This invention discloses a method and
system for assessing the differentiation potential of cardiac stem cells, relating to the field of
biometrics. It is used for efficient and accurate prediction of
cell differentiation potential. Under hypoxic conditions,
continuous dynamic imaging of the mitochondrial network of a single
cardiac stem cell is performed using a live-
cell workstation. Morphometric algorithms are used to quantify
network connectivity and cristae remodeling status, establishing a single-
cell resolution mitochondrial dynamic remodeling atlas. This atlas is then spatiotemporally correlated with synchronously acquired
cellular energy metabolome data to identify specific phenotypic patterns with high differentiation potential. Based on these patterns, a multidimensional feature
training set is constructed, and a differentiation potential prediction model is established using a
random forest algorithm to screen key precursor features. Finally, the prediction model is used to
score the cells to be evaluated, and
functional verification is performed by combining single-cell mitochondrial
genome copy number variation spectra, screening for high-differentiation-potential
cardiac stem cell subpopulations, providing a precise solution for evaluating
stem cell differentiation potential.