Thomopoulos, S., Parks, W. C., Rifkin, D. B. & Derwin, K. A. Mechanisms of tendon injury and repair. J. Orthop. Res. 33, 832–839. https://doi.org/10.1002/jor.22806 (2015).
Google Scholar
Johanna, P. D. J. et al. The incidence of acute traumatic tendon injuries in the hand and wrist: A 10-year population-based study. Clin. Orthop. Surg. 6, 196. https://doi.org/10.4055/cios.2014.6.2.196 (2014).
Google Scholar
Sarıkaya, B. et al. Comparison of the effects of human recombinant epidermal growth factor and platelet-rich plasma on healing of rabbit patellar tendon. Eklem Hastalik. Cerrahisi Joint Dis. Relat. Surg. 28, 92–99. https://doi.org/10.5606/ehc.2017.55396 (2017).
Google Scholar
Medzhitov, R. Origin and physiological roles of inflammation. Nature 454, 428–435. https://doi.org/10.1038/nature07201 (2008).
Google Scholar
Csapo, R., Gumpenberger, M. & Wessner, B. Skeletal muscle extracellular matrix–what do we know about its composition, regulation, and physiological roles? A narrative review. Front. Physiol. 11, 253. https://doi.org/10.3389/fphys.2020.00253 (2020).
Google Scholar
Sharma, P. & Maffulli, N. Biology of tendon injury: Healing, modeling and remodeling. J. Musculoskelet. Neuronal Interact. 6, 181–190 (2006).
Pramod, B. V., Mark, R. B. & Louis, J. S. Tendon healing: Repair and regeneration. Annu. Rev. Biomed. Eng. 14, 47. https://doi.org/10.1146/annurev-bioeng-071811-150122 (2012).
Google Scholar
Dakin, S. G., Dudhia, J. & Smith, R. K. Resolving an inflammatory concept: The importance of inflammation and resolution in tendinopathy. Vet. Immunol. Immunopathol. 158, 121–127. https://doi.org/10.1016/j.vetimm.2014.01.007 (2014).
Google Scholar
Cionne, N. M. et al. The early inflammatory response after flexor tendon healing: A gene expression and histological analysis. J. Orthop. Res. 32, 645. https://doi.org/10.1002/jor.22575 (2014).
Google Scholar
Rees, J., Stride, M. & Scott, A. Tendons–time to revisit inflammation. Br. J. Sports Med. 48, 1553–1557. https://doi.org/10.1136/bjsports-2012-091957 (2014).
Google Scholar
Scott, A. et al. Tenocyte responses to mechanical loading in vivo: A role for local insulin-like growth factor 1 signaling in early tendinosis in rats. Arthritis Rheum 56, 871–881. https://doi.org/10.1002/art.22426 (2007).
Google Scholar
Cooke, J. P. Inflammation and its role in regeneration and repair. Circ. Res. 124, 1166–1168. https://doi.org/10.1161/circresaha.118.314669 (2019).
Google Scholar
Jiang, F. et al. Challenges in tendon-bone healing: Emphasizing inflammatory modulation mechanisms and treatment. Front. Endocrinol. (Lausanne) 15, 1485876. https://doi.org/10.3389/fendo.2024.1485876 (2024).
Google Scholar
Reddy, M. A. et al. Regulation of inflammatory phenotype in macrophages by a diabetes-induced long noncoding RNA. Diabetes 63, 4249–4261. https://doi.org/10.2337/db14-0298 (2014).
Google Scholar
Gao, H. et al. Regulating macrophages through immunomodulatory biomaterials is a promising strategy for promoting tendon-bone healing. J. Funct. Biomater. 13, 243. https://doi.org/10.3390/jfb13040243 (2022).
Google Scholar
Wang, J. et al. Magnesium-pretreated periosteum for promoting bone-tendon healing after anterior cruciate ligament reconstruction. Biomaterials 268, 120576. https://doi.org/10.1016/j.biomaterials.2020.120576 (2021).
Google Scholar
Wei, B. et al. BMP-2/TGF-β1 gene insertion into ligament-derived stem cells sheet promotes tendon-bone healing in a mouse. Biotechnol. J. 18, e2200470. https://doi.org/10.1002/biot.202200470 (2023).
Google Scholar
Emily, C. et al. NCBI GEO: Archive for gene expression and epigenomics data sets: 23-year update. Nucleic Acids Res. 52, 138. https://doi.org/10.1093/nar/gkad965 (2023).
Google Scholar
Haoru, D. et al. Integrated bioinformatic analysis reveals the underlying molecular mechanism of and potential drugs for pulmonary arterial hypertension. Aging (Albany NY) 13, 14234. https://doi.org/10.18632/aging.203040 (2021).
Google Scholar
Haichao, G. et al. Identification of key genes and molecular mechanisms of chronic urticaria based on bioinformatics. Skin Res. Technol. 30, e13624. https://doi.org/10.1111/srt.13624 (2024).
Google Scholar
Emil, K. G., David, Z., Regina, H. R., Sonia, G.-R. & Mina, R. ggtranscript: An R package for the visualization and interpretation of transcript isoforms using ggplot2. Bioinformatics 38, 3844. https://doi.org/10.1093/bioinformatics/btac409 (2022).
Google Scholar
Ruth, B. et al. GeneCaRNA: A comprehensive gene-centric database of human non-coding RNAs in the GeneCards suite. J. Mol. Biol. 433, 166913. https://doi.org/10.1016/j.jmb.2021.166913 (2021).
Google Scholar
Chao, L. et al. Screening and identification of NOTCH1, CDKN2A, and NOS3 as differentially expressed autophagy-related genes in erectile dysfunction. PeerJ 9, e11986. https://doi.org/10.7717/peerj.11986 (2021).
Google Scholar
Damian, S. et al. The STRING database in 2023: Protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 51, 638. https://doi.org/10.1093/nar/gkac1000 (2022).
Google Scholar
Zhengfei, M., Ping, Z., Peidong, Y. & Zhongwu, S. Identification of immune-related molecular markers in intracranial aneurysm (IA) based on machine learning and cytoscape-cytohubba plug-in. BMC Genom. Data 24, 20. https://doi.org/10.1186/s12863-023-01121-w (2023).
Google Scholar
Ali, A., Mohan, J., Nadaf, T. A. A., Ravishankar, H. & Deepa, K. R. Bioinformatics-driven discovery of signaling pathways and genes influencing cervical cancer. SN Comput. Sci. 5, 989. https://doi.org/10.1007/s42979-024-03347-6 (2024).
Google Scholar
Kanehisa, M. & Goto, S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27–30. https://doi.org/10.1093/nar/28.1.27 (2000).
Google Scholar
Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M. & Tanabe, M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 44, D457-462. https://doi.org/10.1093/nar/gkv1070 (2016).
Google Scholar
Zhou, Y. et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun. 10, 1523. https://doi.org/10.1038/s41467-019-09234-6 (2019).
Google Scholar
Simon, J. W., Maryam, A. A. & Daniel, J. H. A bioinformatics toolkit: In silico tools and online resources for investigating genetic variation. Semin. Thromb. Hemost. 45, 674 (2019).
Willi, S., Patrick, R. & Harald, B. Selection of important variables and determination of functional form for continuous predictors in multivariable model building. Stat. Med. 26, 5512. https://doi.org/10.1002/sim.3148 (2007).
Google Scholar
Saejoon, K. Margin-maximised redundancy-minimised SVM-RFE for diagnostic classification of mammograms. Int. J. Data Min. Bioinform. 10, 374. https://doi.org/10.1504/ijdmb.2014.064889 (2014).
Google Scholar
Jan, Y. et al. Machine learning analysis of motor evoked potential time series to predict disability progression in multiple sclerosis. BMC Neurol. 20, 105. https://doi.org/10.1186/s12883-020-01672-w (2020).
Google Scholar
Gaofeng, H. et al. Identification of thyroid cancer biomarkers using WGCNA and machine learning. Eur. J. Med. Res. 30, 244. https://doi.org/10.1186/s40001-025-02466-x (2025).
Google Scholar
Huang, S. et al. Applications of support vector machine (SVM) learning in cancer genomics. Cancer Genom. Proteomics 15, 41–51. https://doi.org/10.21873/cgp.20063 (2018).
Google Scholar
Breiman, L. Random forests. Mach. Learn. 45, 5–32. https://doi.org/10.1023/A:1010933404324 (2001).
Google Scholar
Shi, X. et al. Integrated bioinformatics and experiment validation reveal cuproptosis-related biomarkers and therapeutic targets in sepsis-induced myocardial dysfunction. BMC Infect. Dis. 25, 445. https://doi.org/10.1186/s12879-025-10822-9 (2025).
Google Scholar
Ling, G. & Chong-En, X. Integrated bioinformatics and machine learning algorithms reveal the critical cellular senescence-associated genes and immune infiltration in heart failure due to ischemic cardiomyopathy. Front. Immunol. 14, 1150304. https://doi.org/10.3389/fimmu.2023.1150304 (2023).
Google Scholar
Hu, X., Ni, S., Zhao, K., Qian, J. & Duan, Y. Bioinformatics-led discovery of osteoarthritis biomarkers and inflammatory infiltrates. Front. Immunol. 13, 871008. https://doi.org/10.3389/fimmu.2022.871008 (2022).
Google Scholar
Weitao, S. et al. Sangerbox: A comprehensive, interaction-friendly clinical bioinformatics analysis platform. Imeta 1, e36. https://doi.org/10.1002/imt2.36 (2022).
Google Scholar
DeMars, M. & Perruso, C. MeSH and text-word search strategies: Precision, recall, and their implications for library instruction. J. Med. Lib. Assoc. JMLA 110, 23–33. https://doi.org/10.5195/jmla.2022.1283 (2022).
Google Scholar
Jelinsky, S. A. et al. Regulation of gene expression in human tendinopathy. BMC Musculoskelet. Disord. 12, 86. https://doi.org/10.1186/1471-2474-12-86 (2011).
Google Scholar
Cheng, X. et al. Hypoxia-mimicking microenvironment scaffold for enhanced tendon regeneration. ACS Appl. Mater. Interfaces 17, 8937–8948. https://doi.org/10.1021/acsami.4c18082 (2025).
Google Scholar
Anders, O. Hereditary myosin myopathies. Neuromuscul. Disord. 17, 355. https://doi.org/10.1016/j.nmd.2007.02.008 (2007).
Google Scholar
Homa, T. & Anders, O. Myosinopathies: Pathology and mechanisms. Acta Neuropathol. 125, 3–18. https://doi.org/10.1007/s00401-012-1024-2 (2012).
Google Scholar
Gordon, A. M., Homsher, E. & Regnier, M. Regulation of contraction in striated muscle. Physiol. Rev. 80, 853. https://doi.org/10.1152/physrev.2000.80.2.853 (2000).
Google Scholar
Das, S. et al. Motor neurons and endothelial cells additively promote development and fusion of human iPSC-derived skeletal myocytes. Skelet. Muscle 14, 5. https://doi.org/10.1186/s13395-024-00336-4 (2024).
Google Scholar
Hessa, S. A. et al. MYH1 is a candidate gene for recurrent rhabdomyolysis in humans. Am. J. Med. Genet. A 185, 2131. https://doi.org/10.1002/ajmg.a.62188 (2021).
Google Scholar
Eyyup, U. et al. A homozygous MYH1 variant underlies autosomal recessive isolated recurrent rhabdomyolysis. Am. J. Med. Genet. A https://doi.org/10.1002/ajmg.a.63952 (2024).
Google Scholar
Koetsier, J. L., Amargo, E. V., Todorović, V., Green, K. J. & Godsel, L. M. Plakophilin 2 affects cell migration by modulating focal adhesion dynamics and integrin protein expression. J. Invest. Dermatol. 134, 112–122. https://doi.org/10.1038/jid.2013.266 (2014).
Google Scholar
Todorovic, V., Koetsier, J. L., Godsel, L. M. & Green, K. J. Plakophilin 3 mediates Rap1-dependent desmosome assembly and adherens junction maturation. Mol. Biol. Cell 25, 3749–3764. https://doi.org/10.1091/mbc.E14-05-0968 (2014).
Google Scholar
Kowalczyk, A. P. & Green, K. J. Structure, function, and regulation of desmosomes. Prog. Mol. Biol. Transl. Sci. 116, 95–118. https://doi.org/10.1016/b978-0-12-394311-8.00005-4 (2013).
Google Scholar
Godsel, L. M. et al. Plakophilin 2 couples actomyosin remodeling to desmosomal plaque assembly via RhoA. Mol. Biol. Cell 21, 2844–2859. https://doi.org/10.1091/mbc.E10-02-0131 (2010).
Google Scholar
Godsel, L. M. et al. Desmoplakin assembly dynamics in four dimensions: Multiple phases differentially regulated by intermediate filaments and actin. J. Cell Biol. 171, 1045–1059. https://doi.org/10.1083/jcb.200510038 (2005).
Google Scholar
Takala, T. E. & Virtanen, P. Biochemical composition of muscle extracellular matrix: The effect of loading. Scand. J. Med. Sci. Sports 10, 321–325. https://doi.org/10.1034/j.1600-0838.2000.010006321.x (2000).
Google Scholar
Mukund, K. & Subramaniam, S. Skeletal muscle: A review of molecular structure and function, in health and disease. Wiley Interdiscip. Rev. Syst. Biol. Med. 12, e1462. https://doi.org/10.1002/wsbm.1462 (2020).
Google Scholar
Humphrey, J. D., Dufresne, E. R. & Schwartz, M. A. Mechanotransduction and extracellular matrix homeostasis. Nat. Rev. Mol. Cell Biol. 15, 802–812. https://doi.org/10.1038/nrm3896 (2014).
Google Scholar
Henderson, C. A., Gomez, C. G., Novak, S. M., Mi-Mi, L. & Gregorio, C. C. Overview of the muscle cytoskeleton. Compr. Physiol. 7, 891–944. https://doi.org/10.1002/cphy.c160033 (2017).
Google Scholar
Janácek, J., Cebasek, V., Kubínová, L., Ribaric, S. & Erzen, I. 3D visualization and measurement of capillaries supplying metabolically different fiber types in the rat extensor digitorum longus muscle during denervation and reinnervation. J. Histochem. Cytochem. 57, 437–447. https://doi.org/10.1369/jhc.2008.953018 (2009).
Google Scholar
Bentzinger, C. F. et al. Fibronectin regulates Wnt7a signaling and satellite cell expansion. Cell Stem Cell 12, 75–87. https://doi.org/10.1016/j.stem.2012.09.015 (2013).
Google Scholar
Urciuolo, A. et al. Collagen VI regulates satellite cell self-renewal and muscle regeneration. Nat. Commun. 4, 1964. https://doi.org/10.1038/ncomms2964 (2013).
Google Scholar
Brack, A. S., Conboy, I. M., Conboy, M. J., Shen, J. & Rando, T. A. A temporal switch from notch to Wnt signaling in muscle stem cells is necessary for normal adult myogenesis. Cell Stem Cell 2, 50–59. https://doi.org/10.1016/j.stem.2007.10.006 (2008).
Google Scholar
Almada, A. E. & Wagers, A. J. Molecular circuitry of stem cell fate in skeletal muscle regeneration, ageing and disease. Nat. Rev. Mol. Cell Biol. 17, 267–279. https://doi.org/10.1038/nrm.2016.7 (2016).
Google Scholar
Song, X. & Qian, Y. IL-17 family cytokines mediated signaling in the pathogenesis of inflammatory diseases. Cell Signal 25, 2335–2347. https://doi.org/10.1016/j.cellsig.2013.07.021 (2013).
Google Scholar
Luo, G. et al. Polylactic acid electrospun membranes coated with chiral hierarchical-structured hydroxyapatite nanoplates promote tendon healing based on a macrophage-homeostatic modulation strategy. Bioact. Mater. 47, 460–480. https://doi.org/10.1016/j.bioactmat.2025.01.027 (2025).
Google Scholar
Zhou, S. et al. Brown adipose tissue improves angiogenesis and M2 macrophage polarization in burn wounds by activating IL-17 signaling. Plast. Reconstr. Surg. https://doi.org/10.1097/prs.0000000000011743 (2024).
Google Scholar
Roberto, D. & Kenneth, C. H. Actin structure and function. Annu. Rev. Biophys. 40, 169. https://doi.org/10.1146/annurev-biophys-042910-155359 (2011).
Google Scholar
Kayama, T. et al. Gtf2ird1-dependent mohawk expression regulates mechanosensing properties of the tendon. Mol. Cell Biol. 36, 1297–1309. https://doi.org/10.1128/mcb.00950-15 (2016).
Google Scholar
Subramanian, A., Kanzaki, L. F., Galloway, J. L. & Schilling, T. F. Mechanical force regulates tendon extracellular matrix organization and tenocyte morphogenesis through TGFbeta signaling. Elife 7, e38. https://doi.org/10.7554/eLife.38069 (2018).
Google Scholar
Eliasson, P., Andersson, T. & Aspenberg, P. Rat Achilles tendon healing: mechanical loading and gene expression. J. Appl. Physiol. 1985(107), 399–407. https://doi.org/10.1152/japplphysiol.91563.2008 (2009).
Google Scholar
Freedman, B. R. et al. Dynamic loading and tendon healing affect multiscale tendon properties and ECM stress transmission. Sci. Rep. 8, 10854. https://doi.org/10.1038/s41598-018-29060-y (2018).
Google Scholar
Yoneno, M. et al. Muscle contraction is essential for tendon healing and muscle function recovery after achilles tendon rupture and surgical repair. J. Orthop. Res. 43, 746–755. https://doi.org/10.1002/jor.26044 (2025).
Google Scholar
Diao, L. et al. Eccentric contraction enhances healing of the bone-tendon interface after rotator cuff repair in mice. Am. J. Sports Med. 51, 3835–3844. https://doi.org/10.1177/03635465231202901 (2023).
Google Scholar
Schumacher, S., Vazquez Nunez, R., Biertümpfel, C. & Mizuno, N. Bottom-up reconstitution of focal adhesion complexes. Febs. J. 289, 3360–3373. https://doi.org/10.1111/febs.16023 (2022).
Google Scholar
Revach, O. Y., Grosheva, I. & Geiger, B. Biomechanical regulation of focal adhesion and invadopodia formation. J. Cell Sci. 133, 244848. https://doi.org/10.1242/jcs.244848 (2020).
Google Scholar
Stańczak, M., Kacprzak, B. & Gawda, P. Tendon cell biology: Effect of mechanical loading. Cell Physiol. Biochem. 58, 677–701. https://doi.org/10.33594/000000743 (2024).
Google Scholar
Stańczak, M., Biały, M. & Hagner-Derengowska, M. Ligament cell biology: Effect of mechanical loading. Cell Physiol. Biochem. 59, 252–295. https://doi.org/10.33594/000000773 (2025).
Google Scholar
Oakes, P. W. & Gardel, M. L. Stressing the limits of focal adhesion mechanosensitivity. Curr. Opin. Cell Biol. 30, 68–73. https://doi.org/10.1016/j.ceb.2014.06.003 (2014).
Google Scholar
Mishra, Y. G. & Manavathi, B. Focal adhesion dynamics in cellular function and disease. Cell Signal 85, 110046. https://doi.org/10.1016/j.cellsig.2021.110046 (2021).
Google Scholar
Bosch-Fortea, M. & Martín-Belmonte, F. Mechanosensitive adhesion complexes in epithelial architecture and cancer onset. Curr. Opin. Cell Biol. 50, 42–49. https://doi.org/10.1016/j.ceb.2018.01.013 (2018).
Google Scholar
Leahy, T. P., Chenna, S. S., Soslowsky, L. J. & Dyment, N. A. Focal adhesion kinase regulates tendon cell mechanoresponse and physiological tendon development. Faseb. J. 38, e70050. https://doi.org/10.1096/fj.202400151R (2024).
Google Scholar
Dai, C. & Khalil, R. A. Calcium signaling dynamics in vascular cells and their dysregulation in vascular disease. Biomolecules 15, 892. https://doi.org/10.3390/biom15060892 (2025).
Google Scholar
Heilbrunn, L. V. & Wiercinski, F. J. The action of various cations on muscle protoplasm. J. Cell Comp. Physiol. 29, 15–32. https://doi.org/10.1002/jcp.1030290103 (1947).
Google Scholar
Alam, S., Sargeant, M. S., Patel, R. & Jayaram, P. Exploring metabolic mechanisms in calcific tendinopathy and shoulder arthrofibrosis: Insights and therapeutic implications. J. Clin. Med. 13, 6641. https://doi.org/10.3390/jcm13226641 (2024).
Google Scholar
Docheva, D., Müller, S. A., Majewski, M. & Evans, C. H. Biologics for tendon repair. Adv. Drug. Deliv. Rev. 84, 222–239. https://doi.org/10.1016/j.addr.2014.11.015 (2015).
Google Scholar
Hegedus, E. J. et al. Vascularity and tendon pathology in the rotator cuff: A review of literature and implications for rehabilitation and surgery. Br. J. Sports Med. 44, 838–847. https://doi.org/10.1136/bjsm.2008.053769 (2010).
Google Scholar
Wong, J. K. et al. The cellular biology of flexor tendon adhesion formation: An old problem in a new paradigm. Am. J. Pathol. 175, 1938–1951. https://doi.org/10.2353/ajpath.2009.090380 (2009).
Google Scholar
Sunwoo, J. Y., Eliasberg, C. D., Carballo, C. B. & Rodeo, S. A. The role of the macrophage in tendinopathy and tendon healing. J. Orthop. Res. 38, 1666–1675. https://doi.org/10.1002/jor.24667 (2020).
Google Scholar
Sugg, K. B., Lubardic, J., Gumucio, J. P. & Mendias, C. L. Changes in macrophage phenotype and induction of epithelial-to-mesenchymal transition genes following acute achilles tenotomy and repair. J. Orthop. Res. 32, 944–951. https://doi.org/10.1002/jor.22624 (2014).
Google Scholar
Marsolais, D., Côté, C. H. & Frenette, J. Neutrophils and macrophages accumulate sequentially following achilles tendon injury. J. Orthop. Res. 19, 1203–1209. https://doi.org/10.1016/s0736-0266(01)00031-6 (2001).
Google Scholar
Hays, P. et al. The role of macrophages in early healing of a tendon graft in a bone tunnel. J. Bone Joint Surg. 90, 565–579. https://doi.org/10.2106/jbjs.F.00531 (2008).
Google Scholar
Lichtnekert, J., Kawakami, T., Parks, W. & Duffield, J. Changes in macrophage phenotype as the immune response evolves. Curr. Opin. Pharmacol. 13, 555–564. https://doi.org/10.1016/j.coph.2013.05.013 (2013).
Google Scholar
Liu, M. et al. Bispecific antibody inhalation therapy for redirecting stem cells from the lungs to repair heart injury. Adv. Sci. (Weinh) 8, 2002127. https://doi.org/10.1002/advs.202002127 (2020).
Google Scholar
Sica, A. & Mantovani, A. Macrophage plasticity and polarization: In vivo veritas. J. Clin. Invest. 122, 787–795. https://doi.org/10.1172/jci59643 (2012).
Google Scholar
Mosser, D. M. & Edwards, J. P. Exploring the full spectrum of macrophage activation. Nat. Rev. Immunol. 8, 958–969. https://doi.org/10.1038/nri2448 (2008).
Google Scholar
Lu, J. et al. The functions and mechanisms of basic fibroblast growth factor in tendon repair. Front. Physiol. 13, 852795. https://doi.org/10.3389/fphys.2022.852795 (2022).
Google Scholar
Murray, P. J. & Wynn, T. A. Protective and pathogenic functions of macrophage subsets. Nat. Rev. Immunol. 11, 723–737. https://doi.org/10.1038/nri3073 (2011).
Google Scholar
Wynn, T. A. & Vannella, K. M. Macrophages in tissue repair, regeneration, and fibrosis. Immunity 44, 450–462. https://doi.org/10.1016/j.immuni.2016.02.015 (2016).
Google Scholar
Fadok, V. A. et al. Macrophages that have ingested apoptotic cells in vitro inhibit proinflammatory cytokine production through autocrine/paracrine mechanisms involving TGF-beta, PGE2, and PAF. J. Clin. Invest. 101, 890–898. https://doi.org/10.1172/jci1112 (1998).
Google Scholar
Sindrilaru, A. et al. An unrestrained proinflammatory M1 macrophage population induced by iron impairs wound healing in humans and mice. J. Clin. Invest. 121, 985–997. https://doi.org/10.1172/jci44490 (2011).
Google Scholar
Chamberlain, C. S. et al. Extracellular vesicle-educated macrophages promote early achilles tendon healing. Stem Cells 37, 652–662. https://doi.org/10.1002/stem.2988 (2019).
Google Scholar
Hu, J., Liu, S. & Fan, C. Applications of functionally-adapted hydrogels in tendon repair. Front. Bioeng. Biotechnol. 11, 1135090. https://doi.org/10.3389/fbioe.2023.1135090 (2023).
Google Scholar
Nichols, A. E. C., Best, K. T. & Loiselle, A. E. The cellular basis of fibrotic tendon healing: Challenges and opportunities. Transl. Res. 209, 156–168. https://doi.org/10.1016/j.trsl.2019.02.002 (2019).
Google Scholar
Murray, P. et al. Macrophage activation and polarization: Nomenclature and experimental guidelines. Immunity 41, 14–20. https://doi.org/10.1016/j.immuni.2014.06.008 (2014).
Google Scholar
Sun, J. et al. M2 macrophage membrane-mediated biomimetic-nanoparticle carrying COX-siRNA targeted delivery for prevention of tendon adhesions by inhibiting inflammation. Small 19, e2300326. https://doi.org/10.1002/smll.202300326 (2023).
Google Scholar
Liu, Y. et al. Mechanical stimulation improves rotator cuff tendon-bone healing via activating IL-4/JAK/STAT signaling pathway mediated macrophage M2 polarization. J. Orthop. Translat. 37, 78–88. https://doi.org/10.1016/j.jot.2022.08.008 (2022).
Google Scholar
Wang, L. et al. TGF-β1 derived from macrophages contributes to load-induced tendon-bone healing in the murine rotator cuff repair model by promoting chondrogenesis. Bone Joint Res. 12, 219–230. https://doi.org/10.1302/2046-3758.123.Bjr-2022-0368.R1 (2023).
Google Scholar
Li, Y. et al. Neutralization of excessive levels of active TGF-β1 reduces MSC recruitment and differentiation to mitigate peritendinous adhesion. Bone Res. 11, 24. https://doi.org/10.1038/s41413-023-00252-1 (2023).
Google Scholar
Xu, Z. et al. Role of low-intensity pulsed ultrasound in regulating macrophage polarization to accelerate tendon-bone interface repair. J. Orthop. Res. 41, 919–929. https://doi.org/10.1002/jor.25454 (2023).
Google Scholar
Jing, J., Qian Qian, Y., Jie, S. & You Lang, Z. Macrophages regulated by cyclooxygenases promote tendon healing via Pla1a/Etv1 axis. Chem. Eng. J. 477, 147144. https://doi.org/10.1016/j.cej.2023.147144 (2023).
Google Scholar
He, X. et al. MSC-derived exosome promotes M2 polarization and enhances cutaneous wound healing. Stem Cells Int. 2019, 7132708. https://doi.org/10.1155/2019/7132708 (2019).
Google Scholar
Chen, W. et al. Lipid nanoparticle-assisted miR29a delivery based on core-shell nanofibers improves tendon healing by cross-regulation of the immune response and matrix remodeling. Biomaterials 291, 121888. https://doi.org/10.1016/j.biomaterials.2022.121888 (2022).
Google Scholar
Brown, B. N. et al. Macrophage phenotype as a predictor of constructive remodeling following the implantation of biologically derived surgical mesh materials. Acta Biomater. 8, 978–987. https://doi.org/10.1016/j.actbio.2011.11.031 (2012).
Google Scholar
Li, Z. & Bratlie, K. M. The influence of polysaccharides-based material on macrophage phenotypes. Macromol. Biosci. 21, e2100031. https://doi.org/10.1002/mabi.202100031 (2021).
Google Scholar
Cai, J. et al. Constructing high-strength nano-micro fibrous woven scaffolds with native-like anisotropic structure and immunoregulatory function for tendon repair and regeneration. Biofabrication 15, 025002. https://doi.org/10.1088/1758-5090/acb106 (2023).
Google Scholar
Wei, Y. et al. Wnt3a-modified nanofiber scaffolds facilitate tendon healing by driving macrophage polarization during repair. ACS Appl. Mater. Interfaces https://doi.org/10.1021/acsami.2c20386 (2023).
Google Scholar
Shen, H. & Lane, R. A. Extracellular vesicles from primed adipose-derived stem cells enhance achilles tendon repair by reducing inflammation and promoting intrinsic healing. Stem Cells 41, 617–627. https://doi.org/10.1093/stmcls/sxad032 (2023).
Google Scholar
Citeroni, M. R. et al. In vitro innovation of tendon tissue engineering strategies. Int. J. Mol. Sci. 21, 6726. https://doi.org/10.3390/ijms21186726 (2020).
Google Scholar
Paredes, J. J. & Andarawis-Puri, N. Therapeutics for tendon regeneration: A multidisciplinary review of tendon research for improved healing. Ann. N. Y. Acad. Sci. 1383, 125–138. https://doi.org/10.1111/nyas.13228 (2016).
Google Scholar
Ali, A., Hulipalled, V. R., Patil, S. S. & Abdulkader, R. DPEBic: Detecting essential proteins in gene expressions using encoding and biclustering algorithm. J. Ambient. Intell. Humaniz. Comput. https://doi.org/10.1007/s12652-021-03036-9 (2021).
Google Scholar
