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AI-based-detection-of-T-cell-features

Protein-patterning has emerged as a powerful tool to interrogate adherent cells . Yet, there are no standard tools of fabrication, or analysis of the response of the cell to a spatially pe- riodic stimulus. We propose a technique combining electron-beam lithography and surface functionalization to fabricate nano-patterns compatible with advanced imaging. The regu- larity of the pattern is exploited by a deep-learning algorithm to reveal that T cells organize their actin network differently on patterned or homogeneously stimulating substrates - an ef- fect invisible to the unassisted human eye even after extensive image analysis. Our integrated fabrication and analysis tool-box should be useful for exploring general correlation between a spatially-structured stimulation and the cellular response.

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