Bartholomew Starich

This study identifies functional senescence subtypes in aging human dermal fibroblasts using single-cell morphology and machine learning, showing subtype-specific responses to senotherapies.

This study introduces qMAP, a deep learning-based workflow for microanatomical mapping of human skin, identifying 10 core processes strongly associated with aging and achieving age prediction accuracy comparable to epigenetic clocks.

This study shows that substrate stiffness affects the development and strength of senescence features in fibroblasts, with mechanosensitive regulation of key biomarkers.