AI designs the ideal burger for taste, health, and planet
Peer-Reviewed Publication
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Objective: This commentary outlines how single-cell and multi-omic approaches can advance biomarker discovery and translational validation in exercise medicine.
Methods: The article synthesizes emerging evidence from human and animal exercise studies using single-cell RNA sequencing, single-nucleus RNA sequencing, single-cell ATAC sequencing, spatial transcriptomics and related multi-omic technologies. It focuses on skeletal muscle, immune regulation, ageing-related cellular states, chronic disease contexts and translational validation strategies.
Results: Single-cell approaches can resolve exercise-responsive cell types, cellular states, regulatory programmes and cell-cell communication that are masked by tissue-level or bulk measurements. The article highlights applications in muscle repair and fibre-type adaptation, immune redistribution and inflammatory regulation, vascular and metabolic adaptation, biological ageing and responder profiling. It proposes a pipeline that links discovery of cell-derived signatures to validation through accessible assays, including flow cytometry, targeted RNA panels, proteomics, methylation assays, immunoassays and routine clinical chemistry platforms.
Conclusions: Single-cell sequencing is best viewed as a discovery engine for precision exercise biomarkers rather than a near-term routine clinical test. Future work should combine well-defined exercise protocols, longitudinal sampling, spatial and tissue-specific profiling, physiological outcomes, human-animal comparisons and rigorous independent validation.
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