"Machine learning-based classification of dual fluorescence signals reveals muscle stem cell fate transitions in response to regenerative niche factors" published in NPJ Regenerative Medicine
Figure from Togninalli et al.
Muscle stem cells (MuSCs) reside in a niche, which generates various signals essential for regeneration of skeletal muscle. In this manuscript, Togninalli, Ho, and Madl developed a dual fluorescence imaging time lapse (Dual-FLIT) microscopy approach that leverages machine learning to track single cell fate decisions. Intriguingly, their analysis revealed that the lipid metabolite, prostaglandin E2, accelerates the rate of MuSC proliferation, biasing division events toward symmetric self-renewal. In contrast, Oncostatin M decreases proliferation rate after the first generation, blocking myogenic commitment. Future applications of this technology will expand our understanding of how niche factors control tissue regeneration.