral condyle, and tibial plateau, as well as articular surface damage (Fig. 11.4). Shear fractures also occur in the distal humerus, mainly due to partial flexion of the elbow joint, pronation of the forearm, and palm landing posture, and the force transmitted upward from the ground along the radius acts on the capitulum of the humerus. In addition, due to the low strength of cancellous bone, shear damage is more likely to occur in cancellous bone. Shear bone fracture is common in long bone fractures caused by violence and traffic accidents. 11.2.1.5 Bone fracture under torsional load Torsional load is a torsional force (force couple) at both ends of the bone in the opposite direction. The bone distorts in its axis and generates shear stress in the bone. For example, the upper limb of a tennis swing and the lower limb of in situ rotation. Human bone is the least able to bear torsional load and is the most vulnerable to injury. The ultimate torque of long bone is between 12 and 140 Nm, and the ultimate torsion angle is between 1.5 and 35.7 degrees [7]. Long bones of limbs are prone to spiral fractures in rapid torsion, in which the bone fracture surface shows spiral changes (Fig. 11.5). Due to the traction of local muscles and ligaments, the bone fracture surface is extremely unstable. Usually, there will be obvious displacement of the bone fracture end, and the bone fracture surface may even pierce the skin to form an open bone fracture. Generally, the internal fixation is carried out after the reduction of the bone fracture surface by surgical methods. If the fixation is not firm enough after the reduction, it will cause the displacement of the bone fracture surface again, resulting in nonunion or malunion of the bone fracture.

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FIG. 11.4 Tibial plateau shear bone fracture.

11.2.1.6 Bone fracture under composite load In the process of human movement, various loads are often applied to the bone simultaneously to form a composite load. Because bones are subjected to loads from different directions and sizes in the process of growth, bones constantly adapt to these loads through changes in shape and structure. The composite load can be regarded as the superposition of two or more single loads among tensile load, compressive load, bending load, shear load, and torsional load. Therefore, various loads are superimposed to form various combinations, resulting in various bone deformations and injuries in the clinic, such as insertional bone fracture, long oblique bone fracture, short oblique bone fracture, spiral bone fracture, star bone fracture, crack bone fracture, comminuted bone fracture, and others.

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FIG. 11.5 Spiral bone fracture of the humerus.

Some occupational groups are associated with bone diseases, which may be caused by excessive bone load when holding a certain posture under a heavy load or repeatedly completing a certain action. Studies have shown that heavy manual workers such as porters and farmers are more likely to suffer from knee, hip, spine, and neck OA than other groups, construction workers are more likely to suffer from shoulder OA, and dentists are more likely to suffer from hand OA. This risk increases with the increase of professional years [10]. On the contrary, people who often do not exercise or exercise less, such as office staff and patients who stay in bed for a long time, have too little load on their bones, lack mechanical stimuli, and have a greater chance of OP and bone fracture [11]. In addition, the bone is subjected to non-physiological stress for a long time and then repaired after slight local damage. If bone is continually subjected to external force during the repair process, this can cause repair obstacles and increase bone resorption. Repeat this process, and finally leads to the emergence and increase of bone microcracks (mussel shell cracks) due to the more

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significant bone resorption than bone repair, resulting in bone fracture and damage, called fatigue bone fracture [12]. This phenomenon is common in long-term military training and sports training. Slight changes in fatigue bone fracture surface are difficult to diagnose by early X-ray. Because there is no obvious history of trauma, it is easy to misdiagnose the problem or miss the diagnosis entirely (Fig. 11.6).

FIG. 11.6 Fatigue bone fracture of the tibia.

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11.2.2 Spinal diseases biomechanics The spine consists of vertebrae (26 in adults), ligaments, joints, and intervertebral discs. It connects the skull upward and the hip downward and participates in forming the thorax, abdominal cavity, and pelvic cavity. The spine is the trunk’s main body, which functions to maintain human posture, participate in movement, and protect internal organs, blood vessels, spinal cord, and spinal nerves. Spinal disease is disease of the bones, ligaments, joints, intervertebral discs, and the muscles around the spine, which reduces the support and movement ability of the spine, compresses the spinal cord, spinal nerve, and its surrounding blood vessels, and presents complex symptoms. Common spinal diseases include cervical spondylosis (CS), lumbar spondylosis, spinal deformity, and so on.

11.2.2.1 Cervical spondylosis CS is a disease formed by degenerative pathological cervical spine changes. It is due to changes in anatomical structures of the neck, such as cervical strain, hyperosteogeny, intervertebral disc degeneration, cervical ligament thickening, or calcification. The stability of the cervical spine decreases, the spinal canal and intervertebral foramen become narrow, and the cervical nerves or blood vessels are mechanically compressed, resulting in dysfunction. According to the different involved tissues and structures, CS can be divided into soft tissue, nerve root, spinal cord, sympathetic, vertebral artery, and other types (Fig. 11.7A). If more than two types exist simultaneously, it is called “mixed-type” CS.

FIG. 11.7 Spinal diseases and osteoporosis. (A) Cervical spondylosis: (a) compression esophagus type, (b) nerve root type, and (c) spinal cord type. (B) Lumbar disease and osteoporosis: (d) normal type, (e) intervertebral disc degenerating type, (f) Intervertebral disc protrusion type, (g) nucleus pulposus protrusion type, (h) vertebral bone hyperplasia type, (i) normal bone, and (j) osteoporosis.

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Soft tissue type CS is the early stage of CS during which there are acute or chronic injuries to cervical muscles, ligaments, and joint capsules; there may be a small degree of intervertebral disc degeneration. Patients with cold, fatigue, improper sleep posture, or improper pillow height can experience neck muscle spasm, excessive extension or flexion of the cervical spine, and compression of cervical nerves and blood vessels and other tissues, resulting in neck pain. There are no obvious degenerative changes such as intervertebral space stenosis on the X-ray. Still, there can be changes in the physiological curve of the cervical spine, instability between vertebrae, and mild hyperosteogeny. In comparison with the other types, the CS with the highest incidence is nerve root type CS, which accounts for 60%–70% of all CS cases. It is caused by the stimulation and compression of cervical nerve roots in the spinal canal or intervertebral foramen due to intervertebral disc herniation, intervertebral joint displacement, hyperosteogeny, and other reasons. It often occurs in the C5–C6 and C6–C7 spaces. Spinal cord CS is mainly caused by spinal canal stenosis caused by vertebral hyperplasia, which compresses the spinal cord and causes sensory-motor and reflex disorders. Sympathetic-type CS is caused by intervertebral disc degeneration or external force, leading to segmental instability of the cervical spine, stimulating the sympathetic nerve and producing sympathetic nerve disorder. Vertebral artery-type CS is caused by segmental instability of the cervical spine, narrowing the transverse foramen of the cervical spine and stimulating or compressing the vertebral artery walking in the transverse foramen, resulting in insufficient blood supply to the brain. Other types of CS are mainly esophageal compression CS due to the beak-like hyperplasia in front of the cervical vertebra, which oppresses the esophagus and causes dysphagia. In the clinic, mixed-type CS is also common. It is dominated by one type and combined with other types to varying degrees. CS is an age-related disease, and the incidence rate increases with age. However, recent clinical studies have shown that the incidence rate of CS decreases with age in the elderly older than 60 years, increasing with age in young adults and adults [13]. On the one hand, with increasing age, the intervertebral disc water gradually decreases and loses strength and elasticity, making it easy to induce intervertebral disc herniation. On the other hand, with age, the chronic degeneration of the intervertebral disc leads to nuclear atrophy, the volume of the nucleus becomes smaller, and the inflammatory response decreases [14,15]. Before 50 years old, nucleus inflammation is stronger than degeneration’s. On the contrary, after age 60, inflammation of the nucleus is weaker than its degeneration.

11.2.2.2 Spine deformity Under normal conditions, in the coronal position, the volume of vertebrae increases from top to bottom, and the spine forms a straight line in the longitudinal direction. Sagittal observation is showed that the spine has physiological curvature: cervical, thoracic, lumbar, and sacral curvature. The neck and waist

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curvature are forward, and the chest and sacrum curvature are backward. The gravity line on the sagittal plane passes through C1, T1, T12, and S1 from top to bottom to maintain the best physiological curve of the human body and maintain balance and coordination ability. Spinal deformity is the abnormal shape of the spine that deviates from the normal position in the coronal, sagittal, or axial position. Scoliosis refers to one or more segments of the spine bending to one side in the coronal position or accompanied by vertebral rotation. Clinically, scoliosis greater than 10 degrees can be diagnosed as scoliosis deformity. It includes idiopathic scoliosis, congenital scoliosis, and neuromuscular scoliosis. The etiology of idiopathic scoliosis is unclear, but it has a certain relationship with genes and heredity. There are often morphological changes in vertebrae, thickening, and hardening of small joints to form osteophytes. The rotation of the vertebral body causes the ribs on the convex side to move to the dorsal side, making the rear back protrude; this is called “razor back.” It can also cause changes in intervertebral discs, muscles, and ligaments. Severe thoracic deformities can cause compression and deformation of the lungs and even cause pulmonary heart disease. Congenital scoliosis is an abnormal vertebral structure caused by congenital dysplasia. The pedicle on one side of the vertebral body is underdeveloped or disappeared, or it merges with the adjacent vertebral body, or the intervertebral space is abnormal, resulting in scoliosis or kyphosis. Congenital scoliosis is usually accompanied by spinal cord deformities, such as an intraspinal tumor, longitudinal fissure of the spinal cord, syringomyelia, meningocele, and so on. Neuromuscular scoliosis, mainly due to systemic muscle system disease, leads to chest and back muscle weakness and disease in which the paravertebral muscle cannot support the spine well. It includes upper motor neuron damage, such as cerebral palsy, spinal cord injury, and lower motor neuron damage, such as poliomyelitis, spinal muscle atrophy, and so on. In the sagittal position, spinal deformity is seen in the changes in the physiological curvature of the spine. The first is that the curvature of the spine becomes larger than normal. The normal range of anterior convex angle of cervical curvature is 20–35 degrees and that of lumbar curvature is 20–60 degrees. Long-term study and work in the forward bending posture will relax the neck and waist flexor muscles, tension the ascending muscles, and increase the local curvature. Under normal circumstances, the physiological kyphosis angle of thoracic vertebrae is less than 50 degrees, and the crest of kyphosis is at T6–T8, forming a balanced physiological arc with lumbar lordosis. When the kyphosis angle is greater than 60 degrees, this balance is broken, the stress on the spine in the axial direction is unbalanced, the support capacity of the surrounding muscles and ligaments decreases, and pain and even dysfunction occur. The second is that the curvature of the spine becomes smaller, the spine becomes straight, and even reverse curvature occurs. It is related to abnormal posture, fatigue, lack of exercise, spinal injury, spinal calcification, aging, and other factors. The curvature of the spine becomes smaller, which makes the

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space between vertebrae smaller, and the pressure of the intervertebral disc increases, making the intervertebral disc and vertebrae susceptible to injury. In addition, it reduces the balance ability of the human body.

11.2.3 Osteoarthritis biomechanics OA is a degenerative and inflammatory reaction in the articular cartilage. The progress of the disease affects the subchondral bone, synovium, and joint capsule. Affected by various factors, the transparent, smooth, elastic, and regular edge of articular cartilage on the joint surface turns pale yellow, loses luster, the surface becomes rough, and there is local softening and loss of elasticity, which is the main manifestation of OA in the early stage. With disease progression, the surface of articular cartilage appears fragmented with peeling and ulcer and the subchondral bone plate is exposed. The density of the subchondral bone in the central part with the greatest cartilage wear increases, the subchondral bone in the peripheral part atrophies, and cystic degeneration occurs. At the edge of the cartilage, the cartilage proliferates excessively and forms a cartilaginous osteophyte. Osteophytes can be located at the attachment of the tendon, ligament, and joint capsule or protrude into the joint cavity. At the same time, synovium also shows congestion, fibrosis, and loss of elasticity, and even lymphatic follicles and immune complexes can be seen (Fig. 11.8). Fibrous degeneration and thickening of the joint capsule limit the joint’s range of motion. The clinical manifestations include joint tenderness, joint stiffness, joint swelling, joint limited movement, joint deformity, and so on.

FIG. 11.8 Osteoarthritis. (A) Cartilage damage, (B) meniscus injury, and (C) bone spur.

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OA is the most common arthritis, which occurs most commonly in the more flexible joints of the whole body, such as hip, knee, hand, foot, and spine [16]. An estimated 250 million people worldwide suffer from knee OA [17]. It is believed that OA is a bone and cartilage disease caused by many factors, including general factors, mechanical injury, lifestyle, and nutrition. General factors include age, gender, heredity, obesity, and so on. Age has the most obvious effect on OA; the incidence of OA increases with age. Compared with men, women are more prone to OA, mainly in the hands, feet, and knees [18], which may also be related to the secretion of sex hormones. There are significant differences in OA incidence rates among people in different color [16]. About 30%–65% of OA risk is determined by genes [19,20]. Warner et al. [21] reported that 21 independent OA susceptibility sites had been identified in a whole genome-related scanning study. Obesity is also a predisposing factor for OA, especially in the knee and hip joints with a load-bearing solid capacity [22]. Mechanical injury is an important risk factor for OA. Due to the structural changes around the joint, the stress distribution on the joint surface is uneven or the joint is overloaded, resulting in cartilage wear, damage, and even subchondral bone damage. This is particularly common in the joints of the lower limbs. Anterior cruciate ligament injury, meniscus tear, and direct injury to articular cartilage are all associated with subsequent knee OA [19,20]. Some occupational activities are closely related to the incidence of OA. Footballers and weightlifters have a high incidence of knee OA, while baseball players have a high incidence of elbow OA. Miners and carpenters take a high risk of knee OA, while distal interphalangeal joint OA incidence is greater in workers with repetitive grip [16]. This may be due to long-term, high-intensity and repetitive joint movement; the joint’s excessive stress and wear lead to OA. In addition, joint trauma can also lead to post-traumatic OA, which may be due to irreparable tissue damage in the joint under a sudden high load. After trauma, long-term structural changes occur in the joint, resulting in biomechanical changes similar to dysplasia [23]. In terms of lifestyle, some surveys have shown that smoking can reduce the risk of knee OA, but other factors of smokers may also cause it. The relevant mechanism is unclear [24,25]. In addition, a lack of nutrients is related to the development of OA. These nutrients include vitamin C, vitamin D, vitamin K, and selenium [16]. These vitamins may be involved in the differentiation and metabolism of articular cartilage. Therefore, a healthy and balanced diet is also important for preventing OA. OA has a high probability of disability. At the same time, it also affects the psychology of patients, resulting in problems such as anxiety and depression [26–28]. In addition, OA is a risk factor for the development of cardiovascular disease, which is closely related to coronary heart disease and myocardial infarction [29–31].

11.2.4 Osteoporosis biomechanics OP is a bone disease caused by endocrine diseases, nutritional diseases, longterm braking, and other reasons. In OP, bone mineral density (BMD), bone

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quality, bone strength and bone stiffness decrease, whereas bone fragility increases, making bone more prone to fracture. There are two types of OP: primary OP and secondary OP. Primary OP is bone loss with increasing age. Women are at greater risk than men, especially postmenopausal women. Secondary OP is bone loss caused by chronic disease (chronic kidney disease, blood system diseases, gastrointestinal diseases), drugs, malnutrition, and so on. Pathological manifestations include thinning of BMD, porous bone, thinning and loss of bone trabeculae (Fig. 11.7B) [32], defects in the properties of organic and inorganic materials of bone tissue, repair defects of bone tissue micro-injury caused by normal daily activities, and excessive bone remodeling rate [33]. Clinically, the diagnosis of OP is often made in the lumbar spine. Dual-energy X-ray may show fishtails like double concave or wedge-shaped collapse of the vertebral body or even a completely flattened one. The common clinical manifestations are pain, body deformation, bone fracture, respiratory dysfunction, and so on. Pain is the most common symptom of OP, mainly muscle pain and bone pain, which can occur in all body parts, especially the waist and back. The degree of pain in different positions is also different. The pain in a supine or sitting position is reduced and aggravated by standing upright or sitting for a long time. This may be due to the reaction caused by the decline of bearing capacity after bone strength and stiffness decline. The pain is relieved during the day and aggravated when waking up at night or early in the morning. The patient’s body length is shortened and there is a hunchback. This is because the height of the vertebral body decreases during the reconstruction of the bone in the non-weight-bearing direction, especially the height of the anterior column of the vertebral body, which makes the spine lean forward and form a hunchback. OP worsens with increased of age and the curve of the hump increases. Bone fracture is the biggest hazard of OP, which often occurs in thoracic vertebrae, lumbar vertebrae, distal radius, proximal femur, proximal humerus, and so on. The change of spinal curvature and bone fracture will cause kyphosis and thoracic deformity, resulting in the reduction of vital capacity and maximum ventilation, chest tightness, shortness of breath, dyspnea, and other symptoms, as well as pulmonary embolism, accumulation pneumonia, and other serious complications. OP is a global public health problem. The population with greatest incidence is the elderly. More women than men are affected, with about 30% of postmenopausal women suffering from OP [34]. The pathogenic factors of OP include general factors, disuse, lifestyle and nutrition, diseases and drugs, and others. General factors include age, gender, race, low weight, and so on. The bone mass of the human body reaches its peak at the age of 40 years, that is, the peak bone mass. Bone loss increases with age, especially after menopause [35]. Of course, the higher the bone peak in youth, the lower the probability of OP caused by bone loss in old age because there is a sufficient bone mineral reserve in the body. The incidence rate of OP in different races is also significant, whites are higher than the yellow race, and blacks are relatively low. Among Whites and Asians, the proportion of women over 50 years of age is higher.

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Among Hispanic subjects aged 50–59 years, the proportion of men with OP was greater than that of women; however, after age 60 years, incidence in women was greater than that in men. Before the age of 70 years, the proportion of Black men with OP was greater than that of Black women. After age 70 years, this trend reversed. Regardless of gender or race, OP incidence increases sharply with age [35]. Low body fat percentage or low body mass index is associated with an increased risk of low bone mass and rapid bone loss, which are risk factors for OP [36]. In terms of factors of disuse, long-term bed rest is the cause of aggravating OP. Long-term bed rest leads to reduced activity, reduced mechanical stimuli to the bone, bone loss in trabecular and cortical areas, and greater bone absorption than bone formation. These mainly occur in patients with bone fractures and neuromuscular injuries, especially elderly patients. In addition, bone loss caused by space flight is a process of microgravity adaptation, and OP will also occur among astronauts on missions in space. From a microscopic point of view, bone cells sense mechanical load through mechanical sensors, which convert extracellular mechanical signals into intracellular biochemical signals and regulate gene expression [37]. The mechanical load exerted on bone cells determines the metabolism and gene expression of bone cells. In terms of lifestyle and nutrition, smoking, excessive drinking, and drinking coffee (tea) are positively correlated with OP [38,39]. Insufficient intake of nutrients such as protein, calcium, and vitamin D is also an important factor inducing OP [40]. Secondary OP is associated with many diseases, including gastrointestinal diseases, blood diseases, hypogonadism, and so on [41]. Some drugs interfere with calcium absorption and cause OP, including diuretics, glucocorticosteroids, anticonvulsants, immunosuppressive drugs, nonsteroidal anti-inflammatory drugs, asthma drugs, glucocorticoids, and some antibiotics [35].

11.2.5 Rickets and osteomalacia biomechanics Rickets and osteomalacia (OM) is a new bone disease characterized by bone matrix mineralization disorder. Patients often have systemic calcium and phosphorus metabolism disorders and bone changes. In addition, the disease affects the functions of nerves, muscle, hematopoiesis, immunity, and other tissues and organs. Rickets is an incomplete calcification of cartilage and bone tissue in children’s metaphysis of long bones. The high-risk group for this disease is infants younger than 2 years. It is characterized by stunting, late independent walking, anemia, hepatosplenomegaly, malnutrition, and susceptibility to diarrhea and pneumonia. Children with low blood calcium may have low calcium spasms, increased neuromuscular excitability, facial, hand, and foot muscle convulsions, or generalized convulsions. Children with rickets have decreased bone stiffness, increased bone toughness and ductility, and exhibit bone bending and deformation. Children learn to sit and stand before they are 1 year old,

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as ligament relaxation can cause spine deformity, forming a “chicken chest.” After age 1, after standing and walking, both lower limbs bear weight. OM causes low bone strength and relaxation of muscle joints, femur, tibia, and fibula bend, forming knee varus (“O” shape) or knee valgus (“X” shape) deformity. In addition, children are in a period of growth and development, and the proportion of organic matter in bone is more than that of adults. Children’s bone toughness is greater than that of adults, and the inorganic matter is relatively less. Bone stiffness is reduced, as is bone load-bearing capacity. The size of children’s bones is smaller than that of adults, and their bearing capacity to load is also small. The low stiffness, high toughness, and ductility of bones cause “greenstick” fractures to appear after fractures, and the bone fracture surface will not be completely broken [42]. Rickets is a bone matrix mineralization disorder that occurs from birth to adolescence, during which the long bone epiphysis is in the growth stage or prophase of closure. However, in adulthood, after the growth of epiphysis has been closed, impairment in mineralization in the bone matrix renewal process is called OM. The common symptoms of OM include bone pain, muscle weakness, muscle spasms, and bone tenderness. The early symptoms may not be obvious. Back, waist, and leg pain is common and intensifies during activities. Once bone softening is aggravated, long-term weight-bearing or muscle traction during activities will cause bone deformity, resulting in cervical shortening, lumbar lordosis, thoracic kyphosis, scoliosis, and height shortening, accompanied by obvious local or systemic pain. Patients with reduced activity may have disuse muscular atrophy and decreased bone strength and stiffness. Minor trauma will lead to pathological fractures, especially at the ends of long bones and the junction of ribs and costal cartilage. This type of disease causes malnutrition, vitamin D deficiency, absorption disorder, and chronic hypophosphatemia (Fig. 11.9) [43,44].

11.2.6 Osteosclerosis biomechanics In contrast to rickets and OM, osteosclerosis is a relatively rare hereditary bone disease, and at least 10 gene mutations in humans have been identified as pathogenic factors [45]. The typical manifestations are bone fracture, bone pain, and hypocalcemia. Osteosclerosis may also cause anemia, bleeding, deafness, decreased vision, infection, and other complications. Due to the dysfunction of OCs, the absorption of bone is weakened, resulting in excessive deposition of calcium salt in bone and increased BMD [46]. Osteosclerosis increases the stiffness of bone, reduces strength and ductility, and the surface of bone looks like marble or ivory. Articular cartilage calcifies gradually and joint space becomes narrower (Fig. 11.10). The bone becomes very brittle and prone to fracture [47]. Clinically, there are two categories of osteosclerosis: autosomal recessive osteosclerosis (ARO) and autosomal dominant osteosclerosis (ADO). ARO is

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FIG. 11.9 Rickets.

FIG. 11.10 Normal bone and OC.

often found in newborns. Children are prone to short stature, bone fracture, hepatosplenomegaly, skull sclerosis, compression of head and facial nerves, ankylosing epilepsy, and so on. Patients usually die within 10 years of age due to severe infection and bleeding. ADO is more common in adults. It has a late onset, stable condition, and better recovery. Nearly half of ADO patients have no symptoms, and one quarter may have low back pain. There may also be manifestations of cerebral nerve compression. Anemia and hepatosplenomegaly are rare, with hip varus, lateral femoral arch, and other deformities. The incidence rate of ARO is 1:250000 and the incidence of ADO is 1:20000 [45].

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11.2.7 Osteogenesis imperfecta biomechanics Osteogenesis imperfecta (OI) is a rare genetic disease caused by a gene mutation. It is caused by insufficient collagen fibers in bone, increased bone cortical space, reduced thickness, degenerated trabecular bone structure, thinner bone, and decreased bone stiffness and strength (Fig. 11.11) [48,49]. Most cases of OI (85%–90%) are associated with dominant pathogenic variants of COL1A1 or COL1A2 genes. The remaining cases of OI (10%–15%) are caused by pathogenic variation of non-ollagen genes, encoding proteins involved in collagen biosynthesis, or transcription factors and signal molecules related to Oy differentiation and mineralization. These cases are associated with autosomal recessive, dominant, or X-linked inheritance [50]. The clinical symptoms of OI are increased bone fragility, and slight injury can cause fractures. Most of these fractures are “greenstick” fractures, with less displacement of the bone fracture surface, less pain, and fast bone fracture healing. OI usually appears in childhood. After puberty, the number of fractures is reduced, but children are prone to scoliosis, flat pelvis, short stature, and so on [51]. The estimated incidence rate of OI is about 1:10 000 [1]. OI lesions are not limited to bones but often involve other connective tissues, such as eyes, ears, skin, teeth, and so on. Complications include abnormal teeth, blue-gray sclera, hearing loss, hyperkinesia of joints, muscle weakness, cardiovascular and pulmonary diseases, and more. The incidence of pulmonary complications is a major cause of morbidity and mortality of OI, mainly due to rib bone fracture, scoliosis, myasthenia gravis, and pulmonary dysfunction [52]. OI complications lead to bone and joint dysfunction, discomfort, and chronic pain, which significantly affect patient quality of life [53,54].

FIG. 11.11 Normal bone and OI.

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11.3 Therapeutic strategies for bone diseases by using mechanical stimuli Bone is a sensitive mechanical organ. Appropriate mechanical stimuli can regulate bone tissue’s metabolism and maintain bone’s biological function. Similarly, when bone is damaged, mechanical stimuli also play a very important role in treating bone diseases. These stimuli can accelerate the proliferation and differentiation of bone cells, reshape the histological structure of bone, and promote bone repair. Next, we introduce various methods of mechanical stimuli treatment of bone diseases in the clinic.

11.3.1 Mechanical stimuli of bone fracture Reduction, fixation, and healing comprise the trilogy of bone fracture treatment. Bone fracture reduction is to restore the displaced bone fracture end to normal or close to normal anatomical relationship and reconstruct the role of the bone scaffold. It is the basis of bone fracture fixation and rehabilitation. The purpose of bone fracture fixation is to obtain sufficient stability at the bone fracture site, create a good mechanical environment for bone fracture healing, and accelerate bone fracture healing.

11.3.1.1 Type of bone fracture fixation Bone fracture fixation includes external fixation and internal fixation. External fixation is to fix the reduced bone fracture surface outside the limb (Fig. 11.12A). Common external fixation equipment includes plaster bandage, small splint, tractor, external fixator, and so on. Internal fixation is the incision of the tissue where the bone fracture is located, the reduction of the bone

FIG. 11.12 Bone fracture fixation. (A) External fixation. (B) Internal fixation.

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fracture, and then fixation with an internal fixator (Fig. 11.12B). Commonly used internal fixators include bone plate, screw, intramedullary needle, bone round needle, steel wire, degradable biomaterial, and other materials.

11.3.1.2 Bone fracture healing mechanism In the bone fracture healing process, when the interspace is less than 1 mm, blood vessels and primitive mesenchymal cells enter the bone fracture and OBs differentiate and proliferate to form osteoid on the bone fracture surface. Especially in the close contact part of the bone fracture, the bone reconstruction unit can directly cross the bone fracture line without forming internal and external callus, which is the direct healing of the bone fracture (primary healing). In most cases, the bone fracture interspace is more than 1 mm, the callus is generated at the bone fracture end to promote the formation of the original callus, and the bone fracture is healed through callus transformation and shaping is indirect healing (secondary healing). The process of indirect healing can be divided into four stages: inflammation, proliferation, consolidation, and remodeling. In the inflammatory period after bone fracture (day 1–4), the blood vessels around the bone fracture rupture and bleed, and the surrounding hematoma is formed. Severe injury and vascular rupture make the bone fracture end ischemic, leading to the necrosis of some soft tissue and bone tissue and causing an aseptic inflammatory reaction at the bone fracture. In the proliferative stage (day 5–21), fibroblasts in granulation tissue synthesize and secrete a large number of collagen fibers, which are transformed into fibrous connective tissue to connect the two ends of the bone fracture. During the consolidation period (week 4–8), callus is constantly produced and callus calcification is strengthened. The bone fracture will achieve clinical healing when it is enough to resist muscle contraction, shear, and rotation. The remodeling stage (after week 9) is reshaped into the mature bone after the callus forms a bone bridge connection. 11.3.1.3 Mechanical environment of bone fracture healing Mechanical stimuli are the key factors in promoting bone fracture healing. In bone fracture healing, the initial level of mechanical stimuli is determined by functional limb load and stable bone fracture fixation environment [55]. Mechanical stimuli can act on the cells in the healing area, make the mesenchymal cells aggregate in the early healing stage, form callus in the repair stage, trigger callus formation, and promote bone fracture healing [56]. There is no consensus on the best mechanical environment for bone fracture healing because it depends on factors such as bone fracture geometry, bone fracture type, bone fracture interspace, and movement between fragments [57]. From the perspective of biomechanics, very strict fixation will lead to bone stress shielding, destruction of blood vessels around the bone fracture surface, and reduction of bone mass, resulting in delayed bone fracture healing and even nonunion. For example, if the rigidity of the fixator is insufficient, large bending

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deformation will occur after fixation, the stability of the bone fracture end will be poor, and a large shear force will be generated, resulting in abnormal healing or delayed healing of the bone fracture. There are two types of bone fracture fixation: flexible and rigid fixation. In flexible fixation, the stiffness of the fixator is less than that of rigid fixation, and the mechanical stimuli intensity on the bone fracture surface is greater than that of rigid fixation. At the initial stage of bone fracture, the effect of rigid fixation is better than that of flexible fixation before callus formation. This has been confirmed in animal experiments [58]. There is a healing response of periosteal repair and callus formation without mechanical stimuli, and the stiffness of the bone is significantly greater than that with mechanical stimuli [59,60]. This is because early mechanical stimuli will inhibit macrophages from entering the inflammatory injury surface and affect the self-healing of tissues [61,62]. Once the calcified callus is formed, if there is not enough mechanical strain (despite the healing activity), the process of abandoned atrophy may prevail [63]. At this stage, the effect of flexible fixation is better than that of rigid fixation. Therefore, different fixation methods in different periods of bone fracture are more conducive to bone fracture healing, which requires that the “variable stiffness fixator,” which integrates flexible and rigid fixation functions, may be more suitable for bone fracture fixation. This variable fixation technology changes its mechanical properties from “rigid” to “dynamic” during bone fracture healing, speeds up callus formation, and promotes bone fracture healing. Still, there are more stringent requirements for fixator materials, bone fracture interspace, and operation difficulty [64].

11.3.1.4 Additional mechanical stimuli after bone fracture fixation There are also many preclinical animal studies on applying additional mechanical stimuli after bone fracture fixation. During the healing process of the sheep tibial bone fracture internal fixation model, Barcik et al. [65] applied mechanical stimuli with constant amplitude (amplitude 1.00 mm, 1000 stimuli cycles per day) to the bone fracture site through the active fixator during the day for 12 h. They rested at night for 12 h for 9 weeks. During this period, they found that the stiffness of bone fracture repair tissue first decreased and then slowly increased in the stimuli stage. The stiffness increased continuously in the rest of the stage, and the change of stiffness in the rest of the stage was significantly greater than that in the stimuli stage. Thus, researchers [66] applied intermittent mechanical stimuli with constant amplitude for 5 weeks in the sheep tibial bone fracture model. They found that compared with intermittent mechanical stimuli with a rest time of 10 s and a rest time of 2 h, the shorter rest time inhibited callus formation and did not increase bone stiffness. Long rest time can promote callus’s strong formation and increase bone stiffness. It shows that the formation of the callus is regulated by the number of stimuli cycles applied in a day. In applying mechanical stimuli to the bone, the length of stimuli time affects bone

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metabolism, and too-frequent stimuli will affect the formation of callus [66]. Appropriate stimuli time is the key factor in accelerating bone tissue repair. Further research is needed to determine the optimal time distribution of mechanical stimuli after bone fracture.

11.3.2 Vibration training Vibration training is a kind of mechanical stimuli characterized by oscillatory motion. The human body relies on the vibration platform to receive vibration stimuli and produce local or systemic adaptive responses. Biomechanical parameters include amplitude (peak-to-peak displacement of oscillatory motion; unit: mm), frequency (repetition frequency of vibration period; unit: Hz), and magnitude (determined by acceleration). There are various types of vibration, and sinusoidal vibration is the only single-frequency response type used to study the efficacy of animal and human tissues [67]. Vibration training first appeared in the 1930s and was used for treating cardiovascular diseases [68]. Thereafter, it was widely used in treating vascular, nervous system, and musculoskeletal system diseases.

11.3.2.1 Types of vibration training Vibration training includes local body vibration (LBV) and whole-body vibration (WBV) (Fig. 11.13) [69]. LBV applies vibration stimuli to a target area of the body, such as a joint or muscle, making the mechanical stimuli effect more significant [70]. WBV is generally stimulated at the foot, and the vibration direction includes the up-and-down displacement from the sole to the top of the head and the displacement on the left and right sides of the fulcrum [67].

FIG. 11.13 Vibration training modes of different body parts. (A) Upper limb vibration training. (B) Hip vibration training. (C) Whole-body vibration training (upright position). (D) Whole-body vibration training (tilt position).

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At present, the safety parameter values of vibration equipment used in the clinic include vibration frequency of 15–60 Hz, amplitude less than 14 mm, and acceleration delivered of up to 15 g(1.0 g ¼ Earth’s gravitational field ¼ 9.8 m/s2) [67]. LBV is a more suitable method in areas with local bone, joint, and muscle injury, high risk of bone fracture, or requiring muscle strengthening [71]. WBV can improve bone mass and BMD in children and adolescents with bone injury [72].

11.3.2.2 Treatment parameters and efficacy Low-intensity (2 W/cm2 [85]. The principle of ultrasound therapy is to use ultrasound to penetrate human tissue to produce vibration, which causes the movement of particles in the tissue to form a micro impact effect to produce mechanical stimuli. 11.3.3.2 Treatment parameters and efficacy Ultrasound has thermal and non-thermal effects on biological tissues. The greater the intensity, the greater the thermal effect. The heat generated by low-intensity pulsed ultrasound (LIPUS) is less than 1°C and will not cause thermal damage. LIPUS generally applies the frequencies of 1–3 MHz (Fig. 11.14) [86]. It is commonly used to treat bone diseases, including brittle fractures, instrumented fractures, and infectious nonunion [87,88]. Salem et al. [89] and Farkash et al. [90] used LIPUS for patients with delayed bone healing for more than three months. Patients were treated previously for tibial defects and underwent callus distraction surgery after trauma or scaphoid fracture fixation. The treatment lasted for 20 min daily, with a frequency of 1.5 MHz, repetition rate of 1.0 kHz, pulse length of 200 μs, and sound intensity of 30 mW/cm2. In the LIPUS group, the bone healing index of patients with tibial defects who underwent callus distraction surgery was shortened by 12 days/cm, which promoted callus formation during distraction osteogenesis. The cure rate of scaphoid bone fracture patients with delayed healing was 76%. The earlier

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FIG. 11.14 Ultrasound therapy.

LIPUS was used, the higher the cure rate was. Leighton et al. [88] systematically analyzed 1359 patients (aged 17–77 years) who were treated with LIPUS for bone diseases. Results showed that the cure rates of LIPUS for instrument fracture nonunion, infectious fracture nonunion, and fragile bone fracture nonunion were 82%, 82%, and 91%, respectively. LIPUS has a good curative effect and provides a conservative treatment option for patients with bone diseases to avoid the impact of surgery on the economy and patient quality of life. If callus formation is not obvious after 3–4 months of LIPUS treatment, it should be terminated, and surgery or other methods should be recommended.

11.3.4 Extracorporeal shock wave therapy A shock wave is formed when the moving speed of the wave source exceeds its propagation speed. It is the propagation of a discontinuous peak in the medium, which leads to the sudden change of physical quantities such as pressure, temperature, and density of the medium. There are two kinds of shock waves: mechanical waves and electronic waves. Extracorporeal shock wave (ESW) is a mechanical shock wave with sound, light, and mechanical properties. It can reach a peak value of 500 bar (1 bar ¼ 105 Pa) in a very short time (about 10 ns) and has a short period (10 μs) and wide frequency spectrum (16–2  108 Hz) [91]. Extracorporeal shock wave therapy (ESWT) is a method to stimulate damaged tissues and treat diseases by focusing shock waves on the damaged parts of the human body. It was first used in treating renal calculi in Germany in 1979. The accidental observation of the OB response pattern in animal research in 1980 opened a path to the treatment of bone diseases. The principle of ESWT is to generate acoustic wave energy by water explosion caused by high pressure. The reflector reflects the acoustic wave and is concentrated into high-energy

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shock waves to act on the body surface. Through energy conversion and transmission, shock wave causes energy gradient difference and torsional tension between tissues with different densities, forms a cavitation effect, stimulates the production of growth factors, leads to angiogenesis, and achieves the function of tissue regeneration and repair [92,93].

11.3.4.1 Treatment parameters and efficacy Currently, ESWT is widely used in the treatment of bone diseases (Fig. 11.15). It has a good therapeutic effect, few side effects, and does not cause trauma. Cacchio et al. [94] treated patients with long bone nonunion with ESWT (4000 pulses, energy flux density of 0.40 mg/mm2 or 0.70 mJ/mm2) and surgery, respectively. The curative effect of the ESWT group was greater than that of the operation group at 3 and 6 months after treatment. However, there was no difference between the two groups at 12 and 24 months after treatment. The results show that ESWT has the same effect as surgery in promoting the healing of long bone nonunion, and the short-term clinical effect of ESWT is better. Elster [95] and Xu et al. [96] also showed that ESWT has a good effect in treating long bone nonunion. Yu et al. [97] systematically reviewed the treatment of ESWT in femoral head necrosis. They concluded that ESWT is a safe and effective physical therapy method that can improve motor function and reduce pain in patients with femoral head necrosis, especially at the early stage. Wang et al. [98] compared the therapeutic effects of ESWT, core decompression, and bone grafting on early femoral head necrosis and found that ESWT had the best effect. In addition, ESWT is also effective in the treatment of tendon and ligament injuries such as humeral lateral epicondylitis [99,100], shoulder calcified

FIG. 11.15 Extracorporeal shock wave therapy.

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tendinitis [101,102], patellar tendinopathy [103], and Achilles tendon disease [104,105].

11.3.5 Magnetic therapy Magnetic therapy is a method of applying a magnetic field to the human body to treat diseases. There are many electrolytes distributed in the human body. When the magnetic field acts on the human body, the distribution, concentration, and movement speed of ions in the human body will change under the action of the magnetic field force. The cell membrane potential and permeability will also change and form mechanical stimuli on the local or whole body.

11.3.5.1 Types of magnetic field Magnetic fields are categorized according to their size and direction as constant, alternating, pulsed, pulsating, magnetic resonance heat, or pulsed electromagnetic fields (PEMFs). The action of magnetic therapy relies on the magnetic field effect to accelerate cell repair and renewal, correct endocrine disorders, and regulate the balance of physiological functions of the body. 11.3.5.2 Treatment parameters and efficacy PEMFs produce the magnetic field effect via a current of a certain strength passing through the Helmholtz coil. The intensity of the magnetic field will change with time, but the direction of the magnetic field will not change with time, and there are pulse intervals (Fig. 11.16) [106]. There are low-, medium-, and highfrequency PEMFs. Low-frequency PEMFs (6–500 Hz) do not produce thermal effects. Instead, they act on bone tissue to produce an effect similar to fluid mechanical shaping and affect biological metabolism through asymmetric wide pulse to improve the pathological state of bone, muscle, and other tissues [107].

FIG. 11.16 Treatment of bone diseases with PEMFs.

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When the frequency of pulse current generated by PEMFs matches the cyclotron resonance frequency of key ions (such as Na+, K+, and Ca2+), corresponding biological changes can occur by affecting the activity of ion channels [108]. PEMFs were first applied to bone diseases in the 1970s and achieved good results in treating bone nonunion after bone fracture [109]. In recent years, as noninvasive, safe, and effective physical therapy, PEMFs have been more widely used in the clinic. Massari et al. [110] used PEMF therapy for patients with femoral head necrosis. The stimulator was used for 8 h a day for 6 months. The frequency was 75 Hz and the pulse duration was 1.3 ms. The results showed that 94% of patients with stage I or II femoral head necrosis were cured by PEMF therapy. Streit et al. [111] used PEMF therapy in patients with delayed healing or nonunion of the fifth metatarsal bone fracture. Compared with the non-stimulated control group, the growth factor at the bone fracture in the treatment group was significantly increased and the bone fracture healing time was shortened. PEMFs can accelerate bone fracture healing and reduce pain in tibial bone fracture, femoral neck bone fracture, and femoral shaft bone fracture. The treatment frequency is 5–105 Hz and intensity is 0.5–2 mT. The treatment time is 1–8 h/day for 6–12 weeks [112,113]. In the treatment of bone fracture, PEMFs can inhibit the production of inflammatory cells in the inflammatory stage, promote the proliferation of bone cells in the proliferative stage, consolidation stage, and remodeling stage, and accelerate the repair of bone tissue [114]. Huang et al. [115] systematically reviewed the treatment of patients with OP by PEMFs. They believed that PEMFs can effectively alleviate the pain of primary OP, promote bone formation, and increase the BMD of secondary OP. However, there is controversy about the impact on BMD and bone resorption of primary OP.

11.3.6 Massage therapy Massage therapy is a treatment method that uses manipulation or instruments (such as a massage hammer, massage pad, and massage chair) to stimulate specific parts of the human body. Massage therapy can regulate the physiological and pathological processes of the body, promote local or systemic blood circulation, improve tissue excitement, and improve human immune capacity. It is the oldest method of physical therapy.

11.3.6.1 Types of massage techniques and treatment scope Massage techniques include massage, friction, pressing, tapping, vibration, shaking, and more. In orthopedic diseases, massage therapy is used to treat CS, scapulohumeral periarthritis, sprain and contusion, joint dislocation, joint sprain, lumbar muscle strain, intervertebral disc herniation, degenerative osteoarthropathy, tenosynovitis, and so on. In traditional Chinese medicine, massage therapy has a wider range of applications, including uses in medicine,

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surgery, gynecology and obstetrics, pediatrics, and other specialties. It is based on the theory of viscera and meridians in traditional Chinese medicine. Massage therapy is also used in health care, beauty, smoking cessation, weight loss, and more. Its advantages are that it is non-invasive, simple, controllable, and does not require complex instruments.

11.3.6.2 Therapeutic effects in bone diseases Massage therapy has an effect on the growth and development of bone. Aly et al. performed daily appropriate physical activity and whole-body massage on preterm infants at 28–35 weeks of gestation. The results showed that the combination of physical activity and infant massage stimulated the bone formation of preterm infants, which was manifested by the increase of propeptide of type I collagen (PICP) and parathyroid hormone (PTH) activity, which further stimulated bone growth and mineralization [116]. Samsung et al. [117] gave postmenopausal women a 2-hour Thai traditional massage twice a week for 4 weeks. It was found that traditional Thai massage can increase bone formation, especially in older and shorter postmenopausal women. In addition, massage therapy is also effective in correcting spinal deformities and improving lumbar stability. Massage can improve blood circulation around bones and joints, stretch shortened muscles, release adhesion, increase joint range of motion, and adjust the position of bones and joints [118,119]. Although massage therapy is safe and reliable, it should be avoided or used with caution in patients with spinal diseases, OP, and malignant tumors, as it may lead to serious complications such as bone fracture, cerebrovascular disease, and tumor tissue diffusion [120,121].

11.4 Conclusion and future perspectives The mechanical environment is a key factor affecting bone metabolism. This chapter examined the close relationship between abnormal biomechanical environment and bone diseases and summarized various methods of mechanical stimuli in the clinical treatment of bone diseases. How to avoid the adverse mechanical factors of bone metabolism and prevent the occurrence of bone diseases need more attention. In the research and treatment of bone diseases, biomechanics reveals the mechanical response of bone from macro to micro, from local to whole, and from stillness to motion. Its application is more and more extensive. A survey of medical institutions in the United States found that 72% of respondents provided biophysical stimuli to patients with bone fractures that had not healed for three months [122]. In Canada, 45% of surgeons currently use bone stimulators as an important means of bone fracture treatment. Of the survey respondents, 80% said they believe that mechanical stimuli of bone can shorten the healing time by at least 6 weeks or more [123]. Compared with drug therapy,

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mechanical stimuli have become an important treatment method to accelerate bone repair because of advantages such as causing little trauma, high safety, strong controllability, and remarkable therapeutic effect. In treating bone diseases by mechanical stimuli, there are still some applications in the initial or in vitro experimental stage. The physical parameters of mechanical stimuli need to be further optimized so that the stimuli can act on the damaged parts accurately and effectively. In conclusion, biomechanics is increasingly important in the research and treatment of bone diseases. To improve the therapeutic effect of mechanical stimuli, we must carefully and accurately use biomechanical methods, constantly update relevant equipment, and improve the treatment scheme. At the same time, we believe that its integration with rehabilitation engineering, artificial intelligence, information engineering, and other disciplines could promote biomechanics-based development in the treatment of bone diseases.

Acknowledgments The authors are grateful to those whose work was cited within and to those whose work was not due to space limitations. This publication was supported by the horizontal research project of Xi’an Medical University, China in 2023. Project No. 2023 [604].

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[51] V. Rossi, B. Lee, R. Marom, Osteogenesis imperfecta: advancements in genetics and treatment, Curr. Opin. Pediatr. 31 (6) (2019) 708–715. [52] A. Tam, S. Chen, E. Schauer, I. Grafe, V. Bandi, J.R. Shapiro, R.D. Steiner, et al., A multicenter study to evaluate pulmonary function in osteogenesis imperfecta, Clin. Genet. 94 (6) (2018) 502–511. [53] L.L. Tosi, M.K. Floor, C.M. Dollar, A.P. Gillies, Members of the Brittle Bone Disease Consortium, et al., Assessing disease experience across the life span for individuals with osteogenesis imperfecta: challenges and opportunities for patient-reported outcomes (PROs) measurement: a pilot study, Orphanet J. Rare Dis. 14 (1) (2019) 23. [54] Y. Song, D. Zhao, L. Li, F. Lv, O. Wang, Y. Jiang, W. Xia, X. Xing, M. Li, Health-related quality of life in children with osteogenesis imperfecta: a large-sample study, Osteoporos. Int. 30 (2) (2019) 461–468. [55] J. Barcik, D.R. Epari, Can optimize the mechanical environment deliver a clinically significant reduction in fracture healing time? Biomedicine 9 (6) (2021) 691. [56] M. Haffner-Lutzer, A. Liebert, A. Ignatius, Mechanobiology of bone remodeling and fracture healing in the aged organism, Innov Surg Sci. 1 (2) (2016) 57–63. [57] B. Mavcic, V. Antolic, Optimal mechanical environment of the healing bone fracture/osteotomy, Int. Orthop. 36 (4) (2012) 689–695. [58] D.R. Epari, H. Schell, H.J. Bail, G.N. Duda, Instability prolongs the chondral phase during bone healing in sheep, Bone 38 (6) (2006) 864–870. [59] B. McKibbin, The biology of fracture healing in long bones, J. Bone Joint Surg. Br. 60-B (2) (1978) 150–162. [60] L. Claes, R. Blakytny, M. G€ockelmann, M. Schoen, A. Ignatius, B. Willie, Early dynamization by reduced fixation stiffness does not improve fracture healing in a rat femoral osteotomy model, J. Orthop. Res. 27 (1) (2009) 22–27. [61] P. Augat, J. Merk, A. Ignatius, K. Margevicius, G. Bauer, D. Rosenbaum, L. Claes, Early, full weight bearing with flexible fixation delays fracture healing, Clin. Orthop. Relat. Res. 328 (1996) 194–202. [62] M.J. Gardner, M.C.H. Meulen, D. Demetrakopoulos, T.M. Wright, E.R. Myers, M.P. Bostrom, In vivo cyclic axial compression affects bone healing in the mouse tibia, J. Orthop. Res. 24 (8) (2006) 1679–1686. [63] S. Hankemeier, S. Gr€assel, G. Plenz, H.U. Spiegel, P. Bruckner, A. Probst, Alteration of fracture stability influences chondrogenesis, osteogenesis and immigration of macrophages, J. Orthop. Res. 19 (4) (2001) 531–538. [64] D. W€ahnert, J. Greiner, S. Brianza, C. Kaltschmidt, T. Vordemvenne, B. Kaltschmidt, Strategies to improve bone healing: innovative surgical implants meet nano-/micro-topography of bone scaffolds, Biomedicine 9 (7) (2021) 746. [65] J. Barcik, M. Ernst, M. Balligand, C.E. Alaska, L. Drenchev, S. Zeiter, D.R. Epari, M. Windolf, Short-term bone healing response to mechanical stimulation—a case series conducted on sheep, Biomedicine 9 (8) (2021) 988. [66] R. Hence, S.M. Perren, Mechanical stimulation of fracture healing-stimulation of callus by improved recovery, Acta Chir. Orthop. Traumatol. Cech. 85 (2018) 385–391. [67] M. Cardinale, J. Rittweger, Vibration exercise makes your muscles and bones stronger: fact or fiction? J. Br. Menopause Soc. 12 (1) (2006) 12–18. [68] C.E. Sanders, Cardiovascular and peripheral vascular diseases: treatment by a motorized oscillating bed, JAMA 106 (1936) 916. [69] D.S. Eide, P. Magnusson, Does whole-body vibration treatment make children’s bones stronger? Curr. Osteoporos. Rep. 18 (5) (2020) 471–479.

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Part IV

New technologies for bone disease

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Chapter 12

New technologies for bone diseases Shuo Gao, Hao Zhang, Linbin Lai, Menglei Xu, Hong Yu, Airong Qian, and Wenjuan Zhang* Lab for Bone Metabolism, Xi’an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of China * Corresponding author.

12.1 Introduction Common bone diseases include osteoporosis (OP), osteoarthritis (OA), fractures, osteosarcoma, and others. Among them, OP is the most frequent and common metabolic bone disease characterized by reduced bone mass and a dramatic increase in the risk of fragility fractures as well as high impact on healthcare systems and morbidity [1]. Osteoarthritis is always associated with joint pain, which occurs with activity and disappears or improves with rest. In acute attacks, pain increases, while joint swelling, joint stiffness, and intra-articular friction sounds may also intensify [2]. Fractures are a common and serious complication of OP. A common fracture condition is the loss of joint function, in which patients with intermediate and advanced osteoarthritis lose joint function and cannot perform daily walking [3]. Most current treatment options for bone diseases are medication, such as fluoride, isoflavonoids, and parathyroid hormone. Although some drugs are clinically effective in relieving bone disease, they are accompanied by adverse effects of long-term use, such as renal failure, dyspepsia, and neurological deterioration, as well as increased drug resistance. In addition, the therapeutic targets and underlying mechanisms of bone diseases are also unclear. Therefore, there is a great need to further investigate the pathogenesis of bone diseases to find effective molecules or targets, which in turn can provide new methods for the clinical treatment of skeletal disease disorders. Several new technologies such as artificial intelligence (A), single-cell sequencing, and universal genome sequencing have emerged in recent years. In this section, we examine the prospects and future state of AI, single-cell sequencing technology, and whole genome sequencing technology in bone diseases. Bone Cell Biomechanics, Mechanobiology, and Bone Diseases. https://doi.org/10.1016/B978-0-323-96123-3.00014-2 Copyright © 2024 Elsevier Inc. All rights reserved.

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12.2 Artificial intelligence 12.2.1 Artificial intelligence in medical research The rapid development of AI has provided new methods and ideas to assist physicians in making highly accurate disease diagnoses. AI has penetrated various aspects of disease diagnosis, such as radiology, pathology, and osteopathy, where it can extract valid information from medical data and make initial diagnoses of diseases. Moreover, the intricacies of the traditional medical diagnosis and treatment paradigm greatly consume the energy of clinicians and researchers, especially in disease diagnosis, where doctors’ energy is always limited. Valuable judgments and decisions as well as accurate guidance and assistance can be provided by AI, which can be used for disease diagnosis and treatment [4]. Targeted therapies for patients can be designed with algorithms that fully integrate patient history information including symptoms, laboratory results, and physical examination results [5]. Based on massive data training, an AI image interpretation system can quickly target lesion sites and make a diagnosis, helping radiologists by improving diagnostic precision. The union of AI with robotics allows the development of intelligent surgical robots with autonomy. The technical advantages of AI enable further improvement of diagnosis and treatment, make up for the lack of individual technical skills, and reduce the labor intensity of healthcare workers. In the early years of AI, it was very tough to build a neural network with excellent performance due to insufficient computing power and lack of training data. It was not until recently that the development of massive data and hardware equipment made neural network research a reality. The shallow machine learning model based on statistical theory has achieved remarkable results in theoretical analysis and practical application in the early stage but has developed more slowly over time due to the difficulty of theoretical analysis, limitations of training methods and skills, and experience dependence. The discovery by Hinton and Salakhutdinov of using unsupervised pretraining to initialize the parameters of the model and then fine-tune them using supervised training to tackle the gradient vanishing problem of back propagation (BP) algorithms set off the third tidal wave of both academic and industrial deep learning [6]. With the progress of science and technology as well as the rapid growth of data volume, data mining has become a new challenge. The diversity and precision of biological sequencing technology has led to the creation of more and bigger data. Thus, the applications of machine learning are being transformed and used in the research and analysis of biology. The use of deep learning methods to mine biological information has become a hot topic of current research. With the popularization of AI deep learning methods in recent years, AI has gradually been integrated into clinical and scientific research of various medical imaging systems. Although research on related diseases is still in its infancy, the accuracy of disease types and models remains to be improved.

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However, as AI technology continues to develop, AI medical imaging technology will inevitably continue to develop and make breakthroughs, provide more effective help for doctors’ diagnosis and treatment, and promote intelligent medical imaging to enter a new stage. Fig. 12.1 shows the process of an intelligent medical system. Another application of AI in imaging is the opportunity it offers for pathology. In pathology images, AI can automatically detect stained tissue tumorigenic epithelial cells in breast tissue, which is complicated by their extreme morphological variability [7]. Routine assessment relies on manual cell counting by the operator, which is often error-prone. Instead, multiscale generative adversarial networks (GANs) are employed to generate good-quality left-hand videotape frame in time-lapse microscopy videos to assess biological processes such as interactions and cell migration. And the accuracy is similar to that of manual detection, or even better [8]. Fetal biometrics using ultrasound imaging techniques, especially fetal head thickness measurements, are prone to spatial variation. This imaging can be done automatically and reproducibly many times by using two deep learning networks. In the first, a pretrained tiny-YOLOv2 is used to locate the fetal head, and in the second, a U-shaped mesh is used to determine the head thickness of the fetus [9]. Another example of deep learning when applied in fetoscopy imagery is the division into structures [10]. Machine learning is applied for MRI imagery characteristics to recognize the placental proliferation spectrum, with abnormal invasion of the trophoblastic muscular layer [11]. Computer technology has spawned the digital image technology of medical imaging, which is widely used in clinical work. With the development of deep learning technology, it is widely used in the detection and recognition of various diseases, especially bone diseases. As a traditional branch of bulk surgery, orthopedics is developing in the direction of intelligence, efficiency, and precision in the new era. At this stage, AI demonstrates strong potential for development and application in the diagnosis and treatment of orthopedic diseases.

12.2.2 Application of AI in bone diseases Most bone diseases can be diagnosed by X-ray, CT, MRI, ultrasound, and other imaging examinations. AI has been applied to the diagnosis of OP, as it can not only simulate the risk of brittle fracture but can also help image segmentation and recognition [5]. AI can better predict the risk of fracture. The artificial intelligence-based assistive tools have been initially applied to the study of OP, and their efficiency and accuracy is gradually improved in continuous correction. Fig. 12.2 is a system flow diagram of the bone cancer detection framework.

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FIG. 12.1 Intelligent medical system.

End Consumerss

Patients and epidemic prevention,etc. Service acceptance groups

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FIG. 12.2 The system flow diagram of the bone cancer detection framework.

12.2.2.1 Application of AI in osteoporosis OP is a disease featuring reduced bone mineral density, degradation of bone tissue microarchitecture, and increased bone fragility. Moreover, with increasing attention to ossification in the elderly population, the high incidence of osteoporotic fractures makes the diagnosis of OP critical. Singh et al. [6] extracted six statistical features including texture intensity and contrast associated with bone microarchitectural changes from X-ray films of the heel bone of osteoporotic patients to train a machine learning model to which they applied a supervised classification. This supervised classification approach was used to differentiate between patients with OP and healthy subjects. Yoo et al. [7]. collected data from 1674 Korean postmenopausal women, 1000 training sets, and 674 test sets, and developed and validated various machine learning models, including support vector machine (SVM) and artificial neural network (ANN), to compare with the performance of traditional clinical decisionmaking tools in terms of accuracy, receiver operating characteristic curve (ROC), and area under the curve (AUC). In addition, machine learning has been applied to assess the risk of osteoporotic hip fractures through statistical analysis of hip fracture risk factors and their interactions. These studies have shown that the union of trabecular microstructural features and AI algorithms can enable better prediction of the biomechanical stiffness of trabeculae and contribute to an automated goal evaluation of disorder progression and therapy response in OP [12]. Although there has been some clinical research on the use of AI in OP symptoms, the research is not comprehensive. Part of the reason for this is that there are certain ethical and patient privacy concerns associated with the creation of databases. This aspect can be regulated in the future by an anonymous conversion system to ensure the adequacy of the information sample while focusing on the privacy of the patient. In the future, the application of AI in OP should include prevention, diagnosis, treatment, medication, rehabilitation exercise,

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and postcare to improve the detection rate and treatment efficiency of the disease through real-time monitoring of the patient’s body, thus ensuring a better prognosis.

12.2.2.2 Application of AI in bone tumor diseases For bone tumor diseases, histopathology, which can be used as an effective reference to judge tumor invasion and patient prognosis, is the qualitative gold standard of diagnosis. With the emergence of full-slice scanning technology, highresolution digital images have replaced traditional slides, laying the foundation for the construction of AI pathological interpretation systems. Based on huge amounts of training specimens, the usage of in-depth acquisition techniques enables computers to mine features from histopathological images, quickly locate lesions, and make interpretations from many images. Christian et al. used new nerve grids on large-scale graphical datasets to differentiate the morphology of bone marrow cells with high accuracy, providing a new direction for the study of bone marrow cells [13]. Multiple myeloma (MM) is characterized by an excess of heavy- and light-chain monoclonal proteins (M proteins) resulting from the proliferation of tumorigenic clones of plasma cells in the bone marrow microenvironment. In addition, a decrease in normal gamma globulin leads to an increased risk of immune paralysis infection. In most cases, the root locus for almost all patients affected by MM is the bone marrow. Osteolytic lesions are frequently seen in 80% of MM patients. These can worsen quality of life and negatively affect patient survival. MM is known to involve the bone and lead to myeloma bone disease. In turn, the essential pathogenesis of myeloma bone disease is related to the decoupling of bone remodeling processes. Here, osteoclast (OC)activating factor and osteoblast (OB)-inhibiting factor are released as biochemical markers due to the interface with the bone marrow microenvironment. The most notable development in the last decade is that improvement of MM with the addition of various new therapies. These new therapies include protein lysosome inhibitors, exemption modulators, steroidal antibodies, inducers of histone deacetylases, chemically selective inhibitors of nuclear export, and late-stage anti-B-cell maturation antigen (BCMA) therapies. Thereby, better strategies must be developed to align with the findings of newer and more active anti-myeloma therapies. The principal pillars of current myeloma bone disease (MBD) management are bisphosphonates and denosumab. It is urgent that therapies aimed at pinpointing the bone and bone marrow microenvironment be developed. They must have the capacity to effectively address amelogenesis while keeping bones healthy to possibly mitigate global disease. 12.2.2.3 Application of AI in osteoarthritis OA is the most common joint disease, often resulting in chronic pain and limited motion, affecting the daily lives of 10%–15% of adults worldwide. The

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occurrence of the disease is influenced by a variety of factors, including lifestyle habits, gender, obesity, and chronic disease. The clinical manifestations of OA are usually degenerative changes and loss of cartilage. Identifying changes in cartilage allows for early diagnosis of OA [8]. Current research focuses on techniques for the identification of articular cartilage (automatic segmentation) and the qualitative detection of cartilage damage. For example, Norman et al. [9] used a 2DU-Net convolutional neural network. Automatic segmentation of cartilage as well as meniscus was performed on knee MRI data to establish laxity measurements and morphometry, with the aim of analyzing the accuracy and precision of automatic segmentation compared to manual segmentation to assess the feasibility of detecting cartilage degeneration and acute cartilage injury in knee cartilage, adopting a totally automated in-depth learning chondral lesion testing system with high-level performance in diagnosis and consistent observers. Another study sought to appraise the viability of using deep learning methods to detect cartilage lesions (encompassing chondral tenderness, fibrosis, localized lesions, pervasive disorders due to cartilage degeneration, and acute cartilage injury) in knee MRI [14] and found machine learning to be promising in the classification of patients with OA [15]. Lim et al. [10] developed a deep learning model to detect the prevalence of OA and identify high-risk factors for OA development based on some health behavior information and statistics of medical resource utilization, with the aim of early detection of patients at high risk of OA. When OA is in the middle and late stages, the bone structure changes, such as osteophytes and subdural sclerosis, and the joint space becomes narrower, which is more obvious on X-ray. Tiulpin et al. [11] applied knee X-ray imaging based on an AI algorithm to construct a network model to automate the identification of whether the knee joint has OA according to the Kellgren-Lawrence grading scale. The probability distribution of OA severity was inferred, which may not clearly categorize the severity into a certain grade but is not much different from what physicians do in clinical practice. In addition, Hirvasniemi et al. [16] performed feature extraction analysis of bone changes in hip OA to achieve automatic prediction of OA incidence and assessment of conditions requiring total hip replacement therapy. These studies, which run through the whole process of OA development, can be integrated and further improved in the future, such as by expanding the scope of application to include spinal joints, interphalangeal joints, and others to address the prevention and diagnosis and treatment of OA with a holistic approach to achieve precise treatment and improve prognosis.

12.2.2.4 Fracture In actual clinical work, X-ray plain film is a necessary examination for patients with suspected or definite fracture. Current research mainly focuses on AI in fracture interpretation and anatomical localization in X-ray and CT examinations, or in predicting fracture risk in combination with bone structure and bone

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density analysis, as well as predicting fracture risk in patients with cancer bone metastases. AI-assisted fracture identification is currently the most widely applied AI technology in the field of orthopedics. Related research has established models based on AI algorithms to achieve automatic detection of skeletal X-rays to determine the presence of fractures. These algorithms have achieved AUC values greater than 0.95 in all performance tests and an average accuracy rate of 90%–97%, which is similar to the skill level of human specialists; thus, these algorithms offer medical practitioners and urgent care physicians accurate and timely decision support [17]. In their study, Chung et al. [18] attempted to identify humeral fracture type based on Neer typing. Although only 86% of the optimal model accuracy was obtained, the study proved the feasibility and development potential of the network model for fracture type judgment. In addition, AI research on fracture mainly involves determination of body side, identification and localization of fracture, and other characteristics. Several studies have shown that the accuracy of AI diagnosis is not less than that accomplished by physicians.

12.2.2.5 Spine-related diseases Along with the progress of research in the application of AI-assisted imaging recognition, the ability to automatically assess spine shape based on radiographs has been achieved [12,13]. Horng et al. [12] used sagittal images of the spine to detect and segment vertebral bone contours and then measured the Cobb angle size to calculate spine curvature. Galbusera et al. [13] proposed an automated method for extracting anatomical parameters from biplanar radiographs of the spine, which is able to deal with a wide scenario of conditions, including sagittal and coronal deformities, degenerative phenomena as well as images acquired with different fields of view. They evaluated T4–T12 kyphosis, L1–L5 anterior kyphosis, pelvic incidence angle, and sacral and pelvic tilt, in addition to Cobb angle measurement, based on 78 anatomical landmarks such as the center of the hip joint and S1 endplate edge, to achieve a more comprehensive and fully automated radiological analysis of spinal deformities. These studies will help to eliminate the errors associated with manual measurements by physicians and provide more objective measurements more quickly to better assist in the diagnosis, treatment, and follow-up of spine-related disorders such as adolescent idiopathic scoliosis, adult deformity, and spinal stenosis. AI has been applied to the diagnosis of OP, bone tumor disease, OA, and other bone-related diseases because it can better predict the risk of bone disease occurrence. However, the development and application of AI in the field of orthopedics faces some challenges. First, orthopedics and AI are both highly specialized disciplines and their intersection requires interdisciplinary cooperation. For better practical application, the development team is bound to be very large, requiring the joint participation of orthopedic clinicians, orthopedic researchers, statistical engineers, and even mechanical engineers. Second, since orthopedic AI is based on big clinical data, collecting, storing, and analyzing

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these massive data requires powerful servers and supercomputer support, with large initial investment. Third, medical data are characterized by privacy, diversity, incompleteness, and complexity [19]. We should actively participate in the research and development of AI medical technology based on ensuring data privacy and security to promote better integration of AI and medical treatment. The development goal of AI application in the field of orthopedics has been clearly defined, and the AI algorithm will be expanded with the increase of data in the future, the performance will be further improved, and its development space will be more extensive.

12.3 Single-cell sequencing 12.3.1 Introduction of single-cell sequencing Single-cell sequencing is a tool for distinguishing the atomic scale characteristics of diverse cell clusters. It requires a priori knowledge of cell population through comprehensive, nonbiased analysis of lysis pregenitality, metastatic tumor cells, cancer stem cells (CSCs), and circulating tumor cells (CTCs). Single-cell sequencing has become a reference tool for analyzing tumor tissue composition and building the microenvironmental characteristics of cells. Understanding individual tumor cells can help us understand therapeutic resistance and cell physiology. The analysis of tumor genetic variation, specific metabolic activity, and evolution process using a single-cell sequencing technique is integral to the study of tumor occurrence and progression mechanism [20]. Compared with overall sequencing, single-cell sequencing techniques are more conducive to the interpretation of tumor heterogeneity and can obtain more information from a limited sample. The latest developments in single-cell RNA sequencing (scRNA-seq) have greatly facilitated the study of heterogeneous cell groups, which could be used to explore the transcriptional composition of single cells to their functional state of development. The appearance of scRNA-seq has made it possible to analyze cell population specificity at the single-cell level. scRNA-seq can show the changes that occur in individual cell types [21]. Fig. 12.3 maps the development of single-cell sequencing technology. In the sections that follow, we enumerate common personalized analyses based on single-cell sequencing data.

12.3.1.1 Comprehensive decomposition and clustering of single cells The first and most important step for single-cell transcriptomes is cell identification. We need to identify the cell category of the obtained cluster based on the cell-specific marker gene, and the accuracy of the cell identification will directly affect the results of a series of subsequent analyses. Once the cell types are presented, the data can then be used to mine for specific marker genes to fully characterize the cell types and to achieve cell-type purification by using

FIG. 12.3 The development process of single-cell sequencing technology.

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FIG. 12.4 Single-cell sequencing data analysis and processing process.

labeling techniques such as labeling on the cell surface or fluorescent labeling. Cell identification results can be obtained based on specific marker gene tSNE expression [22]. Fig. 12.4 shows the single-cell sequencing process.

12.3.1.2 The proposed timing analysis During the development of biological growth, cells do not grow in perfect synchrony. For example, in a group of cells obtained at the same time, some cells may have been there for a long time, while others have not even started the growth process yet. This synchronization can be a major problem when you want to understand the sequence of tuning changes that occur as cells transition from one state to another. The proposed timing analysis, also known as trajectory analysis, does not directly tell us what state each cell is in, so some analytical methods are needed to sequence the trajectories to infer the evolutionary relationship between potential cells. The trajectory analysis of abnormal tissue cells and normal tissue cells is used to adjust the heterogeneity of the genome between patients and to identify the main genes that control tumor progression. 12.3.1.3 Divide into subclusters After each cluster cell identification is complete, further type segmentation of the cells of interest can be made, and these subclusters can be assigned to known

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cell types based on the marker gene. The differences between subcluster cells and the function of subclusters in the biological process can be studied in greater depth.

12.3.2 Application of single-cell sequencing in bone cell Single-cell sequencing technology can obtain cellular genomic and transcriptomic expression levels at the individual cell level, revealing the heterogeneity of cells, which offers a new way to study the heterogeneity of multicellular organisms. In recent years, single-cell sequencing technology has developed rapidly, leading to an exponential growth in single-cell sequencing-related research. The technology has been widely used in various fields such as neurobiology, germline propagation, organ growth, and cancer biology. Some studies have summarized how to use single-cell sequencing technology to analyze bone cells. Two common methods of capturing cells are: relying on Fluorescence Activated Cell Sorting (FACS) index sorting to achieve single cell capture and using microfluidic technology to capture cells into emulsion droplets. The first approach could sequence the whole transcript; however, the cost of a single cell for this technique is typically much higher compared to the unrecorded well plumage approach, and expansion from a single cell to many cells could be limited by sequencing rates. In contrast, the newly developed droplet/microfluidic-based methods, including In Drop, Drop-seq, and 10 Genomics platforms, all allow for rapid capture and processing of huge numbers of cells. In general, the basic analysis process of single-cell sequencing data typically consists of four key steps: data cleaning, dimensionality reduction, clustering, and postclustering gene expression examination [23]. There have been many studies on the analysis of various types of bone cells based on single-cell sequencing. Qiu et al. used single-cell sequencing technology to resolve human femoral head tissue cells (FHTCs) and obtained nine cell types, including granulocytes, T cells, monocytes, B cells, erythrocytes, osteoblast spectrum cells, endothelial progenitor cells (EPCs), endothelial cells and plasmacytoid dendritic cells. In addition, they identified new genes related to bone metabolism: serine protease 23 and mechanism remodeling-related protein 8 [24]. scRNA-seq has been used to study mouse cranial OBs and it was found that the extent of changes in cell abundance and gene expression in bone-derived cells could be detected using single-cell sequencing technology [25]. Li et al. used single-cell sequencing to resolve regulatory factors in the aging process in rats and mice as well as proinflammatory and senescent immune cell subtypes, such as macrophages and neutrophils. They found that bone marrow accumulates a lot of granulocin, which induces premature skeletal aging in mice, suggesting that granulocalcin may be a potential target for the treatment of age-related OP [14]. Hui Peng et al. used single-cell sequencing technology to show that exercise promotes the secretion of a reticular localbin-2 by bone

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marrow macrophages, which initiates bone marrow lipolysis and maintains the energy homeostasis of bone resident cells [15]. Single-cell sequencing technology is increasingly being used in the field of bone cell research. Using this technology for further analysis and research of various types of bone cells will provide new ideas for future research on bone diseases.

12.3.3 Application of single-cell sequencing in bone diseases Single-cell sequencing technology has also been widely used in the research of bone diseases. Bone diseases with a high incidence rate include OA, OP, fractures, and osteosarcoma.

12.3.3.1 Osteoarthritis (OA) OA is the most common musculoskeletal disease in the world and the biggest cause of disability. Some researchers have performed single-cell RNA sequencing analysis on articular cartilage samples from Kashin-Beck disease (KDA) and OA to identify the chondrocyte populations and their genetic characteristics in KDA, OA, and healthy cells. After analysis, they found that the regulatory chondrocyte population identified by the expression of CHI3L1 was significantly expanded in OA [26]. Meanwhile, it has been shown that synovial fibroblasts and synovial macrophages are the core cells of rheumatoid arthritis, and abnormal function of these cells leads to damage of articular chondrocytes and bone. Recent breakthroughs have been made using scRNA-seq technology in the compartmentalized growth, subpopulation identification, functional characterization, and new target therapy of these two synovial cells, which will lead to significant changes in the treatment of RA [27]. Sebastian et al. used single-cell sequencing to analyze articular cartilage from the knee joints of healthy and injured mice and identified nine chondrocyte subtypes with different characteristics, as well as early damage-induced molecular changes in these chondrocytes. This study expands the research on rapid molecular changes in the chondrocyte population in responding to joint trauma [28]. Others studies have used single-cell sequencing analysis on articular cartilage tissue. They compared and analyzed cartilage cells in the knee joints of healthy and injured mice and obtained nine chondrocyte subpopulations with different molecular characteristics. In addition, they also compared and analyzed mouse chondrocyte subpopulations and human chondrocytes and evaluated their similarity, providing new ideas for studying the underlying mechanism of cartilage degradation. Zhang Liang et al. analyzed existing RNA sequencing data and single-cell sequencing data of OA chondrocytes and found that there are 14 key transcription factors in 271 genes. This study provides a reference for further elucidating the pathogenesis of OA [29].

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12.3.3.2 Osteoporosis OP is a worldwide public health problem that typically occurs in postmenopausal women. Studies have shown that >50% of premenopausal women and 50%–80% of men suffer from it. And its harm is also more, the lighter will reduce the patient’s quality of life, and the severer will be unable to take care of themselves, cause lung infections, etc., which will increase the mortality rate [30]. Therefore, the research on treatment of OP is of great significance. One study analyzed the bone marrow adipocytes of bone marrow mesenchymal stromal cells using single-cell sequencing technology to study their differentiation trajectory and found that bone marrow adipocytes may be a new target for OP [31]. A large body of evidence suggests that OBs and their traps exhibit morphological changes in aging bone, suggesting that osteocytes (Oys) are involved in the underlying process of bone aging. Despite this, the transcriptome of bone cells analyzed by advanced RNA-seq has revealed several bone aging-related genes and signaling pathways. In addition, inflammation, immune dysfunction, energy deficiency, and impaired hormonal response may affect age-related bone degeneration in bone cells. [32]. 12.3.3.3 Fractures A fracture is a complete or partial break in the continuity of bone structure. The general patient usually has a single fracture; rarely does someone have multiple fractures. When a fracture occurs, most patients can regain their original function if treated promptly and appropriately, but a minority of patients exist with varying levels of sequelae. Therefore, further research is needed in the field of bone healing. Analysis of immune cells in fracture tissues by scRNA-seq revealed that the number of B cells was significantly reduced during the earlier stages of fracture healing. In addition, B cells in the mouse model of fracture decreased significantly at the epiphyseal stage and gradually returned to normal at the epiphyseal transition stage of fracture healing, indicating that B cells are key regulators of fracture healing [33]. 12.3.3.4 Osteocytoma Single-cell sequencing technology has yielded outstanding results in cancer heterogeneity studies. Although giant cell tumor of bone (GCTB) is a benign tumor, it may lead to apparent osteolysis and bone destruction in the epiphysis of long bones. Studies have been conducted to detect the heterogeneity of GCTB by scRNA-seq, and many genes associated with cell migration have been identified [34]. Some researchers have used scRNA-seq to analyze the molecular characteristics of the progression of MM and confirmed the most significant molecular pathways affected in the progression of MM, identifying new features for predicting patient prognosis and treatment stratification [35].

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Researchers have also used scRNA-seq to discover methods for stratifying existing bone marrow CD34+ cells and thus reveal a stratified structural transcriptional landscape for hematopoietic differentiation [36]. Single-cell sequencing technology is now rapidly evolving and has excellent capabilities in terms of gene composition and gene expression status of individual cells and responding to cell-to-cell heterogeneity. The abnormality of bone cells is often accompanied by the occurrence of bone diseases [37]. Therefore, this technology is also increasingly used in the study of bone diseases. In summary, the emergence and development of single-cell sequencing technology has provided new means and methods for further bone research and new ideas for overcoming disciplinary problems. However, current single-cell sequencing methods pay little consideration to spatial information. Therefore, single-cell sequencing technology has a wide scope for future development. In the future, we expect single-cell technology to be a powerful tool in addressing long-term bone disease.

12.4 Genome-wide association study 12.4.1 The introduction of genome-wide association study Many human skeleton disorders result from DNA variants. Genome-wide association studies (GWASs) are a popular and effective method to reveal unknown susceptibility loci of complex diseases/traits in the field of genetic epidemiology. In recent years, GWASs combined with other omics data have been widely used to screen susceptibility genes and study the key molecular mechanisms of many complex diseases, including cancer, kidney disease, and OP [38]. GWASs also have systematically analyzed the association between different bases of genome-wide single nucleotide polymorphisms (SNPs) and complex diseases, providing a powerful means for mining the susceptibility genes of complex diseases such as OP and diabetes [39]. In the past decade, GWASs have been used to identify and study susceptibility regions the susceptibility genes of many complex diseases such as obesity, diabetes, hypertension, OP, and OA [40,41].

12.4.2 The research of bone diseases susceptibility genes based on GWAS Genetic factors are one of the significant factors affecting the occurrence of OP. Bone mineral density (BMD) is the common criterion to diagnose OP. It has a heritability of up to 0.5–0.8, which can be used as a direct phenotype for genetic susceptibility analysis of OP [42]. Two susceptibility SNPs (rs4355801 and rs3736228) and their respective genes (TNFRSF11B and LRP5) significantly associated with BMD, OP, and osteoporotic fracture were found for the first time by GWAS analysis by Dutch scientists [43]. Another study used metaanalysis combined with 17 GWASs

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related to OP, and identified 56 SNPs significantly related to BMD and 14 SNPs related to osteoporotic fracture risk [44]. A study identified 36 with the hips/vulnerability to spine fracture density or related area by using GWAS metaanalysis, and is verified by the experimental gene EN1 determinants can be used as the potential risk of bone mineral density and bone fractures, further confirmed GWASs used to identify the effectiveness of disease susceptibility genes screening [45]. In addition, Australian researchers used GWAS analysis to identify 153 new SNPs significantly associated with heel BMD and suggested that GPC6 may be a new BMD determining gene through functional experiments [46]. So far, more than 30 studies of GWASs related to bone phenotypes have been reported, and researchers have successfully identified more than 500 susceptible regions significantly associated with BMD [38]. Chen et al. performed a study on BMD by weighted gene co-expression network analysis (WGCNA) to identify the new genetic mechanism of OP through the largest GWAS dataset for BMD in the field, Genetic Factors for Osteoporosis Consortium (GEFOS-2), and transcriptome gene expression datasets generated from trans iliac bone biopsies of women. The findings suggest that the genes in the module play an significant role in regulating bone mass [47]. Through the analysis of the largest GWASs in the field, Zhu et al. identified additional BMD-associated genes. Three genes (C11orf58, AAAS, and UBTF) were implemented at the gene expression level among the BMD-associated genes [48]. Yang et al. highlighted findings from GWAS and studies using omics technologies to determine the mechanisms of OP, as well as summarize and integrate the current data and studies to understand, diagnose, and guide the treatment of OP [42]. Many genetic studies have been conducted to understand the genetic basis of RA, and GWAS has identified more than 50 risk loci. Studies have also found that many nonhuman leukocyte antigen (HLA) loci are involved in multiple pathways including fibroblast differentiation and dedifferentiation, immune activation, and bone modeling and repair [49]. Styrkarsdottir et al. identified the relationship of these variants with other bone-related traits and diseases, and successfully find the risk loci relate to one of these traits/diseases [50]. Jalil et al. analyzed 366 RA cases and identified 33 genotyped SNP susceptibility loci and identified the most significant SNP of RA [51]. In conclusion, GWAS data have provided means and support for the genetic research of complex diseases. They have been widely used in the mining and screening of susceptibility genes for a variety of complex diseases, including OP.

12.4.3 Multiomics study for interpretation of GWAS in bone disease genes Wen et al. integrated transcriptome high-throughput sequencing data and GWAS analysis data to detect the differential expression of STAT1 in both White and Chinese populations. STAT1 was identified as a novel susceptibility

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gene for OP in postmenopausal women. It has also been demonstrated that the STAT1 gene in human circulating monocytes plays an important role in the etiology of OP [52]. By integrating transcriptome association studies and GWAS analysis, Feng et al. identified susceptibility genes and signaling pathways significantly associated with BMD [53]. Farber constructed a coexpression network based on GWAS analysis and gene chip data and identified the significant susceptibility gene sets related to BMD in postmenopausal women [54]. Lin et al. predicted and identified several new OP susceptibility genes by integrating a variety of different omics data and GWAS analysis [55,56]. In conclusion, by integrating GWAS analysis and other omics data, multiple BMD and OP susceptibility genes have been successfully identified and their potential functions and mechanisms in the pathogenesis of the disease have been analyzed. However, the application of this method in disuse osteoporosis susceptibility gene screening and functional studies is relatively minimal. Hu ai et al. [57] studied the chromosome distribution of SNPs in BMD-related GWAS datasets and their correlation with BMD traits and the small effect of population stratification and systematic bias of the GWAS datasets. They then generated expression profiles of 1258 BMD genome-wide associated genes through the match of GWAS and the transcriptome data and subjected them to WGCNA analysis. Finally, the researchers selected the gene with the strongest correlation with BMD for further analysis (Fig. 12.5). Integrating GWAS and multiomics data analysis to mine disuse OP susceptibility genes, and its molecular regulation unity biology experimental analytical function and mechanism, which can effectively discover genetic factors from the upstream to the downstream function susceptibility genes involved in disuse osteoporosis of the complete control model of molecular function mechanism. Thus, this method can provide a clear and comprehensive perspective for the pathogenesis of disuse OP. For more common bone diseases containing a heritable component, the observed phenotype is formed by the sum total of genetic variants. GWAS uses microarray or sequencing technology to screen millions of SNPs for other variations in genomes to find gene loci associated with diseases. Complex traits are much more common and GWAS are used to identify variants/genes to study the

FIG. 12.5 Identification of BMD-related modules in the aged through WGCNA analysis.

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traits of interest. Because of the large number of SNPs and the possibility of greatly increasing false positives in the case of numerous tests, the statistical significance is usually selected as 5.0  10 8 in GWAS studies. The completion of the Human Genome Project has led to a better understanding of the relationship between gene location and genetic diseases [58,59]. By learning from GWAS, advanced and innovative methods can be used to screen and discover genetic loci associated with diseases more quickly. Fig. 12.6 shows common methods of GWAS analysis.

12.5 Conclusion and perspectives The trends and patterns extracted from massive patient-related data by AI, bone disease testing, single-cell sequencing, and whole genome sequencing is of unprecedented significance for the precision and discovery of new mechanisms of medical research. These new technologies are a cross-fusion of biology and computer disciplines. Technological advances in medicine, including AI, single-cell sequencing, and whole genome sequencing, will undoubtedly

FIG. 12.6 Schematic diagram to identify potential susceptibility genes in osteoporosis based on GWAS and transcriptome data.

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provide a new way of thinking for us to understand the mystery of life science. On the premise of perfecting the ethical factors in patients with bone diseases, constructing quality, multicenter, large-scale bone diseases medical library of biological samples, collecting a large number of epidemiological questionnaire, bone mineral density information, disease history, history of drug information is the key to the success or failure of the technology development of the bone diseases.

Acknowledgment This work was supported by the National Natural Science Foundation of China [grant number 81901917]; the Fundamental Research Funds for the Central Universities [grant number D5000210746]; the Key Research and Development Project of Shaanxi Province [grant numbers 2018SF-363, BKJ17J004, 2022SF-295]; the National Program of Innovation and Entrepreneurship for Undergraduates [grant numbers S202110699538, XN2021031, S202010699126].

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376 PART

IV New technologies for bone disease

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Abbreviations 3D 5-HT AC ACI ADO AFM AI AIS ALE ALP ANN ANXA3 AP1 ARO ATF4 ATP AUC BAIBA BAP Bglap+ BMD BMM BM-MSC BMP BMP2 BMP4 BMPR-IA BMU BN BP BV BZG cAMP Cbfa1

three-dimensional serotonin articular cartilage autologous chondrocyte implantation autosomal dominant osteosclerosis atomic force microscopy artificial intelligence adolescent idiopathic scoliosis alendronate alkaline phosphatase artificial neural network annexin A3 activator protein 1 autosomal recessive osteosclerosis activating transcription factor adenosine triphosphate area under curve β-aminoisobutyric acid bone alkalin phosphatase bone gamma-carboxyglutamate protein-expressing bone mineral density bone marrow monocyte/macrophage bone marrow mesenchymal stem cell bone morphogenetic protein bone morphogenetic protein 2 bone morphogenetic protein 4 BMP transmembrane receptors I bone multicellular unit batch normalization backpropagation blood vessel Bushen Zhuanggu granules cyclic adenosine monophosphate core-binding factor alpha-1

377

378 Abbreviations

C/EBPα ceRNA CGRP CH CKD CMP CMS CNN Col I ColIα1 COL1 COL2 Cox Cox2 CS CSCs CS-GAG CT CTCs CTSK CTX CVCs Cx Cx43 DC-STAMP DHACs DIC DKK-1 DL DMP1 DNN DOPC DTR DVL ECM EPC ER ERK ERK5 ER-α Erβ ESW ESWT FAC

CCAAT/enhancer binding protein α competitive endogenous RNAs calcitonin gene-related peptide chloral hydrate chronic kidney disease cartilage mucin protein cyclic mechanical stretch convolutional neural network type I collagen type I collagen α1 collagen I collagen 2 cyclooxygenase cyclooxygenase 2 cervical spondylosis cancer stem cells chondroitin sulfate glycosaminoglycan computed tomography circulating tumor cells cathepsin K C-terminal telopeptide calcifying vascular cells connexin connexin 43 dendritic cell-specific transmembrane protein histone deacetylase digital image correlation Dickkopf WNT signaling pathway inhibitor 1 deep learning dentin matrix protein 1 deep neural network directional osteoprogenitor cells diphtheria toxin receptor dishevelled extracellular matrix endothelial progenitors cell endoplasmic reticulum extracellular regulated MAP kinase extracellular signal-regulated kinase 5 estrogen receptor-α estrogen receptor β extracorporeal shock wave extracorporeal shock wave therapy focal adhesion complex

Abbreviations

F-actin FAK FAs FE FEA FEM FGF-2 FGF23 FGFR1 FGFR2 FGF FHTC FN FOXM1 FRAP FSS Fz GAG GANs GCTB GDF15 GDF GMF GPCR GRB2 GSK-3β GSMR GTP GWAS HA HA-PEEK hAT-MSCs HDAC6 HDT HFA HG Hh HIF HIFα HIFβ hjBM-MSC HLU

379

actin filament focal adhesion kinase focal adhesions finite element finite element analysis finite element method gibroblast growth factor 2 fibroblast growth factor 23 fibroblast growth factor receptor 1 fibroblast growth factor receptor 2 fibroblast growth factor femoral head tissue cell fibronectin Forkhead box protein M1 fluorescence recovery after photobleaching fluid shear stress frizzled glycosaminoglycan generative adversarial networks giant cell tumor of bone growth differentiation factor 15 growth differentiation factor geomagnetic field G protein-coupled receptor growth factor receptor-bound protein 2 glycogen synthase kinase-3β generalized summary data-based mendelian randomization guanosine triphosphate genome-wide association study yydroxyapatite hydroxyapatite-polyetheretherketone human adipose tissue multipotential stromal cells histone deacetylase 6 head down tilt high-frequency acceleration high glucose Hedgehog hypoxia inducible factor heterodimeric transcription factor with an oxygen-labile alpha subunit heterodimeric transcription factor with a constitutively stable beta subunit human jawbone marrow mesenchymal stem cell hindlimb unloading

380 Abbreviations

HMGB1 HMGE hMSC HOB HP HSC HU IDH2 IFN-γ IFSS IGF-1 IKK IL IOPC IP3 ISF ITG-β1 JNK KDA KS-GAG KTN LBV LCN LCS LEF LG-HMF LIF LIPUS LIV LMHFV LMV LncRNA lncRNA ODSM LPS LRP5 LRP6 L-VSCC MA MACF1 MAPK MCS M-CSF MEPE microCT

high mobility group box 1 high magneto-gravitational environment human mesenchymal stem cell human alveolar bone-derived osteoblasts hydrostatic pressure hematopoietic stem cells Hounsfield unit isocitrate dehydrogenase 2 interferon-γ intermittent fluid shear stress insulin-like growth factor 1 NF-κB kinase inhibitor interleukin inducible osteoprogenitor cells inositol 1,4,5-triphosphate interstitial fluid integrin subunit beta 1 C-Jun N-terminal kinase Kashin-Beck disease keratan sulfate chondroitin sulfate glycosaminoglycan keratocan local body vibration osteocyte lacuno-canalicular network lacunar-canalicular pore system lymphoid enhance factor large gradient high magnetic field leukemia inhibitory factor low-intensity pulsed ultrasound low-intensity vibration low-magnitude high-frequency vibration low-magnitude vibration long noncoding RNA lncRNA under simulated microgravity lipopolysaccharide lipoprotein receptor-related protein 5 low-density lipoprotein receptor-related protein 6 long-lasting vulvar squamous cell carcinoma micropipette aspiration microtubule actin crosslinking factor 1 mitogen-activated protein kinase mechanical cyclical stretch macrophage colony-stimulating factor matrix extracellular phosphoglycoprotein micro computed tomography

Abbreviations

MIL MiR miRNAs MITF ML MM MMG MMP9 MNGC MRI MSCs MSEA MTC mTOR MURF1 MXRA8 ncRNAs Neat1 NFATc1 NF-κB NF-κB ligand Ni-Ti NO NOS NPY OA OB OC OCN OFF OI OM OMD OP OPG OPN OSF-1 Osx OTM OVX Ocy P2X7 P2Y2R

mean intercept length MicroRNAmicroRNA Micrornas microphthalmiamicrophthalmia- associated transcription factor machine learning multiple myeloma modeled microgravity matrix metallopeptidase 9 multinuclear giant cell magnetic resonance imaging mesenchymal stem cells marker set enrichment analysis magnetic twisting cytometry mammalian target of rapamycin muscle-specific RING finger-1 mechanism remodeling-related protein 8 noncoding RNAs nuclear paraspeckle assembly transcript 1 nuclear factor of activated T cells 1 nuclear factor kappa-B receptor activator of nuclear factor-kappa nickel-titanium nitric oxide nitric oxide synthase neuropeptide Y osteoarthritis osteoblast osteoclast osteocalcin oscillatory fluid flow osteogenesis imperfecta osteomalacia osteomodulin osteoporosis osteoprotegerin osteopontin osteoblast stimulating factor-1 osterix orthodontic tooth movement osteoporosis-ovariectomized osteocytes purinergic receptor purinergic receptor P2Y2

381

382 Abbreviations

Panx1 PCM PDGF PDL PDLSCs PDMS PEEK PEMFs p-ERK PFF PGE2 PGEs PGs PHDs PI3K PICP Piezo1 PKC PKG1 PLC PLCγ PMO PPFC PPARγ PRSS23 P-SAMPNN PTH PTH1R PTHrP R&D RA RANK RANKL Ras RNAKL ROC ROCK1 ROS RPM Runx2 RVD RVE S1P

Pannexin 1 pericellular matrix platelet-derived growth factor periodontal ligament periodontal ligament stem cells polydimethylsiloxane polyetheretherketone pulsed electromagnetic fields phosphorylated extracellular signal-regulated kinase pulsating fluid flow prostaglandin E2 prostaglandin E synthase prostaglandins prolyl hydroxylases phosphatidylinositol 3-kinasekinase procollagen of type I C-terminal propeptide Piezo type mechanosensitive ion channel component 1 protein kinase C CGMP-dependent protein kinase 1 phospholipase C phospholipase Cγ postmenopausal osteoporosis parallel-plate flow chamber peroxisome proliferator activated receptor γ serine protease 23 pretrained self-attention information transfer neural network parathyroid hormone parathyroid hormone receptor 1 parathyroid hormone-related peptide research and development rheumatoid arthritis receptor activator of nuclear factor-kappa B receptor activator of nuclear factor-kappa B ligand rat sarcoma activator of nuclear factor-kappa B ligand receiver operating characteristic Rho-associated coiled-coil kinase 1 reactive oxygen species random positioning machine Runt-related transcription factor 2 regulatory volume decrease representative volume element sphingosine 1-phosphate

Abbreviations

SA-cat SA-β-Gal SCAPs SCF SCI SCID scRNA-seq SEM SEMA SEMA3a SEMA4D SFs SiC SIRT1-AMPK SKR3 SMFs SMG SMI SNPS SOST Sost SREs SS STAT SVM SZ T1D TAZ TBS TCF TGFR-1 TGF-β TGF-β2 TMJ TNF TNF-α TRAP tRNAs TRPM7 TRPV4 tSNE TUG1 T-VSCC

383

stretch-activated cationic aging-related β-galactosidase stress-treated stem cells from apical papilla stem cell factor spinal cord injury severe combined immunodeficiency single-cell RNA-sequencing scanning electron microscopy semaphorin semaphorin 3A semaphorin 4D synovial fibroblasts silicon carbide silent information regulator type 1 and AMP-activated protein kinase serine/threonine protein kinase receptor R3 static magnetic fields simulated microgravity structure model index (SMI) single nucleotide polymorphism sclerostin encoding gene sclerostin skeletal-related events substrate stiffness signal transducers and activators of transcription support vector machine surface zone type 1 diabetes transcriptional coactivator with PDZ-binding motif trabecular bone score T-cell cell factor TGF-β receptor 1 transforming growth factor beta tumor growth factor beta2 temporomandibular joints tumor necrosis factor tumor necrosis factor a tartrate-resistant acid phosphatase transfer RNA transient receptor potential melastatin 7 transient receptor potential vanilloid 4 t-distributed stochastic neighbor embedding taurine upregulated gene 1 transient VSCC

384 Abbreviations

TβRI TβRII VEGF VEGFA VOCCs VSCC WASF2 WBV WGCNA WIPF1 Wnt XFEM YAP YAP1 μs

type I receptors type II receptors vascular endothelial growth factor vascular endothelial growth factor A voltage-operated calcium channels voltage-sensitive calcium channels WAS protein family, member 2 whole-body vibration weighted correlation network analysis WAS/WASL interacting protein family, member 1 wingless-type extended finite element method Yes-associated protein Yes-associated protein 1 μstrain

Index Note: Page numbers followed by f indicate figures and t indicate tables.

A AC. See Articular cartilage (AC) Activating transcription factor (ATF4), 129 Activins, 195 Adenosine triphosphate (ATP), 180–181, 184–185 Adjacent osteocytes intercellular transmission of biochemicalcoupling signals in, 225–226 mechanotransduction between, 223–226 primary biochemical-coupling signals by, 223–225 Adolescent idiopathic scoliosis (AIS), 299–300 bone marrow mesenchymal stem cells (BM-MSCs), 300 causes, 299–300 osteoblasts (OBs), 300–301 osteoclasts (OCs), 301 osteocytes (Oys), 301 AFM. See Atomic force microscopy (AFM) Age, 197 AI. See Artificial intelligence (AI) AIS. See Adolescent idiopathic scoliosis (AIS) Alkaline phosphatase (ALP), 5–6, 34–35, 39–40, 40f, 100, 295–296 ALP. See Alkaline phosphatase (ALP) Amorphous matrix, non-collagenous proteins of, 5–6 Angiogenesis, 8 Anterior cruciate ligament transection (ACLT), 302–304 Antiresorptive drugs, 236–237 Apoptosis, osteocytes (Oys), 299 Appositional growth, 18 Articular cartilage (AC), 18–21, 249–250 degeneration and repair of, 20–21 nutrition of, 19–20 structure and function of, 18–19, 19f Artificial intelligence (AI) bone diseases, application in bone cancer detection framework, system flow diagram of, 357, 359f

bone tumor diseases, 360 fracture, 361–362 osteoarthritis (OA), 360–361 osteoporosis (OP), 359–360 spine-related diseases, 362–363 in medical research, 356–357 Artificial neural network (ANN), 359 Atomic force microscopy (AFM), 182–184, 259–261 Autophagy, 172 Autosomal dominant osteosclerosis (ADO), 331–332 Autosomal recessive osteosclerosis (ARO), 331–332

B Bedrest, 47–48 Bending load, 319–320, 319f Biological fluid systems, 32–33 Biological sequencing technology, 356–357 Biomechanics, 344–345 bone fracture, 316–317 bending load, 319–320, 319f composite load, 321–323, 323f compressive load, 318–319, 318f shear load, 320, 321f tensile load, 317–318, 317f torsional load, 320, 322f bone material and structural mechanics, characteristics of, 315–316 mechanical stimuli (see Mechanical stimuli) osteoarthritis (OA), 327–328, 327f osteogenesis imperfecta (OI), 333, 333f osteomalacia (OM), 330–331 osteoporosis (OP), 328–330 osteosclerosis (OC), 331–332, 332f rickets, 330–331, 332f spinal diseases, 324 cervical spondylosis (CS), 324–325, 324f spine deformity, 325–327 three-dimensional bone models and techniques in, 64–65, 64–66f, 64t

385

386 Index Biomimetics methods, 70–73 bottom-down method, 71–73 homogenization, 71 multiscale modeling, 70–71 top-down method, 71, 72f Blood, 32 vessel of bone, 7–8 BMD. See Bone mineral density (BMD) BM-MSCs. See Bone marrow mesenchymal stem cells (BM-MSCs) Bone cancer detection framework, 357, 359f Bone cell mechanobiology in vitro mechanical methods and models of, 32–43, 33t fluid shear stress (FSS), 32–35, 34–35f hydrogel stiffness, 42–43 hydrostatic compressive force, 36–37 mechanical stretch, 35–36 mechanical unloading microgravity in, 39–42 vibration, 37–39 in vivo mechanical methods and models of, 43–48 bedrest, 47–48 exercise, 44–46 hindlimb immobilization, 46–47 hindlimb unloading (HLU), 46, 47f three-point bending test, 43 vibration, 44 Bone cells, 215–217, 216f adjacent osteocytes, mechanotransduction between, 223–226 intercellular transmission of biochemicalcoupling signals, 225–226 primary biochemical-coupling signals, 223–225, 224f mechanotransduction between osteoblasts and osteoclasts, 226–229 osteoblasts (OBs), 229–233 osteoclasts (OCs), 229–233 osteocytes (Oys), 229–233 and other organs, 234–238, 235f subcellular structural basis for mechanosensing and cell communication in, 217–223 cytoskeleton, 220 focal adhesions (FAs), 221 G-protein-coupled receptors (GPCRs), 221–222 integrins, 218–220 ion channels, 218, 219f lacunar-canalicular network (LCS), 222

osteocytes (Oys), 222 primary cilium, 221 structures for, 222–223 Bone formation, 127, 133–134 Bone-forming cells, 11 Bone fracture, 316–317, 355 artificial intelligence (AI), 361–362 bending load, 319–320, 319f composite load, 321–323, 323f compressive load, 318–319, 318f mechanical stimuli constant amplitude, 336–337 fixation, 334–336, 334f healing, 335–336 reduction, 334 shear load, 320, 321f single-cell sequencing, 368 tensile load, 317–318, 317f torsional load, 320, 322f Bone growth regulators, 5–6 Bone marrow, 6 capillary network, 7–8 Bone marrow-derived preosteoblasts, 10–11 Bone marrow mesenchymal stem cells (BM-MSCs), 9–10, 38, 97–99, 126 characteristics, 98 function, 98–99 mechanical stimulation of, 99–108 mechanical loading effects of, 99–107, 101–103t mechanical unloading effects of, 107–108 mechanobiology osteoporosis (OP), 292, 292–293t, 294f, 295–296 scoliosis, 300 mechanotransduction, mechanism of, 108–114 extracellular matrix-integrin-cytoskeleton system, 108–110, 109f ion channel, 110–111 primary cilia, 111–112 signaling pathways, 112–114, 113f osteoblasts (OBs), 291 Bone matrix, 5–6 Bone mechanobiology, 21–23 Bone mineral density (BMD), 44, 155–156, 369 Bone modeling, and fracture analysis of, 83–85 Bone morphogenetic protein 2 (BMP2), 295–296 signaling pathway, 138 Bone morphogenetic proteins (BMPs), 10–11, 195

Index Bone multicellular unit (BMU), 125 Bone progenitors, 10–11 Bone quality, 61–62 Bone-resorbing cells, 13 Bone salts, 5–6 Bone sialoprotein, 189–190 Bone structure bone mechanobiology, 21–23 cartilage structure and component, 13–21 articular cartilage, 18–21 cartilage stroma, 14–18 cell components, 4–13, 4f blood vessel, lymphatic vessel, and nerve innervation of, 7–9 bone marrow, 6 bone marrow mesenchymal stem cells (BM-MSCs), 9–10 bone matrix, 5–6 osteoblasts (OBs), 11–12 osteoclasts (OCs), 13 osteocytes (Oys), 12 periosteum, 7 preosteoblasts, 10–11 Bone tissue, 4–5, 151 Bone tumor diseases, 360 Bottom-down method, 71–73

C Calcified layer, 19 Calcifying vascular cells (CVCs) effects, 113–114 Cambium layer, 7 Cancer metastasis, 198 Cartilage capsule, 15 Cartilage stroma, 14–18, 16f Cartilage structure, and cellular component, 13–21 articular cartilage, 18–21 cartilage stroma, 14–18, 16f chondrocytes, 15–17 chondrogenesis, growth, and degeneration, 17–18 perichondrium, 17 Cathepsin K (CTSK), 298 Cell-matrix adhesion, 161–162 Cell mechanobiology, 251 Cervical spondylosis (CS), 324–325, 324f CF. See Compressive force (CF) Chloral hydrate (CH), 106 Chondrocyte mechanobiology and osteoarthritis, 302

387

cartilage homeostasis and disorders, 302, 303f mechanical overloading, 302–304 reduced loading, 304 Chondrocytes, 15–17 biomechanical characterization of single chondrocyte, 257–267 measurements of single cell mechanics, 259–262 mechanical behavior, 263–267 single cells mechanics, 257–259 biomechanical microenvironment of, 251–257 pericellular matrix (PCM), 250f, 251–254 recapitulation of, 254–256 tissue engineering, 256–257 geometries, 265, 266f hypo-osmotic loading, 265–267, 267f matrix stiffness, 264, 265f in mechanotransduction, mechanosensitive channels of, 268–277 sense matrix geometry, 275–277, 276f sense substrate stiffness, 273–274, 274–275f TRPV4/PIEZOs channels in, 268–270 activation mechanisms for, 269–270, 269f matrix physical properties, 273–277 mechanical strain, 271–273, 272f osteoarthritic pathogenesis, 272–273 viscoelastic properties of normal and osteoarthritic chondrocytes, 263–264 Chondrodysplasia, 184 Chondrogenesis, growth, and degeneration, 17–18 Chondrogenic osteogenesis, 3–4 Chondrons, 250–251 Chronic kidney disease (CKD), 197–198 Ciliopathies, 182 Cilium, 136 Clinostat design, 40–41 Collagen fibers function, 5–6 Compact bone, 84 Competitive endogenous RNAs (ceRNAs), 129 Composite load, 321–323, 323f Compositional characteristics, 55–56 Compressive force (CF), 99, 131–132 in osteoclast mechanobiology, 157–158, 159f Compressive load, 318–319, 318f Congenital scoliosis, 299–300, 326 Connexin 43 (Cx43), 135

388 Index Connexins (Cx), 5–6, 180–181, 232–233 Cortical bone, 5, 53, 84 mechanical property of, 54–59, 54f, 55t micro and nanoscale property of, 59 strength of, 55–57, 56f structure, 54–55 Young’s modulus/modulus of elasticity, 57–59, 58f Cortical capillary network, 7–8 Cubic lattice, 79, 80t, 80f Cytoskeletal elements, 253–254 Cytoskeletons, 134, 180, 220, 263

Exercise, 44–46 swimming, 45–46 treadmill, 44–45 Extended finite element method (XFEM), 53–54, 84 External fixation, 334–335, 334f Extracellular matrix (ECM), 5–6, 127, 190, 216–221, 252, 254–255 Extracellular matrix-integrin-cytoskeleton system, 108–110, 109f Extracorporeal shock wave therapy (ESWT) principle of, 340–341 treatment parameters and efficacy, 341–342, 341f

D Deep learning methods, 356–357, 361 Dendritic cell-specific transmembrane protein (DC-STAMP), 298 Dentin matrix protein 1 (DMP1), 170–171, 299 Destabilization of medial meniscus (DMM), 302–304 Diabetes, 197 Diaphyseal trophic system, 7–8 Diaphysis, 84 Dickkopf-related protein 1 (Dkk1), 189 Differentiation, 15–17 induction, 15–17 Digital image correlation (DIC), 85 Directional preosteoblasts (DOPCs), 10–11 Distal epiphysis, 84 Disuse osteoporosis, 22, 106 2DU-Net convolutional neural network, 360–361

E Eccentric bending bone fracture, 319–320, 319f ECM. See Extracellular matrix (ECM) Endochondral growth, 18 Endoplasmic reticulum (ER), 10–11, 185 Endosteal niche, 227 Endosteum, 84 Engineering strategies, 256 Epiphyseal line, 84 Epiphyses, 84 Epiphysis-metaphyseal system, 7–8 Estrogen receptor α (ERα), 130 Estrogen signaling pathway, 195–196 ESWT. See Extracorporeal shock wave therapy (ESWT) Euplectella aspergillum (sea sponge), 77–79

F Fatigue bone fracture, 322–323, 323f FEM. See Finite element method (FEM) Femur bone modeling, and meshing, 85–88, 85–89f Fetal biometrics, 357 Fibroblast growth factor receptor 1 (FGFR1), 129 Fibroblast growth factor receptor (FGFR) signaling pathway, 196 Fibroblast growth factors (FGFs) signaling pathway, 196 Fibrous layer, 7 Finite element analysis (FEA), 65–66 Finite element method (FEM), 53–54 for bone analysis, 65–69 boundary condition, 66–69, 67–69f meshing, 66, 67f, 68–69, 69f Flexcell Tension System, 100–104 Flexercell system, 36 Flexible fixation, 335–336 Fluid flow strain (FSS), 128–130 Fluid shear stress (FSS), 31, 104 in bone cell mechanobiology, 32–35, 34–35f in osteoclast mechanobiology, 153–154 Fluorescence recovery after photobleaching (FRAP), 173, 176 Focal adhesions (FAs), 221 pathway, 190 Force from filament (FFF), 269–270 Force from lipid (FFL), 269–270 Forkhead box protein M1 (FOXM1), 158 Four-point bending load, 319–320, 319f Fracture. See Bone fracture FSS. See Fluid shear stress (FSS)

Index

389

G

I

Gap junction, 135–136 Generative adversarial networks (GANs), 357 Genetic Factors for Osteoporosis Consortium (GEFOS-2), 369–370 Genome-wide association study (GWAS), 369 bone diseases susceptibility genes, research of, 369–370 integrating multiomics data, 370–372, 371f Geomagnetic field (GMF), 159–161 Geometric morphological characteristics, 55–56 Giant cell tumor of bone (GCTB), 368–369 Gorham’s syndrome, 8 G protein-coupled receptors (GPCRs), 221–222 Growth differentiation factor 15 (GDF15), 158 Growth differentiation factors (GDFs), 195 GWAS. See Genome-wide association study (GWAS)

Idiopathic scoliosis (IS), 300–301 Integrins, 162, 179–180, 218–220, 253–254 Intelligent medical system, 356–357, 358f Intermediate filaments, 180 Intermediate layer, 19 Intermittent fluid shear stress (IFSS), 104–105 Internal fixation, 334–335, 334f Internal forces, 35 Interstitial fluid (ISF), 32 Interstitial growth, 18 Interterritorial matrix, 250–251 Intracellular calcium ion, 185 Intracellular calcium pathway, 195 Intramembranous osteogenesis, 3–4 Intraosseous nervous system, 9 In vivo stimulation, of osteocyte, 174–178 Ion channels, 110–111, 181–182, 218, 219f

K H Hedgehog (Hh) signaling pathway, 196 Heparan sulfate proteoglycan 2, 184 Hertz equation, 260–261 Hif1α signaling pathway, 196 High-frequency acceleration (HFA), 154 High glucose (HG), 130 Hindlimb immobilization, 46–47 Hindlimb unloading (HLU) system, 46, 47f, 159–161 Hip fractures, 85 Hip vibration training, 337–338, 337f Homogenization, 71 Homologous cell mass, 15 Honeycomb composite, 73–74 Honeycomb-swashplate model, 74, 74–75f, 75t HP. See Hydrostatic pressure (HP) Human adipose tissue multipotent street cells (hAT-MSCs), 130–131 Human jawbone marrow mesenchymal stem cells (hJBM-MSCs), 100 Humerus, spiral bone fracture of, 320, 322f Hydrogel stiffness, in bone cell mechanobiology, 42–43 Hydrogen sulfide (H2S), 113–114 Hydrostatic compressive force, 31 in bone cell mechanobiology, 36–37 Hydrostatic pressure (HP), 36–37, 105, 295–296 Hydroxyapatite-polyetheretherketone (HA-PEEK), 64

Kidney diseases, 197–198 Kyphosis, 326–327

L Lacunar-canalicular network, 222 Lacunar-canalicular system (LCS), in osteocyte mechanobiology, 172–174 Laminar flow, 33 Large-gradient, high-magnetic field (LG-HMF), 39 Loading entire cell, 259 Loading population cells, 259 Local body vibration (LBV), 337–338 Local mechanical probes, 259 Long-lasting voltage-sensitive calcium channels (L-VSCC), 181–182 Long noncoding RNAs (LncRNA), 129 Low-amplitude high-frequency vibration (LMHFV), 154–155 Low-intensity pulsed ultrasound (LIPUS), 339–340 Low-intensity vibration (LIV) method, 38, 155–156 Low-magnitude high-frequency vibration (LMHFV), 106–107, 130, 295–296 Lymphatic vessel, of bone, 8

M Machine learning, 356–357 Macrophage-stimulating factor (M-CSF), 8, 152

390 Index Magnetic therapy treatment parameters and efficacy, 342–343, 342f types of, 342 Massage therapy definition, 343 therapeutic effects, 344 types of, 343–344 Matrix genes, 189–190 Matrix metalloproteinases (MMPs), 302–304 Matrix stiffness, 252–253, 252f, 264 Matrix topography, 253–254, 254f Matrix viscoelasticity, 253 Mechanical cyclical stretch (MCS), 130–131 Mechanical sensitive molecules, 133–137 Mechanical stimuli, 32 of bone fracture constant amplitude, 336–337 fixation, 334–336, 334f healing, 335–336 reduction, 334 extracorporeal shock wave therapy (ESWT) principle of, 340–341 treatment parameters and efficacy, 341–342, 341f magnetic therapy treatment parameters and efficacy, 342–343, 342f types of, 342 massage therapy definition, 343 therapeutic effects, 344 types of, 343–344 ultrasound therapy, 340f frequency, 338–339 physical parameters, 339 treatment parameters and efficacy, 339–340 types of, 339 vibration training biomechanical parameters, 337 treatment parameters and efficacy, 338 types of, 337–338, 337f Mechanical stress, 36 Mechanical stretch, 131 in bone cell mechanobiology, 35–36 in osteoclast mechanobiology, 156–157 Mechanical unloading microgravity in bone cell mechanobiology, 39–42 clinostat design, 40–41

random position machine (RPM), 41–42, 41f superconducting magnet, 39–40, 40f in osteoclast mechanobiology, 159–161, 160f Mechano-desensitization, 222–223 Mechanosensing complexes, 179–184, 179f, 183f Mechanosensitive ion channels, 253–254 Mechanosensors, 223 Mechanotransduction, of bone cells, 217 bone marrow mesenchymal stem cells (BM-MSCs) osteoporosis (OP), 292, 292–293t, 294f, 295–296 scoliosis, 300 chondrocyte mechanotransduction and osteoarthritis, 302 cartilage homeostasis and disorders, 302, 303f mechanical overloading, 302–304 reduced loading, 304 osteoblasts (OBs) osteoporosis (OP), 292, 292–293t, 294f, 296–297 scoliosis, 300–301 between osteoblasts and osteoclasts, 226–229, 228f osteoclasts (OCs) osteoporosis (OP), 292, 292–293t, 294f, 297–298 scoliosis, 301 osteocytes (Oys) osteoporosis (OP), 292, 292–293t, 294f, 298–299 scoliosis, 301 Medullar cavity, 84 Mesenchymal progenitor cells, 126 Mesenchymal stem cells (MSCs), 38, 218, 255 mi-34a, 129 Mice exercise models, 237–238 Microfilaments, 180 Microgravity, 296–297 Micropipette aspiration (MA) technique, 259, 261–262, 262f MicroRNA (miRNA), 129 MicroRNA-138-5p (miR-138-5p), 296–297 Microtubule actin cross-linking factor 1 (MACF1), 134, 134f, 159–161, 227–229, 296–297 Microtubules, 180, 220 Mineralization degree, 57–58 miR-140-5p, 136–137

Index Mitogen-activated protein kinases (MAPKs) signaling pathway, 113, 139 Mixed-type CS, 324–325 Modeled microgravity (MMG), 159 Multi-nuclear giant cells (MNGCs), 13 Multiple myeloma (MM), 360 Multipotent stem cells, 38 Muscle-specific RING finger-1 (MURF1), 159–161 Myeloma bone disease (MBD), 360

N Nacre, 75–77, 77–78f, 78t Nerve innervation, of bone, 8–9 Nerve root type CS, 324f, 325 Neurodegenerative conditions, 198 Neuromuscular scoliosis, 326 Nitric oxide (NO), 185 Noncoding RNAs (ncRNAs), 136 Non-collagen proteins, 5–6 Normal chondrocytes, viscoelastic properties of, 263–264 Notch signaling pathway, 196 Nuclear factor of activated T cells 1 (NFATc1), 129

O OA. See Osteoarthritis (OA) Oblique bone fracture, 318–319, 318f OBs. Osteoblast (OBs) OCs. See Osteoclasts (OCs) OP. See Osteoporosis (OP) Orthodontic tooth movements (OTMs), 155 Oscillatory fluid flow (OFF), 104–105 Osteoarthritic chondrocytes, viscoelastic properties of, 263–264 Osteoarthritis (OA), 249 artificial intelligence (AI), 360–361 biomechanics, 327–328, 327f characteristics, 301–302, 355 chondrocyte mechanobiology, 302 cartilage homeostasis and disorders, 302, 303f mechanical overloading, 302–304 reduced loading, 304 pathological features of, 301–302 single-cell sequencing, 367 Osteoblasts (OBs), 11–12, 31, 126–127, 215, 229–233, 231f, 291, 315 characteristics, 126, 126f function, 127

391

mechanical stimulation of, 127–133, 128t mechanical loading effect, 128–132 mechanical unloading effect, 132–133 mechanobiology and osteoporosis (OP), 292, 292–293t, 294f, 296–297 and scoliosis, 300–301 mechanotransduction, mechanism of, 133–140 mechanical sensitive molecules, 133–137 signaling pathways, 137–140 Osteocalcin (OCN), 5–6, 189–190 Osteochondral junction, 14 Osteoclasts (OCs), 13, 31, 127, 151, 215, 229–233, 231f, 315–316 bone resorption, 291 characteristics, 152 differentiation, 152f mechanical stimuli of, 152–161 compressive force in, 157–158, 159f fluid shear stress (FSS) in, 153–154 mechanical stretch in, 156–157 mechanical unloading microgravity in, 159–161, 160f vibration in, 154–156 mechanobiology and osteoporosis (OP), 291–292, 292–293t, 294f, 297–298 and scoliosis, 301 mechanotransduction, 161–162 Osteocyte-cancer crosstalk, 236–238 Osteocyte dendrite formation, molecular control of, 171 Osteocyte-muscle crosstalk, 234–236 Osteocytes (Oys), 12, 31, 126, 167–172, 215, 222, 229–233, 231f, 291, 315 characteristics, 168–171, 169f function, 171–172 mechanical stimulation of, 172–178 lacunar-canalicular system (LCS) in, 172–174 in vivo stimulation of, 174–178, 177f mechanobiology and osteoporosis (OP), 292, 292–293t, 294f, 298–299 and scoliosis, 301 mechanotransduction, mechanisms of, 178–198 mechanosensing complexes, 179–184, 179f, 183f signaling pathways in, 190–196, 191–193t, 194f

392 Index Osteocytes (Oys) (Continued) temporal responses of, 184–190, 185f, 186–188t in various diseases, 197–198 molecular control of, 171 origin and maturation of, 170–171 Osteocytoma, single-cell sequencing, 368–369 Osteogenesis imperfecta (OI), 333, 333f Osteoid osteocytes, 12 Osteomalacia (OM), 330–331 Osteonectin, 5–6, 189–190 Osteopenia, 301 Osteophytes, 327 Osteopontin, 189–190 Osteoporosis (OP) artificial intelligence (AI), 359–360 biomechanics, 328–330 bone cell mechanotransduction, 292, 292–293t, 294f bone marrow mesenchymal stem cells (BM-MSCs), 295–296 osteoblasts (OBs), 296–297 osteoclasts (OCs), 297–298 osteocytes (Oys), 298–299 characteristics, 292, 355 GWAS and transcriptome data, based on, 372, 372f single-cell sequencing, 368 Osteoprotegerin (OPG), 227–229 Osteosclerosis (OC), biomechanics, 331–332, 332f Osterix (Osx), 12 Ovariectomized (OVX)-induced bone loss, 297 Oys. See Osteocytes (Oys)

P Parallel-plate flow chamber (PPFC), 34 Parasympathetic nerves system, 9 Passive placeholders, 167 Pericellular matrix (PCM), 173, 250–254, 250f Pericellular tethers, 182–184 Perichondrium, 17 Periodontal ligament (PDL), 104–105 Periodontal ligament stem cells (PDLSCs), 298 Periosteum, 7, 84 Periosteum-cortical bone system, 7–8 Perlecan, 184 Peroxisome proliferator activated receptor γ (PPARγ), 295–296 Phosphate homeostasis, 234 Phospholipase C (PLC), 135–136

Piezo 1, 295–296 Piezo channels, 133, 218 activation mechanisms for, 269–270, 269f in chondrocytes, 268–270 matrix physical properties, 273–277 mechanical strain, 271–273, 272f osteoarthritic pathogenesis, 272–273 Plastic deformation, 21 Polymers polyetheretherketone (PEEK), 64 Preosteoblasts, 10–11 Pretrained self-attention information transfer neural network (P-SAMPNN) model, 359 Primary cilia, 111–112, 182, 221, 253–254 Prolyl hydroxylases (PHDs), 196 Proposed timing analysis, 365 Prostaglandin E2 (PGE2), 180–181, 185–189 Protein kinase C (PKC), 135–136 Proximal epiphysis, 84 PTH/PTHrP-PTH1R signaling pathway, 195 Pulsating fluid flow (PFF), 112 Pulsed electromagnetic fields (PEMFs), 342–343, 342f P2Y2 receptor (P2Y2R), 227–229

R Radiative layer, 19 Random positioning machine (RPM), 41–42, 41f, 107, 159–161 Razor back, 326 Receptor activator of nuclear factor kappa-B ligand (RANKL), 152, 172 Red bone marrow, 6 Regulatory volume decrease (RVD), 265–267 Renal osteodystrophy, 197–198 Representative volume element (RVE), development of, 73–83 comparison of biomimetic structures, 81–83, 82–83f Euplectella aspergillum (sea sponge), 77–79 cubic lattice, 79, 80f, 80t stiff walled model, 78, 79f, 79t honeycomb composite, 73–74 honeycomb-swashplate model, 74, 74–75f, 75t spherical honeycomb, 74, 76f, 76t nacre, 75–77, 77–78f, 78t spider silk fiber, 79–81, 81f, 82t Reverse transcription-quantitative polymerase chain reaction (RT qPCR), 112 Rickets, 330–331, 332f

Index Rigid fixation, 335–336 Rotary Cell Culture System, 295 RPM. See Random positioning machine (RPM) Runt-related transcription factor 2 (Runx2), 12, 140, 295–296

S Schwartz-Jampel syndrome (SJS), 184 Sclerostin (Sost), 189, 297, 299, 301 Scoliosis adolescent idiopathic scoliosis (AIS) (see Adolescent idiopathic scoliosis (AIS)) bone cell mechanobiology bone marrow mesenchymal stem cells (BM-MSCs), 300 osteoblasts (OBs), 300–301 osteoclasts (OCs), 301 osteocytes (Oys), 301 characteristics, 299–300 congenital scoliosis, 299–300, 326 idiopathic scoliosis, 326 neuromuscular scoliosis, 326 Sensory nerves, 9 Sex hormones, and medications, 197 Shear bone fracture, 320, 321f Sheep tibial bone fracture model, 336–337 Short oblique serrated bone fracture, 317–318, 317f Signaling pathways, 112–114, 113f, 137–140 in osteocyte mechanotransduction, 190–196, 191–193t, 194f Silicon carbide (SiC), 73 Simulated microgravity (SMG), 137, 295–297, 299 Single cell mechanics, 257–259 measurements of, 259–262, 260f Single-cell RNA sequencing (scRNA-seq), 363 Single-cell sequencing bone cell, application in, 366–367 bone diseases, application in fractures, 368 osteoarthritis (OA), 367 osteocytoma, 368–369 osteoporosis (OP), 368 comprehensive decomposition and clustering, 363–365 developments in, 363, 364f processing process, 363–365, 365f proposed timing analysis, 365 single-cell RNA sequencing (scRNA-seq), 363 subclusters, 365–366

393

Single chondrocyte, biomechanical characterization of, 257–267 Skeletal-related events (SREs), 236–237 Skeletal system, 31 Soft tissue type CS, 325 Spherical honeycomb, 74, 76f, 76t Spider silk fiber, 79–81, 81f, 82t Spinal cord CS, 324f, 325 Spinal cord injury (SCI), 155–156 Spinal diseases artificial intelligence (AI), 362–363 biomechanics, 324 cervical spondylosis (CS), 324–325, 324f spine deformity, 325–327 Spiral bone fracture, of humerus, 320, 322f Static magnetic fields (SMFs), 159–161 Stiff walled model, 78, 79f, 79t Strain, 36 amplification model, 182–184 Stretch stress, 31 Structure model index (SMI), 61–62 Subchondral growth, 18 Substrate stiffness (SS), 101 Superconducting magnet, 39–40, 40f Superficial layer, 19 Support vector machine (SVM), 359 Swimming, 45–46 Sympathetic nervous system, 9 Sympathetic-type CS, 325 Synovial fluid, 19–20

T Taurine upregulated gene 1 (TUG1), 129 Tensile bone fracture, 317–318, 317f Tensile stress, 35 Tensile tests, 57 Tension forces, 99 Terminal differentiation, 15–17 TGF-β signaling pathway, 195 Three-point bending bone fracture, 319–320, 319f Three-point bending test, 43 Tibia, fatigue bone fracture of, 322–323, 323f Tibial plateau shear bone fracture, 320, 321f TNF-a signaling pathway, 196 Top-down method, 71, 72f Torsional load, 320, 322f Trabecular bone, 5, 53 mechanical property of, 60–63 micromechanical property and structure of, 63 strength of, 61–62, 62f structure, 60–61

394 Index Trabecular bone (Continued) Young’s modulus of, 62 Trabecular bone score (TBS), 61–62 Trabecular tissue, micromechanical property and structure of, 63 Transcriptional coactivator with PDZ-binding motif (TAZ) in Hippo pathway, 193–195 signaling pathway, 189 Transient receptor potential (TRP) channels, 218 Transient receptor potential melastatin 3 (TRPM3) channels, 130–131 Transient receptor potential vanilloid 4 (TRPV4) channels, 130–131 activation mechanisms for, 269–270, 269f in chondrocytes, 268–270 matrix physical properties, 273–277 mechanical strain, 271–273, 272f osteoarthritic pathogenesis, 272–273 Transient voltage-sensitive calcium channels (T-VSCC), 181–182 Transmembrane proteins, 108–109 Transverse bone fracture, 317–318, 317f Treadmill, 44–45 Turbulent flow, 33

U Ultrasound therapy, 340f frequency, 338–339 physical parameters, 339 treatment parameters and efficacy, 339–340 types of, 339 Upper limb vibration training, 337–338, 337f

V Variable fixation technology, 336 Vascular endothelial growth factor (VEGF), 8, 172 Vascular endothelial growth factor A (VEGFA), 129

Vascular-osteogenesis coupling formation, 8 Vertebral artery-type CS, 325 Vertebral compression bone fracture, 318–319, 318f Vertical compression bone fracture, 318–319, 318f Vibration, 44, 106 in bone cell mechanobiology, 37–39 effect, of osteoblast, 130 in osteoclast mechanobiology, 154–156 Vibration training biomechanical parameters, 337 treatment parameters and efficacy, 338 types of, 337–338, 337f Vinculin, 161–162 Voltage-sensitive calcium channels (VSCC), 181–182 Volumetric solid bone model, 66f

W WBV. See Whole-body vibration (WBV) Western blotting analyses, 112 Whole-body vibration (WBV), 44, 130, 297, 337–338, 337f training, 337–338, 337f Wnt/β-catenin signaling pathway, 112, 137, 138f, 190–193, 297 Wnt signaling pathway, 189 Wolff’s law, 174–175, 216–217

Y YAP. See Yes-associated protein (YAP) Yellow bone marrow, 6 Yes-associated protein (YAP) in Hippo pathway, 193–195 signaling pathway, 189 transcriptional regulator, 257 Young’s modulus/modulus of elasticity, cortical bone, 57–59, 58f of trabecular bone, 62