Label-free AI-enabled Imaging Flow Cytometry for Discovery of Subpopulations of Extravillous Trophoblast from a Stem Cell-based Model of Trophoblast Differentiation

AI-powered cell imaging may help researchers identify biological differences that are difficult or impossible to see by eye. Yu-Hwa Lo, Ph.D., and Louise Laurent, M.D., Ph.D., describe a system that combines high-speed imaging, cell sorting, microfluidics, and artificial intelligence. The technology creates label-free images of cells, uses AI to classify them, and can isolate selected cells for deeper molecular analysis. Laurent explains how the team is applying the system to human trophoblast stem cells, which give rise to specialized placental cells involved in nutrient transport, hormone production, blood vessel remodeling, and immune regulation. Lo describes how AI can distinguish cell populations and identify features that may not be apparent to human observers. The researchers ultimately hope to connect imaging features with gene expression, proteins, and metabolism, allowing cell characteristics and behavior to be predicted from images alone. Series: "Motherhood Channel" [Health and Medicine] [Show ID: 41637]