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Introduction
Musculoskeletal (MSK) diseases encompass a wide range of pathological conditions that affect our bones, muscles, and joints. [ 1 ] Epidemiologic studies show an increasing global prevalence of MSK disorders, with an estimated 1.71 billion people affected by 2019, representing a significant burden on the global disability landscape. [ 2 ] The etiology of these disorders is diverse, including infectious or inflammatory processes, degenerative changes, trauma and injuries, developmental abnormalities, tumor, and vascular and metabolic conditions. [ 3 ] Noteworthy MSK disorders affect joints (e.g., osteoarthritis (OA) and rheumatoid arthritis (RA)), bone (such as osteoporosis and fragility/traumatic fracture), and muscles (e.g., sarcopenia), giving rise to acute/chronic pain (e.g., fibromyalgia) and inflammatory conditions. [ 4 ] Additionally, the burden of MSK cancers within the realm of MSK disorders should not be overlooked. MSK cancers comprise malignant tumors that arise in the bone or soft tissues, including bone cancers (e.g., osteosarcoma), soft tissue sarcoma, and metastatic cancers originating from other sites in the body and spreading to the bone. [ 5 ] Therefore, MSK disorders pose a formidable threat to human life and well‐being, warranting comprehensive attention and investigation.
Conventional treatments for MSK disorders include nonpharmacological approaches, pharmacological interventions, and surgical procedures. In the case of OA, nonpharmacological management emphasizes regular exercise, rehabilitation, and manipulation to enhance muscle strength, maintain optimal mobility, and preserve joint function. [ 6 ] In advanced stages, surgical resection and subsequent prosthesis implantation are often necessary for joint replacement. Pharmacologic intervention entails a combination of anti‐inflammatory and analgesic drugs, including naproxen, ibuprofen, cyclooxygenase‐2 (COX‐2) selective inhibitors, paracetamol, and weak opioids like tramadol, aiming to alleviate inflammation and pain. [ 7 ] The mode of drug administration can significantly influence its effectiveness. For example, intra‐articular delivery is often complicated by rapid drug clearance from synovial fluid due to continuous exchange with surrounding lymphatic fluid and blood, resulting in reduced drug retention and efficacy. [ 6 ] On the other hand, systemic administration presents challenges due to unfavorable biological distribution patterns, which can increase the risk of gastrointestinal, renal, and cardiovascular complications in patients undergoing long‐term therapy. [ 6 ] Treatment for bone tumors primarily involves surgical resection, sometimes complemented by adjuvant radiotherapy and/or chemotherapy. [ 8 ] While these approaches can mitigate bone metastases and reduce symptoms, achieving a complete cure is infrequent. Furthermore, chemotherapy and radiotherapy in bone tumor patients often entail significant side effects, posing considerable clinical challenges.
In order to advance the treatment of MSK disorders, there is an urgent need for innovative technologies. Among these, nanotechnology has emerged as a promising approach. [ 9 , 10 , 11 , 12 , 13 , 14 ] Initially defined as the study and manipulation of individual atoms and molecules ranging from 1 to 100 nm in size, nanotechnology has evolved to encompass a broader scope of research and applications. [ 15 ] In the context of MSK disorder treatment, nanotechnology involves the utilization of nanoparticles (NPs), nanostructured bioscaffolds, nanosized drug/gene delivery systems, and nanomaterial‐assisted stem cell differentiation. [ 16 ] The unique properties and capabilities of nanomaterials enable targeted and efficacious interventions in MSK disorders, creating new possibilities for diagnosis, drug delivery, tissue regeneration, and biomedical imaging. [ 17 ] NPs can be engineered to transport therapeutic agents, such as anti‐inflammatory drugs, growth factors, and gene therapies, directly to affected MSK tissues. [ 18 , 19 ] These NPs can also enhance drug stability, increase bioavailability, and improve efficacy while minimizing systemic side effects. By selectively delivering drugs to sites of injury or inflammation, nanotechnology‐based drug delivery systems offer a promising approach to precision medicine. Additionally, scaffold materials with nanoscale features can mimic the native extracellular matrix (ECM), and establish a conducive environment for cell adhesion, proliferation, and differentiation. [ 20 ] Nanofibrous scaffolds, nanocomposites, and nanogels have shown promise in promoting tissue regeneration and healing in bone, cartilage, and muscle injuries. [ 20 , 21 , 22 ] In the field of diagnostic imaging, nanotechnology provides innovative solutions for the early detection and monitoring of MSK disorders. For instance, NPs can be functionalized with imaging agents such as fluorescent dyes or produced from magnetic materials, enabling noninvasive imaging of MSK tissues. [ 23 , 24 ] These nanoprobes facilitate high‐resolution imaging, improved contrast, and real‐time monitoring of disease progression and treatment responses.
While nanotechnology‐based therapies for MSK disorders hold immense potential, progress in clinical translation has been hindered by the complexity of nanomaterial behavior in intricate in vivo environments. [ 25 , 26 , 27 ] Organ‐on‐a‐chip (OoC) technology has emerged as a promising solution to address these challenges. By faithfully emulating the in vivo microenvironment, OoCs provides a robust microphysiological platform for evaluating potential therapies and enhancing our ability to comprehend, diagnose, and treat MSK disorders. [ 28 ] OoC platforms typically employ microfluidic devices to replicate the key structural and functional attributes of human organs or tissues, enabling more accurate recapitulation of in vivo physiological conditions compared to conventional cell culture systems. [ 28 ] In additional, OoC technology can enable the creation of microscale models mimicking MSK tissues, including bone, cartilage, and muscle. [ 28 , 29 ] With these platforms, researchers can design highly intricate and physiologically relevant microenvironments. Unlike static culture models, OoC platforms often employ dynamic culture protocols to facilitate continuous nutrient exchange, improve oxygen diffusion, and offer physiological mechanobiological stimuli, thereby more closely mimicking conditions in living organisms and expediting therapeutic evaluations ( Figure 1 A ). [ 30 ] Thus, OoCs offer promising prospects for accelerating the translation of nanotechnology‐based therapies into effective clinical treatments for MSK diseases.
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Although OoCs hold great potential in studying MSK disorders, there are still some limitations and challenges. First, MSK tissues often consist of multiple cell and ECM types and are characterized by their biochemical and biomechanical complexity. Current OoC models mostly focus on specific aspects of MSK function, such as muscle contraction, rather than fully recapitulating the complexity of MSK tissue and organs. Furthermore, it remains challenging to engineer mature MSK tissues and maintain them over long periods in OoCs, thus limiting our ability to accurately mimic MSK physiology and pathology using OoCs. [ 31 ] Additionally, there exist technical challenges in integrating multiple MSK tissue/organ types in OoCs as well as inducing proper on‐chip vascularization and innervation. [ 32 ]
Nanotechnology can contribute to the development of MSK OoC platforms and address the above challenges faced by OoCs. Nanomaterials can be utilized to create bioengineered scaffolds that mimic the native tissue ECM, providing a suitable microenvironment for cell growth and differentiation. [ 33 , 34 ] Nanofabrication techniques allow precise control over the structure, mechanical properties, and surface morphology of tissue scaffolds and microfluidic chips, which are critical for cell behavior and tissue development. [ 35 ] In addition, NPs can encapsulate drugs and be engineered to target specific release sites within the OoC to effectively mimic the localized drug delivery and controlled release for MSK disease treatment. [ 36 ] Advances in nanotechnology has also fueled the development of nano‐biosensors and nanoprobes that can be integrated into OoC systems to monitor a variety of parameters, including pH, oxygen levels, and mechanical forces, and provide real‐time feedback on tissue function and responses to interventions. [ 37 , 38 ] Nanoprobes can be used to detect specific MSK disease biomarkers, thereby facilitating early diagnosis and intervention. [ 37 ]
Nanotechnology presents a promising avenue in the context of managing MSK diseases, as depicted in Figure 2 A . Despite its potential, the current utilization of nanotechnology within MSK The study of nanotechnology in OoC platforms remains notably limited. In 2023, it accounted for less than 7% of the “MSK OoCs” literature (Figure 2B ). Notably, after reviewing the articles on nanotechnology applications in OoCs, we found that most of these articles focused on non‐MSK OoCs, [ 39 , 40 , 41 ] such as heart‐on‐the‐chip, [ 42 ] tumor‐on‐the‐chip (ToC), [ 43 ] and lung‐on‐the‐chip, [ 44 ] suggesting that there is huge potential in integrating nanotechnology and MSK OoCs for the advancement of therapies for MSK disorder treatment, specifically enhancing the functionality and performance of OoC platforms, and increasing the physiological relevance of OoC‐based disease models. This synergistic combination can ultimately lead to more efficacious treatment options and improved patient outcomes.
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Although recent comprehensive reviews have delved into various aspects of OoCs, focusing on microfluidic hydrogel scaffolds, applications in cartilage tissue engineering, cellular responses and reprogramming triggered by nanobiomaterials, [ 45 , 46 , 47 , 48 ] our review stands apart from these existing publications because its specific focus on the interactions between nanotechnology and MSK biology within the context of OoCs. This knowledge gap represents an important area for further exploration as it holds great potential in enhancing our understanding of MSK disease mechanisms and facilitating the development of efficacious treatments.
Disorders of the MSK System and Limitations of Current Models
The optimal functioning of the locomotor system relies on the well‐being of MSK tissues. Impairments to muscles, bones, joints, and adjacent connective tissues lead to transient or lasting functional constraints and limitations. Importantly, MSK diseases often stem from a complex interplay among various factors, including interactions among different tissues or diverse cellular constituents within the same tissue. Therefore, constructing intricate, physiologically relevant models is essential to emulate these relevant attributes in vitro.
MSK Tissue Composition and Function
The complexity of the MSK system is evidenced by the diverse compositions of its constituent tissues, including bone, muscle, cartilage, tendons, ligaments, and other connective tissues that provide structural support and cohesion to tissues and organs ( Figure 3 ).
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Bone
Bone is a calcified tissue within the human body. It consists of ≈60% inorganic material, e.g., hydroxyapatite (HAP), 10% water, and 30% organic compounds (bone ECM protein). [ 49 ] This distinctive chemical and biochemical makeup bestows bone with exceptional mechanical and biological properties necessary for vital functions. These functions include providing structural support for movement and stature, protecting critical organs such as the brain and bone marrow, and maintaining mineral homeostasis. [ 49 ] In addition, bone is a dynamic tissue which undergoes continuous remodeling. [ 50 ] This physiological process involves the degradation of old bone by osteoclasts (cells responsible for bone resorption) and subsequent replacement with new bone formed by osteoblasts (cells responsible for bone formation). [ 50 ] The remodeling process plays a pivotal role in sustaining healthy bone, which is essential for the optimal performance of crucial skeletal functions throughout an individual's lifespan.
Cartilage
Cartilage, a pliable and resilient connective tissue, safeguards joints and bones while effectively cushioning impacts within the body. Among the three prevalent cartilage types, hyaline cartilage is the most common and often referred to as articular cartilage due to its coverage of bone extremities. [ 51 ] Unlike its connective tissue counterparts, articular cartilage has no lymphatic vessels, nerves, or vascular networks. Cartilage thickness ranges between 2 and 4 mm depending on its anatomical location. [ 51 ] Articular cartilage has a dense ECM, in which chondrocytes are present at a low density. This ECM is predominantly comprised of collagen, hyaluronic acid (HA), proteoglycans, elastins, and other proteins. [ 52 ] The articular cartilage has four distinct regions (Figure 3 ), characterized by unique cellular morphology, ECM compositions, functions, and collagenous densities. [ 52 ]
Synovial Membrane
The synovium is a structurally intricate soft tissue lining that thickens in arthritic joints. It comprises an endothelial layer consisting of macrophages and fibroblasts, and a submembranous stratum housing blood and lymphatic vessels embedded within a collagen‐rich ECM. [ 53 ] The functions of the synovium are manifold, including preserving a nonadherent tissue surface, providing lubrication to cartilage, regulating synovial fluid volume, and influencing the composition and nourishment of chondrocytes within the joint. In its normal state, synovial tissue exhibits one to three layers of specialized columnar fibroblast‐like synoviocytes (FLSs), interspersed with macrophages. [ 54 ] This entire architecture is enveloped by a fibrous capsule, a structural component that, along with ligaments, muscles, and tendons, imparts durability and stability to the joint. Maintaining synovial joint homeostasis involves various contributing factors, such as the expression of lubricin and matrix metalloproteinases (MMPs) by FLSs and the functional role of resident macrophages and FLSs as immune sentinels. [ 55 , 56 ] The orchestration of leukocyte entry and exit for immunosurveillance, coupled with the localized regulation of cytokines and growth factors, further contributes to this intricate equilibrium. In conditions of inflammatory arthritis, such as RA, the endothelial layer often exhibits substantial thickening, primarily attributed to increased CD68 + macrophage presence. [ 56 ] Furthermore, the subendothelial region showcases significant infiltration, encompassing T and B lymphocytes, plasma cells, macrophages, stromal edema, and vascular proliferation ( Table 1 ). [ 56 ]
Table 1
Major MSK tissues: core matrix components, cell populations, vascularization, innervation, primary function, and biomechanical stimulation. [ 57 , 58 , 59 , 60 , 61 , 62 ]
Abbreviation: MSK = musculoskeletal; HAP = hydroxyapatite; FLS = fibroblast‐like synoviocytes.
| Tissue | Core matrix composition | Core cell population | Vascularization | Innervation | Main functions | Biomechanical clues |
| Bone | HAP and collagen fibers | Osteocytes, osteoblasts, osteoclasts, microvascular and neural cells | Well‐ developed | Well‐established | Supports the body, protects internal tissues and organs, stores calcium and fat, produces hematopoietic cells | Compression, tension, shear, hydrostatic pressure |
| Cartilage | Collagen fibers and proteoglycans | Chondrocytes | No | No | Transmits loads with a low coefficient of friction and provides a smooth, lubricated surface between bones | Compression, shear, hydrostatic pressure |
| Meniscus | Collagen fibers and proteoglycans | Fibro‐chondrocytes | Well‐vascularized (red zone) | Well‐innervated (red zone) | Acts as an energy absorber, helps distribute forces within the joint, provides stability | Torsion and shear |
| Synovial membrane | Collagen fibers, laminin, fibronectin, and proteoglycans | FLS, macrophages, lymphocytes, neural and endothelial cells | Well‐vascularized | Adequately innervated | Regulates the composition of synovial fluid and maintains the functional and mechanical stability of joints | Multidirectional stretching |
| Skeletal muscle | Collagen fibers, glycoproteins, and proteoglycans | Endothelial cells, muscle and resident mononuclear cells | Highly vascularized | Well‐innervated | Promotes movement, facilitates respiratory mechanics, participates in calorie production and metabolism, helps maintain balance, protects essential organs | Tension, compression, and shear |
| Tendons and ligaments | Collagen fibers and elastin | Fibroblasts, tenocytes, and endothelial cells | Moderately vascularized | Limited | Produces force and movement, allowing the transfer of force from muscle to bone | Unidirectional stretching |
Skeletal Muscle
Human skeletal muscle consists of diverse muscle fiber types that attach to the skeleton via tendons, collectively enabling bodily movements. [ 63 ] These muscle fibers exhibit a distinctive striated appearance characterized by regular, thin red and white lines. [ 64 ] Skeletal muscles are primarily responsible for maintaining the upright posture and generating movement. Besides, it also plays a crucial role in various physiological processes, such as heat production and the secretion of metabolic peptides for intertissue communication. [ 65 , 66 ] Encased within the ECM comprising collagen, glycoproteins, proteoglycans, and elastin, muscle fibers contribute to the overall structure of skeletal muscle. Muscle ECM consists of three layers: the endomysium surrounding individual muscle fibers, the perimysium, and the epimysium encompassing the entire muscle. [ 67 ] Collagen types I and III fibers are the most abundant components of the ECM, constituting ≈75% of the total muscle collagen content. Collage type I fibers, present in the viscera, periphery, and epithelium, form robust parallel structures that confer tensile strength and rigidity to the muscle. On the other hand, collagen type III creates a loose fibrous network, contributing to the elasticity of the viscera and periphery.
Tendons and Ligaments
Tendons and ligaments are dense fibrous connective tissues that establish connections between muscle/bone and bone, facilitating the transmission of mechanical forces essential for bone stabilization and enabling body movements. [ 68 ] These tissues contain triple helical, crosslinked collagen type I fibrils that are assembled into fibers that are held together by the endotenon, bundles of sheaths, forming the fascicular units within tendons or ligaments, and encapsulating the nerves and blood vessels supporting the fascicles. [ 69 ] Multiple bundles of fascicles are then grouped, constituting a larger tissue‐level unit encased by an outer tendon sheath. These units, enveloped by the outer tendon, aggregate to establish a comprehensive organ structure, enclosed by a tertiary sheath—either a synovial or a paratendinous sheath. The synovial sheath facilitates tendon and ligament movement, particularly where they encircle bony or fibrous protrusions, conferring the capacity to withstand substantial stress. [ 69 ]
While collagen dominates the ECM of tendons and ligaments, there are also other important ECM components. The noncollagenous ECM comprises primarily proteoglycans and glycoproteins, which have protein and sugar cores, respectively. [ 70 ] Small proteoglycans like fibromodulin regulate collagen assembly, whereas larger, hydrophilic counterparts such as aggrecan, counteract compressive forces. [ 70 ] Glycoproteins fulfill diverse roles, such as lubrication, elasticity, and binding latent transforming growth factor‐β (TGF‐β) with tenascin C. [ 70 ] Multiple cell types populate healthy tendons and ligaments. Fibroblast‐like stromal cells constitute 90–95% of tendon cells and are often termed tenocytes. [ 71 ] In ligaments, these are referred to as ligament cells. These cells are responsible for ECM synthesis and turnover, contributing to tissue formation and breakdown. Resident immune cells, such as macrophages, might inhabit the inner tendon sheath, although confirmation of their presence in healthy tissues is challenging due to limited research into nondiseased tissues. [ 72 ] Notably, both inner and outer tendon regions are vascularized and innervated, which is crucial in maintaining tendon equilibrium and regulating their responses to injuries.
Multifactorial MSK Diseases
Muscle, bone, and joint diseases are defined based on the primary anatomical site of affliction and prevalence. It is crucial to acknowledge that MSK disorders often result from multiple factors encompassing interactions among various tissue/cell types.
Bone Diseases
Bone diseases include a range of prevalent conditions including osteoporosis, osteopenia, Paget's disease of bone (PDB), fractures, osteomyelitis, and bone tumors. Fragility fractures are of particular concern because they occur as a result of a weakened bone structure and are often associated with conditions such as osteoporosis, the most prevalent chronic metabolic bone disease characterized by decreased bone mass and degradation of bone tissue microarchitecture. [ 73 ] Osteoporotic disease state hampers an individual's ability to achieve optimal peak adult bone mass and increases the likelihood of fractures. [ 74 ] The primary forms of this disease are age‐related and postmenopausal osteoporosis, with women being at higher risk related to their lower peak bone mineral density compared to men. [ 74 ]
PDB is a common metabolic bone disease. PDB is characterized by increased osteoclast activities, leading to accelerated bone resorption and increased compensatory bone formation. Specifically, osteoclasts in PDB increase in size, while osteoblasts appear disorganized. [ 75 ] As a result, the affected bones show a combination of sclerotic and lysogenic regions, resulting in structural damage. PDB is considered a polymorphic disorder with a complex genetic basis influenced by hereditary factors. [ 75 ] Among the genetic risk factors, mutations in Sequestosome‐1 have been associated with both sporadic and familial PDB. [ 76 ] In addition, epigenetic modifications affecting bone remodeling and regulatory genes such as osteoprotegerin have been implicated in the onset and progression of PDB. [ 76 ] Intravenous infusion of aminobisphosphonates, particularly zoledronic acid, is currently a viable therapeutic option for most patients with Paget's disease, effectively inhibiting bone turnover and achieving long‐term remission. [ 77 ]
Osteomyelitis is an inflammatory condition characterized by bone tissue swelling, usually due to a bloodstream infection caused by bacteria, primarily Staphylococcus aureus . [ 78 ] This disease is difficult to cure as bacterial infections are difficult to eradicate within bones. S. aureus , the main pathogen causing osteomyelitis, can invade osteoblasts and persist in them for a long period of time. [ 79 ] This persistence often triggers osteoblast apoptosis, which impairs the normal function of osteoblasts, while inducing osteoclastogenesis through the secretion of probone resorption cytokines. [ 80 ] The activation of osteoclasts makes the patient more susceptible to pathological fractures.
Cancer‐related bone diseases encompass primary (e.g., sarcomas) and secondary bone tumors (metastases). [ 5 ] Among primary bone tumors, osteosarcoma, chondrosarcoma, and Ewing sarcoma are common malignant tumors, with osteosarcoma being the most prevalent. [ 81 ] Bone metastases refer to the migration of cancer cells from various primary tumors (e.g., breast, prostate, and kidney cancers) to bone due to attraction by a microenvironment conducive to metastatic cell adhesion and growth‐promoting molecules. [ 82 ] Both skeletal sarcomas and metastases can thrive in the same tissue microenvironment, and evidence suggests that cancer cells can lie dormant within the metastatic niche for extended periods before initiating proliferation and growth. [ 5 ] Consequently, the interplay between tumor cells and the bone microenvironment creates a self‐perpetuating cycle. Additionally, myeloma and hematologic malignancies are sometimes considered bone tumors due to their interaction with the bone marrow microenvironment and their impact on bone tissue functions. [ 83 ] Medications that modify bone quality, such as bisphosphonates and denosumab, have proven effective in decreasing and delaying the onset of cancer‐related skeletal complications.
In addition to tumor‐associated bone diseases, bone trauma is an important category of bone conditions, causing disturbances to the structure, function, and overall integrity of the skeletal system. Traumatic events, including fractures, dislocations, and forceful impacts, trigger alterations in the skeletal microenvironment and homeostasis. [ 84 ] Notably, the ability to heal without scarring after injury or fracture sets bone apart from most human tissues. [ 85 ] This regenerative potential is orchestrated by a fine‐tuned interplay of anabolic and catabolic processes that include inflammation, angiogenesis, matrix deposition, and tissue remodeling. [ 86 ] Understanding the underlying mechanisms for bone healing in the context of trauma is of paramount importance in the search for effective therapeutic interventions. It is important to recognize that severe trauma is characterized by fractures accompanied by extensive soft tissue damage and an increased risk of complications and long‐term sequelae.
It is noteworthy that different bone diseases are often interconnected. For example, cancer‐induced bone diseases may arise from the tumor itself or as a consequence of its treatment, resulting in bone fragility and elevated incidence of osteoporosis, osteopenia, and fractures. [ 87 ]
Joint Diseases
Joint disorders such as OA and RA are highly prevalent. [ 88 ] Although often considered one type of disease, OA encompasses a group of joint conditions characterized by articular cartilage defects and alterations in underlying bone integrity. [ 89 ] It can manifest as erosive or nonerosive, with the former exhibiting radiographic evidence of subchondral bone erosion. [ 89 ] Disruptions in ECM homeostasis caused by chondrocyte dysfunction contribute to articular cartilage lesions and subchondral bone changes in OA. [ 90 ] The precise etiology of cartilage degradation remains elusive; however, it is speculated that chemical and mechanical factors both play significant roles. Biomechanical factors, including joint trauma, strenuous physical activity, joint instability, and obesity (increased body weight), can increase the susceptibility to OA. [ 91 ]
RA is a systemic inflammatory autoimmune disease. The primary site of inflammation in RA is the synovial tissue, which undergoes hyperplasia and develops synovial outgrowths or villi composed of lymphocytes, macrophages, synovial lining cells, and blood vessels. [ 92 ] In RA, the synovial fluid volume increases, but its viscosity decreases, leading to inadequate joint lubrication and subsequent cartilage damage. Various cell types within the synovium, including monocytes/macrophages, osteoclasts, T cells, B cells, dendritic cells, endothelial cells, and FLSs, are activated or transformed, potentially contributing to the onset and progression of RA. [ 93 ] These cells secrete proinflammatory cytokines and tissue‐degrading proteases, perpetuating the inflammatory cascade. [ 93 ] It is crucial to note that despite sharing clinical manifestations and overlapping cellular and molecular aspects, RA and OA have distinct pathogenic mechanisms. Extensive research has been conducted to identify key genes and pathways associated with RA and OA, aiming to unravel the molecular underpinnings of these diseases.
Aging is an important risk factor for OA because aging cartilage has reduced water content, decreased chondrocyte numbers, and increased cellular senescence mediated by senescence‐associated secretory phenotype (SASP)‐associated factors. [ 91 , 94 ] Aging of the immune system is also an important factor in the development of RA. [ 95 ] In addition to OA and RA, gout is another prevalent, painful arthritis. Gout begins with crystal deposition due to high uric acid levels, which triggers an acute inflammatory attack. [ 96 ] Gout is also closely associated with aging, as the kidneys become less efficient in excreting uric acid as we age, leading to a buildup of uric acid in the body and an increased likelihood of developing gout. [ 96 ] Overall, joint diseases are closely associated with aging, and understanding aging‐associated changes at the cellular level can help researchers gain a deeper understanding of the mechanisms for joint diseases and identify potential therapeutic targets.
Muscle Diseases
Sarcopenia, commonly occurring as a consequence of aging, manifests as a progressive decline in skeletal muscle mass, connective tissue fibrosis, and alterations in microcirculation. [ 97 , 98 , 99 , 100 ] Initially confined to age‐linked muscle atrophy, the definition of sarcopenia has expanded to encompass muscle loss attributed to chronic ailments, sedentary behavior, compromised mobility, and inadequate nutrition. As the biomechanical contractile entity orchestrating movement, muscles are pivotal for metabolic equilibrium, encompassing glucose uptake, amino acid release, and energy generation. [ 101 ] Moreover, muscles indirectly modulate immune responses by furnishing amino acids accessible to immune cells. [ 101 ] The reduction in muscle mass during aging predominantly affects fast‐twitch type II fibers due to diminished muscle protein synthesis in both contractile components and mitochondria, coupled with impaired control over protein hydrolysis. Neurological factors also contribute to muscle degradation, including motor cortical atrophy, neurotransmitter alterations, a decrease in fast‐rhythmic muscle fibers and a shift to slow‐rhythmic muscle fibers, as well as the loss and reorganization of motor neurons. [ 102 ] Sarcopenia is further characterized by deficiencies in muscle mitochondria and mitochondrial enzymes, mutations in mitochondrial DNA, and subsequent damage to fatty acid β oxidation and the mitochondrial respiratory chain responsible for ATP production. [ 103 ] The age‐related malfunctioning of mitochondria, coupled with compromised cellular antioxidant mechanisms, triggers the accumulation of reactive oxygen species (ROS), culminating in detrimental effects on muscle fibers, motor neurons, and the sarcoplasmic reticulum, thereby impeding muscle regeneration. [ 103 ]
Furthermore, an array of neuromuscular diseases, such as motor neuron diseases (e.g., amyotrophic lateral sclerosis), inflammatory myopathies (e.g., inclusion body myositis), and hereditary muscle diseases (e.g., myotonic dystrophy type 2), can manifest symptoms akin to sarcopenia in later stages. [ 104 ] These multifactorial muscle diseases disrupt the intricate interactions between muscle tissue and its interactions with nerves, blood vessels, and other connective tissues. [ 97 ] For instance, conditions like amyotrophic lateral sclerosis and myasthenia gravis affect the neuromuscular junction, a critical component characterized by chemical synapses facilitating communication between muscles and nerves. [ 105 ] Neuromuscular dysfunctions represent a major factor contributing to the pathogenesis of sarcopenia, and age‐related deterioration in the function and structure of the neuromuscular junction causes diminished muscle strength and reduced muscle mass in individuals afflicted by sarcopenia. [ 105 , 106 ]
Limitations of Current In Vitro and In Vivo Models
Considerable research efforts have been directed toward comprehending MSK disorders; however, the available drugs for treating these diseases remain limited, often offering only symptomatic relief. For example, no disease‐modifying OA drugs are available, which can be attributed to the heterogeneous pathological mechanisms, disease presentations, individual susceptibility, and drug response profiles. [ 107 ] Despite the uncertainties in the underlying mechanisms governing OA onset and progression, it is well recognized that different therapeutic strategies are required for different endotypes. [ 108 ] Notably, commonly used animal models and conventional in vitro cellular systems fall short in adequately recapitulating the diverse pathogenesis and manifestations of human MSK disorders.
While 2D and 3D cell cultures are widely employed to model MSK conditions and exhibit cost‐effectiveness, simplicity, and reproducibility, they have insufficient physiological relevance, particularly in replicating physical loading and inter‐tissue communication. These models often lack the vital in vivo attributes that significantly influence cellular phenotypes and reactions to therapeutic agents. [ 109 ] For instance, primary chondrocytes in 2D cultures often undergo dedifferentiation characterized by loss of function and altered responsiveness to external stimuli. Animal models have significantly contributed to our understanding of MSK disorders and unveiled insights into human disease pathophysiology. [ 110 ] Nonetheless, commonly used animal models (e.g., mice and rats) markedly diverge from humans in MSK anatomy, mechanical loading, dimension, and physiology as well as genetic background, potentially causing distinct drug responses and limiting the translational utility of such models in predicting clinical outcomes.
Human OoC systems, as an engineered, physiologically relevant in vitro model, possess unique advantages over traditional in vitro models and animal models and promise to revolutionize drug discovery and development. [ 32 ] As OoCs are predominantly human cell‐based, they can faithfully mimic the physiology and pathology of specific organs in the human body, offering a versatile platform to predict drug safety, efficacy, pharmacokinetics, and pharmacodynamics. By exploiting human OoC models, researchers can gain invaluable insights into clinically relevant drug responses at the cellular, tissue, and organ levels, which greatly reduces our reliance on animal models and potentially obviates the need for certain in vivo studies.
Furthermore, OoC platforms, which are typically made of optically transparent materials such as polydimethylsiloxane (PDMS), allow for real‐time, continuous monitoring, providing insights into tissue responses, possibly at a single‐cell scale, to a wide range of stimuli. Moreover, OoC devices typically necessitate lesser amounts of analytical reagents and cellular populations compared to traditional 2D and 3D models. These platforms have been successfully deployed in recreating various functional tissues and organs, such as lung, liver, and tumor, among others. [ 111 , 112 , 113 ] Importantly, by integrating multiple OoC platforms, multiorgan “body‐on‐a‐chip” systems can be generated for studying disorders affecting multiple organs and evaluating the systemic effects of drugs. [ 114 , 115 ]
In the pursuit of effective MSK models capable of delineating tissue interactions, a modular strategy has emerged. For example, individual joint tissue components, including the osteochondral unit (subchondral bone and cartilage), synovium, ligament, tendon, meniscus, and fat pad, can be generated as distinct OoC units. [ 57 , 116 ] These OoC units can be used individually to investigate tissue‐specific disorders. [ 45 , 117 , 118 ] By interlinking these modular units, a more clinically relevant multitissue chip can be constructed for faithful recapitulation of MSK disease mechanisms and drug testing. [ 119 , 120 , 121 , 122 ] With the ability to effectively reproduce the pathogenesis and progression of human MSK diseases, OoCs allow us to “fail fast and fail early,” thereby greatly increasing the efficiency of clinical trials by reducing the risk of adverse events and decreasing drug attrition rate. Therefore, OoCs offer a more ethical, cost‐effective, and efficient approach to evaluating new drugs and hold enormous potential in bringing a paradigm shift in drug development.
MSK OoCs: From Single Tissue to Integrated Platforms
OoC platforms are devised to construct 3D tissue structures, typically from human cells, that possess the essential functional attributes of their native counterparts for specific applications. Often also termed microphysiological systems or tissue chips, OoCs combine the versatility of traditional human cell culture with the high biofidelity of multitissue/cell systems. This approach can enable the creation of functional tissue units with the capacity to predict organ‐level responses. To construct effective MSK OoCs, it is crucial to obtain mature, functional 3D tissues, spatially arrange multiple tissue/cell types in a meaningful manner, create a physiologically relevant microenvironment, and recreate in vivo‐like biochemical and biophysical cues. [ 123 ]
OoCs typically comprise four key components: microfluidic chip, live cells, stimulus/drug delivery, and sensing modality. [ 124 ] Assembly of these components embodies miniaturization, tissue integration, and automation. Microfluidic chips can be used to guide cell transfer to predetermined locations and facilitate the introduction of culture medium and waste removal during the cultivation process. Live cells are spatially arranged in 3D tissues, with 3D configurations often achieved via the use of injectable biomaterials like hydrogels. The culture of certain tissues necessitates biophysical and biochemical stimuli to replicate the physiological microenvironment and facilitate microtissue maturation and function. Sensing modalities can be integrated with OoC platforms to continuously detect and compile data. [ 125 ]
Design and Fabrication of MSK OoCs
Fabrication methods should be selected to facilitate on‐chip cell/tissue interactions, meet biocompatibility requirements, and allow the construction of microstructures specific to target applications. [ 126 ] It is preferable to employ techniques that offer high resolution, rapid processing times, and precise spatial arrangement. [ 127 ] Various fabrication methods have been developed in establishing MSK OoCs, among which soft lithography and 3D printing have emerged as two most notable approaches. [ 45 , 128 ]
Soft Lithography
Soft lithography represents an extension of conventional lithography to elastic materials, particularly PDMS. [ 129 ] In soft lithography, lithographic techniques are employed on photoresist‐coated substrates, typically silicon wafers, to obtain molds for fabricating microdevices featuring intricate 3D micropatterns. [ 130 ] Soft lithography have emerged to overcome the limitations of conventional lithography within biological contexts, including elevated costs associated with processing and cleanroom expenses, incompatibility with nonplanar substrates, and limited control over surface attributes. [ 131 ] The method offers noteworthy merits, notably rapid patterning and cost‐effectiveness. However, it should be pointed out that the foundation of soft lithography rests on the utilization of other lithographic methodologies, such as photolithography, to generate the initial “master” template on the substrate. [ 132 ]
Pattern design can be done with various computer‐aided design softwares ( Figure 4 A ). Masks are established by high‐resolution printing on transparent films and feature sizes as small as 1 µm can be accommodated. [ 133 ] Commercial high‐resolution printers can generate lines with satisfactory edge resolution for most microfluidic applications. [ 129 ] Photolithography and electron beam lithography (EBL) constitute the primary methods for creating “masters” featuring patterned relief structures on surfaces. Photolithography represents the traditional method for patterning structures with feature sizes exceeding 1 µm and is typically conducted within cleanroom environments. EBL can generate much smaller structures than photolithography. EBL demands sophisticated equipment and adept operators, rendering it a comparatively slower and more financially demanding process than photolithography.
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The production of elastic stamps, marked by surfaces hosting relief structural patterns, is a pivotal step of soft lithography. These stamps are typically fabricated through the casting of liquid precursors onto masters bearing complementary patterns on their surfaces. The mechanical traits of elastomeric stamps are critical to achieving high‐fidelity pattern transfer. While any elastomer can be used to cast stamps, silicone‐based rubber or cross‐linked PDMS are often favored. [ 136 ] In order to mold substrates onto glass, capillary molding is employed to ensure proper contact between the PDMS layer and the substrate (e.g., glass slide). [ 137 ] This technique allows liquid polymers to be molded through capillary action in alignment with the cavity pattern on the PDMS layer. [ 138 ] Microcontact printing involves pressing the PDMS layer, which has been soaked in molecular ink, onto the substrate as a stamp. Alternatively, in microtransfer molding method, the PDMS layer is filled with liquid polymer and subsequently transferred to the substrate while eliminating excess polymer. [ 139 ]
Soft lithography enables the rapid prototyping of a diverse range of micro‐ and nanoscale structures and devices on planar, curved, flexible, and pliant substrates and has high cost‐effectiveness. [ 140 ] Soft lithography offers a versatile framework for producing microdevices featuring intricate patterns for novel applications in microfluidics, tissue engineering, and OoCs. However, soft lithography has its limitations in forming complex organ/tissue structures. For example, it necessitates additional steps for introducing and organizing the cells. [ 141 ] Besides, the need for multiple photolithographic processes and masks restricts the fabrication capabilities of soft lithography. [ 142 ]
3D Bioprinting
Compared to soft lithography, 3D bioprinting in medical and biomedical contexts offers several advantages, such as reduced turnaround time and a broader range of material options. [ 128 , 143 ] This approach demands minimal microfabrication expertise and permits simultaneous or sequential printing of polymers, hydrogels, and diverse cell types, enabling the creation of customized, reproducible, and intricate patient‐specific 3D biomimetic tissue constructs with precise cell placement. [ 142 , 144 ]
3D bioprinting can be categorized into nozzle‐based bioprinting, including inkjet and extrusion bioprinting, and photobioprinting, such as stereolithography (SLA) and laser‐assisted bioprinting (Figure 4B ). [ 145 , 146 ] These techniques can be employed to produce the tissues and/or microfluidic devices for MSK OoCs. For example, Tang et al. utilized SLA technology to fabricate HAP substrates with varying microchannel structures, resulting in HAP–PDMS microfluidic chips to mimic bone structure and function and provide a platform for bone‐related biomedical research. [ 147 ] Conceição et al. employed SLA printing technology to construct an innovative metastasis chip platform. [ 148 ] This platform replicates the influence of sympathetic activation on the interplay between breast cancer cells and bone cells within a fully humanized model ( Figure 5 A,B ). The platform incorporates three distinct human cell types that are carefully separated into discrete compartments to facilitate the study of secreted factors while mitigating direct cell–cell interactions, as shown in Figure 5C . Their results revealed enhanced proinflammatory phenotypes arising from dynamic interactions between sympathetic neurons, breast cancer cells, and osteoblasts, shedding light on previously unexplored mechanisms within the bone metastatic microenvironment. [ 148 , 149 , 150 ] Nour‐Goushki et al. successfully developed microfluidic chips with sub‐micrometer patterns and 3D porous structures (Figure 5D ). [ 151 ] Through two‐photon polymerization (TPP) 3D printing, the team integrated sub‐micrometer columns of varying heights onto the surface of 3D microscaffolds (Figure 5E ). These sub‐micrometer morphologies enhanced surface hydrophilicity and withstood substantial flow rates, with no observed cytotoxic effects on human mesenchymal stem cells (MSCs) (Figure 5F ). This advancement enhances the feasibility of fabricating sub‐micrometer on‐chip structures for bone regeneration studies.
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Besides device fabrication, 3D printing technology has also been employed in tissue or scaffold preparation for MSK OoC models. Laser‐assisted printing techniques, in particular, stand out for their capacity to achieve high droplet resolution through precise laser targeting. [ 145 ] These techniques have enabled the generation of single‐cell droplets and the printing of tissue constructs mimicking the 3D architecture of human bone and skin. [ 134 , 152 ] However, the application of laser‐assisted bioprinting on microfluidic platforms remains underexplored, possibly due to concerns related to laser‐generated heat and the long durations required to produce tissue constructs. [ 153 ]
In a recent study, Ji et al. utilized SLA to create a bone‐on‐chip platform replicating premetastatic niches (PMNs). [ 154 ] Within this platform, the research team employed 3D‐printed HAP and gelatin‐methacryloyl (GelMA) hydrogels to mimic dormant niches. Moreover, MSCs were inoculated to emulate the metastatic site and reproduce the intricate microstructures of bone (Figure 5G ). To maintain the physiological integrity of the system and prevent media evaporation, 3D‐printed scaffolds were securely housed within a 4 mm container (Figure 5H ). As a proof‐of‐concept, the functionality and utility of this platform were demonstrated through the comprehensive analysis of invasive foci formation and the influence of various cell types. In addition, Singh et al. employed a silk cellulose mixture and extrusion‐based printing to create 3D structures with appropriate swelling capacity, degradability, and compressive strength. [ 155 ] These structures supported chondrocyte growth and cartilage ECM formation.
Moreover, 3D printing technology has been explored for the one‐step creation of OoCs. Lee et al. employed an intricate one‐step extrusion‐based biofabrication process to produce OoC systems with poly(ɛ‐caprolactone) used in the microfluidic device and various human cell lines within collagen type I or gelatin hydrogels. [ 144 ] The liver‐mimicking OoC, which contained endothelial cells and hepatocytes, effectively replicated organotypic functions surpassing those attainable by 3D hepatocyte monocultures and off‐chip endothelial cell‐hepatocyte cocultures, as evidenced by upregulated albumin and urea secretion. This study offers guidance on the one‐step preparation of MSK OoCs using 3D printing technology.
In conclusion, 3D printing holds great potential in propelling advancements in MSK OoCs. Furthermore, emerging printing technologies, such as 4D printing, which integrates time as the fourth dimension, and the envisioned 5D printing, where information serves as the fifth dimension, offer promising prospects in OoC fabrication. [ 159 , 160 ] Advances in these fields can offer versatile methods for microfluidic chip fabrication, lead to increased precision, and facilitate one‐step construction of OoCs. Such progress is expected to enhance our ability to establish OoC systems to effectively mimic MSK biology and pathology.
The “Energy Source” of MSK OoCs
The selection of the cell source is pivotal for establishing MSK OoC systems. Primary MSK lineages, cell lines, primary stem cells, and induced pluripotent stem cells (iPSCs) each come with their distinct advantages and drawbacks. While primary cells retain the properties of native tissues, they may require complicated cell isolation and purification processes. Cell lines offer cost‐effectiveness but often lack physiological relevance. iPSCs show promise in personalized regenerative medicine and disease modeling, yet they often require lengthy and complex differentiation protocols. Biomaterials, such as hydrogels and decellularized ECM, have found widespread use in OoC platforms, mimicking key characteristics of the 3D tissue microenvironment. Microfluidic systems, fabricated from biocompatible materials, enable precise control over culture conditions, including medium perfusion. To create effective MSK OoCs, a harmonization of appropriate cell sources, biomaterial scaffolds, microfluidic devices, and various biochemical and biophysical signals is essential. Advances in these fields are propelling the development of physiologically relevant MSK OoCs, providing valuable insights into the understanding of MSK diseases and potential treatments.
Cell Sources
The phenotypes and behaviors of cells underpin the function of MSK OoCs. The selection of cell type depends on various factors, including cell availability and its ability to form functional tissues, ideally using cells from the same origin. Each cell source has distinct advantages and drawbacks based on the intended application of the MSK OoCs.
Primary cells isolated from living tissues can be used to generate OoCs that closely mimic the tissues of origin. However, these cells often yield heterogeneous populations and necessitate purification and enrichment of desired cell types, which can lead to loss of their functions and cell dedifferentiation as primary cells require specific culture conditions to maintain their phenotypes. [ 161 , 162 , 163 ] Furthermore, primary cells are challenging to isolate from most human organs, limited in quantity, and cannot be expanded in culture, hindering their large‐scale applications. Cell lines, on the other hand, can divide indefinitely and have higher affordability and availability. However, they commonly exhibit chromosomal and genetic abnormalities that limit their ability to simulate normal cellular behavior in vitro. [ 164 ] Despite these limitations, cell lines are commonly employed during early design iterations and testing in MSK OoC development, where the requirement on physiologically relevance is less stringent. [ 31 , 123 ]
Stem cells represent a promising cell source in regenerative medicine to address MSK pathologies resulting from diseases or injuries. These cells can self‐renew through symmetric or asymmetric cell division while retaining their undifferentiated state and regenerative potential. Human embryonic stem cells (hESCs) possess pluripotency that renders them promising for therapeutic applications in regenerative medicine. [ 165 ] hESCs can be utilized to establish any type of MSK OoCs to study different orthopedic conditions, but the ethical controversy surrounding hESCs arising from their embryonic origin limits their applications. [ 166 ] Additionally, initial hESC cultures relied on mouse fibroblast feeder layers and animal serum, potentially restricting their clinical applications.
In the quest for alternative stem cell sources, investigations have unveiled the moderate regenerative capacity of extraembryonic fetal tissues and specialized regions in various tissues, both postbirth and into adulthood. These adult stem cells exhibit multipotency and are amenable to differentiation into diverse cell lineages. [ 167 ] Hematopoietic stem cells (HSCs) and MSCs inhabit the bone marrow, with HSCs yielding blood and immune cells through well‐characterized differentiation pathways and in vitro replication. [ 168 ] Hence, bone marrow‐derived HSCs and MSCs serve as an important cell source for MSK OoC applications, particularly in contexts involving interactions between MSK tissues and immune cells.
iPSCs have emerged as a promising cell source with virtually unlimited availability for OoC platforms. iPSCs can be reprogramed from any somatic cells of specific patients and differentiated into multiple lineages. [ 169 ] Tissue units in MSK OoCs can be generated from a single iPSC line to disentangle the genotypic and phenotypic factors in studies on tissue physiology and pathology. This genetic uniformity is instrumental in modeling drug effects on individual patients or patient groups to investigate, for example, mutations that impact drug efficacy and toxicity. [ 170 ] Moreover, genetic manipulation of iPSCs to introduce or rectify MSK disease‐associated culprit genes facilitates mechanistic explorations and targeted drug development. [ 31 ] Notably, the use of human iPSC‐derived cells from autologous donors has triumphed over previous hurdles in constructing patient‐specific OoC models. The pluripotency of human iPSCs is particularly useful in the construction of MSK OoCs containing heterogeneous tissues with diverse cell types, such as osteochondral tissues and vascularized and innervated muscle and bone structures. [ 145 ] The successful implementation of human iPSCs in MSK OoCs necessitates efficient and reproducible multilineage differentiation protocols, and many publications provide detailed strategies for generating MSK lineages from human iPSCs. [ 171 , 172 , 173 , 174 ] Nonetheless, iPSC‐derived lines might encounter loss of epigenetic markers during derivation and exhibit developmental immaturity. [ 175 ] To address these challenges, the maturation and phenotypic stability of iPSC‐derived tissues can be enhanced through physical conditioning and the inclusion of organ‐specific supporting cells, such as fibroblasts, MSCs, and endothelial cells. [ 176 , 177 ]
Materials as Extracellular Matrix and for Chip Production
Hydrogels play a pivotal role in the construction of MSK OoCs by serving as bioscaffolds that replicate the ECM microenvironment and structural support needed for appropriate cellular functionality. [ 178 ] Hydrogels fall broadly into natural (e.g., gelatin) and synthetic (e.g., polycaprolactone) categories. [ 179 ] Natural hydrogels generally have biocompatibility, biodegradability, and minimal cytotoxicity, yet modulation of their mechanical properties poses challenges. [ 180 ] Consequently, they are often used to complement synthetic hydrogels. Synthetic hydrogels are gaining increasing attention due to their outstanding comprehensive properties and their synthesis typically involve chemical modifications that allow, for example, photo‐crosslinking. [ 181 ] The popularity of hydrogels in OoCs stems from their biocompatibility, permeability, and mechanical resemblance to native tissue ECM. Micromachining techniques, including lithography, 3D printing, and molding, facilitate the fabrication of hydrogel‐based intricate tissue constructs. [ 182 ]
Besides hydrogels, ECM‐derived biomaterials have also been widely used in MSK OoCs. Common methods for fabricating ECM‐based scaffolds include electrospinning and 3D printing. [ 123 ] Electrospun fibrous scaffolds furnish nano‐ to microscale fibrous structures with interconnected pores, and 3D printed materials enable tailored geometries. [ 183 ] These methodologies allow the meticulous structuring fabrication of scaffolds. However, challenges linger in replicating in vivo cell–ECM interactions and attaining biomechanical harmony between biomaterial scaffolds and target tissues. A corpus of literature has explored biomaterials and fabrication approaches as pivotal factors in the generation of effective MSK disease models ( Table 2 ). [ 184 , 185 ]
Table 2
Typical biomaterials used as extracellular matrices in OoCs and for chip fabrication.
Abbreviation: PCL = polycaprolactone; GelMA = gelatin methacryloyl; ECM = extracellular matrix; PDMS = polydimethylsiloxane; PC = polycarbonate.
| Role | Materials | Advantages | Disadvantages | Refs. |
| Extracellular matrix | Gelatin | Biocompatibility Biodegradability Good water solubility Low cost | Poor stability Poor mechanical properties Modification is often required | [ 45 , 118 ] |
| Collagen | Biocompatibility Permeability Enzymatic degradability Major component of ECM | Poor mechanical properties Low thermal stability | [ 118 , 186 , 187 ] | |
| PCL | Low cost Biocompatibility Good mechanical properties | Poor biodegradability | [ 188 , 189 , 190 ] | |
| GelMA | Good biocompatibility Adjustable physical properties Visible light‐photocrosslinkable Biodegradability | Limited stability Low mechanical strength Limited scalability | [ 122 , 191 ] | |
| Matrigel | Biocompatibility Biomimicry to native ECM Facilitates cell adhesion Commercially available | Undefined composition Uncertainty in biological activity Lot‐to‐lot variability | [ 192 , 193 , 194 ] | |
| Chitosan | Deformability Biocompatibility Conductivity Biodegradability | Weak mechanical properties | [ 45 , 188 ] | |
| Decellularized ECM | Preserves tissue mechanical and biochemical properties Promotes cell proliferation Clues for cell differentiation | Complex extraction process Batch‐to‐batch variability | [ 58 , 186 , 195 ] | |
| Chip production | PDMS | Biocompatibility Optically transparent Low cost Good air permeability | Adsorption of hydrophobic molecules Challenges in upscaling | [ 196 , 197 ] |
| Silicone | High resolution channel creation Low power consumption Compatible with existing manufacture | Manufacturing time‐consuming Relatively expensive Opacity | [ 188 , 196 ] | |
| Glass | Good optical transparency Relatively inert Biocompatibility | Time‐consuming manufacturing Fragile Expensive | [ 196 , 197 , 198 ] | |
| PC | Light transmission Biocompatibility High mechanical strength Good gas permeability | Hydrophobicity Poor chemical resistance Relatively high cost | [ 188 , 199 ] |
Microfluidic platforms, widely used in biomedical research, have historically relied on inorganic materials like silicon or glass. [ 200 , 201 ] Silicon‐based microfluidic chips achieved through photolithography and etching techniques can offer sub‐micrometer features that allow precise manipulation of biomolecules and individual cells. [ 202 ] However, the complexity and cost of fabricating silicon‐based microfluidic platforms, caused by the need for specialized equipment, cleanrooms, and techniques, have posed challenges. [ 202 ] Moreover, opacity of silicon limits its applicability in scenarios requiring optical measurements. Besides silicon, metals like gold and titanium find applications in well‐designed OoCs equipped with integrated sensor systems for real‐time data acquisition. [ 203 ]
In contrast to inorganic materials, organic polymeric materials, notably PDMS, confer several advantages in microfluidic chip development, including cost‐effectiveness, facile fabrication process, biocompatibility, and ease of functionalization. [ 204 ] PDMS, as a transparent elastomer with low Young's modulus and surface energy, adheres to surfaces and can be peeled from SU‐8 templates after molding. [ 202 ] Its nontoxic and inert nature renders PDMS suitable for cellular experiments. However, it is crucial to recognize that PDMS adsorbs hydrophobic molecules, potentially leading to microfluidic channel blockage and complicating the interpretation of drug testing data. [ 205 ] To address this challenge, other organic materials, such as styrene–ethylene/butylene–styrene block copolymers and polyurethanes, have been explored in the preparation of microfluidic devices. [ 206 , 207 ] Porous membranes are often integral to microfluidic devices as they facilitate segregation of distinct cellular compartments while permitting material exchange within the chip. [ 208 ] The selection of membrane materials, such as PDMS, polycarbonate (PC), hinges on materials attributes like elasticity, transparency, and biocompatibility. [ 209 ] It is important to develop protocols that enable seamless compatibility and adherence of the membranes to the substrate material. [ 210 ]
Nanotechnology holds great promise for the development of advanced materials for MSK OoC systems, where the incorporation of nanoscale features can enhance material functionality and performance. One notable application of nanotechnology is the design and fabrication of bioengineered scaffolds that mimic native ECM. [ 197 ] Electrospun nanofibrous scaffolds from polymers such as PCL can closely mimic the structural and mechanical properties of native ECM. [ 121 ] These nanofibrous scaffolds facilitate cell adhesion, proliferation, and differentiation. In addition, nanoscale surface modifications within microfluidic devices, such as nanotopographical features, can influence cellular behavior and enable precise control over cellular responses within the chip. [ 211 ] Furthermore, the integration of nanosensors and imaging modalities into microfluidic devices further exemplifies the potential of nanotechnology in OoC development. With the incorporation of functional nanosensors and nanoprobes, OoCs can be utilized to monitor cellular behaviors, measure biochemical markers, and enable real‐time imaging and analysis. [ 194 , 212 ]
Nanotechnology for MSK Disease Treatment and OoC Platform Innovation
MSK OoC platforms bear significance as robust in vitro models for probing a spectrum of MSK diseases (Figure 1A ). Exploiting functional nanomaterials and harnessing nanotechnology in stem cell differentiation, novel therapeutics have been explored to treat various MSK conditions. Moreover, the integration of nanomaterials and nanoscale attributes into OoC systems augments their ability to recapitulate native tissue microenvironments, thereby enhancing structural coherence within these systems (Figure 1B ). Additionally, nanotechnology empowers the assessment and monitoring of MSK OoCs’ performance and functionality, which are closely tied to their biological interfaces (Figure 1C ).
Advances in Nanotechnology for MSK Disorder Treatment
Based on the type of nanotechnology utilized in MSK disease treatment, we focus on the latest 5‐year advances in relevant nanomaterials (represented by NPs), biological scaffolds, as well as stem cells and their derivatives with representative studies ( Table 3 ). We will elaborate the impact of nanotechnology on the development of regenerative biomaterials for MSK tissue engineering, emphasizing the effects of nanotechnology on the scaffolds’ physicochemical and biological properties.
Table 3
Representative recent advances in nanotechnology for the treatment of MSK diseases.
Abbreviation: miR‐29b = microRNA‐29b; pBAE = poly‐beta‐amino‐esters; BMF = BCL‐2 modifying factor; TGF‐β3 = transforming growth factor beta‐3; Cys@SeNPs = cysteine‐decorated selenium nanoparticles; ROS = oxygen‐containing reactive species; Wnt = wingless‐related integration site; NAHA = Alendronate and o‐phenylenediamine grafted on hyaluronic acid; CaP = calcium phosphate; CA9 = carbonic anhydrase IX; siRNA = small interfering RNA; NO = nitric oxide; TGF‐β1 = transforming growth factor‐beta1; FR = forskolin and RepSox; PLGA = poly(lactic‐ co ‐glycolic acid); F = forskolin; R = RepSox; PCEC = poly(ɛ‐caprolactone)–poly(ethylene glycol)–poly(ɛ‐caprolactone); BTZ = bortezomib; MSN = mesoporous silica nanoparticles; ZOL = zoledronic acid; BGN = bioactive glass nanoparticle; PDA = polydopamine; DOX = Doxorubicin; SHED = stem cells from human exfoliated deciduous teeth; EV = extracellular vesicles; AT‐SC = aged tendon stem/progenitor cells; SM = systemic mastocytosis; RUNX2 = Runt‐related transcription factor 2; SAMD = mothers against decapapentaplegic; BGN = bioactive glass nanoparticles; BMSCs = bone marrow mesenchymal stem cells; NFATc1 = nuclear factor of activated T cells 1; UPR = unfolded protein response; PPD = ɛ‐polylysine–polyethylene–distearyl phosphatidylethanolamine; Mu‐EVs = muscle‐secreted multiple EVs; f(n)EVs = extracellular vesicles from muscle stem/progenitor cells cultured on flattened substrates (nanogratings); DMGP = DFO/MnCO@gelatin methacryloyl‐polylactide; DFO = deferoxamine; MnCO = manganese carbonyl; HA = hydroxyapatite; GLUT = glucose transporter pathway; HNPs/ HMPs = hair‐derived antioxidative nano/micro particles; MSCM = mensenchymal stem cell membrane; µRB = microribbon; HDB = high cell density beads; D‐CuS = Dexamethasone sodium phosphate‐loaded hollow mesoporous CuS nanoparticles; PEG = polyethylene glycol; NIR = near‐infrared; PCL = polycaprolactone; AKT = akermanite; Fe 3 O 4 = iron oxide; CaO 2 = calcium peroxide; H 2 O 2 = hydrogen peroxide; MNAs = multifunctional nanoparticulate agonists; Ap = apatite; NBS = nanofiber bundle scaffold; CeNPs = ceria nanozyme; ATP = adenosine triphosphate; TDSCs = tendon‐derived stem cells; SASP = senescent‐related secretory phenotypic.
| Nano biomaterials type | Material | Disease model | Mechanisms and effects | Refs. |
| Nanoparticles | miR‐29b‐pBAE‐NP | Osteosarcoma | Inhibiting BMF expression, which induces intrinsic apoptotic pathway; promoting bone remodeling by inhibiting TGF‐β3 signaling. | [ 229 ] |
| Chiral Cys@SeNPs | Osteoporosis | l ‐Cys@SeNPs showed higher uptake in osteoblasts, more effective scavenging of excess ROS accumulation, which in turn reduced apoptosis by activating the Wnt/β‐catenin pathway. | [ 269 ] | |
| NAHA‐CaP/siCA9 NPs | OA | Scavenging intracellular NO and downregulate CA9 mRNA expression, repolarizing M1 macrophages to an M2 phenotype and increasing TGF‐β1 mRNA expression, and inhibiting chondrocyte apoptosis. | [ 270 ] | |
| FR‐PLGA‐NPs | Skeletal muscle injury | Releasing a mixture of small molecules (F and R) in situ to repair skeletal muscle by inducing activation and expansion of resident satellite cells | [ 233 ] | |
| Microwave‐responsive Fe 3 O 4 /Au NPs | Osteomyelitis | Clearing of S. aureus infection and inducing M2 polarization of macrophages to improve osteogenic differentiation of MSCs under microwave irradiation | [ 271 ] | |
| Multiple myeloma cell membrane‐coated PCEC@BTZ NPs | Multiple myeloma | Increasing drug availability at the tumor site to inhibit multiple myeloma growth; evading phagocytosis of mononuclear phagocyte system to achieve a long circulation time. | [ 272 ] | |
| Au@MSNs‐ZOL | Bone metastasis | Inhibiting osteoclast formation and promoting osteoblast differentiation and achieving bone‐targeting ability; enabling photothermal therapy to inhibit tumor growth and relieve pain and bone resorption. | [ 273 ] | |
| BGN@PDA–DOX | Bone metastasis | Inhibiting the growth of cancer cells and achieving better local anticancer efficacy in vivo; demonstrated good bone repair ability in rat cranial defect models. | [ 274 ] | |
| Chondrocyte membrane‐coated NPs | OA | Achieving deeper penetration into the cartilage matrix and a residence time of more than one month; decreasing catabolism of rat and human chondrocytes and cartilage explants under inflammatory conditions; attenuating OA development and providing cartilage and bone protection in rat and canine models. | [ 223 ] | |
| EV | SHED‐EVs | Aging‐impaired tendon disease | Regulating histone methylation and inhibiting nuclear factor‐κB to reverse AT‐SC senescence. | [ 237 ] |
| SM‐EVs | Systemic mastocytosis | Increasing miRNA‐30a and miRNA‐23a, which in turn attenuated osteoblast maturation by inhibiting the expression of the key drivers of osteogenesis, RUNX2 and SMAD1/5. | [ 275 ] | |
| BGN + BMSC‐EVs | Osteoporosis | Enriching long noncoding RNA NRON, which inhibited osteoclast differentiation by inhibiting the nuclear translocation of NFATc1 through binding to activating T cell nuclear factor transcription factors. | [ 276 ] | |
| Myocytes EVs‐ceramides | Skeletal muscle injury | Secreting and inducing UPR activation in naive myotubes via dihydroceramide accumulation, potentially promoting regeneration of injured skeletal muscle | [ 277 ] | |
| MSC‐derived EVs | Bone defect | MSC‐secreted EVs from early stage of osteoinduction rich in alkaline phosphatase induced osteoblast differentiation; calcium/phosphorus‐rich EVs released at late stages promoted mineralization. | [ 265 ] | |
| PPD‐EVs | OA | Positively charged PPD‐EVs led to improved cellular uptake, cartilage penetration, and joint retention compared to unmodified EVs; PPD‐EVs had increased bioavailability, thereby reducing number of intra‐articular injections and improving efficacy in in vivo studies | [ 278 ] | |
| Mu‐EVs | Osteoporosis | Muscle‐secreted EVs delivered lactate dehydrogenase A to BMSCs cells, promoting glycolysis and regulating the osteogenic differentiation of BMSCs | [ 279 ] | |
| fEVs; nEVs | Aged skeletal muscle injury | EVs produced by young muscle stem/progenitor cells (MPCs) cultured on flat substrates (fEVs) promoted proliferation of senescent MPCs; those released by MPCs cultured on nanogratings (nEVs) facilitated differentiation of myoblasts. Sequential use of fEVs and nEVs effectively promoted the increase in muscle fiber size and functional recovery. | [ 280 ] | |
| Nanostructured scaffolds | Multicomponent DMGP scaffold | Bone defect | Triggering a sustained release of carbon monoxide and Mn 2+ , attenuating the inflammatory response; DFO inhibited osteoclast differentiation and synergized with the osteoinductive activity of HA. | [ 281 ] |
| HNPs/HMPs scaffold | OA | Stimulating GLUT and stimulating chondrocyte proliferation and maturation; accelerating the osteogenic differentiation of BMSCs | [ 282 ] | |
| MSCM‐coated µRB scaffold | Bone defect | Promoting macrophage polarization toward a regenerative phenotype, inducing CD8 + T cell apoptosis, and enhancing regulatory T cell differentiation. | [ 283 ] | |
| Matrigel HDB‐MSCs | Volumetric muscle loss | Enhancing MSC function, increasing MSC proliferation, migration, and extracellular vesicle production to achieve near‐natural cell density and reduce fibrosis during skeletal muscle regeneration | [ 284 ] | |
| D‐CuS–PEG–PCL scaffold | Bone defect | Controlled release of dexamethasone sodium phosphate promoted osteogenic differentiation of MSCs under NIR and warm conditions; showed excellent bone regeneration ability in rat bone defect models. | [ 285 ] | |
| AKT–Fe 3 O 4 –CaO 2 scaffold | Osteosarcoma | Achieving H 2 O 2 self‐sufficiency for nanocatalytic osteosarcoma treatment and providing Ca 2+ for bone regeneration; magnetothermal effect and the generation of toxic hydroxyl radicals under alternating magnetic fields for osteosarcoma treatment | [ 286 ] | |
| MNAs–Ap–PLGA scaffold | Bone defect | Modulating Hedgehog signaling; binding to hydroxyapatite for potential bone tissue targeting; overcoming cell membrane barriers, ultimately improving in vitro osteogenesis and calvarial bone healing in mice | [ 287 ] | |
| NBS@CeO scaffold | Tendon injury | Scavenging excessive ROS and stabilizing ATP synthesis in TDSCs; reducing oxidative damage and accelerating collagen fibers regeneration in vivo; alleviating senescence and apoptosis in TDSCs, downregulating SASP | [ 288 ] |
Nanoparticles
NPs are useful tools for improving the efficiency of drug delivery to MSK tissues. [ 213 ] Several prominent review articles have extensively discussed the advantages of NPs in drug delivery, highlighting their unique characteristics, including their small size, remarkable retention ability, and evasion of phagocytosis. [ 19 , 214 , 215 ] In addition, NPs can load and release functional chemicals and proteins to modulate the local immune microenvironment. [ 215 ] Moreover, surface modification of NPs can enhance drug accumulation and enable targeted delivery. Furthermore, internalization of NPs can induce changes in cellular functions, including osteogenic differentiation of MSCs, leading to treatments of MSK disease. [ 218 , 219 ] In this context, we will mainly discuss the use of NPs for drug delivery in joint diseases, bone repair, and muscle regeneration.
Joint diseases such as OA and RA affect multiple joint tissues. Systemic drug administration is limited by the low efficiency in reaching the target site and the risk of systemic toxicity. Intra‐articular drug administration is commonly used for joint disease management, but current strategies are mostly hindered by uneven drug distribution and reduced drug dose reaching the target site. Moreover, drugs in the joint cavity usually undergo quick clearance from the lymphatics via macrophage activity, leaving only a small amount of the drug for tissue uptake. [ 213 ] Targeted delivery of drugs to cartilage is desirable in OA treatment due to limited angiogenesis in cartilage; this strategy can reduce drug clearance by macrophages and maintaining a stable drug supply in the cartilage ECM. [ 220 ] However, the dense collagen type II network and negatively charged aggrecan present in the cartilage ECM create physical and electrical barriers that significantly impede drug penetration into the articular cartilage. [ 220 ] In RA, the enhanced permeability and retention (EPR) effect comes into play due to open capillaries and lymphatic fluid leakage, facilitating passive delivery of nanomedicines. [ 221 , 222 ]
In a recent study, Deng et al. designed poly(lactide‐ co ‐glycolic acid) (PLGA) NPs coated with chondrocyte membranes (CM‐NPs), which were found to be more readily taken up by rat chondrocytes than noncoated NPs. [ 223 ] In ex vivo experiments, it was found that these CM‐NPs could adhere to the rat cartilage ECM, penetrate deep into the tissue, and remain for more than one month. In addition, CM‐NPs loaded with an inhibitor of Wnt signaling pathway [ 224 ] effectively delayed the catabolism of rat and human chondrocytes and cartilage explants under inflammatory conditions. The drug‐loaded CM‐NPs showed cartilage‐ and bone‐protective effects and attenuated OA development in both rat and canine models of OA. This study thus provides a novel idea for targeted and sustained drug delivery to cartilage and chondrocytes.
Surface modification of NPs with hydrophilic polymers serves to impede rapid renal clearance and drug degradation, thereby augmenting drug accumulation in target tissues. [ 221 ] In the realm of nanomedicine‐based RA treatment, a key objective is to attract anti‐inflammatory macrophages and inhibit lymphocyte proliferation by targeted interaction of NPs with the surface markers of these cells. [ 225 ] The immune microenvironment's pivotal role in bone repair and regeneration is well recognized. Hence, immune modulation is a critical consideration when assessing the osteogenic effects of biomaterials. Studies have demonstrated that inorganic NPs, such as gold and mesoporous silica, can enhance bone regeneration by stimulating immune regulation. [ 227 ] Additionally, lipid NPs, like poly‐β‐amino ester (pBAE) NPs, have garnered attention in drug delivery due to their low toxicity and high biocompatibility, primarily attributed to the recurring ester groups in their primary chains, rendering them susceptible to intracellular biodegradation through hydrolysis. [ 228 ]
Freeman et al. have developed a drug delivery system using pBAE NPs and HA for the targeted delivery of miR‐29b ( Figure 6 A ). [ 229 ] MiR‐29b, a microRNA of considerable significance, has been closely associated with various facets of cancer development and progression and has also emerged as a pivotal player in the intricate process of bone remodeling. In vitro studies have demonstrated the efficacy of this system in achieving precise, localized, and sustained release of either pBAE:miR‐29b NPs or BMP‐2 (Figure 6B ). [ 232 ] The inclusion of BMP‐2, a well‐established inducer of bone remodeling, served as a control to evaluate the osteogenic potential of miR‐29b NPs. In vivo experiments showed that local delivery of miR‐29b significantly attenuated osteolysis and maintained healthy bone homeostasis for longer periods of time compared to local delivery of BMP‐2 (Figure 6C ). Furthermore, coadministration of miR‐29b and systemic chemotherapy significantly reduced osteosarcoma tumor size, prolonged mouse survival, and significantly reduced osteolysis compared to chemotherapy alone, thereby ameliorating tumor‐induced dysregulation of osteolytic activity.
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In addition, Fang et al. defined a chemical cocktail that selectively and robustly differentiated dermal and muscle stromal cells into myogenic stem cells for the regeneration of injured adult, aged, and atrophic muscle. [ 233 ] Notably, the team also used a PLGA NP system to deliver these chemicals in situ to cardiotoxin‐injured muscle in adult and aged mice, leading to significant promotion of in situ myogenic stem cell expansion and muscle repair. Furthermore, previous studies have shown that pathological muscle fibrosis retards muscle regeneration. [ 234 , 235 ] This NPs drug release system could have additional benefits on muscle regeneration by reducing fibrosis, possibly due to the inhibitory effect of the small molecule drug RepSox on TGF‐β. [ 236 ]
In parallel, emerging NPs, including chiral NPs and nucleic acid‐based NPs, have made inroads into the field of regenerative medicine. [ 238 , 239 , 240 ] It is anticipated that as nanotechnology continues to advance and our understanding of MSK disorders deepens, novel NPs will play a pivotal role in addressing the complexities of MSK disorders and ushering in innovative therapeutic options for the future.
Stem Cells and Their Exosomes
Stem cells, with their high proliferative potential and ability to differentiate into a variety of MSK lineages, have gained increasing attention in the field of MSK disease therapy. [ 241 , 242 , 243 ] Among the different types of stem cells, MSCs have emerged as a particularly promising source of cells for the treatment of MSK diseases. [ 244 , 245 ] This is mainly attributed to the immunomodulatory and trophic effects exhibited by MSCs. [ 246 , 247 ] Over the past two decades, several MSC‐based strategies have been developed and comprehensively reviewed for the treatment of MSK diseases. [ 248 , 249 ] These approaches encompass combining MSCs with other cell types, [ 250 , 251 ] using MSCs alone, [ 252 , 253 ] or combining MSCs with biomaterials and growth factors. [ 254 , 255 , 256 ] These strategies have shown promising results in promoting MSK tissue regeneration.
Nanoscale modulation of the stromal environment has garnered attention because of its potential in enhancing the expansion and differentiation ability of MSCs. Studies have revealed that nanoscale biomaterials like porous silk fibroin/chitosan, PLL/nano‐HAP, and electrospun HA/chitosan can induce chondrogenic and osteogenic differentiation of bone marrow‐derived human MSCs. [ 16 ] In a novel approach showcased by Ren et al., a zinc‐based metal–organic framework called zeolitic imidazolium framework‐8 (ZIF‐8) was harnessed to differentiate MSCs into an osteoblast lineage. [ 257 ] The ZIF‐8 NPs were encapsulated in a stem cell membrane (SCM) to enhance their biocompatibility and target specificity toward MSCs. The internalized SCM/ZIF‐8 NPs were found to be biocompatible and augmented the osteogenic potential of MSCs. In vivo investigations further validated the osteogenic properties of SCM/ZIF‐8 NPs, in which these NPs significantly augmented new bone tissue formation at the femoral head defect within four weeks.
Moreover, the concept of hierarchical targeting and microenvironmentally responsive peptide‐functionalized NPs has been proposed by Lu et al. They conjugated ultrasmall copper oxide (CuO) NPs with the dual‐targeting WPV peptide for recognizing type 2 collagen and MSCs. [ 258 ] These NPs, featuring MMP‐2‐sensitive sequences, enable hierarchical targeting by initially penetrating cartilage and subsequently attracting MSCs via MMP‐2 clearance, thereby fostering cartilage formation. Additionally, this team also showcased the therapeutic potential of CuS@MnO 2 NPs functionalized with an MSC‐targeting peptide and supplemented with metformin. [ 259 ] These NPs enhanced the efficacy of MSC therapy for RA by modulating oxidative stress thereby increasing cell viability and favorably affecting cell migration, anti‐inflammation ability, and chondrogenesis. Another noteworthy approach employs biomimetic copper sulfide@phosphatidylcholine (CuS@PC) NPs containing TGF‐β1‐encoding plasmid DNA (pDNA) to facilitate MSC chondrogenesis for augmenting OA treatment via cartilage regeneration. [ 260 ]
MSC‐derived exosomes, nanosized extracellular vesicles, have garnered considerable attention in MSK disease treatment in recent years. Secreted by all cell types, exosomes serve as carriers for proteins, biologically active lipids, and genetic components like microRNAs (miRNAs) and facilitate intercellular communication under physiological and pathological conditions. [ 261 , 262 ] Exosome therapy, as a cell‐free approach, presents distinct advantages over stem/stromal cell‐based therapies, circumventing concerns related to undesired proliferative effects, cell heterogeneity, and immunogenicity. [ 263 ] Due to their stability in circulation, high biocompatibility, and low immunogenicity, exosomes have emerged as a promising avenue for treating various human diseases, including MSK disorders. [ 262 ]
Lee et al. developed exosome mimetics (EMs) with bone‐targeting capabilities by integrating HAP‐binding molecules via bioorthogonal functionalization. [ 264 ] The osseointegration ability of these EMs was validated in vitro through HAP‐coated scaffolds, ex vivo with a bone‐binding assay, and in vivo in a mouse calvarial defect model. Furthermore, biodistribution studies proved the preferential accumulation of systemically administered EMs within bone. In another study, Jin et al. showed that exosomes derived from young human deciduous tooth stem cells (SHED‐Exos) provide abundant antiaging signals (Figure 6D ). [ 237 ] These bio‐NPs effectively alleviated the senescent phenotype of aging tendon stem/progenitor cells (AT‐SCs) and preserved their tendon sheath generation capacity (Figure 6E,F ). Systemic administration of SHED‐Exo bio‐NPs delayed tendon degradation in a natural aging mouse model. Notably, the administration of SHED‐Exos‐loaded microspheres produced antiaging effects through topical application. These effects included a reduction in cartilage matrix deposition (Figure 6G,H ) and ectopic bone formation. Additionally, these treatments restored endogenous tendon regeneration and repair capacity in aging rats both structurally and functionally. These straightforward engineering methodologies hold promise as a versatile tool for augmenting MSK regeneration, offering a nanomedicine‐based avenue to tackle complex MSK diseases.
The preparation of tissue scaffolds with supportive and osteoinductive properties is crucial to most bone regeneration strategies. A study by Wei et al. revealed the role of EVs secreted by MSCs at different stages of osteoinduction. [ 265 ] Notably, EVs produced at early stages exhibited high levels of alkaline phosphatase (ALP), an early maker of osteoblast differentiation. [ 266 ] In contrast, EVs produced at later stages were rich in calcium and phosphorus, which facilitate the nucleation of mineral crystals in the extracellular environment. To further enhance the therapeutic potential of the MSC‐derived EVs, the team loaded them in a layered delivery system based on autologous blood‐derived hydrogels. [ 267 ] This innovative approach not only leveraged an osteoinductive biomimetic ECM scaffold rich in collagen fibrils, which provide the sites for crystal deposition and mineralization, but also allowed for the gradual, controlled release of functional EVs. This study presents a multifunctional platform for addressing bone tissue repair and enhancing the efficacy of EVs.
Furthermore, exosomes can function as adaptable transporters for various cargos, including proteins, lipids, DNA, RNA, and mitochondria, allowing for their uptake by recipient cells via endocytosis or phagocytosis. This capacity allows exosomes to regulate gene transcription and activity in target cells like osteoblasts and chondrocytes. [ 268 ] Among their biologically significant functions, exosomes play a pivotal role in the delivery of miRNAs. [ 261 ] Moreover, it was found that MSC‐derived exosomes exhibit multifaceted capabilities, including the induction of angiogenesis, immunomodulation, apoptosis inhibition, and the promotion of cellular proliferation. These effects are attributed to their ability to activate key signaling pathways, specifically, the extracellular signal‐regulated kinase (ERK) 1/2 and mitogen‐activated protein kinase pathways. [ 263 ]
Nanostructured Scaffolds
Several insightful reviews have comprehensively discussed recent advances in scaffold design aimed at facilitating MSK tissue regeneration and the seamless integration of engineered orthopedic tissues. [ 289 , 290 , 291 , 292 , 293 ] When selecting materials for tissue engineering, several key requirements must be met, including biocompatibility, biointegration, mechanical stability, ease of production and handling, and cost‐effectiveness. [ 294 , 295 ] Ideally, 3D nanoscaffolds should consist of biomimetic materials that create a favorable environment for cell growth, proliferation, and differentiation. [ 296 , 297 , 298 , 299 ] For example, chondroitin sulfate, HAP, and collagen‐binding peptides have been commonly used to construct bioscaffolds to promote the proliferation and differentiation of stem cells and facilitate tissue regeneration. [ 16 , 300 , 301 , 302 ] These biomaterials play a crucial role in providing the necessary support and cues for successful regeneration of MSK tissues.
An emerging strategy in bone regeneration involves bone immunomodulation, aimed at promoting immune‐bone homeostasis through orchestrated interactions between immune cells and bone cells. [ 303 ] Upon implantation of scaffolds engineered with favorable osteoimmunomodulatory properties, the immune system is activated to dynamically regulate the osteoimmune microenvironment, ultimately enhancing osseointegration under physiological conditions. [ 304 ] Zhang et al. have developed a scaffold for bone repair that consists of deoxyamine@poly(ɛ‐caprolactone) NPs (DFO@PCL NPs), manganese carbonyl (MnCO) nanosheets, gelatin methacryloyl hydrogel, and a polylactide/HAP matrix. [ 281 ] This scaffold is characterized by biomimetic layering and aims to restore immune system balance and improve bone metabolism ( Figure 7 A ). The scaffold has a 3D‐printed structure resembling the composition of both cortical and cancellous bone tissues (Figure 7B,C ). The association of MnCO with the implanted tissue instigates the sustained release of CO and Mn 2+ , significantly attenuating inflammatory responses by promoting the M2 phenotype of macrophages. Additionally, DFO inhibits osteoclast differentiation and synergizes with the osteogenic activity of HAP. In vitro and in vivo data affirm the immunomodulatory and osteogenic prowess of this bone immunomodulatory scaffold (Figure 7D ), providing valuable insights into large‐scale bone defect repair.
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The treatment of bone defects resulting from osteosarcoma surgery is a major clinical challenge. To address this issue, Dong et al. developed a 3D multifunctional nanoscaffold. [ 286 ] The team incorporated calcium peroxide (CaO 2 ) and iron oxide (Fe 3 O 4 ) NPs into a 3D‐printed scaffold. The incorporation of CaO 2 NPs served the dual purpose of 1) acting as a source of H 2 O 2 for Fe 3 O 4 ‐enabled nanocatalytic osteosarcoma treatment, and 2) promoting bone regeneration through the release of Ca 2+ ions. In addition, under an applied magnetic field, the magnetothermal effect and the generation of toxic hydroxyl radicals by the magnetic Fe 3 O 4 NPs resulted in a synergistic effect on osteosarcoma treatment. [ 305 , 306 ] By combining these multifunctional elements in a 3D bioscaffold, the research team hoped to address the multiple challenges associated with bone defects after osteosarcoma surgery, offering a promising avenue for improving clinical treatment strategies.
Nanostructured scaffolds also hold promise for muscle and skin tissue regeneration. Cheesbrough et al. introduced an innovative bio‐based nanohybrid elastomer that mimics the ECM of skeletal muscle. [ 307 ] Through static tensile loading studies, this elastomer demonstrated hyperelastic properties comparable to those of native skeletal muscle. Notably, the uniaxially aligned nanofibers in the elastomer promoted myocyte alignment, stimulated the formation of myotubes, and facilitated myotube fusion and myofiber maturation. In addition, Chen et al. employed nanofibers as a scaffold for loading highly active, adipose stem cell‐conditioned medium. [ 308 ] In vitro studies showed that this conditioned medium released from nanofibers accelerated the migration of fibroblasts and controlled the excessive proliferation of fibroblasts, thereby preventing abnormal ECM deposition. Furthermore, in vivo experiments showed that the system greatly accelerated wound healing by inhibiting the excessive deposition of type I collagen and type III collagen.
In summary, nanostructured scaffolds designed with biocompatible materials and appropriate microstructures and surface modifications possess minimal cytotoxicity, enhance biocompatibility, and promote cell adhesion. [ 20 ] A variety of nanostructured scaffolds have been developed using polymers, carbon‐based materials, ceramics, and metals. [ 309 , 310 ] These nanostructured scaffolds can also be used as carriers to locally deliver antimicrobial, anti‐inflammatory, and anticancer substances, thereby optimizing tissue regeneration in MSK diseases.
Nanotechnology‐Fueled Development of MSK OoCs
Nanotechnology is a transformative force in the field of MSK OoC platforms, revolutionizing the way MSK tissues are replicated and studied in vitro. Nanotechnology has been employed to address the challenges of established materials such as PDMS (e.g., solvent incompatibility, hydrophobic molecular adsorption, and biomolecular interactions [ 35 ] ), advance the construction of bionic tissues with nanoscale structures, and unlock nanotechnology‐enabled imaging and real‐time sensing for comprehensive functional analysis.
Mimicking Cellular Microenvironments: Nanoscale Features in OoCs
The integration of nanomaterials and nanoscale features into MSK OoC systems allows effective replication of the intricate cellular microenvironment that governs MSK tissue functionality. Through meticulous engineering of biomechanical and biochemical cues, these OoCs exhibit enhanced fidelity in emulating the in vivo conditions of MSK tissues. This integration not only ensures a more faithful representation of tissue architecture but also facilitates in‐depth investigation of cell–cell interactions, cell–matrix dynamics, and signaling cascades. The confluence of nanotechnology with OoCs thus establishes an innovative platform for unraveling profound insights into MSK biology.
In native fibrocartilage, mechanotransduction plays a pivotal role in coordinating cellular responses to the physical microenvironment, encompassing intrinsic ECM properties and externally applied mechanical cues, such as shear induced by medium flow. To seamlessly integrate nanotopography and flow‐related stimuli into the microenvironment, studies have explored the effects of microfluidic and nanotopographic environments on MSCs through the design of biomimetic microfluidic devices. [ 211 ] For instance, Abagnale and colleagues devised a microgrooved polyimide chip with 25 diverse structure combinations, featuring systematic variations in groove and ridge widths. Their study revealed the direct impact of ridge width on MSC cell morphology at the micrometer scale, demonstrating that elongated forms were conducive to osteogenic development, while rounded morphologies promoted adipogenesis. Additionally, nanonotched surfaces showed enhanced adipogenesis and osteogenic differentiation. In a recent investigation, Ross et al. identified that square arrangement nanotopography could modulate MSCs’ immunomodulatory capacity by reducing intracellular tension and enhancing oxidative glycolysis. [ 311 ]
Current cell‐laden hydrogels face constraints in replicating the intricate nature of highly mineralized bone tissues. Mineral deposition typically manifests as dispersed nodules, a phenomenon observable in engineered bone constructs after an incubation period of 14–21 days. [ 118 ] HAP NPs have been incorporated into the ECM to successfully emulate mineralized bone tissue. [ 312 ] Recently, some researchers have designed a bone‐mimicking microenvironment by integrating HAP NPs into the fibronectin ECM and used a microfluidic platform to model the bone metastasis tumor microenvironment (TME) in a bone‐mimicking composite. [ 33 ] The HAP‐rich microenvironment was found to have an inhibitory effect on the migration of Colorectal (SW620) and gastric (MKN74) cancer cells. In addition, Jusoh et al. have introduced 3D microvascular networks to HAP‐doped ECM to obtain vascularized bone tissue models in microfluidic devices. [ 313 ] It was found that by regulating the concentration of HAP, the ECM had different mechanical properties. Moreover, the sprouting of blood vessels is affected by the interaction of mechanically regulated HAP with the extracellular matrix, generating a vascularized bone microenvironment model. A group of researchers have fabricated a scaffold based on PCL nano‐ and microfibers through electrostatic spinning. [ 121 ] The microfiber and nanofiber layers were seeded with osteoblasts and chondrocytes, respectively, and designed to prevent the cells from migrating into the other layer. With the ability to deposit bone‐ and cartilage‐specific ECM, the osteochondral unit‐mimicking chip was used to model OA.
Ji et al. have developed a sophisticated bone chip platform to mimic PMNs. [ 154 ] This innovative platform represents a valuable tool for investigating the complex interactions between bone‐resident cells and metastatic tumor cells in response to primary cancer stimuli ( Figure 8 A ). To create a comprehensive bone metastasis model, the research team utilized a 3D‐printed nano‐HAP–GelMA scaffold that mimics the quiescent niches present within the bone microenvironment. By introducing MSC inoculation as a substitute for metastatic sites, the model replicates the intricate architecture of bone tissues, including dormant niches, perivascular niches, and “malignant circulation” niches (Figure 8B ). The effectiveness and usefulness of this innovative platform were demonstrated through thorough various analyses, including the evaluation of formation of invasive foci and the impact of various cellular components (Figure 8C,D ). The dynamic niches produced by this model offer a promising route to advance our understanding of PMN formation and to accelerate the discovery of relevant therapeutic agents.
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To construct an on‐chip bone TME model, Ahn et al. used fibronectin conjugated with HAP nanocrystals as a filler material in microfluidic chip channels to simulate bone matrix. [ 33 ] In addition, Tang et al. incorporated HAP paste into a microfluidic chip to create an highly biomimetic skeletal environment. [ 147 ] Notably, researchers successfully utilized the Christmas tree‐structured HAP–PDMS chip to create a concentration gradient of the model drug doxorubicin hydrochloride (DOX). These findings demonstrate the potential of the HAP–PDMS microfluidic chip in high‐throughput screening of bone‐related drugs and emphasize its importance in advancing bone‐related research. An innovative triphasic vascularized osteochondral model has been devised by Pirosa et al. to elucidate the intricate osteochondral tissue microenvironment. [ 314 ] This model incorporated HAP NPs to enhance its biomimetic properties and the PCL/HAP nanoscaffolds were complemented by the incorporation of GelMA hydrogels. These nanoscaffold components were seeded with human bone marrow MSCs and human umbilical vein endothelial cells (HUVECs). This cellular ensemble was cultivated within a dual chamber bioreactor to obtain distinct chondrogenic and osteogenic markers in the human bone marrow MSC population.
Nanotechnology also offers an avenue for synergizing external stimuli like mechanical strain, electrical stimulation, and biochemical gradients into biomimetic cues to provide potent signals for modulating cellular responses and tissue development. [ 315 ] Wang et al. innovatively crafted multichannel hollow fibers embedded with nanostructured black phosphorus (BP) through microfluidic spinning‐based 3D printing technology (Figure 8E ). [ 34 ] These scaffolds exhibited reversible contraction and expansion under near‐infrared (NIR) irradiation, attributed to the BP nanosheets’ NIR heating capacity and temperature‐triggered poly( N ‐isopropylacrylamide) (poly(NIPAM)) volume phase transition (Figure 8F,G ). This behavior facilitated cell infiltration into the scaffold channels. The photothermal‐responsive scaffolds notably enhanced HUVEC infiltration and proliferation within the channels. Moreover, these scaffolds promoted rat bone MSC proliferation and osteogenic differentiation, as evidenced by augmented ALP activity and calcium accumulation. In in vivo tests, the NIR‐responsive channels facilitated angiogenesis and expedited bone regeneration within rat cranial defects.
In summary, the incorporation of nanomaterials into MSK OoC systems has significantly enhanced the reproduction of the intricate cellular microenvironment that regulates the function of MSK tissues. Furthermore, the integration of nanotechnology and stimulus‐responsive agents into biomimetic channel scaffolds opens new avenues for designing smart biomaterials for MSK engineering applications.
Functional Assessment and Analysis: Nanotechnology‐Enabled Sensing and Imaging
The integration of nanotechnology into MSK OoCs extends beyond merely tissue emulation. Nanotechnology can also provide these platforms with enhanced capabilities for sensing, imaging, and performance analysis. The incorporation of nanosensors within OoCs enables real‐time, high‐resolution monitoring of critical parameters, facilitating meticulous evaluation of the impact of therapeutic agents, mechanical forces, and biochemical cues on MSK tissues. This dynamic synergy between nanotechnology and OoCs provides researchers with a versatile tool to unravel the intricate interplay among various factors governing MSK health and the progression of pathological states.
MSK OoCs respond with distinct biomarker patterns under specific stimuli and in different maturation phases. To quantify these biomarkers, analytical techniques must possess sufficient sensitivity and selectivity to detect trace biomarker levels and allow real‐time, unobstructive data acquisition without interfering in cellular behaviors. [ 140 ] Established methodologies for in situ biomarker detection encompass antigen–antibody interactions, adaptor‐based assays, and bead‐based immunoassays. [ 316 ] Notably, successful incorporation of biosensors into MSK OoCs mandates the appropriate immobilization of bioreactive elements onto electrodes, primarily through substrate anchoring. [ 317 ] Various immobilization techniques have been devised to ensure effective presentation of the bioreactive component on electrode surfaces and achieve sufficient assay stability and sensitivity. [ 318 ] Ortega et al. established a bespoke platform that allows muscle cell stimulation under fluidic conditions with a highly sensitive electrochemical sensing system for real‐time monitoring. [ 212 ] By quantifying in vitro interleukin‐6 (IL‐6) and TNF‐α release levels from 3D muscle microtissues, they demonstrated the microtissues’ capability to express and release these factors in response to electrical stimulation and lipopolysaccharide administration. In addition, the device applied screen‐printed gold electrodes enabling in vitro cytokine detection with a sensitivity of nanograms per milliliter.
To understand RA mechanisms, Rothbauer et al. pioneered a 3D synovial chip system. [ 194 ] Their approach involves the use of a hydrogel and particle suspension, including cells and polystyrene NPs, designed to monitor the inflammatory responses within synovial tissue. The system was seamlessly integrated into a biochip equipped with an embedded photodiode array and light scattering detection capabilities ( Figure 9 A ). Comprising four distinct incubation chambers, the biochip architecture is structured from three layers of microscope slides (Figure 9B ). Utilizing a label‐free and noninvasive optical light scattering biosensing strategy based on NPs, this platform rapidly detects 3D tissue structural changes due to inflammation within just two days. This innovation led to the development of a synovial chip system that enables in‐depth exploration of inflammatory arthritis initiation and progression through innovative light scattering techniques. Dornhoff et al. introduced an OoC platform to support substrate‐based heterogeneous 3D cultures. [ 319 ] In brief, the fabrication process started with a glass wafer. The team applied a 500 nm insulating layer of silicon nitride through plasma‐enhanced physical vapor deposition [ 320 ] and patterned the image reversal resist by spin‐coating. Thereafter, nanoscale layers of titanium and platinum were added using a lift‐off process. Additionally, an insulating layer was stacked between 800 nm silicon nitride and 200 nm silicon oxide employing the same technique. This innovative design integrates electrochemical biosensor arrays based on nanomaterial to detect essential energy metabolites, including oxygen, lactate, and glucose (Figure 9D,E ). Furthermore, the chip enables real‐time quantification of metabolite consumption and production under varying culture conditions and anticancer drug exposure. This device allows continuous in situ metabolite monitoring in 3D cell cultures and facilitates drug screening for diseases such as breast cancer and its bone metastases.
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Kalmykov et al. prepared a 3D self‐winding biosensor array (3D‐SR‐BAs) of active field‐effect transistors or passive microelectrodes (Figure 9F,G ). [ 321 ] 3D‐SR‐BAs fabrication included silicon substrate preparation, photoresist coating, and deposition of nanometal layers for interconnections, with passivation or additional nanogold deposition performed after these processes. These arrays enable continuous, stable multiplexed recording of field potentials with high sensitivity and spatiotemporal resolution and support simultaneous calcium imaging. The team enabled electrophysiological investigation and monitoring of complex signaling in 3D cellular assemblies, establishing an organ‐on‐electronic‐chip platform for assessing tissue maturation.
Extensive research underscores the pivotal role of hypoxia in preserving the stemness of bone marrow mesenchymal stem cells (BMSCs). [ 322 , 323 , 324 ] It is observed that oxygen levels progressively increase from nonvascularized cartilage to hypoxic bone marrow and further to vascularized bone. This nuanced transition potentially guides chondrogenesis to osteogenesis in the regenerative process of the skeletal system. Therefore, it is highly desirable to modulate oxygen levels in the MSK OoCs. [ 325 ] In the study by Kim et al., BMSCs were cultured within a microchip, in which the O 2 levels in avascular cartilage, vascularized bone, and hypoxic bone marrow were recorded using a pin‐type O 2 sensor with nanoscale coatings and elements. [ 325 ] Within this experimental paradigm, basal oxygen levels were found to promote chondrogenesis, with BMSCs demonstrating robust antioxidant potential. Intermediate oxygen levels drove BMSCs toward quiescence, while elevated oxygen levels induced osteogenesis by perturbing redox homeostasis and desiccation. Furthermore, endochondral or intramembranous osteogenesis was observed in vivo at low to high oxygen concentrations. The results highlight the potential of developmental mechanism‐driven approach of modulating the oxygen tension to orchestrate the shift from chondrogenesis to osteogenesis in skeletal repair.
Nanotechnology‐driven high‐resolution imaging has made exciting advancements in the realm of MSK OoC research. A group of researchers successfully devised an on‐chip bone microfluidic platform that faithfully replicates the physical and chemical attributes of the bone microenvironment. [ 326 ] Notably, through the deployment of 3D phase‐contrast nanocomputed tomography (nanoCT) in conjunction with TPP laser lithography, intricate bone trabecular features were faithfully reproduced. The accuracy of these biomimetic bone models was conclusively corroborated by means of 3D optical stereomicroscopy and laser confocal analysis, affirming their precision and fidelity in emulating the bone microenvironment.
In summary, the effects of therapeutic agents, mechanical forces, and biochemical cues on MSK tissues can be more meticulously assessed using nanotechnology and based on the unique properties of nanosensors, such as material composition, size, and chirality. [ 240 , 327 , 328 ] As nanotechnology and microfluidics continue to advance and converge, advanced MSK OoCs will be developed and play an increasingly important role enhancing our capability in engineering functional MSK tissue, studying orthopedic conditions, and assessing potential regenerative therapies.
MSK OoCs: Bridging Nanotechnology Gaps in MSK Treatments
The combination of MSK OoC technology and nanotechnology presents a valuable opportunity for the development of targeted drug delivery and therapeutic treatments for MSK disorders. This convergence leverages the precision aspect of nanotechnology and the biological fidelity of OoC platforms to gain a better understanding of NP delivery to MSK tissues’ intricate microenvironments. Through robust in vitro analysis, MSK OoCs shed light on the physicochemical properties of NPs on multifaceted tissue conditions, providing valuable insights for advancing MSK therapies. This section examines the dynamic landscape of MSK OoCs as a testing platform to bridge the gap in nanotechnology translation for MSK disorder treatment, exploring the critical role of MSK OoCs in maximizing the precision, safety, and efficacy of nanotherapeutic interventions.
MSK OoCs for Evaluating Nanotherapy Safety
With the mounting prominence of nanotherapies in MSK treatment, there arises a concomitant necessity to understand their potential adverse effects. MSK OoC platforms, which can possess nanotechnology‐enabled attributes, offer a controlled microenvironment for meticulous examination of the interplays between NPs and biological systems.
A representative study delved into the assessment of efficacy of anti‐TNF‐α monoclonal antibody (mAb)‐chondroitin sulfate/poly(amidoamine) dendritic polymer NPs encapsulated within tyrosine‐modified cold gels. [ 329 ] This investigation employed a 3D cartilage OoC model containing human monocyte cell lines (THP‐1) and human chondrogenic progenitor cells (hCH). Live/Dead assays confirmed the viability of inflamed THP‐1 cells within NPs‐hydrogels. While healthy THP‐1 cells exerted no deleterious impact on hCH survival, inflamed THP‐1 cells caused hCH cells to exhibit susceptibility to cellular death, which could be ameliorated through the utilization of NPs‐hydrogels. This agrees with observations in RA patients, where an inflammatory context precipitates chondrocyte death. Assessment of possible drug toxicity is also pivotal in the development of anticancer drug, as shown in recent studies on NP‐loaded macrophages for drug delivery in TME and lipid NPs for anti‐osteosarcoma applications in microfluidic settings. [ 330 , 331 ]
OoC‐based investigations into nanomedicines have extended to bone and bone marrow models. The inaccessibility of living bone marrow within scenarios of drug‐, radiation‐, or mutation‐induced myelotoxic stress poses a challenge in elucidating its pathophysiology. Chou et al. introduced a vascularized human bone marrow chip (BM chip) that remarkably nurtured the differentiation and maturation of multiple hematopoietic cell lineages in just 4 weeks ( Figure 10 A,B ). [ 332 ] Notably, the BM chip enhances CD34 + cell maintenance and adeptly recapitulates features of bone marrow injury resulting from chemotherapeutic agents and ionizing radiation exposure as well as recovery after drug‐induced myelosuppression. The utility of BM chips is further exemplified through the evaluation of AZD2811, a selective small‐molecule inhibitor of aurora B kinase currently undergoing Phase II clinical trial, encapsulated in a polymer NP. [ 333 ] As aurora B is a vital orchestrator of chromosome alignment and segregation during mitosis, its inhibitors are receiving intense interest for treating solid and hematological cancers. [ 334 ] While the impact of aurora B kinase inhibitors on leukemia cell lines has been documented, the effects on normal human bone marrow cells remain understudied. The outcomes demonstrate that BM chips showed responsiveness to AZD2811 (Figure 10C–E ) and 5‐Fluorouracil, a widely used chemotherapeutic agent with well‐known myelosuppressive effects, and replicated clinically relevant AZD2811 doses for human BM. [ 335 ] The BM chip overcomes the limitations of static suspension or 3D gel culture, offering superior insights into drug toxicity and BM recovery. The BM chip holds great promise in reducing animal studies and expediting the drug development process.
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In summary, MSK OoCs provide a versatile platform for the real‐time, comprehensive evaluation of nanotherapy safety, setting the stage for an enhanced scientific understanding of MSK pathology as well as breakthroughs in MSK nanomedicine.
MSK OoCs as Advanced Preclinical Models for Assessing Nanotherapy Efficacy
MSK OoCs can mirror both the physiological pathogenic states of human tissues and organs, [ 336 ] and OoC‐based in vitro disease models hold immense promise in deciphering the pathophysiological mechanisms of MSK disorders and facilitating the preclinical assessment of therapeutic interventions. [ 337 ] The convergence of MSK OoC technology and nanotechnology presents a novel approach to efficacy evaluation for nanotherapies targeting different MSK disorders. The construction of intricate OoC‐based MSK models enable researchers to effectively replicate the in vivo performance of nanotherapeutic interventions targeting various MSK maladies. Through targeted administration of nanotherapeutic agents, OoCs can be used to emulate the intricate tapestry of cellular interactions, mechanical cues, and biochemical gradients governing therapeutic efficacy.
A dynamic microfluidic platform was used to probe the impacts of methotrexate (MTX) encapsulation in various matrices. [ 331 ] The findings revealed the superiority of MTX‐containing lipid NPs to an equivalent dose of free drug, as the former exhibited enhanced efficacy in eradicating osteosarcoma cells. Additionally, the required drug dosage for NP‐based treatment was ≈100 times lower than that of free drug administration, signifying the potential of NPs to mitigate the side effects and improve patient outcomes. [ 331 , 338 ] MSK OoCs have also been utilized to investigate the inhibition of cancer development by nanomedicine. For example, bone metastasis in hepatocellular carcinoma (HCC) was modeled in an OoC containing HepG2 cell‐encapsulated, GelMA‐based microtissue zones and bone‐mimicking, HAP/GelMA zones. [ 339 ] Thymoquinone, a metastasis‐inhibiting herbal compound, was introduced in both free and chitosan‐encapsulated NP forms, and sustained inhibition of HCC metastasis was observed for thymoquinone‐coated NPs. The results underscore the platform's potential in studying bone metastasis and accelerating antimetastasis drug screening.
The achievement of sufficient physiological relevance is pivotal to the applications of OoCs in preclinical evaluations of nanotherapeutics. In an attempt to create a clinically relevant OA model, Occhetta et al. used a newly developed microphysiological cartilage‐on‐a‐chip system to apply strain‐controlled compression to 3D articular cartilage microtissues to recapitulate the mechanical factors involved in the pathogenesis of OA. [ 340 ] The application of supraphysiological stress triggered a shift in cartilage homeostasis toward catabolism, inflammation, and hypertrophy, and results in a gene expression profile like that of clinical osteoarthritic tissues. This cartilage model was then used to screen drugs that are currently used in clinical management of OA or under development. We recently devised a human MSC‐derived joint‐mimicking OoC system, named miniJoint, that integrated engineered osteochondral complex, synovial‐like fibrous tissue, and adipose tissue within a microfluidic bioreactor. [ 122 ] Responding to IL‐1β‐induced “synovitis,” the miniJoint system effectively recapitulated the key features of joint inflammation and cartilage degradation akin to those seen in human OA joints. In addition, this novel platform was used to test the efficacy of naproxen ( Figure 11 A–C ) as well as four potential disease‐modifying OA drugs currently under development. With proven clinical relevance, miniJoint‐based disease models can serve as a versatile platform for assessing the efficacy of NPs targeting joint conditions to accelerate their translation to clinical applications.
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Macrophage phenotypes (including proinflammatory M1 and anti‐inflammatory M2 macrophages) play significance roles in joint health and disease models. [ 341 , 342 ] The phenotype of macrophages as potential carriers for targeted NPs or small molecule drugs can be modulated to treat immune‐related diseases. [ 343 , 344 ] An OoC model of the TME was developed to cocultivate tumor spheroids (SKOV3) and macrophages (RAW 264.7) within a 3D gel matrix, which enabled real‐time observation of macrophage migration and infiltration into tumor spheroids. [ 330 ] The results highlight the potential of macrophage‐based drug carriers, which can achieve higher drug efficacy than NPs alone by facilitating drug delivery to deep tumor regions. This chip model can be utilized to assess various cell‐mediated nanodrug delivery systems and cell therapies under controlled environmental conditions.
Furthermore, Ran et al. introduced a microfluidic ToC model to test the cancer targeting ability and efficacy of multifunctional liposomes, spherical lipid vesicles with a diameter of 70– 90 nm. [ 345 ] By culturing, settling, and growing SKOV3 cells, the ToC device integrates distinct sets of hemispherical pores of varying sizes to foster tumor spheroid formation and the assessment of liposomes under controlled flow conditions. Impressively, the tumor targeting kinetics of fluorescent liposomes within the ToC model closely mimicked that of in vivo mouse models. The evaluation of four paclitaxel‐loaded liposome formulations highlighted the ToC model's superior predictive ability for in vivo anticancer effects of targeted liposomes to conventional 2D cell monolayers and 3D tumor sphere models. Moreover, the ToC model is capable of probing the impacts of flow rate and tumor size on treatment efficacy, thus offering a robust platform for advancing nanotherapeutic strategies ( Table 4 ).
Table 4
Representative MSK OoC models for evaluating the safety and efficacy of potential therapeutics.
Abbreviations: HUVECs = human umbilical vein endothelial cells; DRG = dorsal root ganglion; RA = rheumatoid arthritis; OA = osteoarthritis; PLGA = poly(lactic‐ co ‐glycolic acid); THP‐1 = human leukemia monocytic cell line; TNF‐α = tumor necrosis factor; CS = chondroitin sulfate; anti‐TNF‐α mAb = monoclonal anti‐TNF‐α antibody; PAMAM = poly(amidoamine); IL‐1Ra = interleukin‐1 receptor antagonist; NPX = naproxen; FGF 18 = fibroblast growth factor 18; SOST = sclerostin; SM04690 = a powerful and selective inhibitor of Wnt signaling; AZD2811 = a powerful and selective Aurora kinase B inhibitor; MC3T3‐E1 = a preosteoblast cell line; IDG‐SW3 = a cell line that replicates the differentiation of osteoblasts to late osteoclasts in vitro and increases bone formation in vivo; α‐miR‐23b = AntagomiR against microRNA‐23b; Hu5/KD3 = immortalized human myogenic cells.
| MSK OoC types | Cell source | Biomimetic strategy | Disease modeled | Tested drug | Refs. |
| Neurovascular micropathological chip | HUVEC; embryonic DRG explants; mouse primary bone marrow cells | Compart‐mentalized design | Osteoarthritis and rheumatoid arthritis | PLGA NPs loaded with ibuprofen | [ 346 ] |
| Cartilage‐on‐a‐chip | THP‐1; primary human chondrogenic cells | Compart‐mentalized design | Rheumatoid arthritis | Anti‐TNF‐α mAb‐CS/PAMAM dendrimer NPs | [ 329 ] |
| Cartilage‐on‐a‐chip | Equine primary chondrocytes | Nutrient gradient control | Osteoarthritis | Triamcinolone | [ 347 ] |
| Cartilage‐on‐a‐chip | Human articular chondrocytes | Microscale compression system | Osteoarthritis | IL‐1R; rapamycin | [ 340 ] |
| Joint‐on‐a‐chip | hBMSC | Modular design for tissue crosstalk | Osteoarthritis and rheumatoid arthritis | NPX; FGF18; SOST protein; SM04690; IL‐1Ra | [ 122 ] |
| Bone‐marrow‐on‐a‐chip | HUVEC; human CD34 + cells; BMSCs | Vascular lumen design | Bone marrow injury‐related disease (e.g., leukemia) | AZD2811 | [ 332 ] |
| Bone‐on‐a‐chip | IDG‐SW3; MC3T3‐E1 | Decellularized extracellular matrix | Osteoporosis | Anti‐SOST monoclonal antibody | [ 186 ] |
| Muscle‐on‐a‐chip | Immortalized human fibroblasts | Myocyte myotubularization | Myotonic dystrophy | α‐miR‐23b | [ 348 ] |
| Muscle‐on‐a‐chip | Hu5/KD3 | Engineered Skeletal Muscle | Skeletal muscle atrophy | Antiatrophic peptide | [ 349 ] |
Targeted Delivery: Maximizing Precision in MSK Therapeutics
Through meticulous emulation of the complex MSK tissue environments in vitro, MSK OoCs provide a platform to elucidate how NPs’ physicochemical properties and the intricate tissue microenvironments influence delivery efficiency. NPs, commonly harnessed for therapeutic cargo transport, are engineered to aggregate at disease sites to mitigate unintended off‐target effects. [ 350 ] It has been established that this target‐specific delivery can be achieved by tailoring various NP attributes, [ 351 ] prompting significant research endeavors to devise OoC models for in‐depth analysis of how NP properties impact their transport, accumulation, and cellular internalization.
Bone is a common site of metastasis for various tumors. In bone metastasis, complex interactions between tumor cell receptors (e.g., CXCR4, RANKL) and stromal cells in the bone marrow drive hematogenous spread. [ 5 ] These interactions trigger the release of growth factors, cytokines (e.g., IL‐6, IL‐8), and angiogenic factors, promoting tumor growth, osteoclast activation, and bone destruction, which is aligned with the seed and soil hypothesis. [ 5 ] The broader context of cancer metastasis involves a series of stages, including cell detachment, local invasion, systemic circulation, extravasation, establishment of metastatic foci, and angiogenesis. [ 352 ] These intricate processes underscore the challenges in developing and delivery of antitumor therapeutics.
Conventional in vitro models employed to assess drug delivery within the TME often suffer from oversimplification, making them poor predictors of the drugs’ in vivo performance. Prabhakarpandian et al. investigated a microfluidic platform that incorporated 3D tumor tissue cultures and tumor vasculature to model in vivo tumor conditions. [ 353 ] Comparing two nanopolymer‐based gene delivery systems (PPC and Express‐In), the study found equivalent performance upon intratumoral injection but different outcomes in intraperitoneal and clinical scenarios. [ 354 , 355 , 356 ] The compromised performance of Express‐In might be attributed to serum protein interactions which led to aggregation and hindered uniform transfection, whereas PPC exhibited unhindered uniform transfection owing to its minimal aggregation propensity.
Neto et al. developed neurovascularized bone microfluidic chips (NVB chips) tailored for the encapsulation of neurons, blood vessels, and osteoblasts, effectively mimicking the skeletal microenvironment (Figure 11D ). [ 346 ] Leveraging fully differentiated primary mouse osteoblasts and IL‐1β, they established a proinflammatory and proangiogenic skeletal microenvironment. Employing PLGA NPs encapsulating ibuprofen as an anti‐inflammatory nanomedicine, they investigated the tissue responses to drug treatment under inflammatory conditions (Figure 11E,F ). Enhanced endothelial barrier permeability facilitated the diffusion of NPs into adjacent inflamed bone regions, demonstrating promising potential for localized therapeutic delivery. Nanodrug testing in the NVB chip underscored the significance of inflammatory conditions in influencing endothelial layer permeability and NP passage.
A substantial challenge in NP research utilizing conventional in vitro methods is to create an integrated physiological microenvironment to study NP transport. The impact of biochemical cues, such as spatial and temporal gradients of soluble factors, and physical cues, including fluid shear stress and tissue stretching, have profound implications on NP behavior. [ 310 , 357 , 358 ] Nevertheless, traditional in vitro models have limitations and often overlook these crucial factors. [ 221 ] Leveraging advanced capabilities, it is possible to emulate intricate physiological microenvironments to facilitate in vitro modeling of NP delivery and prediction of their in vivo efficacy. A notable study by Kim et al. showcases the potential of organoids in elucidating flow‐mediated NP delivery. [ 359 ] Employing a three‐layer microfluidic device with controllable permeability, the study revealed a direct correlation between vascular permeability and endothelial NP translocation. In another study, the effect of flow on endocytosis of targeted nanocarriers was explored by Han et al., revealing flow‐modulated uptake based on different epitopes. [ 360 ]
In conclusion, the combination of MSK OoCs with nanotechnology promises to offer novel insights into targeted NP delivery to diseased tissues. This approach is expected to greatly enhance our comprehension of challenges in nanodrug delivery and accelerate the development of precise and effective nanotherapeutic strategies for MSK disease treatment.
Challenges and Future perspectives
The integration of nanotechnology and MSK biology in OoCs holds great promise in basic, applied, and translational research, but several challenges must be overcome to unlock its full potential.
Addressing the Insufficiency of Cell Types and Organizational Structures in OoC Models
Achieving a high level of biomimicry in terms of tissue complexity and functionality is one major challenge in OoC‐related studies. Current OoC models often lack the full range of cell types and complex tissue structures found in native MSK organs. To improve the physiological relevance of these models, future studies should aim to incorporate a broader range of relevant components, such as immune cells, blood vessels, and innervation. [ 122 , 361 , 362 ] Reproducing the interaction of engineered NPs with the immune system remains challenging since the immune system has a considerable impact on NP transport, efficacy, and toxicity. Relevant studies in the OoC field are actively exploring the development of on‐chip lymph nodes to simulate immune organs. Integrating these nodes with target organ models can result in more accurate predictions of nanotherapeutics’ transport and biological functions in vivo.
Furthermore, it is essential to have an in‐depth understanding of the active, bidirectional tissue crosstalk for the establishment of physiologically relevant MSK OoCs. When modeling MSK diseases using OoCs, it is often necessary to incorporate multiple tissues to achieve a more accurate simulation of the disease conditions. For example, when modeling joint‐related diseases using OoCs, bone compartments, synovial compartments, cartilage components, and adipose tissue should ideally all be included to accurately represent the whole‐joint disease nature. Besides, it is crucial to apply appropriate medium flow rate, oxygenation, and nutrient levels for different organs to understand their interdependent functioning. Medium perfusion parameters such as shear stress can profoundly affect tissue function and crosstalk and should be thoroughly explored to identify appropriate long‐term culture conditions to maintain tissue viability and functionality for longitudinal studies ( Figure 12 ).
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Exploring Biomaterials and Nanotechnology for Modeling Tissue Properties
Developing suitable biomaterials with physicochemical properties (e.g., stiffness, porosity, composition, nanosized features) similar to those of native tissue microenvironments represents another significant challenge in creating MSK OoCs. For example, there is a lack of appropriate synthetic biomaterials with the capability to accommodate and support the function of various cellular components of native bone, such as osteoblast, osteoclast, HUVEC, neurons, and immune cells. The integration of nanomaterials and nanofabrication techniques into MSK OoCs can provide precise control over the mechanical properties of substrates and matrices, thereby enhancing the functionality of the model. Although PDMS is commonly used for OoC systems due to its unique advantages, its limitations include perturbation of the uptake of hydrophobic small molecules in drug testing applications. In future studies, the interaction between nanotherapeutics containing hydrophobic payloads or surface moieties and PDMS should be carefully evaluated. Alternative materials to PDMS are being actively explored to mitigate this issue.
Integrated Sensing Components for Real‐Time Monitoring in OoCs
The potential of integrating sensing elements into microfluidic cell cultures has been well recognized to improve these devices’ analytical capabilities. Such integrated models can enable better understanding of how engineered microtissues and organoids respond to nanotherapies. Implementing electrochemical and optical sensors capable of real‐time monitoring will facilitate spatiotemporal on‐chip analysis of biological responses, which may be challenging using conventional tissue culture techniques. [ 37 ] Advanced imaging and biosensing technologies integrated into MSK lamellar organs can provide real‐time monitoring of cellular behavior and responses to nanomaterials, leading to deeper insights into nanotechnology–biology interactions. Furthermore, developing sensing elements like microelectrode arrays enables the measurement and stimulation of neurons, which is highly desirable in studies on innervated tissue models of joints and bone. [ 363 ] Additionally, exploring single‐cell sequencing and bioinformatics technologies can provide a more detailed mechanistic understanding of biological responses to NPs in the context of OoC models.
Artificial Intelligence (AI)‐Enhanced Integration of OoCs and Nanotechnology for Precision Medicine
Utilizing artificial intelligence (AI) to assist in the integration of nanotechnology with OoC technology is a promising approach to precision medicine. Driven by advanced machine learning algorithms, AI is capable of analyzing large amounts of patient data, including genetic information, medical history, and environmental factors, to provide personalized treatment recommendations. In OoC models, AI‐based visual recognition, electrochemical detection and analysis can already be used to probe organ function and identify optimal drug dosage. [ 364 ] In addition, AI‐based algorithms can assist in processing large datasets and identifying complex patterns that can be used to improve the personalized design of diagnostic and therapeutic nanotechnologies. [ 365 ] It is therefore expected that future development of MSK OoCs will benefit from AI and deep learning to create an automated and highly accurate high‐throughput screening platform for nanomedicines.
Validating In Vitro Findings for Sufficient Clinical Significance
It is still a major obstacle to validate the physiological and clinical relevance of in vitro findings from OoC models related to nanotechnology research. Critical analysis of in vitro – in vivo correlation with data from human patients is crucial to the reliability and predictive powder of OoC‐produced results. Addressing this challenge requires collaboration between OoC developers, medical practitioners, clinical toxicologists, AI technologists, and pharmaceutical companies for close scrutiny of the data during model validation. The results will then inform the design process of OoC models and the relevant biological and physiological endpoints that need to be analyzed in various OoC applications.
Conclusion
MSK OoCs are a powerful tool for unraveling the complex interplay between nanotechnology and MSK biology, which can improve our understanding of MSK disorders and lead to more efficacious treatments. By combining nanotechnology, microfluidics, and tissue engineering principles, these models can effectively mimic the complex composition and dynamics of MSK tissues in a controlled, adjustable manner. Thus, these models can serve as valuable tools for studying disease mechanisms and assessing therapeutic approaches, such as nanotechnology‐based interventions. Despite current challenges, the advances in biomaterials, microfabrication technologies, and tissue engineering strategies, taken together, promise to overcome the current obstacles and improve the functionality and physiological relevance of MSK OoCs. Integrating nanotechnology into these platforms creates unique opportunities for targeted drug delivery, precise sensing, and versatile manipulation of cellular processes in MSK tissue/organ mimics. Therefore, the combination of MSK OoCs with nanotechnology is poised to spearhead a paradigm shift in MSK research and disease treatment. This transformative synergy paves the way for personalized medicine, streamlined drug development processes, and improved therapeutic interventions for MSK conditions. As a bridge between nanotechnology and MSK biology, MSK OoCs have the potential to significantly advance our understanding and management of MSK conditions, ultimately leading to better patient outcomes and higher quality of life.
Conflict of Interest
The authors have no conflicts of interest to declare.
Supporting information
Supporting Information
Supporting Figure 1
Acknowledgements
Z.A.L. acknowledges the support from CUHK's Vice‐Chancellor Early Career Professorship Schemeand CUHK Research Committee (via Direct Grant for research 2022/2023, 4055182). R.S.T. was supported by the Lee Quo Wei and Lee Yick Hoi Lun Professorship in Tissue Engineering and Regenerative Medicine of CUHK. This work was supported in part by the Center for Neuromusculoskeletal Restorative Medicine (to P.Y., G.L., Z.A.L., and R.S.T.), under the Health@InnoHK program launched by the Innovation and Technology Commission, the Government of the Hong Kong S.A.R. of the People's Republic of China, the National Natural Science Foundation of China (to Z.A.L., 82302753), the Research Grants Council of Hong Kong S.A.R. of the People's Republic of China (to Z.A.L., 24203523), and National Key Research & Development Program of China (to C.D., 2023YFE0209700). Y.L. received funding support from the Shenzhen Science and Technology Project (JCYJ 20210324102815040) Y.W. is supported by CUHK postgraduate studentship. Figures 1 , 3 , 4 , and 12 were created with BioRender.com.
Yuwen Wang is a Ph.D. student in the Department of Biomedical Engineering at the Chinese University of Hong Kong (CUHK). He received his B.Sc. degree in applied chemistry from Shandong University (2020) and M.Res degree in nanomaterials from Imperial College London (2021). His current research interest is to develop novel nano‐biomaterials for musculoskeletal disease treatment.
Chuanbin Mao is a Professor of Biomedical Engineering at CUHK. He is a fellow of eight prestigious professional societies, including the American Chemical Society (ACS), ACS Division of Polymeric Materials Science & Engineering (PMSE), Royal Society of Chemistry (RSC), American Association for the Advancement of Science (AAAS), American Academy of Microbiology (AAM), International Academy of Medical and Biological Engineering (IAMBE), American Institute for Medical and Biological Engineering (AIMBE), and Biomedical Engineering Society (BMES). His research interests include virus bioengineering, infectious disease therapy, nanomedicine, and regenerative medicine.
Zhong Alan Li is a vice‐chancellor assistant professor at CUHK's Department of Biomedical Engineering. He was previously a postdoctoral associate at the Department of Orthopaedic Surgery and later a research assistant professor at the Department of Neurobiology, University of Pittsburgh School of Medicine. He obtained his Ph.D. and received his first postdoctoral training at Nanyang Technological University Singapore. His transdisciplinary research is focused on organs‐on‐chips, nanobiomaterials, and tissue engineering.
Rocky S. Tuan is the Vice‐Chancellor and President and Lee Quo Wei and Lee Yick Hoi Lun professorship in tissue engineering and regenerative medicine at CUHK. His research interests are in musculoskeletal biology, stem cells, organs‐on‐chips, tissue engineering and regeneration. He has been elected to the fellowships of the National Academy of Inventors (NAI), the Chinese Association of Inventions (CAI), the American Association of Anatomists (AAA), the Orthopaedic Research Society (ORS), International Combined Orthopaedic Research Societies (ICORS), American Institute for Medical and Biological Engineering (AIMBE), and the Tissue Engineering and Regenerative Medicine International Society (TERMIS) for his accomplishments in innovation and translational research.
1 P. N. Erick , D. R. Smith , BMC Musculoskeletal Disord. 2011 , 12 , 260 . 10.1186/1471-2474-12-260 PMC3250950 22087739
2 A. Cieza , K. Causey , K. Kamenov , S. W. Hanson , S. Chatterji , T. Vos , Lancet 2006 , 396 , 2006 10.1016/S0140-6736(20)32340-0 PMC7811204 33275908
3 Selected Health Conditions and Likelihood of Improvement with Treatment , National Academies Press , Washington, US 2020 . 32687289
4 C. Martin , in Encyclopedia of Quality of Life and Well‐Being Research (Ed: A. C. Michalos ), Springer , Dordrecht, Netherlands 2014 , pp. 4228 – 4231 .
5 M. Wang , F. Xia , Y. Wei , X. Wei , Bone Res. 2020 , 8 , 30 . 32793401 10.1038/s41413-020-00105-1 PMC7391760
6 Y. Wang , L. Liu , Z. Le , A. Tay , Adv. Nanobiomed. Res. 2022 , 2 , 2200085 .
7 L. J. Crofford , Arthritis Res. Ther. 2013 , 15 , S2 . 10.1186/ar4174 PMC3891482 24267197
8 J. Liao , R. Han , Y. Wu , Z. Qian , Bone Res. 2021 , 9 , 18 . 33727543 10.1038/s41413-021-00139-z PMC7966774
9 N. Ashammakhi , S. Ahadian , M. A. Darabi , M. El Tahchi , J. Lee , K. Suthiwanich , A. Sheikhi , M. R. Dokmeci , R. Oklu , A. Khademhosseini , Adv. Mater. 2019 , 31 , 1804041 . 10.1002/adma.201804041 PMC6709364 30565732
10 S.‐S. Jin , D.‐Q. He , D. Luo , Y. Wang , M. Yu , B. Guan , Y. Fu , Z.‐X. Li , T. Zhang , Y.‐H. Zhou , C.‐Y. Wang , Y. Liu , ACS Nano 2019 , 13 , 6581 . 31125522 10.1021/acsnano.9b00489
11 H. Gholami Derami , P. Gupta , K.‐C. Weng , A. Seth , R. Gupta , J. R. Silva , B. Raman , S. Singamaneni , Adv. Mater. 2021 , 33 , 2008809 . 10.1002/adma.202008809 PMC8363531 34216406
12 N. Wang , X. Yang , X. Zhang , Nat. Commun. 2023 , 14 , 814 . 36781865 10.1038/s41467-023-36461-9 PMC9925762
13 H. Wei , B. Zhang , M. Lei , Z. Lu , J. Liu , B. Guo , Y. Yu , ACS Nano 2022 , 16 , 4734 . 35225602 10.1021/acsnano.1c11589
14 B. Yang , J. Yin , Y. Chen , S. Pan , H. Yao , Y. Gao , J. Shi , Adv. Mater. 2018 , 30 , 1705611 . 10.1002/adma.201705611 29333689
15 MA. Secretariat, Ont. Health Technol. Assess. Ser. 2006 , 6 , 1 . 23074479 PMC3379525
16 K. Chaudhury , V. Kumar , J. Kandasamy , S. RoyChoudhury , Int. J. Nanomed. 2014 , 9 , 4153 . 10.2147/IJN.S45332 PMC4159316 25214780
17 H. Wei , J. Cui , K. Lin , J. Xie , X. Wang , Bone Res. 2022 , 10 , 17 . 35197462 10.1038/s41413-021-00180-y PMC8866424
18 L. Zhu , Y. Wang , S. Jin , Y. Niu , M. Yu , Z. Li , L. Chen , X. Wu , C. Ding , T. Wu , X. Shi , Y. Zhang , D. Luo , Y. Liu , npj Regener. Med. 2023 , 8 , 14 . 10.1038/s41536-023-00289-0 PMC10006208 36899012
19 S. Zhang , M. Xing , B. Li , Acta Biomater. 2019 , 93 , 135 . 30685475 10.1016/j.actbio.2019.01.043 PMC6615977
20 T. Gong , J. Xie , J. Liao , T. Zhang , S. Lin , Y. Lin , Bone Res. 2015 , 3 , 15029 . 26558141 10.1038/boneres.2015.29 PMC4639780
21 X. Wang , S. Chen , D. Wu , Q. Wu , Q. Wei , B. He , Q. Lu , Q. Wang , Adv. Mater. 2018 , 30 , 1705668 . 10.1002/adma.201705668 29504155
22 M. A. Grimaudo , A. Concheiro , C. Alvarez‐Lorenzo , J. Controlled Release 2019 , 313 , 148 . 10.1016/j.jconrel.2019.09.015 31629040
23 J. Chen , J. Qi , C. Chen , J. Chen , L. Liu , R. Gao , T. Zhang , L. Song , D. Ding , P. Zhang , C. Liu , Adv. Mater. 2020 , 32 , 2003399 . 10.1002/adma.202003399 32743864
24 R. Mohammadinejad , M. Ashrafizadeh , A. Pardakhty , I. Uzieliene , J. Denkovskij , E. Bernotiene , L. Janssen , G. S. Lorite , S. Saarakkala , A. Mobasheri , Curr. Rheumatol. Rep. 2020 , 22 , 12 . 32248371 10.1007/s11926-020-0884-z PMC7128005
25 L. M. Liz‐Marzán , A. E. Nel , C. J. Brinker , W. C. W. Chan , C. Chen , X. Chen , D. Ho , T. Hu , K. Kataoka , N. A. Kotov , W. J. Parak , M. M. Stevens , ACS Nano 2022 , 16 , 13257 . 10.1021/acsnano.2c10967 36440801
26 P. J. Gawne , M. Ferreira , M. Papaluca , J. Grimm , P. Decuzzi , Nat. Rev. Mater. 2023 , 8 , 783 . 39022623 10.1038/s41578-023-00581-x PMC11251001
27 J. P. A. Ioannidis , B. Y. S. Kim , A. Trounson , Nat. Biomed. Eng. 2018 , 2 , 797 . 30931172 10.1038/s41551-018-0314-y PMC6436641
28 Z. A. Li , R. S. Tuan , Stem Cell Res. Ther. 2022 , 13 , 431 . 35987699 10.1186/s13287-022-03130-5 PMC9392934
29 Z. A. Li , S. Sant , S. K. Cho , S. B. Goodman , B. A. Bunnell , R. S. Tuan , M. S. Gold , H. Lin , Trends Biotechnol. 2023 , 41 , 511 . 35995600 10.1016/j.tibtech.2022.07.011 PMC9938846
30 X. Chen , Y. S. Zhang , X. Zhang , C. Liu , Bioact. Mater. 2021 , 6 , 1012 . 33102943 10.1016/j.bioactmat.2020.09.022 PMC7566214
31 K. Ronaldson‐Bouchard , G. Vunjak‐Novakovic , Cell Stem Cell 2018 , 22 , 310 . 29499151 10.1016/j.stem.2018.02.011 PMC5837068
32 B. Zhang , A. Korolj , B. F. L. Lai , M. Radisic , Nat. Rev. Mater. 2018 , 3 , 257 .
33 J. Ahn , J. Lim , N. Jusoh , J. Lee , T.‐E. Park , Y. Kim , J. Kim , N. L. Jeon , Front. Bioeng. Biotechnol. 2019 , 7 , 00168 . 10.3389/fbioe.2019.00168 PMC6653063 31380359
34 X. Wang , Y. Yu , C. Yang , C. Shao , K. Shi , L. Shang , F. Ye , Y. Zhao , Adv. Funct. Mater. 2021 , 31 , 2105190 .
35 S. Kruss , L. Erpenbeck , M. P. Schön , J. P. Spatz , Lab Chip 2012 , 12 , 3285 . 22858992 10.1039/c2lc40611j PMC3448975
36 Z. Zhao , G. Li , H. Ruan , K. Chen , Z. Cai , G. Lu , R. Li , L. Deng , M. Cai , W. Cui , ACS Nano 2021 , 15 , 13041 . 34342981 10.1021/acsnano.1c02147
37 R. O. Rodrigues , P. C. Sousa , J. Gaspar , M. Bañobre‐López , R. Lima , G. Minas , Small 2020 , 16 , 2003517 . 10.1002/smll.202003517 33236819
38 H. M. U. Farooqi , B. Kang , M. A. U. Khalid , A. R. C. Salih , K. Hyun , S. H. Park , D. Huh , K. H. Choi , Nano Convergence 2021 , 8 , 3 . 33528697 10.1186/s40580-021-00253-y PMC7855143
39 S. Kang , S. E. Park , D. D. Huh , Nano Convergence 2021 , 8 , 20 . 34236537 10.1186/s40580-021-00270-x PMC8266951
40 M. Stavrou , N. Phung , J. Grimm , C. Andreou , Nanoscale 2023 , 15 , 9927 . 37254663 10.1039/d3nr01661g PMC10619891
41 J. Lim , H. Ching , J.‐K. Yoon , N. L. Jeon , Y. Kim , Nano Convergence 2021 , 8 , 12 . 33846849 10.1186/s40580-021-00261-y PMC8042002
42 R. X. Z. Lu , B. F. L. Lai , T. Benge , E. Y. Wang , L. Davenport Huyer , N. Rafatian , M. Radisic , Adv. Mater. Technol. 2021 , 6 , 2000726 .
43 M. R. Carvalho , D. Barata , L. M. Teixeira , S. Giselbrecht , R. L. Reis , J. M. Oliveira , R. Truckenmüller , P. Habibovic , Sci. Adv. 2019 , 5 , 1317 . 10.1126/sciadv.aaw1317 PMC6531003 31131324
44 D. Huh , B. D. Matthews , A. Mammoto , M. Montoya‐Zavala , H. Y. Hsin , D. E. Ingber , Science 2010 , 328 , 1662 . 20576885 10.1126/science.1188302 PMC8335790
45 H. Tolabi , N. Davari , M. Khajehmohammadi , H. Malektaj , K. Nazemi , S. Vahedi , B. Ghalandari , R. L. Reis , F. Ghorbani , J. M. Oliveira , Adv. Mater. 2023 , 35 , 2208852 . 10.1002/adma.202208852 36633376
46 C. F. Guimarães , A. P. Marques , R. L. Reis , Adv. Mater. 2022 , 34 , 2105645 .
47 S. Soltani Dehnavi , Z. E Zadeh , A. R. Harvey , N. H. Voelcker , C. L. Parish , R. J. Williams , R. Elnathan , D. R. Nisbet , Adv. Mater. 2022 , 34 , 2108757 . 10.1002/adma.202108757 35396884
48 M. Filippi , T. Buchner , O. Yasa , S. Weirich , R. K. Katzschmann , Adv. Mater. 2022 , 34 , 2108427 . 10.1002/adma.202108427 35194852
49 X. Feng , Curr. Chem. Biol. 2009 , 3 , 189 . 20161446 10.2174/187231309788166398 PMC2790195
50 S. Bolamperti , I. Villa , A. Rubinacci , Bone Res. 2022 , 10 , 48 . 35851054 10.1038/s41413-022-00219-8 PMC9293977
51 A. J. Sophia Fox , A. Bedi , S. A. Rodeo , Sports Health 2009 , 1 , 461 . 23015907 10.1177/1941738109350438 PMC3445147
52 N. Liu , H. Zhang , X. Ni , T. Liu , N. Jiang , Adv. Eng. Mater. 2022 , 24 , 2200304 .
53 M. D. Smith , Open Rheumatol. J. 2011 , 5 , 100 . 22279508 10.2174/1874312901105010100 PMC3263506
54 M. D. Smith , E. Barg , H. Weedon , V. Papengelis , T. Smeets , P. P. Tak , M. Kraan , M. Coleman , M. J. Ahern , Ann. Rheum. Dis. 2003 , 62 , 303 . 12634226 10.1136/ard.62.4.303 PMC1754505
55 D. K. Rhee , J. Marcelino , M. Baker , Y. Gong , P. Smits , V. Lefebvre , G. D. Jay , M. Stewart , H. Wang , M. L. Warman , J. D. Carpten , J. Clin. Invest. 2005 , 115 , 622 . 15719068 10.1172/JCI200522263 PMC548698
56 C. Orr , E. Vieira‐Sousa , D. L. Boyle , M. H. Buch , C. D. Buckley , J. D. Cañete , A. I. Catrina , E. H. S. Choy , P. Emery , U. Fearon , A. Filer , D. Gerlag , F. Humby , J. D. Isaacs , S. A. Just , B. R. Lauwerys , B. L. Goff , A. Manzo , T. McGarry , I. B. McInnes , A. Najm , C. Pitzalis , A. Pratt , M. Smith , P. P. Tak , S. W. Tas , R. Thurlings , J. E. Fonseca , D. J. Veale , Nat. Rev. Rheumatol. 2017 , 13 , 463 . 28701760 10.1038/nrrheum.2017.115
57 C. A. Paggi , L. M. Teixeira , S. L. Gac , M. Karperien , Nat. Rev. Rheumatol. 2022 , 18 , 217 . 35058618 10.1038/s41584-021-00736-6
58 D. Petta , U. D'Amora , D. D'Arrigo , M. Tomasini , C. Candrian , L. Ambrosio , M. Moretti , Biofabrication 2022 , 14 , 042001 . 10.1088/1758-5090/ac8767 35931043
59 L. Wang , X. You , L. Zhang , C. Zhang , W. Zou , Bone Res. 2022 , 10 , 16 . 35181672 10.1038/s41413-022-00190-4 PMC8857305
60 V. Duong , W. M. Oo , C. Ding , A. G. Culvenor , D. J. Hunter , JAMA, J. Am. Med. Assoc. 2023 , 330 , 1568 . 10.1001/jama.2023.19675 37874571
61 B. Day , W. G. Mackenzie , S. S. Shim , G. Leung , Arthrosc. J. Arthrosc. Relat. Surg. 1985 , 1 , 58 . 10.1016/s0749-8063(85)80080-3 4091911
62 J. Sun , Y. T. Chan , K. W. K. Ho , L. Zhang , L. Bian , R. S. Tuan , Y. Jiang , Bioact. Mater. 2023 , 25 , 256 . 36825224 10.1016/j.bioactmat.2023.01.025 PMC9941420
63 W. Scott , J. Stevens , S. A. Binder‐Macleod , Phys. Ther. 2001 , 81 , 1810 . 11694174
64 H. D. Dave , M. Shook , M. Varacallo , StatPearls , StatPearls Publishing , Treasure Island, FL 2023 .
65 X. Hu , M. Sun , Q. Chen , Y. Zhao , N. Liang , S. Wang , P. Yin , Y. Yang , S. M. Lam , Q. Zhang , A. Tudiyusufu , Y. Gu , X. Wan , M. Chen , H. Li , X. Zhang , G. Shui , S. Fu , L. Zhang , P. Tang , C. C. L. Wong , Y. Zhang , D. Zhu , Nat. Commun. 2023 , 14 , 7916 . 38036537 10.1038/s41467-023-43402-z PMC10689447
66 K. K. Baskin , B. R. Winders , E. N. Olson , Cell Metab. 2015 , 21 , 237 . 25651178 10.1016/j.cmet.2014.12.021 PMC4398026
67 R. Csapo , M. Gumpenberger , B. Wessner , Front. Physiol. 2020 , 11 , 00253 . 10.3389/fphys.2020.00253 PMC7096581 32265741
68 H. Asahara , M. Inui , M. K. Lotz , J. Bone Miner. Res. 2017 , 32 , 1773 . 28621492 10.1002/jbmr.3199 PMC5585011
69 E. Gracey , A. Burssens , I. Cambré , G. Schett , R. Lories , I. B. McInnes , H. Asahara , D. Elewaut , Nat. Rev. Rheumatol. 2020 , 16 , 193 . 32080619 10.1038/s41584-019-0364-x PMC7815340
70 H. R. C. Screen , D. E. Berk , K. E. Kadler , F. Ramirez , M. F. Young , J. Orthop. Res. 2015 , 33 , 793 . 25640030 10.1002/jor.22818 PMC4507431
71 P. Kannus , Scand. J. Med. Sci. Sports 2000 , 10 , 312 . 11085557 10.1034/j.1600-0838.2000.010006312.x
72 M. Kurowska‐Stolarska , S. Alivernini , Nat. Rev. Rheumatol. 2022 , 18 , 384 . 35672464 10.1038/s41584-022-00790-8
73 J. Barnsley , G. Buckland , P. E. Chan , A. Ong , A. S. Ramos , M. Baxter , F. Laskou , E. M. Dennison , C. Cooper , H. P. Patel , Aging: Clin. Exp. Res. 2021 , 33 , 759 . 33742387 10.1007/s40520-021-01817-y PMC8084810
74 J. Lu , Y. Shin , M.‐S. Yen , S. S. Sun , J. Clin. Densitom. 2016 , 19 , 180 . 25440183 10.1016/j.jocd.2014.08.001 PMC4402109
75 F. R. Singer , Nat. Rev. Endocrinol. 2015 , 11 , 662 . 26284446 10.1038/nrendo.2015.138
76 B. Banaganapalli , I. Fallatah , F. Alsubhi , P. J. Shetty , Z. Awan , R. Elango , N. A. Shaik , Front. Genet. 2023 , 14 , 1131182 . 37180975 10.3389/fgene.2023.1131182 PMC10169728
77 L. Gennari , D. Rendina , D. Merlotti , G. Cavati , C. Mingiano , R. Cosso , M. Materozzi , F. Pirrotta , V. Abate , M. Calabrese , A. Falchetti , Front. Cell. Dev. Biol. 2022 , 10 . 10.3389/fcell.2022.932065 PMC9412102 36035996
78 M. I. Hofstee , G. Muthukrishnan , G. J. Atkins , M. Riool , K. Thompson , M. Morgenstern , M. J. Stoddart , R. G. Richards , S. A. J. Zaat , T. F. Moriarty , Am. J. Pathol. 2020 , 190 , 1151 . 32194053 10.1016/j.ajpath.2020.02.007
79 E. Hsieh , S. Shiau , O. Nolan , C. L. Gibert , R. J. Bedimo , M. C. Rodriguez‐Barradas , A. C. Justice , J. A. Womack , M. T. Yin , Clin. Infect. Dis. 2019 , 69 , 1239 . 30715288 10.1093/cid/ciz077 PMC6743834
80 J. Josse , F. Velard , S. C. Gangloff , Front. Cell. Infect. Microbiol. 2015 , 5 , 00085 . 10.3389/fcimb.2015.00085 PMC4660271 26636047
81 F. R. Evola , L. Costarella , V. Pavone , G. Caff , L. Cannavò , A. Sessa , S. Avondo , G. Sessa , Front. Pharmacol. 2017 , 8 , 000150 . 10.3389/fphar.2017.00150 PMC5383728 28439237
82 R. E. Coleman , P. I. Croucher , A. R. Padhani , P. Clézardin , E. Chow , M. Fallon , T. Guise , S. Colangeli , R. Capanna , L. Costa , Nat. Rev. Dis. Primer 2020 , 6 , 83 . 10.1038/s41572-020-00216-3 33060614
83 H. Zhang , J. L. Liesveld , L. M. Calvi , B. C. Lipe , L. Xing , M. W. Becker , E. M. Schwarz , S.‐C. A. Yeh , Bone Res. 2023 , 11 , 15 . 36918531 10.1038/s41413-023-00249-w PMC10014945
84 A. Bigham‐Sadegh , A. Oryan , Int. Wound J. 2015 , 12 , 238 . 24618334 10.1111/iwj.12231 PMC7950494
85 J. Löffler , A. Noom , A. Ellinghaus , A. Dienelt , S. Kempa , G. N. Duda , Commun. Biol. 2023 , 6 , 327 . 36973478 10.1038/s42003-023-04652-1 PMC10042875
86 J. Klavert , B. C. J. van der Eerden , Front. Bioeng. Biotechnol. 2021 , 9 , 663357 . 33937219 10.3389/fbioe.2021.663357 PMC8085338
87 R. Rizzoli , J.‐J. Body , M.‐L. Brandi , J. Cannata‐Andia , D. Chappard , A. El Maghraoui , C. C. Glüer , D. Kendler , N. Napoli , A. Papaioannou , D. D. Pierroz , M. Rahme , C. H. Van Poznak , T. J. de Villiers , G. El Hajj Fuleihan , I. O. F. C. S. A. W. G. C.‐I. B. Disease , Osteoporosis Int. 2013 , 24 , 2929 . 10.1007/s00198-013-2530-3 PMC5104551 24146095
88 G. Murphy , H. Nagase , Nat. Clin. Pract. Rheumatol. 2008 , 4 , 128 . 18253109 10.1038/ncprheum0727
89 H. I. Roach , S. Tilley , in Bone Osteoarthritis (Eds: F. Bronner , M. C. Farach‐Carson ), Springer , London 2007 , pp. 1 – 18 .
90 J. Beasley , J. Hand Ther. 2012 , 25 , 163 . 22326361 10.1016/j.jht.2011.11.001
91 D. Hayashi , F. W. Roemer , A. Guermazi , in Atlas Osteoarthritis (Eds: N. Arden , F. Blanco , C. Cooper , A. Guermazi , D. Hayashi , D. Hunter , M. K. Javaid , F. Rannou , F. Roemer , J.‐Y. Reginster ), Springer Healthcare Ltd. , Tarporley, UK 2014 , pp. 55 – 68 .
92 E. Choy , Rheumatology 2012 , 51 , v3 . 22718924 10.1093/rheumatology/kes113
93 D. Woetzel , R. Huber , P. Kupfer , D. Pohlers , M. Pfaff , D. Driesch , T. Häupl , D. Koczan , P. Stiehl , R. Guthke , R. W. Kinne , Arthritis Res. Ther. 2014 , 16 , R84 . 24690414 10.1186/ar4526 PMC4060460
94 Y. He , Z. Li , P. G. Alexander , B. D. Ocasio‐Nieves , L. Yocum , H. Lin , R. S. Tuan , Biology 2020 , 9 , 194 . 32751156 10.3390/biology9080194 PMC7464998
95 A. M. H. Boots , A. B. Maier , P. Stinissen , P. Masson , R. J. Lories , F. De Keyser , Nat. Rev. Rheumatol. 2013 , 9 , 604 . 23774902 10.1038/nrrheum.2013.92
96 A. G. Fam , Drugs Aging 1998 , 13 , 229 . 9789727 10.2165/00002512-199813030-00006
97 P. Hendrickse , H. Degens , J. Muscle Res. Cell Motil. 2019 , 40 , 127 . 31165949 10.1007/s10974-019-09520-2 PMC6726668
98 M. H. Abd Elsamea , S. A. Mahran , A. N. Badr , D. T. Kamal , T. M. Khidre , Egypt. Rheumatol. 2022 , 44 , 185 .
99 G. Li , N. Han , Z. Li , Q. Lu , Clin. Rheumatol. 2013 , 32 , 609 . 23296645 10.1007/s10067-012-2143-9
100 W. C. Li , D. L. Bai , Y. Xu , H. Chen , R. Ma , W. B. Hou , R. J. Xu , J. Cell. Biochem. 2019 , 120 , 4533 . 30260019 10.1002/jcb.27741
101 A. Tournadre , G. Vial , F. Capel , M. Soubrier , Y. Boirie , Jt., Bone, Spine 2019 , 86 , 309 . 10.1016/j.jbspin.2018.08.001 30098424
102 K. A. Rygiel , M. Picard , D. M. Turnbull , J. Physiol. 2016 , 594 , 4499 . 26921061 10.1113/JP271212 PMC4983621
103 W. Mitchell , P. Atherton , J. Williams , M. Larvin , J. Lund , M. Narici , Front. Physiol. 2012 , 3 , 00260 . 10.3389/fphys.2012.00260 PMC3429036 22934016
104 F. Hofmeister , L. Baber , U. Ferrari , S. Hintze , S. Jarmusch , S. Krause , P. Meinke , S. Mehaffey , C. Neuerburg , F. Tangenelli , B. Schoser , M. Drey , BMC Neurol. 2021 , 21 , 241 . 34172001 10.1186/s12883-021-02264-y PMC8229316
105 A. Moreira‐Pais , R. Ferreira , P. A. Oliveira , J. A. Duarte , GeroScience 2022 , 44 , 1199 . 34981273 10.1007/s11357-021-00510-2 PMC9213593
106 B. C. Clark , J. Frailty Aging 2019 , 8 , 7 . 30734824 10.14283/jfa.2018.35 PMC9725117
107 A. Ghouri , P. G. Conaghan , Ther. Adv. Musculoskeletal Dis. 2019 , 11 , 1759720X1986449 . 10.1177/1759720X19864492 PMC6651659 31384314
108 L. A. Deveza , R. F. Loeser , Rheumatology 2018 , 57 , iv34 . 29267932 10.1093/rheumatology/kex417 PMC6251697
109 L. A. Low , C. Mummery , B. R. Berridge , C. P. Austin , D. A. Tagle , Nat. Rev. Drug Discovery 2021 , 20 , 345 . 32913334 10.1038/s41573-020-0079-3
110 E. Charlier , C. Deroyer , F. Ciregia , O. Malaise , S. Neuville , Z. Plener , M. Malaise , D. de Seny , Ther. Adv. Arthritis Dis. 2019 , 165 , 49 . 10.1016/j.bcp.2019.02.036 30853397
111 J. Shrestha , S. Razavi Bazaz , H. Aboulkheyr Es , D. Yaghobian Azari , B. Thierry , M. Ebrahimi Warkiani , M. Ghadiri , Crit. Rev. Biotechnol. 2020 , 40 , 213 . 31906727 10.1080/07388551.2019.1710458
112 J. Kim , C. Lee , I. Kim , J. Ro , J. Kim , Y. Min , J. Park , V. Sunkara , Y.‐S. Park , I. Michael , Y.‐A. Kim , H. J. Lee , Y.‐K. Cho , ACS Nano 2020 , 14 , 14971 . 32880442 10.1021/acsnano.0c04778
113 X. Liu , J. Fang , S. Huang , X. Wu , X. Xie , J. Wang , F. Liu , M. Zhang , Z. Peng , N. Hu , Microsyst. Nanoeng. 2021 , 7 , 50 . 34567763 10.1038/s41378-021-00277-8 PMC8433302
114 J. H. Sung , Y. I. Wang , N. Narasimhan Sriram , M. Jackson , C. Long , J. J. Hickman , M. L. Shuler , Anal. Chem. 2019 , 91 , 330 . 30472828 10.1021/acs.analchem.8b05293 PMC6687466
115 N. Picollet‐D'hahan , A. Zuchowska , I. Lemeunier , S. L. Gac , Trends Biotechnol. 2021 , 39 , 788 . 33541718 10.1016/j.tibtech.2020.11.014
116 S. Piluso , Y. Li , F. Abinzano , R. Levato , L. Moreira Teixeira , M. Karperien , J. Leijten , R. van Weeren , J. Malda , Trends Biotechnol. 2019 , 37 , 1063 . 31000204 10.1016/j.tibtech.2019.03.003
117 C. Paggi , B. Venzac , J. Leijten , L. M. Teixeira Leijten , S. Le gac , M. Karperien , EClinicalMedicine. 2020 , 28 , S176 .
118 A. Mansoorifar , R. Gordon , R. C. Bergan , L. E. Bertassoni , Adv. Funct. Mater. 2021 , 31 , 2006796 . 35422682 10.1002/adfm.202006796 PMC9007546
119 M. Rothbauer , R. A. Byrne , S. Schobesberger , I. Olmos Calvo , A. Fischer , E. I. Reihs , S. Spitz , B. Bachmann , F. Sevelda , J. Holinka , W. Holnthoner , H. Redl , S. Toegel , R. Windhager , H. P. Kiener , P. Ertl , Lab Chip 2021 , 21 , 4128 . 34505620 10.1039/d1lc00130b
120 Z. Lin , Z. Li , E. N. Li , X. Li , C. J. Del Duke , H. Shen , T. Hao , B. O'Donnell , B. A. Bunnell , S. B. Goodman , P. G. Alexander , R. S. Tuan , H. Lin , Front. Bioeng. Biotechnol. 2019 , 7 , 00411 . 10.3389/fbioe.2019.00411 PMC6930794 31921815
121 M. Tuerlings , I. Boone , H. Eslami Amirabadi , M. Vis , E. Suchiman , E. van der Linden , S. Hofmann , R. Nelissen , J. den Toonder , Y. Ramos , I. Meulenbelt , Adv. Mater. Technol. 2022 , 7 , 2101310 .
122 Z. Li , Z. Lin , S. Liu , H. Yagi , X. Zhang , L. Yocum , M. Romero‐Lopez , C. Rhee , M. J. Makarcyzk , I. Yu , E. N. Li , M. R. Fritch , Q. Gao , K. B. Goh , B. O'Donnell , T. Hao , P. G. Alexander , B. Mahadik , J. P. Fisher , S. B. Goodman , B. A. Bunnell , R. S. Tuan , H. Lin , Adv. Sci. 2022 , 9 , 2105909 . 10.1002/advs.202105909 PMC9313499 35436042
123 R. E. Ajalik , R. G. Alenchery , J. S. Cognetti , V. Z. Zhang , J. L. McGrath , B. L. Miller , H. A. Awad , Front. Bioeng. Biotechnol. 2022 , 10 , 846230 . 35360391 10.3389/fbioe.2022.846230 PMC8964284
124 Q. Wu , J. Liu , X. Wang , L. Feng , J. Wu , X. Zhu , W. Wen , X. Gong , Biomed. Eng. Online 2020 , 19 , 9 . 32050989 10.1186/s12938-020-0752-0 PMC7017614
125 K. I. W. Kane , E. L. Moreno , S. Hachi , M. Walter , J. Jarazo , M. A. P. Oliveira , T. Hankemeier , P. Vulto , J. C. Schwamborn , M. Thoma , R. M. T. Fleming , Sci. Rep. 2019 , 9 , 1796 . 30741972 10.1038/s41598-018-34828-3 PMC6370836
126 S. Fuchs , S. Johansson , A. Ø. Tjell , G. Werr , T. Mayr , M. Tenje , ACS Biomater. Sci. Eng. 2021 , 7 , 2926 . 34133114 10.1021/acsbiomaterials.0c01110 PMC8278381
127 R. Kalot , R. Mhanna , R. Talhouk , Pharmacol. Ther. 2022 , 237 , 108156 . 35150784 10.1016/j.pharmthera.2022.108156
128 N. Tabatabaei Rezaei , H. Kumar , H. Liu , S. S. Lee , S. S. Park , K. Kim , Adv. Healthcare Mater. 2023 , 12 , 2203172 . 10.1002/adhm.202203172 PMC11469032 36971091
129 D. Qin , Y. Xia , G. M. Whitesides , Nat. Protoc. 2010 , 5 , 491 . 20203666 10.1038/nprot.2009.234
130 N. Convery , N. Gadegaard , Micro Nano Eng. 2019 , 2 , 76 .
131 D. Sticker , M. Rothbauer , S. Lechner , M.‐T. Hehenberger , P. Ertl , Lab Chip 2015 , 15 , 4542 . 26524977 10.1039/c5lc01028d
132 K. Raj M , S. Chakraborty , J. Appl. Polym. Sci. 2020 , 137 , 48958 .
133 D. Qin , Y. Xia , G. M. Whitesides , Adv. Mater. 1996 , 8 , 917 .
134 E. S. Bishop , S. Mostafa , M. Pakvasa , H. H. Luu , M. J. Lee , J. M. Wolf , G. A. Ameer , T.‐C. He , R. R. Reid , Genes Dis. 2017 , 4 , 185 . 29911158 10.1016/j.gendis.2017.10.002 PMC6003668
135 H.‐G. Yi , H. Kim , J. Kwon , Y.‐J. Choi , J. Jang , D.‐W. Cho , Signal Transduction Targeted Ther. 2021 , 6 , 177 . 10.1038/s41392-021-00566-8 PMC8119699 33986257
136 T. W. Odom , J. C. Love , D. B. Wolfe , K. E. Paul , G. M. Whitesides , Langmuir 2002 , 18 , 5314 .
137 M. D. Sarker , S. Naghieh , N. K. Sharma , X. Chen , J. Pharm. Anal. 2018 , 8 , 277 . 30345141 10.1016/j.jpha.2018.08.005 PMC6190507
138 E. Kim , Y. Xia , G. M. Whitesides , J. Am. Chem. Soc. 1996 , 118 , 5722 .
139 D. B. Weibel , W. R. DiLuzio , G. M. Whitesides , Nat. Rev. Microbiol. 2007 , 5 , 209 . 17304250 10.1038/nrmicro1616
140 J. Rogal , K. Schlünder , P. Loskill , ACS Biomater. Sci. Eng. 2022 , 8 , 4643 . 35760397 10.1021/acsbiomaterials.1c01536 PMC9667877
141 D. A. Ferreira , M. Rothbauer , J. P. Conde , P. Ertl , C. Oliveira , P. L. Granja , Adv. Sci. 2021 , 8 , 2003273 . 10.1002/advs.202003273 PMC8061392 33898174
142 Q. Yang , Q. Lian , F. Xu , Biomicrofluidics 2017 , 11 , 031301 . 28529670 10.1063/1.4982945 PMC5423813
143 S. Knowlton , S. Anand , T. Shah , S. Tasoglu , Trends Neurosci. 2018 , 41 , 31 . 29223312 10.1016/j.tins.2017.11.001
144 H. Lee , D.‐W. Cho , Lab Chip 2016 , 16 , 2618 . 27302471 10.1039/c6lc00450d
145 M. Rothbauer , C. Eilenberger , S. Spitz , B. E. M. Bachmann , S. R. A. Kratz , E. I. Reihs , R. Windhager , S. Toegel , P. Ertl , Front. Bioeng. Biotechnol. 2022 , 10 , 837087 . 35252144 10.3389/fbioe.2022.837087 PMC8891807
146 J. Lai , C. Wang , M. Wang , Appl. Phys. Rev. 2021 , 8 , 021322 .
147 Q. Tang , X. Li , C. Lai , L. Li , H. Wu , Y. Wang , X. Shi , Bioact. Mater. 2021 , 6 , 169 . 32913926 10.1016/j.bioactmat.2020.07.016 PMC7453124
148 F. Conceição , D. M. Sousa , J. Loessberg‐Zahl , A. R. Vollertsen , E. Neto , K. Søe , J. Paredes , A. Leferink , M. Lamghari , Mater. Today Bio 2022 , 13 , 100219 . 10.1016/j.mtbio.2022.100219 PMC8857466 35243294
149 L. C. Hofbauer , A. Bozec , M. Rauner , F. Jakob , S. Perner , K. Pantel , Nat. Rev. Clin. Oncol. 2021 , 18 , 488 . 33875860 10.1038/s41571-021-00499-9
150 S. Casimiro , T. A. Guise , J. Chirgwin , Spec. Issue Bone Endocrinol. 2009 , 310 , 71 . 10.1016/j.mce.2009.07.004 19616059
151 M. Nouri‐Goushki , A. Sharma , L. Sasso , S. Zhang , B. C. J. Van der Eerden , U. Staufer , L. E. Fratila‐Apachitei , A. A. Zadpoor , ACS Biomater. Sci. Eng. 2019 , 5 , 6127 . 33405666 10.1021/acsbiomaterials.9b01155
152 A. Sorkio , L. Koch , L. Koivusalo , A. Deiwick , S. Miettinen , B. Chichkov , H. Skottman , Biomaterials 2018 , 171 , 57 . 29684677 10.1016/j.biomaterials.2018.04.034
153 N. A. Sears , D. R. Seshadri , P. S. Dhavalikar , E. Cosgriff‐Hernandez , Tissue Eng., Part B 2016 , 22 , 298 . 10.1089/ten.TEB.2015.0464 26857350
154 X. Ji , H.‐P. Bei , G. Zhong , H. Shao , X. He , X. Qian , Y. Zhang , X. Zhao , Small 2023 , 19 , 2207606 . 10.1002/smll.202207606 37605335
155 Y. P. Singh , A. Bandyopadhyay , B. B. Mandal , ACS Appl. Mater. Interfaces 2019 , 11 , 33684 . 31453678 10.1021/acsami.9b11644
156 N. P. Macdonald , J. M. Cabot , P. Smejkal , R. M. Guijt , B. Paull , M. C. Breadmore , Anal. Chem. 2017 , 89 , 3858 . 28281349 10.1021/acs.analchem.7b00136
157 F. Conceição , D. M. Sousa , J. Loessberg‐Zahl , A. R. Vollertsen , E. Neto , K. Søe , J. Paredes , A. Leferink , M. Lamghari , Mater. Today Bio 2022 , 13 , 100219 . 10.1016/j.mtbio.2022.100219 PMC8857466 35243294
158 F. Conceição , D. M. Sousa , J. Loessberg‐Zahl , A. R. Vollertsen , E. Neto , K. Søe , J. Paredes , A. Leferink , M. Lamghari , Mater. Today Bio 2022 , 13 , 100219 . 10.1016/j.mtbio.2022.100219 PMC8857466 35243294
159 J. Lai , M. Wang , J. Mater. Res. 2023 , 38 , 4692 .
160 X. Kuang , D. J. Roach , J. Wu , C. M. Hamel , Z. Ding , T. Wang , M. L. Dunn , H. J. Qi , Adv. Funct. Mater. 2019 , 29 , 1805290 .
161 O. Shoshani , D. Zipori , BBA‐Gene Regulator Mechanism. 2015 , 1849 , 371 . 10.1016/j.bbagrm.2014.07.006 25038585
162 M. B. Esch , H. Ueno , D. R. Applegate , M. L. Shuler , Lab Chip 2016 , 16 , 2719 . 27332143 10.1039/c6lc00461j
163 H. E. Abaci , K. Gledhill , Z. Guo , A. M. Christiano , M. L. Shuler , Lab Chip 2015 , 15 , 882 . 25490891 10.1039/c4lc00999a PMC4305008
164 J. R. Lorsch , F. S. Collins , J. Lippincott‐Schwartz , Science 2014 , 346 , 1452 . 25525228 10.1126/science.1259110 PMC5101941
165 J. A. Thomson , J. Itskovitz‐Eldor , S. S. Shapiro , M. A. Waknitz , J. J. Swiergiel , V. S. Marshall , J. M. Jones , Science 1998 , 282 , 1145 . 9804556 10.1126/science.282.5391.1145
166 B. Lo , L. Parham , Endocr. Rev. 2009 , 30 , 204 . 19366754 10.1210/er.2008-0031 PMC2726839
167 S. Hombach‐Klonisch , S. Panigrahi , I. Rashedi , A. Seifert , E. Alberti , P. Pocar , M. Kurpisz , K. Schulze‐Osthoff , A. Mackiewicz , M. Los , J. Mol. Med. 2008 , 86 , 1301 . 18629466 10.1007/s00109-008-0383-6 PMC2954191
168 S. H. Orkin , L. I. Zon , Cell 2008 , 132 , 631 . 18295580 10.1016/j.cell.2008.01.025 PMC2628169
169 K. Takahashi , K. Tanabe , M. Ohnuki , M. Narita , T. Ichisaka , K. Tomoda , S. Yamanaka , Cell 2007 , 131 , 861 . 18035408 10.1016/j.cell.2007.11.019
170 P. W. Burridge , Y. F. Li , E. Matsa , H. Wu , S.‐G. Ong , A. Sharma , A. Holmström , A. C. Chang , M. J. Coronado , A. D. Ebert , J. W. Knowles , M. L. Telli , R. M. Witteles , H. M. Blau , D. Bernstein , R. B. Altman , J. C. Wu , Nat. Med. 2016 , 22 , 547 . 27089514 10.1038/nm.4087 PMC5086256
171 C.‐L. Wu , A. Dicks , N. Steward , R. Tang , D. B. Katz , Y.‐R. Choi , F. Guilak , Nat. Commun. 2021 , 12 , 362 . 33441552 10.1038/s41467-020-20598-y PMC7806634
172 T. Nakajima , A. Nakahata , N. Yamada , K. Yoshizawa , T. M. Kato , M. Iwasaki , C. Zhao , H. Kuroki , M. Ikeya , Nat. Commun. 2021 , 12 , 5012 . 34408142 10.1038/s41467-021-25328-6 PMC8373964
173 D. Zujur , K. Kanke , S. Onodera , S. Tani , J. Lai , T. Azuma , X. Xin , A. C. Lichtler , D. W. Rowe , T. Saito , S. Tanaka , H. Masaki , H. Nakauchi , U. Chung , H. Hojo , S. Ohba , Regener. Ther. 2020 , 14 , 19 . 10.1016/j.reth.2019.12.010 PMC6965656 31988991
174 F. Bianchi , M. Malboubi , Y. Li , J. H. George , A. Jerusalem , F. Szele , M. S. Thompson , H. Ye , Stem Cell Res. 2018 , 32 , 126 . 30278374 10.1016/j.scr.2018.09.006
175 J. Colter , K. Murari , J. Biernaskie , M. S. Kallos , npj Regener. Med. 2021 , 6 , 72 . 10.1038/s41536-021-00183-7 PMC8560749 34725374
176 L. Rao , Y. Qian , A. Khodabukus , T. Ribar , N. Bursac , Nat. Commun. 2018 , 9 , 126 . 29317646 10.1038/s41467-017-02636-4 PMC5760720
177 A. J. C. Bloor , A. Patel , J. E. Griffin , M. H. Gilleece , R. Radia , D. T. Yeung , D. Drier , L. S. Larson , G. I. Uenishi , D. Hei , K. Kelly , I. Slukvin , J. E. J. Rasko , Nat. Med. 2020 , 26 , 1720 . 32929265 10.1038/s41591-020-1050-x
178 E. M. Ahmed , J. Adv. Res. 2015 , 6 , 105 . 25750745 10.1016/j.jare.2013.07.006 PMC4348459
179 J. A. Terrell , C. G. Jones , G. K. M. Kabandana , C. Chen , J. Mater. Chem. B 2020 , 8 , 6667 . 32567628 10.1039/d0tb00718h
180 M. C. Catoira , L. Fusaro , D. Di Francesco , M. Ramella , F. Boccafoschi , J. Mater. Sci.: Mater. Med. 2019 , 30 , 115 . 31599365 10.1007/s10856-019-6318-7 PMC6787111
181 Y. Jiang , Y. Yang , X. Zheng , Y. Yi , X. Chen , Y. Li , D. Sun , L. Zhang , NPG Asia Mater. 2020 , 12 , 18 .
182 C. B. Goy , R. E. Chaile , R. E. Madrid , React. Funct. Polym. 2019 , 145 , 104314 .
183 M. M. Smoak , A. Han , E. Watson , A. Kishan , K. J. Grande‐Allen , E. Cosgriff‐Hernandez , A. G. Mikos , Tissue Eng., Part C 2019 , 25 , 276 . 10.1089/ten.tec.2018.0339 PMC6535957 30909819
184 Z. Li , S. Xiang , E. N. Li , M. R. Fritch , P. G. Alexander , H. Lin , R. S. Tuan , in Organotypic Models Drug Development (Eds: M. Schäfer‐Korting , S. Stuchi Maria‐Engler , R. Landsiedel ), Springer International Publishing , Cham 2021 , pp. 235 – 268 .
185 G. M. Cunniffe , P. J. Díaz‐Payno , E. J. Sheehy , S. E. Critchley , H. V. Almeida , P. Pitacco , S. F. Carroll , O. R. Mahon , A. Dunne , T. J. Levingstone , C. J. Moran , R. T. Brady , F. J. O'Brien , P. A. J. Brama , D. J. Kelly , Biomaterials 2019 , 188 , 63 . 30321864 10.1016/j.biomaterials.2018.09.044
186 K. Paek , S. Kim , S. Tak , M. K. Kim , J. Park , S. Chung , T. H. Park , J. A. Kim , Bioeng. Transl. Med. 2023 , 8 , 10313 . 10.1002/btm2.10313 PMC9842054 36684077
187 P. Alamán‐Díez , E. García‐Gareta , M. Arruebo , M. Á. Pérez , J. Biomed. Mater. Res., Part A 2023 , 111 , 88 . 10.1002/jbm.a.37448 PMC9828068 36205241
188 K. Corral‐Nájera , G. Chauhan , S. O. Serna‐Saldívar , S. O. Martínez‐Chapa , M. M. Aeinehvand , Microsyst. Nanoeng. 2023 , 9 , 107 . 37649779 10.1038/s41378-023-00579-z PMC10462672
189 J. Nie , J. Fu , Y. He , Small 2020 , 16 , 2003797 .
190 D. Kang , J. H. Kim , Y. H. Jeong , J.‐Y. Kwak , S. Yoon , S. Jin , Biofabrication 2016 , 8 , 025008 . 27186924 10.1088/1758-5090/8/2/025008
191 G. Agrawal , A. Aung , S. Varghese , Lab Chip 2017 , 17 , 3447 . 28871305 10.1039/c7lc00512a PMC6296378
192 S. Wu , X. Wu , X. Wang , J. Su , J. Mater. Sci. Technol. 2023 , 136 , 21 .
193 A. Sharipol , M. L. Lesch , C. A. Soto , B. J. Frisch , Front. Bioeng. Biotechnol. 2022 , 10 , 855777 . 35795163 10.3389/fbioe.2022.855777 PMC9252162
194 M. Rothbauer , G. Höll , C. Eilenberger , S. R. A. Kratz , B. Farooq , P. Schuller , I. Olmos Calvo , R. A. Byrne , B. Meyer , B. Niederreiter , S. Küpcü , F. Sevelda , J. Holinka , O. Hayden , S. F. Tedde , H. P. Kiener , P. Ertl , Lab Chip 2020 , 20 , 1461 . 32219235 10.1039/c9lc01097a
195 A. Marturano‐Kruik , M. M. Nava , K. Yeager , A. Chramiec , L. Hao , S. Robinson , E. Guo , M. T. Raimondi , G. Vunjak‐Novakovic , Proc. Natl. Acad. Sci. USA 2018 , 115 , 1256 . 29363599 10.1073/pnas.1714282115 PMC5819403
196 C. M. Leung , P. de Haan , K. Ronaldson‐Bouchard , G.‐A. Kim , J. Ko , H. S. Rho , Z. Chen , P. Habibovic , N. L. Jeon , S. Takayama , M. L. Shuler , G. Vunjak‐Novakovic , O. Frey , E. Verpoorte , Y.‐C. Toh , Nat. Rev. Methods Primers 2022 , 2 , 33 .
197 H. Kutluk , E. E. Bastounis , I. Constantinou , Adv. Healthc. Mater. 2023 , 12 , 2203256 . 37018430 10.1002/adhm.202203256 PMC11468608
198 S. Cho , S. Lee , S. I. Ahn , Biomed. Eng. Lett. 2023 , 13 , 97 . 36620430 10.1007/s13534-022-00258-4 PMC9806813
199 S. Hao , L. Ha , G. Cheng , Y. Wan , Y. Xia , D. M. Sosnoski , A. M. Mastro , S.‐Y. Zheng , Small 2018 , 14 , 1702787 . 10.1002/smll.201702787 29399951
200 Y. Song , Y. Zhang , P. E. Bernard , J. M. Reuben , N. T. Ueno , R. B. Arlinghaus , Y. Zu , L. Qin , Nat. Commun. 2012 , 3 , 1283 . 23250413 10.1038/ncomms2292 PMC4266136
201 B. Zhao , J. S. Moore , D. J. Beebe , Science 2001 , 291 , 1023 . 11161212 10.1126/science.291.5506.1023
202 P. Zhang , N. Shao , L. Qin , Adv. Mater. 2021 , 33 , 2005944 . 10.1002/adma.202005944 34270839
203 O. Y. F. Henry , R. Villenave , M. J. Cronce , W. D. Leineweber , M. A. Benz , D. E. Ingber , Lab Chip 2017 , 17 , 2264 . 28598479 10.1039/c7lc00155j PMC5526048
204 D. C. Duffy , J. C. McDonald , O. J. A. Schueller , G. M. Whitesides , Anal. Chem. 1998 , 70 , 4974 . 21644679 10.1021/ac980656z
205 P. M. van Midwoud , A. Janse , M. T. Merema , G. M. M. Groothuis , E. Verpoorte , Anal. Chem. 2012 , 84 , 3938 . 22444457 10.1021/ac300771z
206 K. Domansky , D. C. Leslie , J. McKinney , J. P. Fraser , J. D. Sliz , T. Hamkins‐Indik , G. A. Hamilton , A. Bahinski , D. E. Ingber , Lab Chip 2013 , 13 , 3956 . 23954953 10.1039/c3lc50558h PMC3877836
207 M. D. Borysiak , K. S. Bielawski , N. J. Sniadecki , C. F. Jenkel , B. D. Vogt , J. D. Posner , Lab Chip 2013 , 13 , 2773 . 23670166 10.1039/c3lc50426c PMC3799950
208 D. Stamatialis , Artif. Organs 2018 , 42 , 1104 .
209 T. Pasman , D. Grijpma , D. Stamatialis , A. Poot , J. R. Soc., Interface 2018 , 15 , 20180351 . 30045892 10.1098/rsif.2018.0351 PMC6073644
210 A. Tajeddin , N. Mustafaoglu , Micromachines 2021 , 12 , 1443 . 34945293 10.3390/mi12121443 PMC8707724
211 W. Zhong , W. Zhang , S. Wang , J. Qin , PLoS One 2013 , 8 , 61283 . 10.1371/journal.pone.0061283 PMC3630136 23637803
212 M. A. Ortega , X. Fernández‐Garibay , A. G. Castaño , F. De Chiara , A. Hernández‐Albors , J. Balaguer‐Trias , J. Ramón‐Azcón , Lab Chip 2019 , 19 , 2568 . 31243422 10.1039/c9lc00285e
213 S. Brown , J. Pistiner , I. M. Adjei , B. Sharma , Mol. Pharmaceutics 2019 , 16 , 469 . 10.1021/acs.molpharmaceut.7b00484 PMC7147813 28669194
214 J. Wu , Z. Zhu , W. Liu , Y. Zhang , Y. Kang , J. Liu , C. Hu , R. Wang , M. Zhang , L. Chen , L. Shao , ACS Nano 2022 , 16 , 15627 . 36121682 10.1021/acsnano.2c05317
215 C. W. Shields IV , L. L.‐W. Wang , M. A. Evans , S. Mitragotri , Adv. Mater. 2020 , 32 , 1901633 . 10.1002/adma.201901633 31250498
216 J. A. Kulkarni , D. Witzigmann , S. B. Thomson , S. Chen , B. R. Leavitt , P. R. Cullis , R. van der Meel , Nat. Nanotechnol. 2021 , 16 , 630 . 34059811 10.1038/s41565-021-00898-0
217 D. J. Irvine , E. L. Dane , Nat. Rev. Immunol. 2020 , 20 , 321 . 32005979 10.1038/s41577-019-0269-6 PMC7536618
218 P. Makvandi , M. Chen , R. Sartorius , A. Zarrabi , M. Ashrafizadeh , F. Dabbagh Moghaddam , J. Ma , V. Mattoli , F. R. Tay , Nano Today 2021 , 40 , 101279 . 34518771 10.1016/j.nantod.2021.101279 PMC8425779
219 Q. Qiao , X. Liu , T. Yang , K. Cui , L. Kong , C. Yang , Z. Zhang , Acta Pharm. Sin. B 2021 , 11 , 3060 . 33977080 10.1016/j.apsb.2021.04.023 PMC8102084
220 X. Li , B. Dai , J. Guo , L. Zheng , Q. Guo , J. Peng , J. Xu , L. Qin , Nano‐Micro Lett. 2021 , 13 , 149 . 10.1007/s40820-021-00670-y PMC8222488 34160733
221 M. J. Mitchell , M. M. Billingsley , R. M. Haley , M. E. Wechsler , N. A. Peppas , R. Langer , Nat. Rev. Drug Discovery 2021 , 20 , 101 . 33277608 10.1038/s41573-020-0090-8 PMC7717100
222 Q. Wang , X. Qin , J. Fang , X. Sun , Acta Pharm. Sin. B 2021 , 11 , 1158 . 34094826 10.1016/j.apsb.2021.03.013 PMC8144894
223 R. Deng , R. Zhao , Z. Zhang , Y. Chen , M. Yang , Y. Lin , J. Ye , N. Li , H. Qin , X. Yan , J. Shi , F. Yuan , S. Song , Z. Xu , Y. Song , J. Fu , B. Xu , G. Nie , J.‐K. Yu , Sci. Transl. Med. 2024 , 16 , 9751 . 10.1126/scitranslmed.adh9751 38381849
224 M. Corr , Nat. Clin. Pract. Rheumatol. 2008 , 4 , 550 . 18820702 10.1038/ncprheum0904
225 M. Bottini , K. Bhattacharya , B. Fadeel , A. Magrini , N. Bottini , N. Rosato , Nanomed.: Nanotechnol. Biol. Med. 2016 , 12 , 255 . 10.1016/j.nano.2015.09.013 26707894
226 J. Pajarinen , T. Lin , E. Gibon , Y. Kohno , M. Maruyama , K. Nathan , L. Lu , Z. Yao , S. B. Goodman , Biomater. 2019 , 196 , 80 . 10.1016/j.biomaterials.2017.12.025 PMC6028312 29329642
227 H. Liang , C. Jin , L. Ma , X. Feng , X. Deng , S. Wu , X. Liu , C. Yang , ACS Appl. Mater. Interfaces 2019 , 11 , 41758 . 31610117 10.1021/acsami.9b16848
228 P. Dosta , I. Tamargo , V. Ramos , S. Kumar , D. W. Kang , S. Borrós , H. Jo , Adv. Healthcare Mater. 2021 , 10 , 2001894 . 10.1002/adhm.202001894 PMC8277885 33448151
229 F. E. Freeman , P. Dosta , L. C. Shanley , N. Ramirez Tamez , C. J. Riojas Javelly , O. R. Mahon , D. J. Kelly , N. Artzi , Adv. Mater. 2023 , 35 , 2207877 . 10.1002/adma.202207877 36994935
230 Z. Li , M. Q. Hassan , M. Jafferji , R. I. Aqeilan , R. Garzon , C. M. Croce , A. J. van Wijnen , J. L. Stein , G. S. Stein , J. B. Lian , J. Biol. Chem. 2009 , 284 , 15676 . 19342382 10.1074/jbc.M809787200 PMC2708864
231 J. Shin , H. G. Shim , T. Hwang , H. Kim , S.‐H. Kang , Y.‐S. Dho , S.‐H. Park , S. J. Kim , C.‐K. Park , Cancer Cell Int. 2017 , 17 , 104 . 29176935 10.1186/s12935-017-0476-9 PMC5693545
232 Y. Geng , H. Duan , L. Xu , N. Witman , B. Yan , Z. Yu , H. Wang , Y. Tan , L. Lin , D. Li , S. Bai , R. Fritsche‐Danielson , J. Yuan , K. Chien , M. Wei , W. Fu , Commun. Biol. 2021 , 4 , 82 . 33469143 10.1038/s42003-020-01606-9 PMC7815925
233 J. Fang , J. Sia , J. Soto , P. Wang , L. K. Li , Y.‐Y. Hsueh , R. Sun , K. F. Faull , J. G. Tidball , S. Li , Nat. Biomed. Eng. 2021 , 5 , 864 . 33737730 10.1038/s41551-021-00696-y PMC8387336
234 B. D. Cosgrove , P. M. Gilbert , E. Porpiglia , F. Mourkioti , S. P. Lee , S. Y. Corbel , M. E. Llewellyn , S. L. Delp , H. M. Blau , Nat. Med. 2014 , 20 , 255 . 24531378 10.1038/nm.3464 PMC3949152
235 H. M. Blau , B. D. Cosgrove , A. T. V. Ho , Nat. Med. 2015 , 21 , 854 . 26248268 10.1038/nm.3918 PMC4731230
236 J. K. Ichida , J. Blanchard , K. Lam , E. Y. Son , J. E. Chung , D. Egli , K. M. Loh , A. C. Carter , F. P. Di Giorgio , K. Koszka , D. Huangfu , H. Akutsu , D. R. Liu , L. L. Rubin , K. Eggan , Cell Stem Cell 2009 , 5 , 491 . 19818703 10.1016/j.stem.2009.09.012 PMC3335195
237 S. Jin , Y. Wang , X. Wu , Z. Li , L. Zhu , Y. Niu , Y. Zhou , Y. Liu , Adv. Mater. 2023 , 35 , 2211602 . 10.1002/adma.202211602 36779444
238 Y. Lin , Q. Li , L. Wang , Q. Guo , S. Liu , S. Zhu , Y. Sun , Y. Fan , Y. Sun , H. Li , X. Tian , D. Luo , S. Shi , Int. J. Oral Sci. 2022 , 14 , 51 . 36316311 10.1038/s41368-022-00199-9 PMC9622686
239 S. Zhang , H. Zhou , N. Kong , Z. Wang , H. Fu , Y. Zhang , Y. Xiao , W. Yang , F. Yan , Bioact. Mater. 2021 , 6 , 3288 . 33778205 10.1016/j.bioactmat.2021.02.035 PMC7970259
240 Y. Wang , A. Tay , ACS Nano 2023 , 17 , 9850 . 37267453 10.1021/acsnano.3c02798
241 R. N. Judson , F. M. V. Rossi , npj Regener. Med. 2020 , 5 , 10 . 10.1038/s41536-020-0094-3 PMC7214464 32411395
242 C. M. Kolf , E. Cho , R. S. Tuan , Arthritis Res. Ther. 2007 , 9 , 204 . 17316462 10.1186/ar2116 PMC1860068
243 D. Baksh , L. Song , R. S. Tuan , J. Cell. Mol. Med. 2004 , 8 , 301 . 15491506 10.1111/j.1582-4934.2004.tb00320.x PMC6740223
244 A. Markov , L. Thangavelu , S. Aravindhan , A. O. Zekiy , M. Jarahian , M. S. Chartrand , Y. Pathak , F. Marofi , S. Shamlou , A. Hassanzadeh , Stem Cell Res. Ther. 2021 , 12 , 192 . 33736695 10.1186/s13287-021-02265-1 PMC7971361
245 M. B. Murphy , K. Moncivais , A. I. Caplan , Exp. Mol. Med. 2013 , 45 , 54 . 10.1038/emm.2013.94 PMC3849579 24232253
246 G. Copp , K. P. Robb , S. Viswanathan , Cell. Mol. Immunol. 2023 , 20 , 626 . 37095295 10.1038/s41423-023-01020-1 PMC10229578
247 X. Wei , X. Yang , Z. Han , F. Qu , L. Shao , Y. Shi , Acta Pharmacol. Sin. 2013 , 34 , 747 . 23736003 10.1038/aps.2013.50 PMC4002895
248 Q. Li , R. Xu , K. Lei , Q. Yuan , Bone Res. 2022 , 10 , 61 . 36261411 10.1038/s41413-022-00235-8 PMC9581935
249 Y. Wang , D. Wang , Y. Guo , J. Liu , J. Pan , Regener. Ther. 2020 , 15 , 285 . 10.1016/j.reth.2020.11.002 PMC7770413 33426231
250 C. Loebel , J. A. Burdick , Cell Stem Cell 2018 , 22 , 325 . 29429944 10.1016/j.stem.2018.01.014 PMC5834383
251 Z. Chen , J. Wei , J. Zhu , W. Liu , J. Cui , H. Li , F. Chen , Stem Cell Res. Ther. 2016 , 7 , 70 . 27150539 10.1186/s13287-016-0328-x PMC4858869
252 E. D. Tichy , F. Mourkioti , Cell Stem Cell 2018 , 23 , 462 . 30290174 10.1016/j.stem.2018.09.006
253 P. Kangari , T. Talaei‐Khozani , I. Razeghian‐Jahromi , M. Razmkhah , Stem Cell Res. Ther. 2020 , 11 , 492 . 33225992 10.1186/s13287-020-02001-1 PMC7681994
254 M.‐J. Chung , J.‐Y. Son , S. Park , S.‐S. Park , K. Hur , S.‐H. Lee , E.‐J. Lee , J.‐K. Park , I.‐H. Hong , T.‐H. Kim , K.‐S. Jeong , Int. J. Semant. Comput. 2020 , 14 , 150 .
255 M. Ma , F. Zou , B. Abudureheman , F. Han , G. Xu , Y. Xie , K. Qiao , J. Peng , Y. Guan , H. Meng , Y. Zheng , ACS Nano 2023 , 17 , 6373 . 36961738 10.1021/acsnano.2c10995
256 X. Yan , B. Yang , Y. Chen , Y. Song , J. Ye , Y. Pan , B. Zhou , Y. Wang , F. Mao , Y. Dong , D. Liu , J. Yu , Adv. Mater. 2021 , 33 , 2104758 . 10.1002/adma.202104758 34657320
257 N. Ren , N. Liang , M. Dong , Z. Feng , L. Meng , C. Sun , A. Wang , X. Yu , W. Wang , J. Xie , C. Liu , H. Liu , Small 2022 , 18 , 2202485 . 10.1002/smll.202202485 35633288
258 Y. Lu , J. Chen , L. Li , Y. Cao , Y. Zhao , X. Nie , C. Ding , J. Nanobiotechnol. 2022 , 20 , 89 . 10.1186/s12951-022-01297-w PMC8858465 35183192
259 Y. Lu , Z. Li , L. Li , J. Chen , X. Xu , Z. Lin , T. Zhang , Y. Zhu , C. Ding , C. Mao , Biomaterials 2022 , 283 , 121474 . 35316662 10.1016/j.biomaterials.2022.121474
260 Y. Cai , C. Wu , Q. Ou , M. Zeng , S. Xue , J. Chen , Y. Lu , C. Ding , Bioact. Mater. 2023 , 19 , 444 . 35574050 10.1016/j.bioactmat.2022.04.021 PMC9079106
261 S. W. Ferguson , J. Wang , C. J. Lee , M. Liu , S. Neelamegham , J. M. Canty , J. Nguyen , Sci. Rep. 2018 , 8 , 1419 . 29362496 10.1038/s41598-018-19581-x PMC5780426
262 X. Yao , W. Wei , X. Wang , L. Chenglin , M. Björklund , H. Ouyang , Biomaterials 2019 , 224 , 119492 . 31557588 10.1016/j.biomaterials.2019.119492
263 J. Dai , Y. Su , S. Zhong , L. Cong , B. Liu , J. Yang , Y. Tao , Z. He , C. Chen , Y. Jiang , Signal Transduction Targeted Ther. 2020 , 5 , 145 . 10.1038/s41392-020-00261-0 PMC7406508 32759948
264 C.‐S. Lee , J. Fan , H. S. Hwang , S. Kim , C. Chen , M. Kang , T. Aghaloo , A. W. James , M. Lee , Nano Lett. 2023 , 23 , 1202 . 36762874 10.1021/acs.nanolett.2c04159 PMC10106420
265 Y. Wei , M. Shi , J. Zhang , X. Zhang , K. Shen , R. Wang , R. J. Miron , Y. Xiao , Y. Zhang , Adv. Funct. Mater. 2020 , 30 , 2000015 .
266 S. Ansari , K. Ito , S. Hofmann , ACS Omega 2022 , 7 , 12724 . 35474849 10.1021/acsomega.1c07225 PMC9026015
267 R. J. Miron , J. Chai , P. Zhang , Y. Li , Y. Wang , C. F. de A. B. Mourão , A. Sculean , M. Fujioka Kobayashi , Y. Zhang , Clin. Oral Investig. 2020 , 24 , 2819 . 10.1007/s00784-019-03147-w 31788748
268 A. Marote , F. G. Teixeira , B. Mendes‐Pinheiro , A. J. Salgado , Front. Pharmacol. 2016 , 7 , 00231 . 10.3389/fphar.2016.00231 PMC4971062 27536241
269 Z. Xiong , H. Lin , H. Li , B. Zou , B. Xie , Y. Yu , L. He , T. Chen , Adv. Funct. Mater. 2023 , 33 , 2212970 .
270 Y. Yan , A. Lu , Y. Dou , Z. Zhang , X.‐Y. Wang , L. Zhai , L.‐Y. Ai , M.‐Z. Du , L.‐X. Jiang , Y.‐J. Zhu , Y.‐J. Shi , X.‐Y. Liu , D. Jiang , J.‐C. Wang , Adv. Sci. 2023 , 10 , 2207490 . 10.1002/advs.202207490 PMC10104675 36748885
271 J. Fu , Y. Li , Y. Zhang , Y. Liang , Y. Zheng , Z. Li , S. Zhu , C. Li , Z. Cui , S. Wu , Adv. Mater. 2021 , 33 , 2102926 . 10.1002/adma.202102926 34396595
272 Y. Qu , B. Chu , X. Wei , Y. Chen , Y. Yang , D. Hu , J. Huang , F. Wang , M. Chen , Y. Zheng , Z. Qian , Adv. Mater. 2022 , 34 , 2107883 . 10.1002/adma.202107883 34877715
273 W. Sun , K. Ge , Y. Jin , Y. Han , H. Zhang , G. Zhou , X. Yang , D. Liu , H. Liu , X.‐J. Liang , J. Zhang , ACS Nano 2019 , 13 , 7556 . 31259530 10.1021/acsnano.9b00097
274 Y. Xue , W. Niu , M. Wang , M. Chen , Y. Guo , B. Lei , ACS Nano 2020 , 14 , 442 . 31702885 10.1021/acsnano.9b06145
275 D.‐K. Kim , G. Bandara , Y.‐E. Cho , H. D. Komarow , D. R. Donahue , B. Karim , M.‐C. Baek , H. M. Kim , D. D. Metcalfe , A. Olivera , Nat. Commun. 2021 , 12 , 2527 . 33953168 10.1038/s41467-021-22754-4 PMC8100305
276 Z. Yang , X. Liu , F. Zhao , M. Yao , Z. Lin , Z. Yang , C. Liu , Y. Liu , X. Chen , C. Du , Biomaterials 2022 , 283 , 121438 . 35220020 10.1016/j.biomaterials.2022.121438
277 B. D. McNally , D. F. Ashley , L. Hänschke , H. N. Daou , N. T. Watt , S. A. Murfitt , A. D. V. MacCannell , A. Whitehead , T. S. Bowen , F. W. B. Sanders , M. Vacca , K. K. Witte , G. R. Davies , R. Bauer , J. L. Griffin , L. D. Roberts , Nat. Commun. 2022 , 13 , 1748 . 35365625 10.1038/s41467-022-29363-9 PMC8975934
278 K. Feng , X. Xie , J. Yuan , L. Gong , Z. Zhu , J. Zhang , H. Li , Y. Yang , Y. Wang , J. Extracell. Vesicles 2021 , 10 , 12160 . 10.1002/jev2.12160 PMC8559985 34724347
279 S. Ma , X. Xing , H. Huang , X. Gao , X. Xu , J. Yang , C. Liao , X. Zhang , J. Liu , W. Tian , L. Liao , Cell Metab. 2023 , 35 , 2028 . 37939660 10.1016/j.cmet.2023.10.013
280 K. Wang , N. Frey , A. Garcia , K. Man , Y. Yang , A. Gualerzi , Z. J. Clemens , M. Bedoni , P. R. LeDuc , F. Ambrosio , ACS Nano 2023 , 17 , 19640 . 37797946 10.1021/acsnano.3c02269 PMC10603813
281 J. Zhang , D. Tong , H. Song , R. Ruan , Y. Sun , Y. Lin , J. Wang , L. Hou , J. Dai , J. Ding , H. Yang , Adv. Mater. 2022 , 34 , 2202044 . 10.1002/adma.202202044 35785450
282 C. Deng , Q. Zhou , M. Zhang , T. Li , H. Chen , C. Xu , Q. Feng , X. Wang , F. Yin , Y. Cheng , C. Wu , Adv. Sci. 2022 , 9 , 2105727 . 10.1002/advs.202105727 PMC9036007 35182053
283 N. Su , C. Villicana , D. Barati , P. Freeman , Y. Luo , F. Yang , Adv. Mater. 2023 , 35 , 2208781 . 10.1002/adma.202208781 PMC10057912 36560890
284 Y. Cao , J. Tan , H. Zhao , T. Deng , Y. Hu , J. Zeng , J. Li , Y. Cheng , J. Tang , Z. Hu , K. Hu , B. Xu , Z. Wang , Y. Wu , P. E. Lobie , S. Ma , Nat. Commun. 2022 , 13 , 7463 . 36460667 10.1038/s41467-022-35183-8 PMC9718784
285 X. Xue , H. Zhang , H. Liu , S. Wang , J. Li , Q. Zhou , X. Chen , X. Ren , Y. Jing , Y. Deng , Z. Geng , X. Wang , J. Su , Adv. Funct. Mater. 2022 , 32 , 2202470 .
286 S. Dong , Y. Chen , L. Yu , K. Lin , X. Wang , Adv. Funct. Mater. 2020 , 30 , 1907071 .
287 X. Zhang , J. Fan , C.‐S. Lee , S. Kim , C. Chen , T. Aghaloo , M. Lee , Adv. Funct. Mater. 2020 , 30 , 1909218 . 32952492 10.1002/adfm.201909218 PMC7494204
288 S. Wang , Z. Yao , X. Zhang , J. Li , C. Huang , Y. Ouyang , Y. Qian , C. Fan , Adv. Sci. 2022 , 9 , 2202542 . 10.1002/advs.202202542 PMC9631092 36000796
289 M. A. Barajaa , L. S. Nair , C. T. Laurencin , Regener. Eng. Transl. Med. 2020 , 6 , 451 . 10.1007/s40883-019-00132-3 PMC7747886 33344758
290 Y. Zhang , X. Liu , L. Zeng , J. Zhang , J. Zuo , J. Zou , J. Ding , X. Chen , Adv. Funct. Mater. 2019 , 29 , 1903279 .
291 J. Raphel , M. Holodniy , S. B. Goodman , S. C. Heilshorn , Biomaterials 2016 , 84 , 301 . 26851394 10.1016/j.biomaterials.2016.01.016 PMC4883578
292 G. Narayanan , V. N. Vernekar , E. L. Kuyinu , C. T. Laurencin , Adv. Drug Deliv. Rev. 2016 , 107 , 247 . 27125191 10.1016/j.addr.2016.04.015 PMC5482531
293 P. Yu , F. Yu , J. Xiang , K. Zhou , L. Zhou , Z. Zhang , X. Rong , Z. Ding , J. Wu , W. Li , Z. Zhou , L. Ye , W. Yang , Adv. Mater. 2022 , 34 , 2107922 . 10.1002/adma.202107922 34837252
294 G. L. Koons , M. Diba , A. G. Mikos , Nat. Rev. Mater. 2020 , 5 , 584 .
295 D. L. Taylor , M. in het Panhuis , Adv. Mater. 2016 , 28 , 9060 . 27488822 10.1002/adma.201601613
296 S. Herberg , D. Varghai , D. S. Alt , P. N. Dang , H. Park , Y. Cheng , J.‐Y. Shin , A. D. Dikina , J. D. Boerckel , M. W. Rolle , E. Alsberg , Commun. Biol. 2021 , 4 , 89 . 33469154 10.1038/s42003-020-01576-y PMC7815708
297 L. Yang , B. M. Conley , S. R. Cerqueira , T. Pongkulapa , S. Wang , J. K. Lee , K.‐B. Lee , Adv. Mater. 2020 , 32 , 2002578 . 10.1002/adma.202002578 PMC7606660 32893402
298 J. G. Torres‐Rendon , T. Femmer , L. De Laporte , T. Tigges , K. Rahimi , F. Gremse , S. Zafarnia , W. Lederle , S. Ifuku , M. Wessling , J. G. Hardy , A. Walther , Adv. Mater. 2015 , 27 , 2989 . 25833165 10.1002/adma.201405873
299 Y. Wang , X. Xu , X. Chen , J. Li , Adv. Mater. 2022 , 34 , 2107406 . 10.1002/adma.202107406 34739155
300 B. M. Oosterlaken , M. P. Vena , G. de With , Adv. Mater. 2021 , 33 , 2004418 . 33711177 10.1002/adma.202004418 PMC11469168
301 Y. Zhang , J. Li , V. H. M. Mouser , N. Roumans , L. Moroni , P. Habibovic , ACS Nano 2021 , 15 , 17480 . 34662097 10.1021/acsnano.1c03905 PMC8613905
302 Y. Xu , J. Dai , X. Zhu , R. Cao , N. Song , M. Liu , X. Liu , J. Zhu , F. Pan , L. Qin , G. Jiang , H. Wang , Y. Yang , Adv. Mater. 2022 , 34 , 2106755 . 10.1002/adma.202106755 34741771
303 S. Huo , F. Wang , Z. Lyu , Q. Hong , B. Nie , J. Wei , Y. Wang , J. Zhang , B. Yue , Chem. Eng. J. 2021 , 426 , 130806 .
304 J. Bai , H. Wang , H. Chen , G. Ge , M. Wang , A. Gao , L. Tong , Y. Xu , H. Yang , G. Pan , P. K. Chu , D. Geng , Biomaterials 2020 , 255 , 120197 . 32563944 10.1016/j.biomaterials.2020.120197
305 Y. Liu , Z. Guo , F. Li , Y. Xiao , Y. Zhang , T. Bu , P. Jia , T. Zhe , L. Wang , ACS Appl. Mater. Interfaces 2019 , 11 , 31649 . 31407880 10.1021/acsami.9b10096
306 B. Wang , K. F. Chan , J. Yu , Q. Wang , L. Yang , P. W. Y. Chiu , L. Zhang , Adv. Funct. Mater. 2018 , 28 , 1705701 .
307 A. Cheesbrough , F. Sciscione , F. Riccio , P. Harley , L. R'Bibo , G. Ziakas , A. Darbyshire , I. Lieberam , W. Song , Adv. Mater. 2022 , 34 , 2110441 . 35231133 10.1002/adma.202110441 PMC9131876
308 L. Chen , L. Cheng , Z. Wang , J. Zhang , X. Mao , Z. Liu , Y. Zhang , W. Cui , X. Sun , Bioact. Mater. 2021 , 6 , 361 . 32954054 10.1016/j.bioactmat.2020.08.022 PMC7481508
309 X. Hu , S. Zheng , R. Zhang , Y. Wang , Z. Jiao , W. Li , Y. Nie , T. Liu , K. Song , Biomater. Adv. 2022 , 133 , 112662 . 35074237 10.1016/j.msec.2022.112662
310 G.‐J. Jeong , H. Castels , I. Kang , B. Aliya , Y. C. Jang , Tissue Eng Regen Med 2022 , 19 , 253 . 35334091 10.1007/s13770-022-00446-4 PMC8971233
311 E. A. Ross , L.‐A. Turner , H. Donnelly , A. Saeed , M. P. Tsimbouri , K. V. Burgess , G. Blackburn , V. Jayawarna , Y. Xiao , M. A. G. Oliva , J. Willis , J. Bansal , P. Reynolds , J. A. Wells , J. Mountford , M. Vassalli , N. Gadegaard , R. O. C. Oreffo , M. Salmeron‐Sanchez , M. J. Dalby , Nat. Commun. 2023 , 14 , 753 . 36765065 10.1038/s41467-023-36293-7 PMC9918539
312 G. G. Walmsley , A. McArdle , R. Tevlin , A. Momeni , D. Atashroo , M. S. Hu , A. H. Feroze , V. W. Wong , P. H. Lorenz , M. T. Longaker , D. C. Wan , Nanomed.: Nanotechnol. Biol. Med. 2015 , 11 , 1253 . 10.1016/j.nano.2015.02.013 PMC4476906 25791811
313 N. Jusoh , S. Oh , S. Kim , J. Kim , N. L. Jeon , Lab Chip 2015 , 15 , 3984 . 26288174 10.1039/c5lc00698h
314 A. Pirosa , R. Gottardi , P. G. Alexander , D. Puppi , F. Chiellini , R. S. Tuan , Biomaterials 2021 , 272 , 120773 . 33798958 10.1016/j.biomaterials.2021.120773 PMC12872279
315 S. Hao , M. Wang , Z. Yin , Y. Jing , L. Bai , J. Su , Mater. Today Bio 2023 , 22 , 100741 . 10.1016/j.mtbio.2023.100741 PMC10413201 37576867
316 S. Amirthalingam , J. Rangasamy , in Chitosan Biomaterials III: Structure–Property Relationships (Eds: R. Jayakumar , M. Prabaharan ), Springer International Publishing , Cham 2021 , pp. 233 – 255 .
317 H. Kavand , R. Nasiri , A. Herland , Adv. Mater. 2022 , 34 , 2107876 . 10.1002/adma.202107876 34913206
318 S. Kim , A. K. Rajendran , S. Amirthalingam , J. H. Kim , K.‐H. So , N. S. Hwang , Biosens. Bioelectron. X 2023 , 14 , 100360 .
319 J. Dornhof , J. Kieninger , H. Muralidharan , J. Maurer , G. A. Urban , A. Weltin , Lab Chip 2022 , 22 , 225 . 34851349 10.1039/d1lc00689d
320 M. Li , D. Liu , D. Wei , X. Song , D. Wei , A. T. S. Wee , Adv. Sci. 2016 , 3 , 1600003 . 10.1002/advs.201600003 PMC5102669 27980983
321 A. Kalmykov , C. Huang , J. Bliley , D. Shiwarski , J. Tashman , A. Abdullah , S. K. Rastogi , S. Shukla , E. Mataev , A. W. Feinberg , K. J. Hsia , T. Cohen‐Karni , Sci. Adv. 5 , 0729 . 10.1126/sciadv.aax0729 PMC6707782 31467978
322 S. Y. Kwon , S. Y. Chun , Y.‐S. Ha , D. H. Kim , J. Kim , P. H. Song , H. T. Kim , E. S. Yoo , B. S. Kim , T. G. Kwon , Tissue Eng. Regener. Med. 2017 , 14 , 595 . 10.1007/s13770-017-0068-8 PMC6171625 30603513
323 I. Rosová , M. Dao , B. Capoccia , D. Link , J. A. Nolta , Stem Cells 2008 , 26 , 2173 . 18511601 10.1634/stemcells.2007-1104 PMC3017477
324 P. Malladi , Y. Xu , M. Chiou , A. J. Giaccia , M. T. Longaker , Am. J. Physiol.: Cell Physiol. 2006 , 290 , C1139 . 16291817 10.1152/ajpcell.00415.2005
325 H.‐S. Kim , H.‐S. Ha , D.‐H. Kim , D. H. Son , S. Baek , J. Park , C. H. Lee , S. Park , H.‐J. Yoon , S. E. Yu , J. I. Kang , K. M. Park , Y. M. Shin , J. B. Lee , H.‐J. Sung , Sci. Adv. 9 , 4210 .
326 V. P. Galván‐Chacón , A. Zampouka , B. Hesse , M. Bohner , P. Habibovic , D. Barata , Adv. Eng. Mater. 2022 , 24 , 2101467 .
327 N. H. Cho , A. Guerrero‐Martínez , J. Ma , S. Bals , N. A. Kotov , L. M. Liz‐Marzán , K. T. Nam , Nat. Rev. Bioeng. 2023 , 1 , 88 .
328 K. Zheng , J. Bai , H. Yang , Y. Xu , G. Pan , H. Wang , D. Geng , Bioact. Mater. 2023 , 24 , 263 . 36632509 10.1016/j.bioactmat.2022.12.014 PMC9813540
329 I. M. Oliveira , M. R. Carvalho , D. C. Fernandes , C. M. Abreu , F. R. Maia , H. Pereira , D. Caballero , S. C. Kundu , R. L. Reis , J. M. Oliveira , J. Mater. Chem. B 2021 , 9 , 4211 . 33998627 10.1039/d1tb00802a
330 H.‐F. Wang , Y. Liu , T. Wang , G. Yang , B. Zeng , C.‐X. Zhao , ACS Biomater. Sci. Eng. 2020 , 6 , 5040 . 33455297 10.1021/acsbiomaterials.0c00650
331 O. Mitxelena‐Iribarren , S. Lizarbe‐Sancha , J. Campisi , S. Arana , M. Mujika , Bioengineering 2021 , 8 , 77 . 34199965 10.3390/bioengineering8060077 PMC8228877
332 D. B. Chou , V. Frismantas , Y. Milton , R. David , P. Pop‐Damkov , D. Ferguson , A. MacDonald , Ö. V Bölükbaşı , C. E. Joyce , L. S. Moreira Teixeira , A. Rech , A. Jiang , E. Calamari , S. Jalili‐Firoozinezhad , B. A. Furlong , L. R. O'Sullivan , C. F. Ng , Y. Choe , S. Marquez , K. C. Myers , O. K. Weinberg , R. P. Hasserjian , R. Novak , O. Levy , R. Prantil‐Baun , C. D. Novina , A. Shimamura , L. Ewart , D. E. Ingber , Nat. Biomed. Eng. 2020 , 4 , 394 . 31988457 10.1038/s41551-019-0495-z PMC7160021
333 M. L. Johnson , J. S. Wang , G. Falchook , C. Greenlees , S. Jones , D. Strickland , G. Fabbri , C. Kennedy , J. E Pease , L. Sainsbury , A. MacDonald , S. Schalkwijk , P. Szekeres , J. Cosaert , H. Burris , Br. J. Cancer 2023 , 128 , 1906 . 36871042 10.1038/s41416-023-02185-2 PMC10147685
334 M. Carmena , M. Wheelock , H. Funabiki , W. C. Earnshaw , Nat. Rev. Mol. Cell Biol. 2012 , 13 , 789 . 23175282 10.1038/nrm3474 PMC3729939
335 D. B. Longley , D. P. Harkin , P. G. Johnston , Nat. Rev. Cancer 2003 , 3 , 330 . 12724731 10.1038/nrc1074
336 A. Skardal , T. Shupe , A. Atala , Pathophysiol. Drug Discov. Today 2016 , 21 , 1399 . 10.1016/j.drudis.2016.07.003 PMC9039871 27422270
337 D. E. Ingber , Cell 2016 , 164 , 1105 . 26967278 10.1016/j.cell.2016.02.049
338 S. Shi , L. Han , L. Deng , Y. Zhang , H. Shen , T. Gong , Z. Zhang , X. Sun , J. Controlled Release 2014 , 194 , 228 . 10.1016/j.jconrel.2014.09.005 25220161
339 F. Sharifi , O. Yesil‐Celiktas , A. Kazan , S. Maharjan , S. Saghazadeh , K. Firoozbakhsh , B. Firoozabadi , Y. S. Zhang , Bio‐Des. Manuf. 2020 , 3 , 189 .
340 P. Occhetta , A. Mainardi , E. Votta , Q. Vallmajo‐Martin , M. Ehrbar , I. Martin , A. Barbero , M. Rasponi , Nat. Biomed. Eng. 2019 , 3 , 545 . 31160722 10.1038/s41551-019-0406-3
341 N. Kumari , S. H. Choi , J. Exp. Clin. Cancer Res. 2022 , 41 , 68 . 35183252 10.1186/s13046-022-02272-x PMC8857848
342 N. Jia , Y. Gao , M. Li , Y. Liang , Y. Li , Y. Lin , S. Huang , Q. Lin , X. Sun , Q. He , Y. Yao , B. Zhang , Z. Zhang , L. Zhang , Signal Transduction Targetted Ther. 2023 , 8 , 280 . 10.1038/s41392-023-01499-0 PMC10374631 37500654
343 W. Zhang , M. Wang , W. Tang , R. Wen , S. Zhou , C. Lee , H. Wang , W. Jiang , I. M. Delahunty , Z. Zhen , H. Chen , M. Chapman , Z. Wu , E. W. Howerth , H. Cai , Z. Li , J. Xie , Adv. Mater. 2018 , 30 , 1805557 . 10.1002/adma.201805557 PMC6506271 30368972
344 T. Hou , T. Wang , W. Mu , R. Yang , S. Liang , Z. Zhang , S. Fu , T. Gao , Y. Liu , N. Zhang , Nano‐Micro Lett. 2020 , 13 , 6 . 10.1007/s40820-020-00531-0 PMC8187668 34138195
345 R. Ran , H.‐F. Wang , F. Hou , Y. Liu , Y. Hui , N. Petrovsky , F. Zhang , C.‐X. Zhao , Adv. Healthcare Mater. 2019 , 8 , 1900015 . 10.1002/adhm.201900015 30868753
346 E. Neto , A. C. Monteiro , C. Leite Pereira , M. Simões , J. P. Conde , V. Chu , B. Sarmento , M. Lamghari , Adv. Healthcare Mater. 2022 , 11 , 2102305 . 10.1002/adhm.202102305 PMC11468530 35158409
347 J. Rosser , B. Bachmann , C. Jordan , I. Ribitsch , E. Haltmayer , S. Gueltekin , S. Junttila , B. Galik , A. Gyenesei , B. Haddadi , M. Harasek , M. Egerbacher , P. Ertl , F. Jenner , Mater. Today Bio 2019 , 4 , 100023 . 10.1016/j.mtbio.2019.100023 PMC7061638 32159153
348 X. Fernández‐Garibay , M. A. Ortega , E. Cerro‐Herreros , J. Comelles , E. Martínez , R. Artero , J. M. Fernández‐Costa , J. Ramón‐Azcón , Biofabrication 2021 , 13 , 035035 . 10.1088/1758-5090/abf6ae 33836519
349 K. Yamamoto , S. Ohsumi , T. Nagashima , H. Akiyama , H. Honda , K. Shimizu , Biotechnol. Bioeng. 2022 , 119 , 2196 . 35478456 10.1002/bit.28125
350 W. H. De Jong , P. J. Borm , Int. J. Nanomed. 2008 , 3 , 133 . 10.2147/ijn.s596 PMC2527668 18686775
351 A. Banerjee , J. Qi , R. Gogoi , J. Wong , S. Mitragotri , J. Controlled Release 2016 , 238 , 176 . 10.1016/j.jconrel.2016.07.051 PMC5289391 27480450
352 C. A. Klein , Science 2008 , 321 , 1785 . 18818347 10.1126/science.1164853
353 B. Prabhakarpandian , M.‐C. Shen , J. B. Nichols , C. J. Garson , I. R. Mills , M. M. Matar , J. G. Fewell , K. Pant , J. Controlled Release 2015 , 201 , 49 . 10.1016/j.jconrel.2015.01.018 PMC4418523 25599856
354 J. G. Fewell , M. M. Matar , J. S. Rice , E. Brunhoeber , G. Slobodkin , C. Pence , M. Worker , D. H. Lewis , K. Anwer , J. Gene Med. 2009 , 11 , 718 . 19507172 10.1002/jgm.1356
355 K. Anwer , F. J. Kelly , C. Chu , J. G. Fewell , D. Lewis , R. D. Alvarez , Gynecol. Oncol. 2013 , 131 , 169 . 23863356 10.1016/j.ygyno.2013.07.081
356 K. Anwer , M. N. Barnes , J. Fewell , D. H. Lewis , R. D. Alvarez , Gene Ther. 2010 , 17 , 360 . 20033066 10.1038/gt.2009.159
357 A. B. Engin , D. Nikitovic , M. Neagu , P. Henrich‐Noack , A. O. Docea , M. I. Shtilman , K. Golokhvast , A. M. Tsatsakis , Part. Fibre Toxicol. 2017 , 14 , 22 . 28646905 10.1186/s12989-017-0199-z PMC5483305
358 Y. Huai , M. N. Hossen , S. Wilhelm , R. Bhattacharya , P. Mukherjee , Bioconjugate Chem. 2019 , 30 , 2247 . 10.1021/acs.bioconjchem.9b00448 PMC6892461 31408324
359 Y. Kim , M. E. Lobatto , T. Kawahara , B. Lee Chung , A. J. Mieszawska , B. L. Sanchez‐Gaytan , F. Fay , M. L. Senders , C. Calcagno , J. Becraft , M. Tun Saung , R. E. Gordon , E. S. G. Stroes , M. Ma , O. C. Farokhzad , Z. A. Fayad , W. J. M. Mulder , R. Langer , Proc. Natl. Acad. Sci. USA 2014 , 111 , 1078 . 24395808 10.1073/pnas.1322725111 PMC3903216
360 J. Han , V. V. Shuvaev , P. F. Davies , D. M. Eckmann , S. Muro , V. R. Muzykantov , J. Controlled Release 2015 , 210 , 39 . 10.1016/j.jconrel.2015.05.006 PMC4793278 25966362
361 M. L. Ewald , Y.‐H. Chen , A. P. Lee , C. C. W. Hughes , Lab Chip 2021 , 21 , 3244 . 34396383 10.1039/d1lc00530h PMC8635227
362 S. Gribi , S. du Bois de Dunilac , D. Ghezzi , S. P. Lacour , Nat. Commun. 2018 , 9 , 4403 . 30353009 10.1038/s41467-018-06895-7 PMC6199302
363 A. Kundu , L. McCoy , N. Azim , H. Nguyen , C. M. Didier , T. Ausaf , A. D. Sharma , J. L. Curley , M. J. Moore , S. Rajaraman , ACS Biomater. Sci. Eng. 2021 , 7 , 3018 . 34275292 10.1021/acsbiomaterials.0c01184
364 S. Deng , C. Li , J. Cao , Z. Cui , J. Du , Z. Fu , H. Yang , P. Chen , Theranostics 2023 , 13 , 4526 . 37649608 10.7150/thno.87266 PMC10465229
365 O. Adir , M. Poley , G. Chen , S. Froim , N. Krinsky , J. Shklover , J. Shainsky‐Roitman , T. Lammers , A. Schroeder , Adv. Mater. 2020 , 32 , 1901989 . 10.1002/adma.201901989 PMC7124889 31286573