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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5603_Библиотеки_им_академика_М_И_Перельмана.pdf
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- •Aim and Scope
- •Preface
- •Acknowledgments
- •Contents
- •Contributors
- •About the Editors
- •1.1 Introduction
- •1.2.1 Friction
- •1.2.1.3 Friction Under Lubricated Conditions
- •1.7.1 Joint Tribology
- •1.7.2 Skin Tribology
- •1.7.3 Oral Tribology
- •1.8 Summary
- •References
- •2.1 Introduction
- •2.3.1 Fluid Pressurization/Fluid-Film Lubrication
- •2.3.2 Boundary Lubrication
- •2.3.3 Hydrodynamic Lubrication
- •2.3.4 Squeeze-Film Lubrication
- •2.3.5 Synovial Fluid
- •2.3.6 Hydration Lubrication
- •2.5.2 Scaffolds
- •2.5.3 Synthetic Polymer
- •2.5.4 Polyacrylamide
- •2.5.5 PEG Hydrogel
- •2.5.6 PVA Hydrogel
- •2.5.7 Double Network Hydrogel
- •2.5.8 Triple Network Hydrogel
- •2.6.1 Polyacrylamide
- •2.6.2 PEG Hydrogel
- •2.6.3 PVA Hydrogel
- •2.6.4 Double Network Hydrogel
- •2.6.5 Triple Network Hydrogel
- •2.7.1 Mechanical Properties
- •2.7.2 Structural Properties
- •2.8 Conclusion
- •References
- •3.1 Introduction
- •3.3.1 Label-Based Biosensors
- •3.3.2 Label-Free Biosensors
- •3.4 Different Nanobiosensing Techniques
- •3.4.1 Optical Sensing
- •3.4.2 Electrochemical/Electrical Sensing
- •3.4.3 Magnetic Sensing
- •3.4.4 Mass-Based Sensing
- •3.6.2 Neurodegenerative Diseases
- •3.6.3 Infectious Diseases
- •3.6.4 Metabolic Diseases
- •References
- •4.1 Introduction
- •4.2.1 Surface Functionalization
- •4.2.2 Bioconjugation
- •4.3 Synthesis Approach
- •4.3.1 Hydrothermal Method
- •4.3.2 Chemical Vapor Deposition (CVD)
- •4.3.3 Wet Chemical Method
- •4.4 Plasmonic Black Bodies (PBBs)
- •4.4.1 Gold NP (AuNPs)-Based PBB
- •4.4.2 Silver NPs (Ag NPs)-Based PBB
- •4.4.3 Platinum NPs (Pt NPs)-Based PBB
- •4.5 Biomimetic NP
- •4.6 Upconverting NP (UCNP)
- •4.6.1 Synthesis
- •4.7 Inorganic NP
- •4.7.1 Synthesis
- •4.8 Photothermal Therapy (PTT)
- •4.9 Conclusion
- •References
- •5.1 Introduction
- •5.2 Human Skin
- •5.10 Future Scope
- •5.11 Conclusion
- •References
- •6.1 Introduction
- •6.1.1 Class 1
- •6.1.2 Class 2
- •6.1.3 Class 3
- •6.4.1.1 Surface Patterning
- •6.4.1.2 Direct-Write Patterning
- •6.4.1.5 Dip-Pen Nanotechnology
- •6.4.1.7 Composing Using Beams
- •6.4.1.8 Direct Write Photolithography (DWP)
- •6.4.1.9 Light-Beam Lithography Electron
- •6.4.1.10 Focused Ion Beam Lithography
- •6.4.2 Fabrication Techniques
- •6.4.2.4 Non-invasive Glucose Monitoring Devices Technique
- •6.4.2.6 Cost-Effective Electrochemical Voltametric Sensors Techniques
- •6.4.2.7 Three-Dimensional (3D) Printing Techniques
- •6.4.2.8 UV-LED Stereolithography Printer Technique
- •6.4.2.9 4D Printing Techniques
- •6.4.2.10 Advanced Biomedical Techniques Involving Biorobots
- •References
- •7.1 Introduction
- •7.6 Mechanical Biocompatibility Challenges
- •7.7 Poor Bio-Printing Resolution
- •7.9 Limited Biomaterial Selection
- •7.11 Conclusion
- •8.2 Animal Tribology
- •8.2.1 Joint
- •8.2.3 Integumentary Change
- •References
- •8.1 Introduction
- •8.3.1 Nanotribology
- •8.4 Green Tribology
- •8.5 Conclusion
- •References
- •9.1 Introduction
- •9.2 Bio-Tribological Issues
- •9.3.2 Bone Fracture Fixation
- •9.3.4 Cardiovascular Devices
- •9.3.5 Minimal Invasive Surgical Devices
- •References
- •10.1 Introduction
- •10.2.2.1 Structural Integrity
- •10.2.2.2 Controlled Release Properties
- •10.2.2.3 Enhanced Drug Loading Capacity
- •10.2.2.4 Tailored Material Properties
- •10.2.3.1 Biocompatibility
- •10.2.3.3 Mechanical Properties
- •10.2.3.4 Drug Compatibility
- •10.2.3.5 Fabrication Compatibility
- •10.3.1 Matrix Material Properties
- •10.3.4 Biocompatibility Assessment
- •10.3.4.1 In Vitro Cell Culture Studies
- •10.3.4.2 Hemocompatibility Studies
- •10.3.4.3 In Vivo Animal Studies
- •10.3.4.4 Histological Analysis
- •10.3.4.5 Immune Response Evaluation
- •10.3.4.6 Biodegradation Assessment
- •10.4 Surface Engineering Considerations
- •10.4.2.1 Surface Coatings
- •10.4.2.2 Plasma Treatment
- •10.4.2.3 Surface Grafting
- •10.4.2.4 Dip Coating
- •10.4.2.5 Spray Coating System
- •10.4.2.6 Electrotreated Coating
- •10.4.2.9 Microfabrication Techniques
- •10.4.2.10 Surface Roughness Control
- •10.5.1.2 Mechanical Properties
- •10.5.1.3 Surface Characteristics
- •10.5.1.4 Release Kinetics Analysis
- •10.5.1.5 Biological Compatibility
- •10.5.1.7 Other Analyses
- •10.6 Advanced Fabrication Techniques
- •10.8 Conclusion
- •References
- •11.1 Introduction
- •11.2 Shape Memory Alloys (SMA)
- •11.3 Shape Memory Polymers
- •11.3.1 Heat
- •11.3.2 Light
- •11.3.3 Magnetic Field
- •11.4 Shape-Changing Hydrogels
- •11.5 Biomedical Applications
- •11.6 Conclusion
- •References
- •12.1 Introduction
- •12.3 Bioresorbable Orthopedic Implants
- •12.4.1 Polylactides
- •12.4.2 Poly (Ortho Esters)
- •12.4.3 Polyphosphoesters
- •12.4.4 Polyphosphazenes
- •12.4.5 Polycaprolactone
- •12.4.6 Polyurethanes
- •12.4.7 Polycarbonates
- •12.5.1 Compression Molding
- •12.5.2 Transfer Molding
- •12.5.3 Injection Molding
- •12.5.4 Extrusion
- •12.5.5 Blow Molding
- •12.5.6 Calendering Process
- •12.5.7 Fiber Spinning
- •12.5.8 Thermoforming
- •12.5.9 Polymer Foaming
- •12.7 Challenges
- •12.8 Conclusion
- •References
- •13.1 Introduction
- •13.3.1.1 Total Hip Replacement (THR)
- •13.3.2 Resurfacing Hip Replacement (RHR)
- •13.5.1 Adhesive Wear
- •13.5.2 Abrasive Wear
- •13.5.3 Fatigue Wear
- •13.5.4 Corrosion/Oxidative Wear
- •13.5.5 Surface Cracking
- •13.6.1 Metallic Implants
- •13.6.1.1 Stainless Steel
- •13.6.1.2 Co-Cr Alloys
- •13.6.1.3 Ti-Alloy
- •13.6.2 Ceramic Implants
- •13.6.3 Polymer Implants
- •13.6.4 Composite Implants
- •13.6.5.2 Surface Coatings
- •13.7.2.1 Hydrodynamic Lubrication
- •13.7.2.2 Boundary Lubrication
- •13.7.2.3 Elastohydrodynamic Lubrication
- •13.7.3 Biomimetic Lubrication Approaches
- •13.7.3.1 Replicating Natural Lubrication Mechanisms
- •13.7.4.1 Implant Wear
- •13.7.4.3 Synovial Fluid Degradation
- •13.8.1 Hydroxyapatite Coatings
- •13.8.1.1 Bone Integration
- •13.8.1.2 Implant Stability
- •13.8.1.4 Biocompatibility
- •13.8.2 Diamond-Like Carbon Coatings
- •13.8.3 Metal Nitride Coatings
- •13.8.4 Polymeric Coatings
- •13.8.5 Nanocomposite Coatings
- •13.9.1 Pin-on-Disk Testing
- •13.9.2 Hip Joint Simulators
- •13.9.3 Knee Joint Simulators
- •13.9.4 Tribo-Corrosion Testing
- •13.9.5 Wear Debris Analysis Techniques
- •13.9.5.1 Scanning Electron Microscopy (SEM)
- •13.9.5.2 Energy-Dispersive X-Ray Spectroscopy (EDS)
- •13.10.1.1 Tailored Geometries
- •13.10.1.2 Improved Wear Characteristics
- •13.10.1.3 Accelerated Innovation
- •13.10.2.1 Real-Time Wear Monitoring
- •13.10.2.2 Functionality Assessment
- •13.10.2.3 Implant Status Monitoring
- •13.10.2.4 Patient-Centric Healthcare
- •13.10.3.1 Advanced Biomaterials
- •13.10.3.4 Multidisciplinary Approaches
- •13.10.4.1 Wear Data Analysis
- •13.10.4.2 Predictive Wear Patterns
- •13.10.4.3 Early Intervention Strategies
- •13.10.4.4 Personalized Treatment Plans
- •13.11 Conclusion
- •References
- •14.1 Introduction
- •14.2.1 Powder Bed Fusion (PBF)
- •14.2.2 Directed Energy Deposition
- •14.3.1 Extrusion-Based AM
- •14.5 Biomanufacturing
- •14.5.1 Tissue Engineering
- •14.5.2 Organ-on-a-Chip Models
- •14.6 Conclusion
- •References
- •Index

13 Wear andFriction Mechanism Study inKnee andHip Rehabilitation
417
optimized friction properties and reduced susceptibility to wear. Such modications
have the potential to signicantly improve the longevity of implants by minimizing
abrasion and friction-induced degradation [157].
13.10.3.4 Multidisciplinary Approaches
Biomaterial innovations for wear resistance in hip and knee replacement prosthetics
are benetting from a multidisciplinary approach. Collaboration between materials
scientists, engineers, and medical professionals is fostering a comprehensive understanding of the complex interactions between biomaterials and the human body.
This collaborative effort ensures that emerging biomaterials are not only wearresistant but also biocompatible, addressing the holistic needs of patients undergoing joint replacement procedures. Hence, ongoing biomaterial innovations present a
transformative outlook for hip and knee replacement prosthetics, promising even
greater wear resistance through the integration of advanced materials, coatings, and
surface modications. As these innovations progress, they hold the potential to
redene the standards for implant durability, contributing to improved patient outcomes and the sustained success of joint replacement procedures [252].
13.10.4 Articial Intelligence inWear Prediction
The integration of articial intelligence (AI), particularly machine learning algorithms, marks a groundbreaking development in hip and knee replacement prosthetics. AI’s capacity to analyze wear data and predict wear patterns holds tremendous
potential for advancing orthopedic care, enabling early intervention, and tailoring
personalized treatment strategies for optimal patient outcomes [253].
13.10.4.1 Wear Data Analysis
Machine learning algorithms excel at processing vast datasets, and in the context of
hip and knee replacements, they can prociently analyze wear data. These algorithms can discern intricate patterns that may elude traditional analytical methods
by assimilating information on joint articulation, implant materials, patient activity
levels, and other relevant factors. This data-driven approach provides a comprehensive understanding of wear dynamics, laying the foundation for precise wear prediction [253].

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A. Choudhari et al.
13.10.4.2 Predictive Wear Patterns
The predictive capabilities of AI extend to forecasting wear patterns over time. By
identifying subtle changes and trends in wear data, machine learning models can
generate predictive models that anticipate the progression of wear in hip and knee
implants. This proactive approach empowers healthcare professionals to foresee
potential issues before they manifest clinically, facilitating early intervention and
preventing complications associated with wear-related deterioration [254].
13.10.4.3 Early Intervention Strategies
The real-time wear predictions provided by AI enable the formulation of early intervention strategies. Healthcare providers can leverage this information to implement
personalized treatment plans tailored to each patient’s unique wear patterns.
Whether through adjustments in rehabilitation protocols, changes in physical activity recommendations, or modications to the implant itself, early interventions
based on AI predictions aim to mitigate wear-related complications and optimize
the long-term performance of the prosthetic joint.
13.10.4.4 Personalized Treatment Plans
Articial intelligence facilitates the creation of personalized treatment plans for
patients undergoing hip and knee replacement procedures. By considering individual wear proles, patient characteristics, and lifestyle factors, machine learning
algorithms can assist healthcare professionals in tailoring interventions that align
with each patient’s specic needs and circumstances. This personalized approach
maximizes the efcacy of treatments, contributing to improved patient satisfaction
and overall outcomes. Therefore, the integration of articial intelligence in wear
prediction represents a transformative leap in hip and knee replacement prosthetics.
Machine learning algorithms offer a data-driven, predictive approach that not only
enhances our understanding of wear dynamics but also empowers healthcare providers to intervene early and deliver personalized treatment strategies. As AI technologies continue to evolve, their role in wear prediction is poised to shape a future
where orthopedic care is not only proactive but also uniquely tailored to the individual needs of each patient [255].
13.10.4.5 Effect ofEnvironment onTesting
The inuence of environmental conditions, manufacturing techniques to produce
the prosthetics using conventional methods such as CNC technology [256], and the
extent of vacuum testing are critical factors in understanding wear and friction
mechanisms in knee and hip rehabilitation. In a comprehensive review, these

13 Wear andFriction Mechanism Study inKnee andHip Rehabilitation
419
elements collectively shape the reliability and accuracy of research outcomes.
Efcient HVAC systems [257, 258], coupled with precise temperature control, are
pivotal in maintaining consistent environmental conditions during wear and friction
studies. Fluctuations in temperature and humidity can introduce variables that
impact material properties and friction behavior. Thus, meticulous control of the
environment ensures reproducibility and reliability of experimental results. Vacuum
conditions are crucial for simulating physiological environments where lubrication
and wear occur in knee and hip joints [259, 260]. By eliminating air and moisture,
vacuum testing enhances the reliability of tribological measurements, providing
insights into the performance of implant materials under realistic conditions.
13.11 Conclusion
The realm of knee and hip rehabilitation, encompassing research on wear and friction mechanisms, is a multifaceted arena that extends beyond the immediate scope
of implant longevity and material selection. By exploring pivotal factors such as
biological responses to wear debris, regulatory standards, and patient-specic considerations, this comprehensive review has illuminated a rich tapestry of considerations essential for optimizing prosthetic performance. The study has underlined the
pivotal role of clinical standards, underscored the clinical signicance of wear and
friction in various hip and knee replacements, and delineated the diverse types of
wear in these joints. The exploration of materials, from traditional metallic and
ceramic implants to the burgeoning realm of composite and surface-modied
implants, has underscored the evolving landscape of wear-resistant materials. The
pivotal role of synovial uid and the potential of biomimetic approaches have been
explored in the realm of lubrication strategies. The discussion on surface coatings
for wear resistance, encompassing hydroxyapatite, diamond-like carbon, and nanocomposite coatings, has elucidated the wealth of options available to mitigate wear.
Further, the review has delved into experimental methodologies like pin-on-disk
testing and tribo-corrosion testing, showcasing the diverse tools researchers wield
to understand wear and friction mechanisms. Notably, exploring future directions,
including additive manufacturing for custom implants and the integration of smart
implants, has offered a glimpse into the potential of emerging technologies to revolutionize prosthetic wear performance.
Overall, this review has delineated the multifaceted realm of wear and friction
mechanisms in knee and hip rehabilitation, underscoring the critical importance of
interdisciplinary research in optimizing prosthetic performance. Future research
should bridge the gaps identied in this review, focusing on unexplored facets like
patient-specic considerations and the long-term performance of emerging materials and technologies. By fostering collaborations between clinicians, material scientists, and engineers, the eld can advance toward the ultimate goal of enhancing the
longevity and functionality of prosthetic implants, thereby signicantly improving
the quality of life for millions worldwide.

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A. Choudhari et al.
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