Spatiotemporal immunomodulation with programmable biomaterials to promote musculoskeletal tissue regeneration

Abstract

Musculoskeletal disorders (MSDs), encompassing a variety of degenerative and inflammatory conditions, are frequently associated with immune dysregulation. This dysregulation can result in significant pathological changes within the tissue microenvironment, including abnormal inflammatory responses, biochemical and biophysical imbalances, and epigenetic modifications. Such alterations can serve as endogenous stimuli for targeted therapeutic interventions in MSDs. This review introduces the innovative concept of programmable biomaterials, which are designed to respond dynamically to specific endogenous signals within the tissue microenvironment. A comprehensive overview of the pathogenesis of several key MSDs is provided, detailing the disease-specific endogenous signals that can be exploited to enhance the functionality of programmable biomaterials. Central to the discussion is the importance of spatiotemporal immunomodulation in the treatment of various MSDs. Programmable biomaterials are categorized based on their mechanisms of endogenous responsiveness, highlighting their potential applications in clinical settings. Future directions for the design of advanced programmable biomaterials are explored, emphasizing their capacity to transform existing therapeutic strategies for MSDs. This emerging field holds great promise for improving patient outcomes by tailoring treatment approaches to the intricate biological cues present in musculoskeletal tissues.

Graphical abstract

Highlights

• •Introduces programmable biomaterials that dynamically respond to endogenous signals in musculoskeletal disorders.
• •Explores the role of internal stimuli-responsive materials in modulating inflammation and promoting tissue repair.
• •Emphasizes the importance of spatiotemporal immunomodulation for effective therapeutic interventions in MSDs.
• •Discusses future directions for enhancing biomaterial design to improve patient outcomes through tailored treatments.

1. Introduction

Musculoskeletal disorders (MSDs) encompass a broad spectrum of degenerative and inflammatory conditions affecting bones, joints, muscles, and connective tissues, including osteoarthritis (OA), rheumatoid arthritis (RA), intervertebral disc degeneration (IVDD), and other conditions involving bone resorption, such as periodontitis. These disorders frequently lead to chronic pain, functional impairment, and reduced quality of life, ranking among the most disabling and economically burdensome health conditions worldwide [1]. In China alone, MSDs accounted for 30.4 million disability-adjusted life years (DALYs) in 2019, with the age-standardized DALYs rate projected to rise to 1779.08 per 100,000 by 2030. The number of patients requiring rehabilitation increased sharply from 186 million in 1990 to 322 million in 2019 and is expected to reach 466 million by 2030 [2]. Globally, the World Health Organization (WHO) estimates 335 million new MSD cases annually, underscoring their substantial societal and economic burden [3]. Unlike many other diseases, MSDs present unique regenerative challenges due to the structural and biological complexity of musculoskeletal tissues and their irreversible immunological alterations. For instance, bone regeneration is often time-consuming and prone to non-union, while cartilage repair is severely limited by its avascular and anural nature, leading to poor self-healing capacity [4,5]. Moreover, MSDs are often characterized by immune cell accumulation, pro-inflammatory cytokine secretion, increased levels of reactive oxygen species (ROS), and pH alterations following inflammation [3,6]. These dynamic pathological features collectively create an adverse and complex microenvironment that poses significant challenges for therapeutic strategies.

Current treatment strategies, including surgical interventions, symptomatic management, and rehabilitative care, primarily aim to alleviate symptoms and restore mobility. However, bone tissue engineering scaffolds, such as those using recombinant BMP-2 or bisphosphonates, face significant limitations: exogenous BMP-2 can induce ectopic ossification or uncontrolled inflammation [7], while bisphosphonates, despite inhibiting bone resorption, carry risks of osteonecrosis and fail to address underlying inflammation [8]. The efficacy of these strategies is compromised as the spatiotemporal management of the disease is often overlooked. Indeed, MSDs exhibit spatiotemporal immune microenvironment dynamics that are critical for musculoskeletal tissue repair [9]. This characteristic serves as an endogenous trigger for internal stimuli-responsive materials (ISMs)-mediated on-demand delivery of anti-inflammatory agents or immunomodulators [10]. Similarly, the marked pH reduction observed in periodontitis and other infectious MSDs (ΔpH ≈ 1.5-2.0) acts as a trigger for pH-responsive biomaterials [11]. Such systems achieve closed-loop immunoregulation through mechanisms such as acid-triggered drug release and alkaline-phase deactivation, effectively coupling therapeutic action with pathological progression [12]. Thus, ISMs with advanced design, or programmable smart materials, represent a transformative approach in regenerative medicine [13]. These materials are engineered to sense specific biological cues, such as reactive oxygen species (ROS), pH changes, or enzymatic activity, within the disease microenvironment [14].

In this review, programmable biomaterials are defined as a class of advanced engineered materials capable of dynamically interacting with specific biological cues in the disease microenvironment through “sense–response” mechanisms. They are “programmed” to undergo predetermined, sequential, or reversible changes in their physical properties, chemical states, or bio-functional outputs in response to endogenous stimuli such as ROS, pH variations, enzymatic activity, and other pathological signals [15]. This programmability lies in the precise engineering of material composition and structure to achieve spatiotemporally controlled immunomodulation, distinguishing them from conventional static biomaterials or simple duel-responsive or multi-responsive biomaterials. Here, spatiotemporally controlled immunomodulation refers to a therapeutic strategy that aims to precisely regulating immune responses in a manner that is dynamically adapted to the evolving immune landscape of a disease, both anatomically (at the specific lesion site or within particular immune cell populations or targeting sub-cellular structure) and chronologically (across the acute inflammatory, resolution, and regenerative phases).

Thus, this review systematically explores the design and application of ISMs for spatiotemporal-controlled immunomodulation in various muscle and bone tissue repairs (Fig. 1a). Starting with an analysis of disease-specific immunological microenvironments, the review identifies key stimuli signals and their pathological significance, linking them to material design strategies. It then transitions to the engineering principles underlying stimuli-responsive biomaterials, detailing how they can be programmed to respond to specific cues such as ROS, pH, and enzymes (Fig. 1b). Finally, the review discusses current challenges and future directions, emphasizing innovations in multi-stimuli responsiveness, precision medicine, and closed-loop systems. Collectively, this work provides a comprehensive roadmap for advancing programmable biomaterials to achieve targeted and effective immunomodulation in MSDs (Fig. 1c).

Fig. 1.

Schematic illustration of ISMs-based spatiotemporal immunomodulation therapy. Transitioning from a) the destructive inflammatory microenvironment via b) a multiple programmable internal stimuli-responsive platform to c) the reparative regenerative microenvironment for musculoskeletal tissue regeneration. Created in Biorender with license.

2. Disease-specific immunological microenvironments and stimuli-responsive targets

According to the WHO, there are over 150 types of musculoskeletal conditions affecting bones, joints, muscles, and connective tissues. For this review, four representative diseases, including OA, IVDD, periodontitis, and RA, have been selected to illustrate the fundamental principles of programmable biomaterial applications. This selection encompasses the most extensively studied MSDs in the context of internal stimuli-responsive immunomodulation.

MSDs share common pathological features in their immunological microenvironments, primarily characterized by three core elements: (1) aberrant accumulation of ROS driving oxidative stress; (2) dysregulated pH gradients resulting from metabolic alterations and inflammatory processes; and (3) predominant polarization of immune cells toward pro-inflammatory phenotypes. While the specific spatiotemporal patterns and relative contributions of these elements vary across diseases, they collectively create distinctive microenvironmental signatures that can be leveraged for targeted therapeutic intervention (Table 1).

Table 1.

Characteristic alterations as triggers for internal stimuli-responsive MSDs therapeutics.

Diseases	Parameters, typical pathological range
	pH	ROS	MMP	Temperature	Oxygen levels
Physiological Parameter	∼7.4 [16]	10 – 100 nM (H2O2), 0.1 nM (O2−) [17]	MMP-2 (ng/ml):1160 ± 189 [18]	∼37 °C [19]	1-4 % (bone marrow) [20]; 8% (human articular chondrocytes) [21]; 2%-10% (Muscle) [22]; 1%-5% (Tendon) [23]
OA	6.6–7.2 (Early stage), <6.0 (Late stage) [24]	Elevated [25]	Elevated [26,27]	/	/
OP	4.5-5.0 [[28], [29]]	Elevated [30]	MMP-2 (ng/ml): 1280.3 ± 276.6 [18]	/	Decreased [31]
IVDD	5.7-6.3 [32]	Crucial intermediators, elevated	/	/	No correlation was seen [33]; 1-2% O2
DND	/	Overproduction [34]	/	/	/
RA	6 - 6.8[[35], [36], [37]]	Plasma O2−(nmol/ml): 8.90 ± 1.28 (RA), 3.04 ± 0.38 (health); Plasma H2O2 (nmol/ml): 4.08 ± 0.31 (RA), 2.39 ± 0.13 (health) [38,39]	Serum MMP-3 (ng/ml): 46.78 ± 46.99 (RA), 1.98 ± 1.71 (health) [40,41]	∼5% higher than the skin temperature of normal joints [42]	3.2% [range 0.46–7%] [43]
Periodontitis	Salivary pH: 6.14 ± 0.60 (periodontitis), 7.05 ± 0.01 (health); GCF: 8.19 ± 0.29 (periodontitis), 6.73 ± 0.14 (health) [44]	GCF H2O2 (μM): ∼11.19 (periodontitis), ∼7.76 (gingivitis), and ∼5.55 (healthy) [[45], [46], [47]]	GCF MMP-8 (ng/ml): 13.17 ± 16.43 (severe periodontitis), 5.61 ± 6.55 (health); MMP-2 (pg/ml): ∼458 (periodontitis), ∼75 (health) [[48], [49], [50], [51]]	Higher site temperature (0.65 °C higher) of the diseased subjects [52,53]	1.8% O2 in untreated periodontal pockets [54,55]
IAIs	Synovial fluid: ∼7.08 (infection), ∼7.83 (no infection after joint replacement) [56]	Elevated [[57], [58], [59]]	Implant site MMP-2 (pg/mL): ∼649 (peri-implantitis), ∼40 (health) Implant site active MMP-8 (ng/mL): ∼142.32 (peri-implantitis), ∼49.25 (health) [48,60]	/	HIF-1α (ng/sample): 0.61 ± 0.2 (peri-implant mucositis), 0.46 ± 0.2 (healthy peri-implant) [61]
Bone tumor	6.4 to 7.3 [62]	H2O2: up to 100 mM (malignant tumor cells can be), less than 20 nM (normal cells) [63,64]	/	/	Hypoxia is present in 90% of solid tumors [65]
Spinal Cord Injury	Decreased [66]	Elevated [67,68]	MMP-2: no relation, MMP-9: elevated from 3.81E+05 ± 5.03E+04 pg ml−1(baseline) to 8.05E+05 ± 7.21E+04 pg ml−1 [69]	/	/
Muscle injury	6.8–7.0 [70]	Highly elevated [71]	Acute injuries: MMP-2 and -9 elevated, return to baseline by 7 days; Chronic injuries: MMP-9 elevated [72]	/	Less than 2% [22]
Tendon injury	Decreased as lactose accumulates [73]	Elevated [74]	MMP-1, -2, -8, -9, and -13 increased [72]	/	Less than 1% [23]

Abbr.: OA: Osteoarthritis; OP: Osteoporosis; IVDD: Intervertebral Disc Degeneration; DND: Degenerative Neurological Disease; RA: Rheumatoid Arthritis; IAIs: Implant-Associated Infections; ROS: Reactive Oxygen Species; MMP: Matrix Metalloproteinase; H₂O₂: Hydrogen Peroxide; O₂⁻: Superoxide Anion; GCF: Gingival Crevicular Fluid; HIF-1α: Hypoxia-Inducible Factor 1-alpha.

2.1. Osteoarthritis

OA is a degenerative joint disorder driven by multifaceted pathological mechanisms with distinct temporal evolution and spatial distribution characteristics [25,75,76]. Chronologically, early-stage OA is characterized by ROS overproduction and focal synovitis dominated by classically activated (M1) macrophage infiltration, which initiates an inflammatory cascade involving the release of pro-inflammatory cytokines such as Tumor necrosis factor-alpha (TNF-α) and interleukin-1β (IL-1β) [25]. Spatially, immune activation and cellular stress are initially confined to areas of high mechanical stress within the cartilage and adjacent synovium [77]. At the intermediate/chronic stage, sustained inflammation and metabolic dysregulation drive progressive tissue remodeling [75,78]. This phase is characterized by persistent oxidative stress, amplified cytokine (e.g., interleukin-6 (IL-6), C-C motif chemokine ligand 2 (CCL2)), and elevated matrix metalloproteinase (MMP) levels [75,77,78]. Cumulative endoplasmic reticulum and Golgi stress disrupt chondrocyte homeostasis, accelerating apoptosis and extracellular matrix loss [79]. Spatially, damage expands from focal lesions to broader joint involvement. Synovial hyperplasia and progressive fibrosis become evident, and immune cell infiltration often forms a specific pattern localized to the osteochondral junction and the sublining layer of the synovium [25,80]. In the advanced stage, pathology culminates in irreversible structural damage, including extensive cartilage loss with eburnated bone, synovial fibrosis, osteophyte formation, and subchondral sclerosis [25]. The microenvironment is marked by chronic hypoxia, severe acidosis, and impaired autophagy-apoptosis balance, manifesting as mixed infiltration of innate and adaptive immune cells and the activation of a senescence-associated secretory phenotype [25,80,81].

Among these spatiotemporal alterations, key stimulus signals exist for targeting OA through modulation of its underlying mechanisms, including elevated ROS, localized pH drops, overactivated MMPs, endoplasmic reticulum (ER) stress, and Golgi stress [[82], [83], [84], [85]]. Typical ISMs targeting ROS have become a cornerstone in OA therapy. For instance, ROS-scavenging nanoparticles loaded with immunomodulatory drugs (e.g., curcumin, rapamycin) directly address ROS-driven inflammation [83,84,86]. ROS-sensitive bond cleavage enables spatiotemporal drug release, targeting synovial macrophages to suppress NF-κB/mTOR pathways [84]. In OA joints, the pH of synovial fluid drops from its normal 7.4–7.8 range to around 6.6–7.2, making pH-responsive platforms viable [85]. Another approach targeting MMPs and the hypoxic microenvironment involves a hydrogel microsphere system composed of hydrophilic sulfonated azocalixarene, which enables synergistic OA therapy via MMP-13 and hypoxia-responsive drug (hydroxychloroquine) release [87]. Additionally, ER stress disrupts the autophagy–apoptosis balance in joint chondrocytes [88] which can be reprogrammed through hypoxia-inducible factor 1-alpha (HIF-1α) and tackling pro-inflammatory mediator release in synovial cells also constitutes promising therapeutic targets [89].

At a higher level of spatial precision, organelle-specific ISMs that target subcellular compartments to reprogram metabolic processes play a pivotal role in achieving sustained correction of pathological states in recent years [83,84]. For example, organelle-targeting nanocarriers can reprogram cellular metabolism to correct pathological states [83]. Moreover, internal stimuli-responsive nanoparticles can release drugs (e.g., astaxanthin, rapamycin) to clear damaged organelles [84]. For example, Li et al. reprogrammed ER-mitochondria function by enhancing mitophagy and oxidative phosphorylation. This suppressed the NLRP3 inflammasome, promoted M1-to-M2 macrophage repolarization, and provided cartilage protection [85].

Moreover, sequential immunomodulation is required to achieve closed-loop regulation in a spatiotemporal manner [90]. For example, a synergistic and durable reprogramming of macrophages from a pro-inflammatory to an anti-inflammatory phenotype was achieved by orchestrating a fast-acting chemical scavenging of nitric oxide alongside a slower, sustained genetic silencing of Carbonic anhydrase IX (CA9) (Fig. 2) [24]. Chronologically, this therapeutic strategy follows a well-defined cascade that progresses from physical retention to chemical response and ultimately to biological reprogramming: it begins with prolonged retention within the joint, proceeds through specific cellular uptake by M1 macrophages (Fig. 2a), triggers rapid intracellular disassembly in response to ROS (Fig. 2b), achieves precise localization to the Golgi apparatus, and sequentially reprograms lipid metabolism (Fig. 2c)—first by alleviating organelle stress (Fig. 2d) and then by inhibiting inflammatory pathways (Fig. 2e)—to drive a phenotypic switch from M1 to M2 macrophages, culminating in tissue repair (Fig. 2f). Spatially, the action of the nanodrug traverses multiple biological scales: it first localizes to the joint cavity, then targets M1 macrophages, further homes to the Golgi complex within these cells, and finally engages specific lipid metabolism pathways at the molecular level [24].

Fig. 2.

The temporally orchestrated cascade mechanism of the self-assembled nanomedicine licofelone-chondroitin sulfate bilirubin (LCF-CSBN). a) Phase 1: targeted delivery and prolonged retention. The nanoparticle (∼160 nm in diameter) resists rapid clearance from the synovium, enabling retention for up to 28 days. Surface chondroitin sulfate (CS) facilitates cell-specific internalization via CD44 receptor-mediated endocytosis into CD44-overexpressing M1 macrophages, a process completed within hours post-injection. b) Phase 2: intracellular responsive disassembly and organelle targeting. Upon entering the high-ROS microenvironment of M1 macrophages, the hydrophobic bilirubin (BR) moiety is oxidized to hydrophilic biliverdin, triggering rapid nanoparticle disassembly. Concurrently, CS acts as a substrate for N-acetylgalactosaminyltransferase (GalNAc-T), guiding the nanoparticles to specifically accumulate in the Golgi apparatus following lysosomal escape. c) Phase 3: sequential metabolic reprogramming. The localized BR component immediately scavenges ROS, alleviating Golgi stress within hours. This stabilizes the organelle and establishes a foundation for dual lipid metabolic reprogramming: d) Sphingolipid reprogramming (reducing pro-inflammatory ceramide levels) and e) Arachidonic Acid (AA) reprogramming (inhibiting the synthesis of PGE2 and LTB4 via the released LCF). f) Phase 4: Phenotype switch and therapeutic outcome. The combined metabolic reprogramming drives an M1-to-M2 macrophage phenotype switch, leading to an anti-inflammation cascade, facilitating tissue repair in the osteoarthritic joint. Copyright © 2025 The Author(s). Adv. Sci. published by Wiley‐VCH GmbH, [24].

In summary, OA progression is governed by spatiotemporally dynamic stimuli, including ROS bursts, metabolic dysregulation, and immune cell polarization. Advanced biomaterials that leverage these signals—through internal stimuli-sensitive drug release, ER/Golgi-targeted metabolic modulation, dual-pathway inhibition, and reverse inflammation—demonstrate precise immunomodulation with transformative potential for OA therapy. However, the clinical translation of such strategies requires careful evaluation of efficacy and safety parameters, particularly concerning dosage and timing. The therapeutic action often depends on the consumption of responsive components (e.g., the hydrophobic bilirubin moiety) and the release kinetics of active drugs (e.g., licofelone) [24]. While internal responsiveness enables on-demand release, a potential limitation is the lack of a built-in “off-switch.” This could pose a risk of drug overdosing or sustained immunosuppression if the therapy continues to act after homeostasis is restored, as the agents are not completely inert and may not be rapidly cleared. Future designs should consider incorporating feedback mechanisms to better mimic physiological regulation.

2.2. Intervertebral disc degeneration

IVDD is a major chronic condition in spine surgery, usually occurring as a result of herniated discs, spinal stenosis, instability, vertebral slippage, radiculopathy, scoliosis, or other pathologies, causing acute or chronic pain in the cervical and lumbar spine regions [91,92]. The spatiotemporal alteration of IVDD progression is initiated by phenotypic changes in the IVD and abnormal production of cytokines and catabolic molecules by IVD cells [93]. It initiates with phenotypic changes in disc cells and extracellular matrix breakdown, enabling immune cell infiltration and release of cytokines (e.g., TNF-α) and neurogenic factors (e.g., β-NGF, BDNF). These mediators drive nociceptive nerve ingrowth and upregulation of pain-related ion channels (e.g., ASIC3, TRPV1), establishing chronic discogenic pain [94]. The degenerative disc microenvironment is further characterized by elevated ROS, overexpression of catabolic enzymes (e.g., MMPs), and a pronounced acidic shift (pH ∼6.2) [95], collectively forming actionable stimuli for responsive therapeutics.

ROS-labile linkers could be synthesized via chemical reactions or mixed with inorganic components (e.g., CeO₂) or organic moieties (e.g., phenol groups, sulfur, and boronic acid) to form ROS-scavenging hydrogels [10]. An example is an injectable ROS-scavenging hydrogel loaded with rapamycin that promoted M2 macrophage polarization and facilitated disc regeneration (Fig. 3a–c) [96]. Given the upregulation of MMPs in advanced IVDD [97], enzyme-responsive systems allow precise drug delivery. An MMP-degradable hydrogel sequentially released miR-29a polyplex micelles, which suppressed fibrotic signaling by silencing MMP-2 and blocking β-catenin nuclear translocation, effectively reversing extracellular matrix degradation [98]. Moreover, pH-responsive platforms, such as MOF-based scaffolds, hydrogen sulfide-loaded ammonia borane nanocarriers, and polyphenol nanoparticles, have been adopted to deliver protocatechuic acid [99], hollow polydopamine [100], and miRNA [101] to the nucleus pulposus area as strategies targeting the acidic microenvironment in IVDD.

Fig. 3.

ROS-scavenging therapeutic systems for IVDD. a) - c) ROS-scavenging scaffold with rapamycin for treatment of IVDD. a) Schematic illustration of rapamycin-loaded ROS-responsive hydrogel modulating the IVD immune microenvironment and promoting tissue repair. b) ROS-scavenging capacity evaluated by titanyl sulfate detection of H₂O₂ content, showing significant reduction by PVA-TSPBA hydrogel (20 mM) compared to control. c) Cumulative release profile of rapamycin from hydrogels in PBS with or without H₂O₂ (1 mM) demonstrating ROS-responsive drug release behavior (n = 3). a) - c) Reprinted with permission from Ref. [96], Copyright 2019 WILEY-VCH. d) - g) ROS-responsive magnesium-containing microspheres (Mg@PLPE) for antioxidative treatment of IVDD. d) Schematic illustration of Mg@PLPE MSs fabrication. e) Hydrogen generation profiles from PLGA MSs, Mg MPs, and Mg@PLPE MSs in PBS with or without H₂O₂. f) Western blot analysis showing protein expression levels of MMP-1, MMP-13, and ADAMTS-4 (n = 3). g) Proposed oxidation mechanism of poly (PBT-co-EGDM) triggered by H₂O₂ and corresponding structural changes of Mg@PLPE MSs after oxidative exposure. d) - g), Reprinted with permission from Ref. [102]. Copyright 2023 Acta Materialia Inc. (Published by Elsevier Ltd.).

From a sequential perspective, IVDD progression follows a stimulus hierarchy: ROS surges in acute inflammation, MMPs dominate chronic degeneration, and acidosis persists throughout. This cascade informs the design of stage-specific ISMs. ROS-responsive magnesium microspheres (Mg@PLPE MS) were developed to release hydrogen in a spatially controlled manner (Fig. 3d and e), sequentially inhibiting pro-inflammatory cytokines (TNF-α, IL-1β) and catabolic enzymes (MMP-1, MMP-13, ADAMTS-4), thereby coordinating anti-inflammatory and matrix-stabilizing effects (Fig. 3f and g) [102]. This case establishes a paradigm for designing programmable biomaterials whose action is precisely aligned with the temporal dynamics of IVDD. For example, ROS-responsive magnesium-containing microspheres have been demonstrated to downregulate elevated MMP levels within the lesion, thereby providing sequential correction of inflammation in the IVDD region. This action reduces oxidative stress and inflammatory responses while promoting extracellular matrix secretion [102].

As a more precise strategy, ISMs have been utilized for the treatment of IVDD that involves a complicated tissue-specific immune alteration-driven tissue remodeling. For example, a selenium-based nanocarrier with ROS-cleavable Se–Se bonds provided on-demand release of isoginkgetin (IGK), enhancing mitophagy and restoring mitochondrial function in degenerative discs [103]. The efficacy of this system stems from the tight coupling of its temporal and spatial properties: it executes a defined therapeutic sequence precisely when (during the ROS burst) and where (inside nucleus pulposus cells of the degenerated disc) it is most needed. Temporally, the immunomodulatory action begins with a rapid primary response—ROS scavenging via cleavage of the Se–Se bonds—followed by a slower, sustained secondary phase in which released IGK enhances autophagy to clear damaged organelles. Spatially, targeting proceeds across multiple scales: from organ-level localization via intradiscal injection, to cellular uptake by nucleus pulposus cells (NPCs), and ultimately to subcellular action through clearance of dysfunctional mitochondria [104].

Despite demonstrating a coherent spatiotemporal immunomodulatory framework, the study leaves mechanistic questions unresolved. A key limitation is the lack of an elucidated targeting rationale: it remains unclear what drives the apparent cellular accumulation of the nanoparticles. While uptake by NPCs is observed, the diselenide-containing polyethylene glycol (PEG) copolymer does not display known targeting ligands for specific phagocytic recognition. Thus, the observed cellular internalization may result from non-specific endocytosis or passive entrapment within the disc's confined avascular space, rather than active receptor-mediated targeting. Furthermore, the organelle-level effects, though beneficial, are not conclusively linked to a designed targeting mechanism, leaving open whether mitochondrial clearance results from general autophagy upregulation or more specific organelle-directed action.

2.3. Rheumatoid arthritis

RA is a chronic autoimmune disorder marked by synovial inflammation, progressive cartilage destruction, and systemic immune dysregulation. The pathogenesis of RA involves aberrant activation of CD4⁺ T cells, which orchestrate macrophage polarization toward pro-inflammatory phenotypes and promote B cell production of autoantibodies (e.g., anti-cyclic citrullinated peptide antibodies) [105]. This cascade leads to synovial hyperplasia and sustained release of inflammatory cytokines (e.g., TNF-α, IL-1β, IL-6), creating a self-perpetuating inflammatory microenvironment. Activated synovial fibroblasts and macrophages further exacerbate tissue damage by secreting MMPs [106] and ROS [107], while systemic cytokine spillover contributes to comorbidities such as cardiovascular disease [108].

The spatiotemporal development of RA presents distinct therapeutic windows for interventions. At the early stage of RA, synovial infiltration by immune cells (T cells, macrophages) initiates localized inflammation [109], which progresses to synovial hyperplasia and cartilage erosion in chronic phases. Advanced stages are characterized by irreversible bone destruction and systemic complications [110]. Spatially, inflamed joints exhibit hypoxic conditions [111], acidosis (pH ∼6.0) [35], and elevated ROS levels, with immune cells distributed heterogeneously: macrophages and T cells dominate the synovial sublining, while neutrophils accumulate in synovial fluid [112].

Key stimuli in the RA microenvironment (including ROS, acidic pH, and overexpressed enzymes) provide actionable targets for spatiotemporally controlled therapies. For instance, a ROS-sensitive micelle (HA@RH-CeO_X) was designed to deliver a nanozyme and the clinically approved RA drug Rhein (RH) to pro-inflammatory M1 macrophage populations in inflamed synovial tissues [113]. The abundant cellular ROS could cleave the thioketal linker to trigger the release of RH and Ce. Similarly, in a neutrophil-mimetic nanovesicle, the neutrophil membrane ensured the enrichment of the nanovesicles in the RA joint through inflammation tropism, while catalase co-loaded with the natural anti-arthritic agent leonurine accelerated drug release from the biomimetic liposomes (Fig. 4a) [114]. On the other hand, spatial-specific drug release can also be achieved under acidic or MMP-9 enriched conditions in the RA microenvironment, as these conditions degrade the applied nanoparticles and denature the membrane coating (Fig. 4b and c) [[115], [116], [117]]. To regulate multiple cell types in RA progression, a pH- and ROS-dual-sensitive polymer was developed for RA to sequentially release drugs: first in acidic environments to promote cartilage repair, and then in macrophages to clear ROS and regulate immune pathways for synergistic therapy (Fig. 4d) [118].

Fig. 4.

a) The drug release profile of leonurine (Leo) from ROS-responsive nanomaterials at 37 °C in the presence of 50 μM H₂O₂. Reproduced with permission [114]. Copyright 2023, Wiley-VCH GmbH. b) MMP-responsive nanoparticles are selectively distributed in inflamed joints. c) MMP-responsive nanoparticles are found in inflammatory macrophages. Reproduced with permission [116]. Copyright 2021, The Author(s). d) Schematic illustration of pH-responsive (upper) and ROS-responsive (lower) drug release principles of a pH and ROS dual-sensitive polymer. Reproduced with permission [118]. Copyright 2024, Wiley-VCH GmbH. e) Degradation of ROS-responsive hydrogels in PBS and H₂O₂. Reproduced with permission [149]. Copyright 2024, Wiley-VCH GmbH. The weight remains ratio of the hydrogel in f) acid and g) acid and high-ROS-level environment. h) BMP-2 release curves from the hydrogel. Reproduced with permission [151]. Copyright 2025, Wiley-VCH GmbH.

Immunomodulatory outcomes of these materials are closely tied to their stimuli-responsive design. ROS-scavenging nanoparticles not only reduce oxidative stress but also promote macrophage polarization toward anti-inflammatory M2 phenotypes, resolving chronic inflammation. MMP-responsive systems concurrently inhibit cartilage degradation by inducing targeted apoptosis of macrophages and osteoclasts [116], as well as eliminating ROS and alleviating hypoxia [119].

2.4. Periodontitis

Periodontitis is a chronic inflammatory disease characterized by anaerobic biofilm-driven destruction of periodontal tissues, where dysregulated host immune responses exacerbate alveolar bone loss [120,121]. The pathogenesis is a spatiotemporally dynamic process, evolving from reversible gingival inflammation to irreversible connective tissue degradation and bone resorption (Table 2) [[122], [123], [124]].

Table 2.

Temporal and spatial dimensions of periodontal disease pathogenesis.

Dimension	Key characteristics	Pathological process and consequences
Temporal evolution	Microbial dysbiosis	Transition from a symbiotic flora to a dysbiotic consortium dominated by periodontal pathogens [142].
	Immune response dysregulation	Evolution from a controlled defensive response to a persistent, excessive, and destructive inflammatory response [[143], [144], [145]].
	Disease stage progression	Progression from the reversible gingivitis stage to the irreversible stage of connective tissue destruction and alveolar bone resorption [128,146].
Spatial distribution	Microbial colonization sites	Formation of spatial heterogeneity in distinct microenvironments such as the subgingival biofilm, gingival crevicular fluid, and crevicular epithelium [147].
	Immune cell infiltration	Neutrophils dominate the periodontal pocket lumen; macrophages and lymphocytes infiltrate the deeper connective tissues [131,148].

The transition from periodontal health to disease is marked by a dramatic temporal shift in the oral microbiota. A symbiotic community, rich in genera like Actinomyces and Streptococci, is displaced by a dysbiotic consortium dominated by anaerobic pathogens such as Porphyromonas gingivalis (P. gingivalis), Treponema denticola, and Tannerella forsythia [125]. This is not merely an overgrowth of individual pathogens but a state of polymicrobial synergy and dysbiosis, where the entire microbial community's ecology and function are altered, tipping the balance from homeostasis to destructive inflammation [125,126]. Critically, the disease's progression is temporally regulated by keystone pathogens like P. gingivalis, which, even at low abundance, can instigate dysbiosis and inflammatory bone loss by subverting host immunity, a process that unfolds over time in susceptible hosts [[127], [128], [129]].

The process of periodontitis exhibits distinct spatial compartmentalization. The subgingival crevice harbors microbes in niches like the tooth-associated biofilm, the gingival crevicular fluid, and the crevicular epithelium. The host immune response is spatially manipulated by the dysbiotic biofilm [130]. A key pathogenic strategy is microbial subversion of host immunity [131]. Rather than simple immunosuppression, periodontal bacteria actively manipulate immune responses to create a chronic, tissue-destructive inflammatory environment that paradoxically supplies them with nutrients. For instance, P. gingivalis can impair host defense mechanisms via complement system manipulation, neutrophil impairment, and TLR signaling subversion, enabling the overgrowth of pathobionts that drive tissue damage [[132], [133], [134]].

The pathological cascade begins with microbial dysbiosis, which triggers hyperactive neutrophil extracellular trap formation and M1 macrophage polarization [135,136]. This creates a pro-inflammatory milieu rich in interleukin-17 (IL-17), TNF-α, and IL-1β. Over time, these cytokines synergize with RANKL overexpression and inhibition of Wnt/β-catenin signaling pathways, promoting osteoclast activation and bone resorption [137,138]. The periodontal microenvironment exhibits distinct biochemical signatures, including sustained oxidative stress (O₂⁻, H₂O₂, and •OH) from hyperactivated neutrophil oxidative bursts [46,139], localized pH drops (pH ∼6.5) due to bacterial lactate fermentation [140], and elevated MMP levels in gingival crevicular fluid during active tissue degradation [141].

ISMs exploit microenvironmental cues for spatiotemporal immunomodulation. For instance, dual-responsive hydrogels combining pH- and H₂O₂-responsive degradation enable localized delivery of water-soluble polyphenol antimicrobial peptides (epigallocatechin-3-gallate) and antimicrobial agents (chlorhexidine) (Fig. 4e) [149]. The characteristic shear-thinning properties allow these hydrogels to be administered directly into the periodontal pocket, establishing an in situ drug delivery depot. Similarly, the PH/M@S hydrogel exhibits injectability, temperature sensitivity, photocrosslinkability, and hyaluronidase responsiveness, allowing it to adapt to complex therapeutic conditions within periodontal pockets [150]. These systems collapse in focus regions, minimizing off-target effects on commensal microbiota. Temporal sequentially, an injectable stimuli-responsive hydrogel achieves sequential periodontal repair by first resolving oxidative stress and inflammation under acidic and oxidative conditions to modulate the immune microenvironment, followed by the sustained release of growth factors and BMP-2 to promote bone and vessel regeneration (Fig. 4f–h) [151].

Immunomodulatory outcomes are tightly linked to spatiotemporal control. For instance, under early inflammatory conditions of periodontitis, mitochondrial calcium ion (mitoCa²⁺) overload triggers the persistent opening of mitochondrial permeability transition pores, aggravating Ca²⁺ overload and increasing ROS levels [152]. Therefore, calcium-selective chelators loaded into nanoparticles specifically manipulate mitochondrial Ca²⁺ levels through pH-responsive effects, inhibiting macrophage inflammatory activation, reducing osteoclast activity, and decreasing periodontal bone loss [153]. At the cellular level, pH-responsive antimicrobial peptide delivery systems activate the FAK/PI3K/AKT pathway and enhance the nuclear localization of YAP, promoting the osteogenic differentiation of bone mesenchymal stem cells [154].

In summary, the detailed analysis of OA, IVDD, RA, and periodontitis highlights a shared pathological foundation characterized by a microenvironmental triad: aberrant ROS accumulation, localized acidosis, and pro-inflammatory immune cell polarization. Despite their distinct etiologies, these conditions exhibit specific spatiotemporal signatures that serve as actionable triggers for ISMs. By leveraging localized pH shifts, overexpressed enzymes (such as MMPs), and oxidative stress, advanced ISMs achieve multi-scale intervention, ranging from joint-level retention to organelle-specific targeting. This on-demand approach facilitates a sophisticated therapeutic sequence: initial resolution of acute inflammation, metabolic reprogramming of immune cells, and the eventual restoration of tissue homeostasis. Beyond these four representative cases, the immunological alterations and specific examples of ISMs designed for spatiotemporal immunomodulation in other representative musculoskeletal diseases are summarized in Table 3, providing a comprehensive landscape of current research. Moving forward, the clinical translation of these technologies will require refining feedback mechanisms to ensure that therapeutic release remains perfectly synchronized with the evolving stages of the disease microenvironment.

Table 3.

Summary of ISMs-based spatiotemporal modulation strategies for addressing immunological alterations in various MSDs.

Disease	Immunological alteration	Spatiotemporal modulation by ISMs
		Spatial	Temporal
OA	Early M1-dominant synovitis & localized ROS overproduction → intermediate cartilage degradation & subchondral bone remodeling → late-stage irreversible cartilage loss & synovial fibrosis [25,75,78,155].	Intra-articular injection of NPs → specific targeting & internalization by CD44-overexpressing M1 synovial macrophages [24].	Fast-acting NO scavenging → slower, sustained CA9 gene silencing → synergistic & durable M1 → M2 repolarization [24].
Osteoporosis	Metabolism-fueled chronic inflammation spatiotemporally disrupts bone remodeling → progressive skeletal deterioration via Th17/RANKL axis [[156], [157], [158], [159]].	Minocycline-modified hyaluronic acid-targeting & pH-responsive ZOL release confined to osteolytic sites → prevents systemic γδ T cell activation [160].	On-demand drug release synchronized with pathological osteoclast activity window → minimizes off-target immune effects [160].
IVDD	M1 infiltration disrupts immune privilege → chronic inflammation; pro-inflammatory cytokines trigger self-sustaining cascade of matrix degradation, cell death, & pathological nerve/blood vessel growth [104,161].	Local injection → targeted NP cells → action on organelles (clearance of damaged mitochondria) [104].	Pathological signal (high ROS) → rapid primary response (ROS clearance) → slow secondary repair (enhanced autophagy) [104].
DND	Focal, compensatory inflammation → systemic, cytotoxic immune response → irreversible neurodegeneration [162].	Glut-1-mediated transport → crosses BBB → precise brain delivery [163].	Response to elevated ROS → nuclear localization → SNCA gene silencing (↓α-synuclein aggregates) & promotion of autophagy via TFEB [163].
RA	Autoantibody production; T-cell dysregulation (Th17 ↑/Treg ↓); B-cell activation; cytokine imbalance; immunosenescence [164,165].	Targeting peptide → accumulation in RA joints → response to MMP2/acidic pH → formation of vessel-protective nanofibers & release of RGD-exposed NPs for deep penetration & precise delivery [166].	pH- & ROS-dual-sensitive polymer: 1) Acidic environment → cartilage repair drug release; 2) In macrophages → ROS clearance & immune regulation [118].
periodontitis	Dysregulated host immune response to dysbiotic biofilms → imbalance of pro-inflammatory cytokines & RANKL-mediated bone destruction [131,167].	Macrophage membrane-cloaked NPs (MZ@PNM) → target P.g. via TLR2/1 → direct bacterial killing [168].	(Acidic/oxidative conditions) → rapid hydrogel degradation & release of antioxidative/anti-inflammatory components (M1→M2). (Repair phase) → sustained release of CGF & low-dose BMP-2 → osteogenesis & angiogenesis [151].
IAIs	Biofilm-driven, immune-evasive state → chronic low-grade inflammation, impaired phagocyte function, & suppressed adaptive immunity [169].	ROS-responsive coating on implants releases nanosheets → selective uptake by macrophages via PtdSer receptors → suppresses osteoclastogenesis [170].	pH-responsive platform: (Infection stage) → adequate Ag+ release → antibacterial activity. (Remodeling phase) → slow, stable Ag+ release → anti-inflammation & osseointegration [171].
Bone tumor	Profoundly immunosuppressive TME: dysregulated myeloid cells & impaired anti-tumor T-cell responses [172,173].	Injectable hydrogel → degradation in high-ROS TME → release of MYC inhibitor → repolarizes M2 → M1 macrophages [174].	Reshapes immunosuppressive TME → enhances anti-tumor immunity [174].
Spinal Cord Injury	Irreversible necrosis dominated by M1 macrophages & neutrophils [66].	1) Intracellular: ROS scavenging & NF-κB suppression via Fe3+-PDA-PAT chelate. 2) Extracellular: Aligned topography + SDF-1α/NGF → guides NSC recruitment & differentiation away from lesion [66].	Acute phase: mitigates inflammation → Sub-acute: sustains M2 polarization & GF release → Chronic phase: provides structural/electroconductive support for neural regeneration [66].
Muscle injury	Neutrophils & M1 macrophages → pro-inflammatory signal surge. Macrophages & fibroblasts → tissue remodeling or fibrosis [175].	Injectable in-situ scaffold → confines pro-regenerative niche at lesion site → provides localized support & concentrates therapeutic signals [176].	Quenches initial oxidative stress/inflammation → sustains pro-regenerative (M2-dominant) state → degrades in harmony with new tissue formation [176].
Tendon injury	Chronic low-grade inflammation → imbalanced MMP system → progressive ECM degradation & fibroblast dysfunction → failed repair [177].	Multi-level spatial precision targeting from the administered organ (local IVD injection) → targeted cells (nucleus pulposus cells) → action on organelles (clearance of damaged mitochondria) [177].	Pathological signal triggering (high ROS) → rapid primary response (ROS clearance) → slow secondary repair (enhanced autophagy) [177].

Abbr.: Ag⁺: Silver ions; BBB: Blood-Brain Barrier; BMP-2: Bone Morphogenetic Protein-2; CA9: Carbonic Anhydrase IX; CGF: Concentrated Growth Factors; DND: Degenerative Neurological Disease; ECM: Extracellular Matrix; GF: Growth Factor; IAIs: Implant-Associated Infections; ISM: Immunomodulatory Material; IVD: Intervertebral Disc; IVDD: Intervertebral Disc Degeneration; MAPK: Mitogen-Activated Protein Kinase; M1: Pro-inflammatory Macrophage; M2: Anti-inflammatory/Reparative Macrophage; MMP: Matrix Metalloproteinase; NF-κB: Nuclear Factor Kappa-B; NGF: Nerve Growth Factor; NP: Nanoparticle; NPs: Nucleus Pulposus Cells; NSC: Neural Stem Cell; OA: Osteoarthritis; PDA: Polydopamine; P.g.: Porphyromonas gingivalis; PtdSer: Phosphatidylserine; RA: Rheumatoid Arthritis; RANKL: Receptor Activator of Nuclear Factor Kappa-B Ligand; RGD: Arginine-Glycine-Aspartic acid peptide motif; ROS: Reactive Oxygen Species; SDF-1α: Stromal Cell-Derived Factor-1α; SNCA: Alpha-Synuclein Gene; TFEB: Transcription Factor EB; Th17: T helper 17 cell; TLR: Toll-Like Receptor; TME: Tumor Microenvironment; Treg: Regulatory T cell; ZOL: Zoledronate/Zoledronic Acid.

3. Engineering stimuli-responsive biomaterials: from mechanisms to programmability

3.1. ROS

ROS are generated through endogenous pathways (e.g., mitochondrial electron transport chain, NADPH oxidase activity) and exogenous triggers (e.g., pollutants, radiation) [178,179]. In musculoskeletal tissues, ROS play a dual role. At physiological levels (nM–μM), ROS act as critical signaling mediators in immune regulation (e.g., activation of NF-κB, Mitogen-Activated Protein Kinase (MAPK), and NLRP3 inflammasome pathways), vascular tone modulation, and redox homeostasis [180]. However, dysregulated ROS overproduction (e.g., in chronic inflammation, ischemia-reperfusion injury, or cancer) disrupts redox balance, causing oxidative damage to DNA, lipids, and proteins, which exacerbates tissue degeneration and impairs repair [181]. In MSDs (e.g., OA), excessive ROS degrade the extracellular matrix (ECM) by upregulating MMPs and suppressing chondrocyte viability [182]. This dual role—signaling vs. oxidative stress—positions ROS as a dynamic therapeutic target for immunomodulation.

To harness this potential, design strategies for ROS-responsive biomaterials focus on integrating sensitive chemical moieties into polymer backbones or scaffolds [[183], [184], [185]]. This integration enables tailored responsiveness to oxidative microenvironments, through two primary mechanisms. The first mechanism involves solubility switching (Fig. 5a). In designing these systems, strategies often include the selection of chalcogen-containing polymers (e.g., sulfur in poly (propylene sulfide) (PPS), selenium, or tellurium) via controlled polymerization techniques such as ring-opening polymerization or radical polymerization, which allow precise control over molecular weight, oxidation, and hydrophilicity changes [[186], [187], [188]]. Specifically, thioether groups in PPS oxidize to sulfoxides/sulfones, transforming hydrophobic polymers into hydrophilic networks that swell and release encapsulated drugs [182,189]. Additional design considerations involve copolymerization with hydrophilic segments (e.g., PEG) to enhance biocompatibility and modulate swelling kinetics, or surface functionalization to improve targeting to inflamed tissues [190]. In addition, selenium-based copolymers exhibit faster ROS sensitivity due to lower bond dissociation energy [191]. By precisely tuning the density and sensitivity of these responsive groups, these biomaterials can be programmed to maintain mechanical integrity under physiological conditions while rapidly transforming their physical state to promote musculoskeletal tissue repair in response to pathological oxidative stress [191,192]. The second mechanism relies on bond cleavage, where ROS-labile bonds (e.g., thioketal, phenylboronic ester) degrade under oxidative stress (Fig. 5b) [[193], [194], [195], [196]]. Design strategies here emphasize the synthesis of degradable linkages through click chemistry or condensation reactions, ensuring selective cleavage on demand [[197], [198], [199]]. For instance, thioketal-based polyurethane bone cement can be selectively resorbed by cells involved in bone remodeling in ROS-enriched bone defect areas while simultaneously providing the mechanical strength necessary for weight-bearing applications [200]. Table 4 provides a summary of applications of ROS-responsive platforms.

Fig. 5.

Designs of ISMs for various applications. a) Schematic illustration of an oxidation-sensitive thioether group for triggered drug release. Reproduced with permission [281]. Copyright 2019, American Chemical Society. b) Example of ROS-induced bond cleavage and drug release. Reproduced with permission [282]. Copyright 2024, Wiley-VCH GmbH. c) Acidic pH unstable chemical bonds and d) acid-unstable ionizable groups for pH-responsive properties. Reproduced with permission [283]. Copyright 2023, Wiley-VCH GmbH. e) Mechanisms of MMP-responsive drug release. f) A sketch showing an inflammation-regulating and temperature-responsive hydrogel for in situ delivery of stem cells for the therapy of periodontitis. Reproduced with permission [284]. Copyright 2022, Wiley-VCH GmbH. g) Representative release mechanism of a drug in response to glucose. Reproduced with permission [249]. Copyright 2022, American Chemical Society. h) Mechanisms of hypoxia-responsive drug release. i) Chemical scheme depicting mechanophore activation upon the bond rupture due to mechanical deformation. j) Resilience versus recovery time relationship of the ceramic composite sponge. k) Logic map showing relationships between dual inputs of pressure/strain, moisture content, and the output of release. Reproduced with permission [277]. Copyright 2017, The Author(s).

Table 4.

ROS-responsive platforms enabling spatiotemporal immunomodulation in MSDs.

Diseases	Materials platform	Outcome	Immunomodulation effect	Administration	Ref.
OA	Dex@polyphenol–poloxamer assembled NP	Stimuli-responsive drug release	M2 repolarization, anti-inflammatory	IM (close to the OA knee)	[201]
OA	Cationic MSN	ROS-responsive degradation of MSN-PEI	Suppressing M1 polarization of macrophages	IA	[202]
OA	ROS-responsive polymer self-assembled with AST and rapamycin (NP@PolyRHAPM)	ROS-responsive biodegradable polymer, ROS-sensitive release	M2 repolarization, anti-inflammatory	IA	[203]
OA	AST@Lip-FA	Increased cellular uptake efficiency	Efficient removal of overexpressed inflammatory mediators (ROS, nitric oxide)	IV	[204]
OA	G4-TBP NPs-FN	FN-mediated targeting, dissociation in the oxidative inflammatory microenvironment	ROS scavenging, hypoxia attenuation, and M2 polarization of macrophage	IA	[205]
OA	NP@PolyRHAPM	Reduced intracellular ROS levels	Restoration of mitochondrial membrane potential, increased GSH levels, promoted autophagy, M1 to M2 repolarization	IA	[203]
OA	Bilirubin/JPH203 self-assembled NP (IgG/BRJ)	Scavenging of ROS by released bilirubin (BR) and JPH203	Enhancement of M2/M1 ratios	IA	[206]
OA	SiO2@PP-Cur	ROS-responsive Cur conjugate release	M1 to M2 transition via Nrf2 signaling pathway activation	IA	[207]
OA	LCF-CSBN	LCF release	Promotion of M1 to M2 macrophage transition	IA	[83]
RA	DEX/HA-TK-ART micelles	Co-delivered ART&DEX in inflamed joints, ROS-responsive co-release	Macrophage repolarization by inhibition of HIF-1α/NF-κB cascade	IV	[208]
RA	PAM-HA@Sin NPs	Structure change, drug release	Downregulation of proinflammatory factors (TNF-α, IL-1β) and upregulation of anti-inflammatory factors (Arg-1, IL-10) via NF-κB pathway	IA	[209]
RA	Micelle (HA@RH-CeOX)	Thioketal linker cleavage triggers RH and Ce release	M2 repolarization, anti-inflammatory	IA	[113]
RA	Leo@CAT@NM-Lipo	Robust absorption of pro-arthritogenic cytokines and chemokines	Synergistic effects: macrophage polarization, inflammation resolution, ROS scavenging, hypoxia relief	IV	[114]
RA	FTL@SIN MNs	Targeted drug release, enhanced drug accumulation at lesion sites	Repolarization of M1 to M2 macrophages	Transdermal administration	[210]
SCI	RHNP-Cur (RVG29 and HA-Cur)	CD44 recognition increases macrophage/microglia internalization	Inhibition of inflammatory cascade, reduction of M1 microglia/macrophages, and downregulation of STAT3 pathway	IV	[67]
SCI	FCFe@PAT nanofiber felt	Upregulation of COX5A and STAT6, downregulation of IL1β, CD36, p-ERK, NFκB2, and NFκB signaling pathway proteins	Promotion of M2 macrophage polarization, downregulation of inflammatory response	Insitu application	[66]
Femoral condyle infection	Injectable programmable proanthocyanidin (PC)-coordinated zinc-based composite hydrogels (ipPZCHs)	ROS-responsive degradation/disintegration	M2 repolarization, anti-inflammatory	In situ injection	[211]
Pathological Bone Loss	Lentinan-Se (LNT-Se)	Upregulation of selenoproteins, suppression of RANKL-induced NF-κB and NFATc1 pathways	Inhibition of OC differentiation, suppression of M1 polarization, slight increase in M2 polarization via GPx1 upregulation	IP	[212]
IAIs	NP@PDA/Zn	Reduction of immune regulatory factors (IL-6, IL-1β, TNF-α)	Downregulation of M1-related cytokines, decreased M1 macrophage recruitment	SC implantation	[213]
Infected Bone Repair	Injectable programmable proanthocyanidin (PC)-coordinated zinc-based composite hydrogels (ipPZCHs)	Fast Zn2+ release	Promotion of anti-inflammatory M2 macrophage polarization	In situ injection	[211]
Osteosarcoma	IL-11/MM@NPs/Dox	Controlled release of Dox	IL-11-engineered macrophage membrane (MM) coating	IV (tail vein)	[214]
Periprosthetic Osteolysis	PPN@MNTi	Bioresponsive release of nanosheets in osteolysis microenvironment	Inhibition of NF-κB/MAPK and autophagy signaling pathways	Femur implant (In situ)	[170]

Abbr.: OA: Osteoarthritis; RA: Rheumatoid Arthritis; SCI: Spinal Cord Injury; IAI: Implant-Associated Infection; OC: Osteoclast. Dex: Dexamethasone; MSN: Mesoporous Silica Nanoparticles; NP: Nanoparticles; AST: Astaxanthin; FN: Fibronectin; BR: Bilirubin; Cur: Curcumin; LCF: Licofelone; CSBN: Chondroitin Sulfate-Bilirubin Nanomedicine; ART: Artesunate; Sin: Sinomenine; CeOX: Ceria Oxide; FTL: Fucoidan; PDA: Polydopamine; PPN: Polymeric Prodrug Nanosystem; Dox: Doxorubicin; IM: Intramuscular; IA: Intra-Articular; IV: Intravenous; IP: Intraperitoneal; SC: Subcutaneous; ROS: Reactive Oxygen Species; mito: Mitochondrial; ↑/↓: Upregulation/Downregulation; IL-10: Interleukin-10; IL-11: Interleukin-11; Arg-1: Arginase-1.

3.2. pH

pH-responsive biomaterials have emerged as versatile platforms for targeted drug delivery in musculoskeletal tissue regeneration, leveraging pH variations inherent to pathological states (e.g., tumors, infection, inflammation) and specific tissue microenvironments. These strategies dynamically adjust their structure in response to pH changes, enabling site-specific release of bioactive compounds. Common design strategies include incorporating acid-labile covalent bonds or pH-ionizable moieties such as polyacrylic acid, sulfamethazine oligomers, and polyelectrolytes like N-palmitoyl chitosan (CH) [215]. For example, an injectable CH-HAP/NaHCO₃ hydrogel exhibited excellent cell viability and proliferation as a cell carrier, though its differentiation potential across diverse cell types requires further validation [216]. Moreover, innovative composite designs include carboxymethyl chitosan-amorphous calcium phosphate hydrogels, which enhanced mesenchymal stem cell proliferation and BMP9-driven osteogenic differentiation in vitro [217]. In another study, pH-responsive GelMA-oxidized sodium alginate hydrogels loaded with gentamicin sulfate and phenamil synergistically inhibited bacterial growth and accelerated bone repair in vivo [218]. Despite these successes, challenges persist in optimizing pH sensitivity, mechanical durability, and clinical translatability. Future studies should focus on long-term biocompatibility assessments and tailoring intelligent systems to address site-specific microenvironmental complexities.

In summary, the design of pH-responsive materials involves hierarchical engineering across molecular, architectural, and systemic levels. At the molecular scale, ionizable moieties (e.g., ─COOH, ─NH₂) are strategically incorporated with tunable pKa values achieved through electron-donating/withdrawing substituents, enabling precise protonation control (Fig. 5c). Concurrently, acid-labile bonds (hydrazone, orthoester, boronate ester) are integrated to cleave within specific pH windows (e.g., boronate esters at pH 5.5–6.5) (Fig. 5d). These molecular features dictate material architectures: self-assembled nanoparticles (e.g., PEG-polyhistidine micelles disassembling at pH 6.0) exploit hydrophobic-hydrophilic transitions, while hydrogels leverage pH-triggered swelling/deswelling (e.g., methacrylic acid networks expanding at intestinal pH 7.4). For precision optimization, hybrid systems combine pH responsiveness with secondary stimuli (e.g., enzyme-cleavable segments) to achieve sequential drug release, and surface functionalization (e.g., enteric coatings dissolving at pH > 5.5) ensure site-specific activation in biological environments [219]. Table 5 provides a summary of applications of pH-responsive platforms.

Table 5.

pH-responsive platforms enabling spatiotemporal immunomodulation in MSDs.

Diseases	Materials platform	Outcome	Immunomodulation effect	Administration	Ref.
Periodontitis	Loaded BAPTA-AM into PPT nanoparticles	pH-responsive release of BAPTA-AM, which manipulates the levels of mitoCa2+ with a pH-responsive effect	Inhibit the inflammatory activation of macrophages	IP	[153]
Periodontitis with Diabetes	Controlled-release drug delivery system (GOE1): self-assembled nanoparticles (consisting of chlorhexidine acetate and epigallocatechin-3-gallate) into a hydrogel matrix composed of gelatin methacryloyl and oxidized hyaluronic acid.	PBAE degraded to release ZOL upon low pH	CHX/EGCG nanoparticles mediating M1/M2 macrophage transition and	In situ injection	[149]
IAI	PGA/Ag	ROS-responsive cationic polymer B-PDEA, NCs completely packaged pCNTF without leakage and released DNA in response to H2O2	Pro-inflammatory M1 to pro-healing M2 phenotype	In situ application	[171]
SCI	Reprogramming BMSCs with oxidation-responsive transcytosable gene-delivery nanocomplexes	pH-responsive drug release, acidic conditions degraded the MPDA nanoparticles and denatured the membrane coating	M2 repolarization, anti-inflammatory	IV	[220]
RA	Methotrexate (MTX)-human serum albumin (HSA) complex coating with pH-responsive liposome (Lipo/MTX-HSA)	ZIF8 has special stability in aqueous solution and sodium hydroxide aqueous solution, but decomposes in acidic solution	Reduce the secretion of inflammatory factors (TNF-α, IL-1β, MMP-9), regulated the unbalance of M1-type and M2-type macrophages	In situ injection	[221]
RA	Mesoporous polydopamine@Iguratimod, with Macrophage membrane	Delivering drugs specifically to inflamed joints in acidic environments	Reduce the polarization of macrophages to a pro-inflammatory M1 phenotype and inhibit differentiation into osteoclasts	IV	[115]
Osteoporosis	Nanoplatform HA-MC/CaCO3/ZOL@PBAE(micelle)-SA	Accelerating breakdown in acidic conditions with hydrogen peroxide present	Inhibition of OCs functions	IV	[160]
Osteoporosis	ZIF8-NaHCO3@Cas9	Mediates osteoblast/osteoclast coupling through inhibiting CCL3/CCR1 signaling	Promoting osteogenesis and inhibiting osteolysis	Bone marrow cavity injection	[222]

Abbr.: RA: Rheumatoid Arthritis; SCI: Spinal Cord Injury; IAI: Implant-Associated Infection; OC: Osteoclast. PPT: Polyphenol-poloxamer-thioketal; BAPTA-AM: 1,2-Bis(2-aminophenoxy)ethane-N,N,N′,N′-tetraacetic acid acetoxymethyl ester; CHX: Chlorhexidine acetate; EGCG: Epigallocatechin-3-gallate; GelMA: Gelatin methacryloyl; OHA: Oxidized hyaluronic acid; PBAE: Poly(β-amino ester); ZOL: Zoledronate; PGA: Polyglutamic acid; BMSC: Bone Marrow-derived Mesenchymal Stem Cells; MPDA: Mesoporous polydopamine; MM: Macrophage membrane; HA-MC: Hyaluronic acid-methoxy cellulose; SA: Stearic acid; NPs: Nanoparticles; mito: Mitochondrial; IA: Intra-Articular; IV: Intravenous; IP: Intraperitoneal; SC: Subcutaneous.

3.3. Enzyme

MMPs are enzymes that break down components of the extracellular matrix (ECM). They also regulate cell signaling processes critical for normal tissue functions, including repair, angiogenesis, and wound healing [223]. Abnormal MMP activity, including overactivation or excessive production, is associated with various musculoskeletal diseases, including arthritis [224], periodontitis [225], SCI [226], and IVDD [227]. For example, MMP-2 is a protease found in many tissues that breaks down ECM and cytoskeletal proteins. This activity helps regulate muscle contraction by interacting with α-myosin and troponin I. MMP-2 also plays roles in oxidative stress, cell death (through cleavage of glycogen synthase kinase-3β), and blood clotting (via talin cleavage). When working with MMP-9, MMP-2 damages blood vessel basement membranes, promoting the growth of new blood vessels. MMP-2 activation in fibroblasts and T cells depends on interactions between MMP inducers and very late activation antigen 4 (VLA-4) or vascular cellular adhesion molecule 1 (VCAM-1). These processes are controlled by tissue inhibitors of MMPs. MMP-13, another important enzyme regulated by interferon receptor pathways, mainly targets type II collagen in bone and cartilage. MMP-13 supports bone formation and remodeling through a feedback loop involving MMP-13, integrin subunit alpha 3, and RUNX2. High levels of MMP-13 are found in RA and aortic aneurysms, and genetic mutations in MMP-13 can even cause skeletal disorders like spondyloepimetaphyseal dysplasia [223].

Contemporary biomaterial design increasingly leverages dysregulated MMP activity as a pathophysiological trigger for targeted musculoskeletal therapy [228]. Representative systems employ MMP-cleavable peptide sequences—such as GPLGVRG in PEG-GPLGVRG-PAsp(DET)-cholesterol copolymers—to enable site-specific release of therapeutic payloads (e.g., miRNA-29a) within MMP-enriched microenvironments characteristic of tendinopathy or osteoarthritis fibrosis [98]. Other constructs include PEG-PVGLIG-PLA, which exploits MMP-2 substrate specificity for precision drug delivery to tumor tissue, expanding the usage of MMP-responsive intelligent systems [229]. Moreover, injectable platforms incorporating MMP-degradable motifs further demonstrate orthotopic release kinetics: localized liberation of anti-inflammatory agents or growth factors occurs exclusively during pathological MMP upregulation in RA or muscle injury models (Fig. 5e) [230].

Current MMP-responsive therapeutic strategies for musculoskeletal disorders are guided by four distinct yet synergistic mechanisms: 1) Enzymatic Cleavage: Protease-sensitive linkers employ MMP-specific peptide sequences (e.g., GPLGVRG for MMP-13, PVGLIG for MMP-2) as molecular switches. These undergo proteolytic cleavage in disease microenvironments, triggering targeted payload release, exemplified by MMP-13-responsive nanoparticles delivering miRNA-29a to suppress fibrosis in OA cartilage [223]. 2) Pathological Locus Confinement: This exploits tissue-specific MMP overexpression (e.g., MMP-3 in RA synovium). Dual pH/MMP-responsive micelles, such as the PEG–PBA–TGMS system, enable on-demand dexamethasone release at inflamed joints, enhancing therapeutic efficacy while reducing systemic exposure [219]. 3) Dynamic Carrier Reconfiguration: MMP cleavage induces structural transformations (e.g., size reduction, charge reversal) [231]. 4) Immunomodulatory Reprogramming: This delivers immune regulators (e.g., TGF-β inhibitors, resolvins) to reverse pathological signaling [232,233]. Table 6 provides a summary of applications of enzyme-responsive platforms.

Table 6.

Enzyme- and thermo-responsive platforms enabling spatiotemporal immunomodulation in MSDs.

Diseases	Material Platform	Outcome	Immunomodulation effect	Administration	Ref.
OA	HAM-SA@HCQ hydrogel microspheres	Hypoxia/MMP-13-responsive HCQ release	Macrophage inflammation ↓	IA	[235]
RA	CEL@enzyme-responsive NPs	Targeted delivery to macrophages/OCs	Apoptosis of macrophage & OCs	IV	[116]
RA	PDA/MTX@TSG lipogel	Enzyme (esterase/MMP-3)-triggered degradation	M1→M2 polarization	IA	[119]
RA	Dex-DSLip/Cro@Gel	Rapid in situ gelation	Cro inhibits OC ROS production	IA	[236]
Periodontitis	CH-BPNs-NBP thermogel	Controlled drug release	M2 polarization ↑ lymphatic function	In situ	[236,237]
Periodontitis	PH/M@S hydrogel (PF-127/HAMA/M@S)	Crosslinked ROS-scavenging matrix	Anti-inflammatory, ROS ↓	In situ	[150]

Abbr.: OA: Osteoarthritis; RA: Rheumatoid Arthritis, HCQ: Hydroxychloroquine; HAM-SA: Hyaluronic acid-methacrylate/sericin-acrylate; CEL: Celastrol; PDA: Polydopamine; MTX: Methotrexate; TSG: Triptolide-loaded stearic acid-grafted chitosan; Dex: Dexamethasone; DSLip: Deformable liposomes; Cro: Crocin I; CH: Chitosan; BPNs: Black phosphorus nanosheets; NBP: Nimodipine; PF-127: Pluronic F-127; HAMA: Hyaluronic acid methacrylate; OCs: Osteoclasts; MMP: Matrix metalloproteinase; ROS: Reactive oxygen species; ↓/↑: Decrease/Increase; IA: Intra-articular injection; IV: Intravenous injection.

3.4. Body temperature

Temperature-responsive (thermo-responsive) hydrogels are biocompatible materials that undergo structural or morphological changes in response to thermal stimuli. This property, known as thermo-responsiveness, allows materials to undergo morphological changes in response to temperature variations. This characteristic holds great potential for addressing MSDs in specific clinical scenarios, such as irregular tissue defects and critically affected regions (Fig. 5f). Consequently, many polymers with an upper critical solution temperature (UCST) or lower critical solution temperature (LCST) have been optimized for the special physiological environment (e.g., 37 °C) [234].

Positive thermos-responsive hydrogels (e.g., agar, gelatin) experience sol-gel morphological variations when the temperature decreases below the UCST; however, they are unlikely to be used for thermo-responsive applications. In contrast, some negative thermo-responsive biocompatible polymers have an LCST around physiological temperature, allowing for easy gelling and cell encapsulation in uneven musculoskeletal defects when the temperature reaches the LCST near body temperature [234]. For example, when the temperature is below the LCST, the amide moiety of PNIPAAm polymers facilitates the formation of dipole-dipole interactions and hydrogen bonds with water, causing swelling of the hydrogel network. As the temperature rises above the LCST, the weakening of amide-water interactions occurs, while the isopropyl moiety of PNIPAAm induces aggregation of the hydrogel network due to its hydrophobic nature, resulting in phase separation. Soluplus, a poly(N-vinyl caprolactam)-poly(vinyl acetate)-poly(ethylene glycol) scaffold copolymer, is commonly used in the manufacturing of thermo-induced hydrogels, solid dispersion, and pharmaceutical formulations [215].

Additionally, pluronic F127/hyaluronic acid (PF127/HA) has been utilized to fabricate temperature-induced hydrogels with characteristic micelle formation above the LCST at concentrations higher than 20%. Pluronics consist of poly(ethylene oxide)-poly(propylene oxide)-poly(ethylene oxide) (PEO-PPO-PEO) fragments, where PPO is the hydrophobic segment contributing 30% of the block copolymer and PEO is the hydrophilic segment contributing 70%. To overcome the weak mechanical properties, rapid dissolution, and short residence time of PF127, various strategies, including pluronic-based mixed polymeric micelles, pluronic-conjugated nanoparticles, and PF127-based hydrophobically modified thermogels, have been developed to overcome these limitations [234]. For instance, PF-127 has been combined with hyaluronic acid methacrylate loaded with spermidine-modified mesoporous polydopamine nanoparticles [150]. With a critical gelation temperature of approximately 32 °C, which is strategically set below physiological body temperature, the system operates through a sequence of programmable events. At ambient temperature, it exists as a free-flowing sol state, allowing it to be injected and conform to the intricate and irregular geometry of the periodontal pocket. Upon exposure to body temperature (∼37 °C), it undergoes a reversible sol-gel transition, leading to immediate in situ gelation. This phase change precisely localizes and temporarily stabilizes the hydrogel at the disease site, preventing displacement by salivary flow and, crucially, creating a vital temporal window for subsequent stabilization via ultraviolet-induced photo-crosslinking of the HAMA network [150].

Meanwhile, other copolymers, such as cyclodextrins (CDs), can be threaded by polymers like PEG to create a linear supramolecular-nanostructured complex known as a poly(pseudo)rotaxane. These threaded complexes are stabilized by strong interactions between the hydrophobic cavity of the CD and the –CH2OCH2– groups of the PEG backbone. The resulting assembly is thermosensitive, with higher temperatures driving PEG chains to de-thread from the macrocycle. Temperature thus serves as a useful parameter to tune the equilibrium of this interaction; the length of the PEG chain and the concentration of the CD species also influence the properties of the resulting assembly [234].

Despite all the merits, the spatial resolution of physio-pathological temperature-responsive materials is limited, making it difficult to distinguish between normal tissues and those with mild inflammation (which may only exhibit a temperature increase of 1–2 °C) [52]. Furthermore, factors such as individual basal body temperature and local blood flow may also affect its performance. Therefore, examples of temperature-responsive materials remain relatively scarce due to challenges in achieving precise thermal sensitivity within the narrow physiological range (37–40 °C). Table 6 provides a summary of applications of thermo-responsive platforms at body temperature.

3.5. Glucose

Glucose, a primary energy substrate, is ubiquitously present in physiological fluids, with its concentration dynamically regulated by hormones (e.g., insulin, glucagon) and metabolic demands [238]. In musculoskeletal tissues, glucose serves as a crucial nutrient for cellular metabolism, particularly for energy-intensive processes like chondrocyte matrix synthesis in cartilage and osteoblast-mediated bone formation [[239], [240], [241]]. However, dysregulated glucose levels, as seen in hyperglycemic conditions associated with diabetes mellitus, profoundly disrupt musculoskeletal homeostasis [242,243]. Chronic hyperglycemia induces non-enzymatic glycation of ECM proteins (e.g., collagen), forming AGEs that impair tissue biomechanics, promote inflammation via receptor for AGE (RAGE) signaling, and inhibit stem cell function. This ultimately leads to delayed fracture healing, accelerated OA progression, and impaired tendon repair [244,245]. This stark contrast between glucose as an essential nutrient and its detrimental effects in excess makes it a compelling, physiologically relevant stimulus for targeted immunomodulation in musculoskeletal disorders, especially those linked to diabetes.

Glucose-responsive biomaterials leverage the concentration gradient between normoglycemia and hyperglycemia to achieve spatiotemporally controlled immunomodulation, primarily utilizing three key design principles. The first principle exploits enzymatic reactions, notably involving glucose oxidase (Go_x) [246]. Immobilized GOx converts glucose into gluconic acid (pKa ≈3.86), lowering the local pH. This pH shift can trigger the swelling or dissolution of pH-sensitive polymers or the hydrolysis of acid-labile linkers, releasing encapsulated anti-inflammatory agents or pro-regenerative factors precisely within hyperglycemic, inflamed niches [247,248]. For example, a glucose-sensitive core-shell nanofiber scaffold utilizing immobilized GOx and a pH-sensitive chitosan shell triggered rhBMP-2 release in response to ambient glucose levels, effectively promoting mandible regeneration in diabetic rats [248]. The second principle relies on competitive binding, exemplified by phenylboronic acid (PBA) and its derivatives. PBA forms reversible covalent bonds with cis-diols in glucose molecules under physiological pH (Fig. 5g) [249,250]. In the diabetic bone microenvironment, increased glucose concentration competitively displaces PBA from complexes with diol-containing moieties (e.g., on a polymer backbone or a bound sugar), leading to the breakage of borate bonds and subsequent drug release [196,251,252]. By integrating these mechanisms, glucose-responsive biomaterials offer the potential to normalize dysregulated immune responses and enhance anabolic processes specifically at sites of musculoskeletal damage affected by hyperglycemia, while minimizing off-target effects.

The efficacy of glucose-responsive systems is highly context-dependent. They show promise for diabetic bone repair, but their utility in non-diabetic musculoskeletal injuries is constrained under normoglycemic conditions due to a lack of specific triggers for drug release [196]. In contrast, their application can be considered for a broader range of MSDs, given that many such conditions, even in non-diabetic patients, involve pathological glycemic fluctuations that could serve as an endogenous stimulus [253].

3.6. Hypoxia

Hypoxia arises from physiological oxygen gradients (e.g., stem cell niches) or pathological conditions (e.g., vascular damage, inflammation) in musculoskeletal tissues [254,255]. It exerts a dual regulatory role: at moderate levels, hypoxia activates HIF-1α signaling to promote angiogenesis, stem cell differentiation, and ECM remodeling—essential processes for tissue regeneration [[256], [257], [258]]. Conversely, chronic hypoxia (e.g., in RA) dysregulates immune responses, induces oxidative stress, and suppresses osteoblast and chondrocyte function by stabilizing HIF-1α and upregulating pro-inflammatory cytokines like IL-1β and TNF-α [259]. This paradoxical nature—regenerative versus degenerative—makes hypoxia a compelling target for spatiotemporal immunomodulation.

Hypoxia-responsive biomaterials leverage oxygen-depleted microenvironments through two primary strategies. The first, solubility switching, exploits hypoxia-sensitive hydrophobic motifs. Polymers functionalized with nitroimidazoles or azobenzene groups undergo reductase-mediated reduction under low O₂ tension, converting hydrophobic segments to hydrophilic states [260,261]. The second strategy, biomolecule cleavage, utilizes hypoxia-labile linkers. Azobenzene moieties are selectively cleaved by azoreductase-expressing macrophages in hypoxic inflammatory sites, while nitroaromatic groups degrade via intracellular reductases [262]. For instance, azobenzene leads to a structural change upon hypoxia-triggered reduction when it serves as a fragment or linker of amphiphilic copolymers, enabling the burst release of alendronate in ischemic metastatic bone (Fig. 5h) [263].

3.7. Mechanical force

Mechanical force is a fundamental regulator of bone health, primarily mediated through osteocytes acting as mechanosensors [264]. These cells translate mechanical stimuli (via integrins, F-actin, cilia, connexins, and ion channels) into biochemical signals (mechanotransduction) that coordinate bone remodeling by balancing osteoclast and osteoblast activity to maintain bone homeostasis [265]. Physiological loading is essential for preserving bone mass and quality, as disuse (e.g., immobilization, aging) leads to net bone loss, while moderate overload (e.g., exercise) stimulates bone gain. Disruption of this balance, involving pathways like RANK-RANKL, contributes to pathologies such as osteoporosis [266,267]. During fracture healing, mechanical force dictates the repair pathway: stable fixation with minimal interfragmentary movement promotes direct intramembranous ossification, while controlled movement induces endochondral ossification with callus formation, where the amount of cartilage depends on mechanical strain [[268], [269], [270]]. However, excessive motion due to instability risks non-union, highlighting the critical dose-dependent role of mechanical force in bone regeneration.

Compressive forces, inherent to physiological joint movement, provide an internal stimulus that can be harnessed for spatiotemporally controlled immunomodulation in bone repair [271]. Mechano-responsive materials achieve this by undergoing structural changes (e.g., hydrogel deformation, microcapsule rupture, pore collapse) under physiological loads [272,273]. These changes dynamically trigger the release of therapeutic agents (e.g., anti-inflammatory drugs, cells) from integrated depots within scaffolds [274]. For instance, covalently bound drug-loaded micelles in hydrogels, ceramics, or liposomes within crosslinked networks accelerate release specifically when compressed, while tunable microcapsules and macroporous sponges offer sequential or logic-gated delivery in response to tissue-level forces experienced during patient movement (Fig. 5i–k) [[275], [276], [277]]. This mechanism exploits the natural mechanical microenvironment of the injury site to achieve on-demand therapy. While piezoelectric and magnetic field-responsive biomaterials also respond to mechanical and electromagnetic forces, they primarily react to external stimuli and are outside the scope of this review, which focuses on internal triggers [[278], [279], [280]]. Table 7 provides a summary of applications of glucose-, hypoxia-, and mechano-responsive ISMs platforms.

Table 7.

Glucose-, hypoxia-, and mechano-responsive platforms enabling spatiotemporal immunomodulation in MSDs.

Diseases	Material Platform	Outcome	Immunomodulation Effect	Administration	Ref.
Bone defects in diabetic patients	Glucose-sensitive drug-loaded scaffold	Locally controlled delivery of TNFα antibody	Clearance of pro-inflammatory cytokines	In situ	[247]
Bone defects in diabetic patients	Core–shell nanofibers	rhBMP-2 release in real time in response to changes in ambient glucose concentrations	-	In situ	[248]
Bone metastatic prostate cancer	ALN-HR-PMs/DOX copolymers	Rapid drug release responding to hypoxic bone metastasis	Inhibiting osteoclast activity and promoting osteoblast activity	IV	[263]

Abbr.: TNFα: Tumor Necrosis Factor Alpha; rhBMP-2: Recombinant Human Bone Morphogenetic Protein-2; ALN: Alendronate; HR: Hypoxia-Responsive; PMs: Polymeric Micelles; DOX: Doxorubicin; IV: Intravenous.

The design of stimuli-responsive biomaterials is guided by the pathophysiology of the target musculoskeletal disorder. Each strategy presents a unique compromise between specificity and practicality (Table 8). ROS-responsive systems target inflammatory oxidative stress but must navigate dynamic flux to avoid disrupting redox signaling [182]. pH-responsive materials are versatile for acidic niches yet risk off-target release due to physiological pH variations [215]. Enzyme-responsive platforms offer high specificity via cleavable peptides but are challenged by inter-patient variability in protease expression [230]. Glucose-responsive strategies are uniquely suited for diabetic complications but lack broad applicability [247]. Hypoxia-responsive designs target ischemic cores yet must overcome heterogeneous oxygen gradients within lesions [260,261]. Mechano-responsive materials intelligently couple release to biomechanical loading but require precise calibration to in vivo force fields [274].

Table 8.

Comparative analysis of stimuli-responsive strategies for musculoskeletal immunomodulation.

Stimulus	Key Advantages	Main Limitations & Risks	Disease Context Applicability	Outlook & Design Considerations
ROS	High specificity for inflammatory sites [204]. Dual role: scavenging & signaling modulation [204].	Dynamic levels cause inconsistent release [[178], [179], [180]]. Over-scavenging disrupts redox signaling [[178], [179], [180]]. May be inactive during disease resolution [[178], [179], [180]].	Active phases of RA, OA, periodontitis [170,202,209].	Systems must adapt to ROS flux [[197], [198], [199]]. Combine with other strategies for sustained effect [[197], [198], [199]].
pH	Simple design, versatile formats [285]. Highly effective in strong acidity (e.g., infections, tumors) [285].	Narrow effective pH window [221]. High heterogeneity in pathological pH [221]. Premature release in normal acidic compartments [286].	Localized infections (osteomyelitis) [149,171]. Tumor microenvironments [149,171]. Periodontitis/IAI adjacent sites [149,171]	Fine-tune pKa to match target pathology. Often needs a secondary, specific trigger [286,287].
Enzyme	Exceptional biochemical specificity [219,231]. Enables precise, pathology-driven release [219,231].	Activity varies between patients [231]. Risk of off-target cleavage in circulation [231]. Requires validated substrate specificity [231].	Diseases with clear ECM degradation: advanced OA, tendinopathy, aggressive RA [[288], [289], [290]].	Select the most disease-specific enzyme isoform. Multi-enzyme systems improve reliability [219,231].
Temperature	Ideal for minimally invasive injection. Conforms to irregular defects & enables in-situ gelation [150,236,237].	Poor spatial resolution in mild inflammation [52]. Affected by basal body temperature and blood flow [52,234].	Primarily a delivery and retention mechanism. Depot formation in enclosed sites: periodontal pockets, joint cavities, bone defects [116,119,236,284,291].	Enhance stability & release kinetics post-gelation. Often integrated with chemical-responsive mechanisms [234].
Glucose	Unique trigger for diabetes-associated MSDs. (e.g., impaired fracture healing, diabetic OA). Targets a defined metabolic dysfunction [242,243].	Exclusively for hyperglycemic conditions. Ineffective in normoglycemic patients. Rapid trigger fluctuation [253].	Diabetic complications: foot ulcers, osteomyelitis, impaired bone healing [242,243].	Combine with other stimuli (e.g., pH, ROS). Ideal for closed-loop diabetic repair systems [292].
Hypoxia	Directly targets the ischemic core of tissues. Relevant to osteonecrosis, dense tumors, or poorly vascularized scar tissue [260,261].	Heterogeneous gradient within lesions [293]. potentially incomplete activation. Prolonged hypoxia hinders regenerative cell function [263].	Severe, sustained ischemia: avascular necrosis, non-union fractures, and the core of solid tumors in bone [246].	Synergistic designs (e.g., with pro-angiogenic factors) are crucial [294]. Response should match hypoxia severity to avoid targeting marginal, salvageable zones [295].
Mechanical force	Couples therapy to biomechanical environment [265]. On-demand release during tissue loading/repair in bone and cartilage [265].	Complex, dynamic, and unpredictable. Material designs risk premature release under incidental loads or insufficient release under protected loading [[274], [275], [276], [277]].	Healing of load-bearing tissues: fracture callus, OA, tendon/ligament repair [266,267].	Sophisticated material calibration required to match the specific mechanical microenvironment [[278], [279], [280]]. Future integration with feedback sensors [[278], [279], [280]].

Abbr.: ECM: Extracellular Matrix; IAI: Intra-Articular Injection; MMP: Matrix Metalloproteinase; MSDs: Musculoskeletal Disorders; OA: Osteoarthritis; pKa: Acid Dissociation Constant; RA: Rheumatoid Arthritis; ROS: Reactive Oxygen Species.

Advancing beyond single-stimulus systems requires a paradigm shift toward context-aware designs that decode the complex, evolving pathology of MSDs. The key is to engineer materials that respond not only to the presence but also to the combination, sequence, and intensity of disease-specific signals. Furthermore, to achieve true precision, release kinetics must be calibrated to the temporal dynamics of the disease, perhaps through feedback mechanisms where an initial burst of drug modulates the microenvironment, which in turn governs the rate of subsequent release. Success will hinge on the synthesis of smarter polymeric scaffolds that act as integrated diagnostic-therapeutic systems, dynamically interacting with the disease biology rather than merely reacting to a single biomarker.

4. Challenges and future perspectives

4.1. Current challenges for ISMs-based strategies

The clinical translation of intelligent biomaterials remains at an early stage, requiring significant further research and validation. As an illustrative example, an early-phase clinical trial (NCT04727385) investigated a pH-responsive hydrogel for IVDD treatment designed to target the acidic disc microenvironment. This injectable hydrogel features a dual cross-linked network based on a methacrylic acid copolymer, designed for minimally invasive implantation. While this trial represents a pivotal step toward the clinical adaptation of smart materials, its safety and long-term efficacy await confirmation.

Consequently, the clearance pathways and potential long-term toxicity of degradation byproducts from responsive materials necessitate comprehensive pharmacokinetic and toxicological evaluation. Safety considerations regarding degradation products should extend beyond the long-emphasized assessment of passive biocompatibility. A promising strategy involves actively integrating the degradation process into the therapeutic mechanism itself (e.g., leveraging the bioactive selenium compounds generated upon degradation in Se-based ROS-responsive materials) [104].

Furthermore, material accumulation and off-target effects must be addressed during the design phase. Certain nanoparticle carriers or non-degradable polymer components may accumulate in reticuloendothelial system organs, such as the liver and spleen [296]. The stability of “inactive” prodrugs in circulation and their potential for unintended activation in off-target sites with low-level stimuli must be minimized.

Moreover, sustained or potent localized immunomodulation carries a theoretical risk of impairing systemic immune surveillance, which could increase susceptibility to infections or compromise tumor immunosurveillance [297,298]. For example, the durability of induced immune phenotypes (e.g., sustained M2 polarization) and their potential for reversion or dysfunction require investigation. A solution to mitigate this risk lies in advancing the design of “closed-loop” immunomodulatory systems which will be discussed later in Section 4.2.

In addition, patient-specific variability in disease progression complicates the development of universally effective stimuli-responsive therapies. Limited long-term data on the biocompatibility and off-target effects of enzyme-responsive materials also raise safety concerns. The integration of advanced biomaterials, such as 4D-printed implants, into routine clinical practice is further impeded by high costs and insufficient infrastructure [[299], [300], [301]]. Addressing these multifaceted challenges requires interdisciplinary collaboration to refine disease models, establish regulatory benchmarks, and develop cost-effective, patient-tailored solutions [302].

4.2. Future perspectives

The field of programmable biomaterials is rapidly evolving from simple, single-stimulus responsiveness toward autonomous, intelligent systems capable of orchestrating complex regenerative processes. We envision that the next generation of these materials will not merely react to environmental changes but will interpret multifaceted biological signals to execute precise therapeutic programs. By integrating advanced computational tools, such as machine learning and single-cell bioinformatics, with sophisticated hardware like closed-loop biosensors and organoid-on-a-chip platforms, the field is moving toward a truly personalized living interface. This paradigm shift requires a move beyond static material design toward dynamic, temporally-programmed scaffolds that can co-evolve with the host's immune and regenerative stages. In this section, we delineate the critical trajectories and emerging technologies that will define the future landscape of musculoskeletal tissue engineering.

The integration of multi-stimuli-responsive systems is critical for addressing the dynamic complexity of musculoskeletal injury microenvironments (Fig. 6a). In cancer therapy, pH/glutathione (GSH) dual-responsive nanocatalysts have demonstrated spatiotemporally controlled drug release by leveraging tumor-specific acidity and GSH [303]. Similarly, ROS/pH-responsive nano-in-micro composites used in inflammatory bowel disease illustrate how sequential responses to multiple cues can optimize inflammation resolution and tissue remodeling [304]. These principles can be extrapolated to musculoskeletal repair, where inflammation-driven pH gradients, ROS overproduction, and enzyme dysregulation (e.g., MMP) could synergistically guide immunomodulatory biomaterial responses [118,285,305,306]. For example, dual-responsive hydrogels that degrade in response to both MMPs and hypoxia may enhance site-specific anti-inflammatory drug delivery while attenuating oxidative stress [87]. The development of Boolean logic-gate architectures (e.g., “AND” gates) within biomaterials could ensure that therapeutic effects are delivered only when a specific constellation of pathological markers is concurrently present, thereby narrowing the therapeutic window and minimizing off-target effects in healthy tissues [307,308]. Also, future development should strive for temporally programmed transitions, where the material's responsiveness evolves together with the shift from the acute inflammatory phase to the subsequent regenerative remodeling phase [[309], [310], [311]]. This cascade dynamic adaptability is essential for maintaining long-term homeostasis within the complex, multi-tissue interfaces of the musculoskeletal system [[312], [313], [314]]. For example, the AAT-ZCG hydrogel can respond to high glucose and ROS signals in the diabetic microenvironment to release tannic acid and a cascade nanozyme, which depletes glucose through glucose oxidase-mediated catalysis and mitigates inflammation via ROS scavenging, ultimately triggering degradation of the nanozyme to release zoledronic acid for inhibiting excessive osteoclast activation [314].

Fig. 6.

a) Schematic illustration of a spatiotemporal drug release platform based on pH/ROS-responsive hydrogel. Cleavage of Schiff base and boronic ester bonds under specific pH/ROS conditions triggers drug release. b) Schematic representation of a precision medicine strategy for musculoskeletal diseases (e.g., RA) utilizing single-cell sequencing to identify pathogenic subclusters and guide the development of targeted immunotherapy materials. c) Examples of reversible material systems. Thermoplastics (top) form static networks via crystalline interactions below their glass transition (T_g) or melting temperature (T_m), representing one pathway to reversibility through thermal triggering. Alternatively, dynamic states arise from non-covalent/supramolecular interactions governed by equilibrium bonding affinity (K_eq) and exchange rates, enabling reversibility at application-relevant timescales [328].

The advent of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics has revolutionized our understanding of the musculoskeletal microenvironment (Fig. 6b) [[315], [316], [317]]. Rather than designing materials based on bulk tissue assumptions, we can now use bioinformatics to identify specific cell populations or target genes that drive regeneration or pathology. By delineating the transcriptomic heterogeneity and pathogenic mechanisms of specific cell populations (such as effector chondrocytes and inflammatory synovial fibroblasts in OA), scRNA-seq offers critical insights into stage-specific biomarkers, facilitating the identification of new therapeutic targets and the design of precision drug delivery systems for musculoskeletal diseases [[318], [319], [320]]. The transition from single-cell data-driven target identification to precision material development is clearly illustrated in the context of RA. Specifically, researchers investigated niche and cellular characteristic changes in RA using published single-cell sequencing data, confirming that the depletion of immunoglobulin superfamily complement receptor⁺ (CRIg⁺) resident macrophages is an important feature of synovial hyperplasia, significantly contributing to the pathogenesis of RA [321]. They then generated the complement inhibitor CRIg–CD59 and used surface-mineralized ZOL to achieve targeted and sustained release of CRIg–CD59 in the acidic microenvironment of RA. This promoted the repair of the CRIg⁺ lining macrophage barrier, leading to sequential niche remodeling and significant improvement in a rat model of RA. On the other hand, a computational tool called Domino has mapped cell-cell communication networks in response to implanted biomaterials, identifying fibrotic and pro-regenerative fibroblast subpopulations [322]. With single-cell sequencing and other patient-specific biomarker tests, stimuli-responsive biomaterials are poised to enable personalized immunomodulation by aligning with patient-specific molecular profiles. Challenges include ensuring scalability and addressing inter-patient variability in immune responses.

Reversible stimuli-responsive materials can change their properties in response to stimuli such as temperature, pH, light, or magnetic fields, reverting back to their original state once the stimulus is removed (Fig. 6c) [323]. For instance, poly(N-isopropylacrylamide) is a well-known thermo-responsive polymer that undergoes a reversible sol-gel transition with temperature changes [324]. It can be engineered to deliver hormones [325], metal ions [326], or drugs [327] in a controlled manner, modulating the pathological microenvironment of bone-related diseases. This targeted delivery system could enhance the efficiency and effectiveness of bone regeneration therapies.

Closed-loop systems integrating biosensors and stimuli-responsive actuators are automatic control systems that form a complete circuit through a forward signal path and a feedback path (Fig. 7a). In neurology, implantable devices with embedded algorithms adjust deep brain stimulation parameters in real time based on local field potentials, normalizing pathological neural oscillations [329]. Recent work on glucose-responsive insulin hydrogels highlights the potential for autonomous feedback, where a transdermal polymeric microneedle patch can dynamically adjust the release of insulin and glucagon in response to blood glucose fluctuations, achieving glycemic regulation with minimized risk of hypoglycemia [330]. For musculoskeletal repair, analogous systems could combine wearable motion sensors with electrically responsive hydrogels to deliver growth factors in response to abnormal mechanical loading, thereby preventing fibrosis and fatigue [[331], [332], [333], [334]]. Challenges include minimizing latency in stimulus detection and response cycles and ensuring the biocompatibility of integrated electronics.

Fig. 7.

a) Rationale of a closed-loop control system and an example of its application in the field of musculoskeletal research [331,347]. b) Schematic illustration of patient-derived organoid platforms for the high-throughput screening and personalized modeling of responsive immunomodulatory biomaterials for bone-related diseases. c) Schematic overview of the integrated AI-driven workflow for musculoskeletal disease research and treatment, encompassing multi-modal data acquisition, machine learning-based analysis, and subsequent experimental validation. Machine learning can assist in integrating experimental data or published databases, processing and interpreting data through different algorithms, and aiding researchers in selecting candidates or parameters for experimental validation.

Organoids, defined as self-organizing three-dimensional (3D) tissue cultures derived from stem or progenitor cells, recapitulate key structural, functional, and biological complexities of native organs in vitro [335,336]. The primary benefits of organoids are their capacity to reduce reliance on in vivo animal models (aligning with the 3Rs principles: Replacement, Reduction, Refinement) and provide a more relevant, in vitro platform for testing human-specific responses. By replicating the hierarchical cellular organization, extracellular matrix interactions, and multicellular crosstalk inherent to native musculoskeletal tissues—including interactions between osteoblasts, chondrocytes, immune cells, and stromal components—organoids enable the in vitro validation of material-driven immunomodulation under pathologically relevant conditions (e.g., OA, osteoporosis, or traumatic injury) [[337], [338], [339]]. This approach facilitates the screening of material toxicity, responsiveness to endogenous stimuli (e.g., pH, ROS, or enzymatic activity), and dynamic immune cell recruitment and polarization, thereby accelerating the design of personalized immunomodulatory biomaterials tailored to individual patient phenotypes and reducing reliance on costly and ethically sensitive animal models [340,341]. Accurate control of mechanical stimulation types, intensities, and durations—including piezoelectric responses mimicking bone's natural properties under Earth's magnetic field and physiological loading—is imperative for constructing mature, functional bone organoids. This necessitates biomaterials capable of delivering multiple mechano-signals to replicate the complex bone microenvironment [265]. The integration of organoid-on-a-chip technologies with advanced biomaterial scaffolds promises further refinement in mimicking mechanical and biochemical cues critical for predictive therapeutic screening (Fig. 7b). Further consideration must be given to the biocompatibility of the scaffold materials used to support organoid growth, ensuring they do not introduce confounding variables to the results. Ethical considerations, particularly when using patient-derived induced pluripotent stem cells for organoid generation, must strictly adhere to regulatory guidelines, particularly regarding informed consent and data privacy.

The integration of data mining and machine learning into biomaterials research offers significant advantages in efficiency and discovery, fundamentally shifting the paradigm from trial-and-error to data-driven design [[342], [343], [344], [345], [346]]. The core rationale for incorporating AI/ML is the enablement of high-throughput analysis, reduction of human labor, and the ability to efficiently navigate vast and complex design spaces to accelerate the discovery of novel, optimized materials. There are four major algorithms used for machine learning-based biomaterials design: supervised learning algorithms, unsupervised learning algorithms, reinforcement learning algorithms, and neural network and deep learning algorithms (Fig. 7c).

Supervised learning algorithms, the most widely used approach for material classification and property prediction, train models on labeled data to build predictive models for new data [348]. In high-throughput screening, these studies typically adhere to a design pipeline: machine learning-based high-throughput screening, model fitting and prediction, and wet-lab validation of top candidates [349,350]. For instance, a high-throughput screening of 2176 surface topographies employed alkaline phosphatase activity assays followed by Random Forest classification/regression to identify osteogenic features [351]. Similarly, for predicting stem cell lineage fate, public RNA-seq datasets have been leveraged to train k-nearest neighbors models, which can discern early-stage biomaterial-induced cellular differentiation patterns validated against experimental biomaterial systems [352]. The adaptability of supervised learning also extends to the assessment and prediction of materials’ characteristics, optimizing hydrogel design for tendon regeneration by leveraging grouped parameters and time-resolved RNA-seq data in Random Forest and Linear Regression models [353]. In nanomaterial behavior studies, it facilitates the development of mathematical models predicting complex biological interactions, such as nanoparticle transport dynamics in tumors, which are subsequently validated experimentally [354]. This approach provides significant gains in efficiency by identifying optimal experimental parameters with limited sample groups, reducing excessive and labor-intensive experiments while correlating material properties, transcriptional responses, and functional outcomes.

In contrast to supervised methods, unsupervised learning algorithms operate without labeled data, focusing instead on uncovering inherent structures within datasets through tasks like clustering, dimensionality reduction, and anomaly detection [348]. This makes them ideal for similarity analysis, feature extraction, and exploratory data analysis in biomaterials research, particularly when dealing with complex, unlabeled datasets. For example, in a study predicting inorganic nanomaterial cellular toxicity, 8076 raw samples from public datasets and published articles were collected for data exploration and pattern identification [355]. The main benefit here is the ability to efficiently extract hidden patterns and features from large, unlabeled data sets, which would be prohibitively time-consuming or impossible for human analysts, thus enabling high-throughput data curation and knowledge extraction.

Reinforcement learning algorithms train an intelligent agent to learn optimal decision-making strategies through iterative interactions with an environment [356]. The agent receives feedback in the form of rewards or penalties and adjusts its actions to maximize cumulative long-term rewards, making reinforcement learning ideal for sequential problems like structure generation and validation in biomaterials [357]. For instance, deep reinforcement learning has been applied to inverse inorganic materials design. In this approach, the agent learns to generate distributions of functional groups on a material surface [358]. Its actions modify the group placements, while the environment evaluates outcomes (often using molecular dynamics simulations). The agent receives rewards based on how well the generated structure meets target properties and aims to maximize the expected return [359]. The key advantage of reinforcement learning is its capacity for autonomous exploration of complex design spaces, effectively automating the trial-and-error process and generating novel materials with desired functionalities far more efficiently than traditional methods.

Neural network and deep learning algorithms, inspired by the hierarchical structure of the human brain, employ multilayered architectures to autonomously extract high-level patterns from complex biomaterial data [360]. These methods excel in image recognition, feature extraction, and generative design, with key architectures including Convolutional Neural Networks (CNNs) for spatial data (e.g., microstructure imaging), Recurrent Neural Networks (RNNs) for sequential data, and deep generative models (GANs/VAEs) for novel material synthesis [348]. For instance, 3D neural networks integrated with finite element modeling enable experience-free design of architected orthopedicimplants [361]. This data-efficient machine learning method designs non-uniform, 3D-printed microstructures for orthopedic implants that experimentally achieve a 20% higher load-bearing capacity than traditional uniform designs while maintaining biocompatibility. Similarly, Generative Adversarial Networks (GANs) have enabled experience-free inverse design of architectured materials by analyzing massive simulation data of randomly generated architectures, producing configurations that approach Hashin-Shtrikman upper bounds (with porosities ranging from 0.05 to 0.75), validated via modeling and experimental results [362]. Such studies typically follow a unified pipeline: 1) converting biomaterial data (images, sequences) into structured representations; 2) training task-specific models (CNNs for topology, GANs for de novo design); and 3) multi-modal validation combining in silico simulations (e.g., molecular dynamics) and in vitro high-throughput screening [363]. By automating feature discovery and enabling predictive generation, these algorithms are shifting biomaterial design from trial-and-error toward data-driven intelligence, although challenges in data scarcity and model interpretability remain.

5. Conclusion

Current therapeutic advances are harnessing endogenous stimuli—rooted in the distinct pathological features and spatiotemporal heterogeneity of inflammatory responses, immune alterations, and tissue destruction across various diseases—to modulate immunity with precise spatial and temporal control. ISMs exemplify this approach by releasing therapeutic agents or altering their physical properties in response to disease-specific signals, thereby mitigating inflammation, limiting tissue damage, and promoting repair [10]. This targeted responsiveness enables precise immunomodulation, confining therapeutic effects to diseased tissues while minimizing off-target impact, which is crucial for effective musculoskeletal regeneration [364,365].

The strategic advantage of ISMs lies in their capacity to orchestrate multi-level immunoregulatory cascades with cellular precision and sustained control. Unlike externally activated systems, which can trigger non-specific effects, ISMs achieve reduced systemic toxicity through activation thresholds tied to the pathological microenvironment [366,367]. Crucially, ISMs move beyond the unidirectional action of exogenous systems by initiating sequential immunomodulatory circuits that target key pathological checkpoints [364,368]. This programmed coordination enables phased intervention, addressing acute inflammation, reprogramming the chronic microenvironment, and ultimately facilitating functional tissue restoration [364,368].

Research on programmable biomaterials for MSDs is rapidly progressing, offering promising regenerative strategies [369]. However, existing reviews have often focused either on specific MSD subtypes (such as OA [370] or tissue engineering [24,371]), or on general programmable platforms emphasizing controlled drug release, without systematically connecting material design to the dynamic immune microenvironment that dictates MSD progression [372]. Other notable works summarize immunoengineering biomaterials but prioritize aging-related immune senescence over the spatiotemporal evolution of immune responses during MSD pathogenesis [373].

In contrast, this review provides a focused analysis of endogenous stimuli-responsive biomaterials explicitly designed for spatiotemporal immunomodulation in MSDs. We emphasize how these materials can be programmed to interact with the dynamically shifting immune landscape across disease stages—from acute inflammation to chronic dysregulation and tissue remodeling. By integrating disease-specific immune microenvironment profiles with material design principles, this work bridges a critical gap between generalized biomaterial reviews and the immune-pathogenic intricacies specific to MSDs.

CRediT authorship contribution statement

Chao Liang: Writing – review & editing, Writing – original draft, Validation, Methodology, Investigation, Formal analysis. Jiusi Guo: Writing – review & editing, Visualization, Methodology, Investigation, Formal analysis. Wei Qiao: Writing – review & editing, Validation, Supervision, Methodology, Investigation, Formal analysis. Sang Jin Lee: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Wei Qiao is an early career editorial board member for Bioactive Materials and was not involved in the editorial review or the decision to publish this article.

Abbreviations list

MSDs

Musculoskeletal disorders

OA

Osteoarthritis

RA

Rheumatoid arthritis

IVDD

Intervertebral disc degeneration

DALYs

Disability-adjusted life years

ROS

Reactive oxygen species

ISMs

Internal stimuli-responsive materials

M1

Classically Activated Macrophage

TNF-α

Tumor necrosis factor-alpha

IL-1β

Interleukin-1β

IL-6

Interleukin-6

M2

Anti-inflammatory/reparative

CCL2

C-C motif chemokine ligand 2

NF-κB

Nuclear factor kappa-B

mTOR

Mammalian target of rapamycin

HIF-1α

Hypoxia-inducible factor 1-alpha

NLRP3

NLR family pyrin domain containing 3

CA9

Carbonic anhydrase IX

RH

Rhein

IL-17

Interleukin-17

IL-10

Interleukin-17

Arg-1

Arginase-1

β-NGF

Beta-nerve growth factor

BDNF

Brain-derived neurotrophic factor

ASIC3

Acid-sensing ion channel 3

TRPV1

Transient receptor potential vanilloid 1

CD206

Cluster of differentiation 206

YAP

Yes-associated protein

NADPH

Nicotinamide adenine dinucleotide phosphate

MAPK

Mitogen-activated protein kinase

ECM

Extracellular matrix

MMPs

Matrix metalloproteinases

PPS

Poly(propylene sulfide)

PEG

Polyethylene glycol macrophage

4D

Four-dimensional

GSH

Glutathione

scRNA-seq

Single-cell RNA sequencing

CRIg+

Complement receptor of the immunoglobulin superfamily positive

ZOL

Zoledronic acid

PNIPAM

Poly(N-isopropylacrylamide)

3D

Three-dimensional

3Rs

Replacement, Reduction, Refinement

AI

Artificial intelligence

ML

Machine learning

CNNs

Convolutional neural networks

RNNs

Recurrent neural networks

GANs

Generative adversarial networks

VAEs

Variational autoencoders

Data availability

No data was used for the research described in the article.