AI Tracks Senescent Cells

A new artificial intelligence (AI) technique combines high-resolution imaging and machine learning to track senescent cells, which are cells damaged by aging, injury or disease that no longer grow or reproduce normally. Researchers trained a computer system to analyse animal cells and recognise nuclear features indicative of senescence, including expansion, increased density and a more irregular shape. The AI analysis also revealed that the genetic material in the nucleus stained lighter than normal with standard chemical dyes.

From the AI analysis, the researchers created a nuclear morphometric pipeline (NMP) that uses the nucleus's changed physical characteristics to generate a senescent score. To validate the NMP score, researchers tested healthy and diseased mouse cells and found that older cell clusters had significantly lower NMP scores than younger cell clusters. The NMP was also effective in tracking changes in different types of cells during muscle tissue repair in young, adult, and geriatric mice. Understanding and monitoring the behaviour of senescent cells could lead to better therapeutic strategies for reversing cellular damage and improving tissue regeneration.