Article

Nuclear morphology is a deep learning biomarker of senescence across tissues and species

2021-11-11

Abstract excerpt

<title>Abstract</title> <p>Cellular senescence is a critical component of aging and many age-related diseases, but understanding its role in human health is challenging in part due to the lack of exclusive or universal markers. Using neural networks, we achieve high accuracy in predicting senescence state and type from the nuclear morphology of DAPI-stained human fibroblasts, murine astrocytes, murine neurons, an...

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Literature Corpus work: 46156b40-276b-518a-b239-99d96774e873
DOI: 10.21203/rs.3.rs-1017512/v1

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