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Background: The use of biomimetic peptide hydrogels represents an effective strategy to enhance the regenerative properties of adipose-derived mesenchymal stem cells (ADMSCs). The HAVDI peptide sequence, derived from the N-cadherin protein, has been shown to promote mesenchymal stem cell (MSC) proliferation and chondrogenic differentiation. Aims: In this study, we aimed to investigate the effects of an N-cadherin-mimetic microenvironment on stemness-associated features, tissue remodelling, and epithelial-mesenchymal transition (EMT)-related gene expression in ADMSCs. Methods: A two-dimensional culture environment was established using standard tissue culture plates, HAVDI-coated surfaces, and scrambled HAVDI control coatings. TLR4 activation experiments were performed using lipopolysaccharide (LPS) treatment (0.1 μg/mL for 48 h), either alone or in combination with HAVDI or SCRAM peptides. Gene expression profiles were analysed by quantitative real-time PCR, while mesenchymal stem cell surface markers (CD90, CD73, and CD105) were evaluated by flow cytometry. Immunofluorescence staining was performed for E-cadherin and vimentin, and a colony formation assay was conducted.Results: Compared with the tissue culture plate control group, the HAVDI group exhibited increased surface marker expression, with increases of 9% for CD90⁺, 8.2% for CD73⁺, and 9.2% for CD105⁺ cells. Moreover, EMT- and tissue remodelling-associated genes, including CD44, VIM, ZEB1, CDH1, MMP9, TIMP1, and CLDN1, were significantly upregulated in the HAVDI group. Compared to the TC PLATE group, the HAVDI group showed a significant increase in colony formation. TLR4 activation attenuated HAVDI-associated changes in the expression of EMT- and tissue remodelling-related genes in ADMSCs.Conclusion: Overall, the HAVDI biomimetic environment promoted stemness-associated features and modulated EMT- and tissue remodelling-related profiles in ADMSCs. Concurrent epithelial and mesenchymal marker changes suggest a context-dependent phenotype rather than classical EMT, supporting the potential of HAVDI-based platforms for regenerative applications.
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Kaçaroğlu et al. (2026) studied this question.
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