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Introduction: Osteoarthritis (OA), a chronic inflammatory joint disorder, still lacks effective therapeutic interventions. Consequently, the development of convenient experimental models is crucial. Recently, research has focused on the plasticity of Mesenchymal Stem/stromal Cells, particularly adipose-derived ones (ASCs), in halting OA progression. This study investigates the therapeutic potential of a cell-free approach, ASC-derived conditioned medium (CM), in reversing cytokine-induced OA markers in an ex vivo model of human cartilage explants. Methods: 4 mm cartilage punches, derived from the femoral heads of patients undergoing total hip replacement, were treated with 10 ng/ml TNFα, 1 ng/ml IL-1β, or a combination of both, over a 3-day period. Analysis of OA-related markers, such as MMP activity, the release of NO and GAGs, and the expression of PTGS2, allowed for the selection of the most effective inflammatory stimulus. Subsequently, explants challenged with TNFα+IL-1β were exposed to CM, consisting of a pool of concentrated supernatants from 72-h cultured ASCs, in order to evaluate its effect on cartilage catabolism and inflammation. Results: The 3-day treatment with both 10ng/ml TNFα and 1ng/ml IL-1β significantly increased MMP activity and NO release, without affecting GAG release. The addition of CM significantly downregulated the abnormal MMP activity induced by the inflammatory stimuli, while also mildly reducing MMP3, MMP13, and PTGS2 gene expression. Finally, SOX9 and COL2A1 were downregulated by the cytokines, and further decreased by CM. Conclusion: The proposed cartilage explant model offers encouraging evidence of the therapeutic potential of ASC-derived CM against OA, and it could serve as a convenient ex vivo platform for drug screening.

While advanced imaging strategies have improved the diagnosis of bone-related pathologies, early signs of bone alterations remain difficult to detect. The Covid-19 pandemic has brought attention to the need for a better understanding of bone micro-scale toughening and weakening phenomena. This study used an artificial intelligence-based tool to automatically investigate and validate four clinical hypotheses by examining osteocyte lacunae on a large scale with synchrotron image-guided failure assessment. The findings indicate that trabecular bone features exhibit intrinsic variability related to external loading, micro-scale bone characteristics affect fracture initiation and propagation, osteoporosis signs can be detected at the micro-scale through changes in osteocyte lacunar features, and Covid-19 worsens micro-scale porosities in a statistically significant manner similar to the osteoporotic condition. Incorporating these findings with existing clinical and diagnostic tools could prevent micro-scale damages from progressing into critical fractures.