Maddy Parsons

The paper investigates the relationship between cell shape, protein expression, and tissue state using spatial imaging and machine learning, finding a bidirectional link and identifying p53-positive tumor cells.

The paper uses FLIM to measure chromatin compaction in TNBC tissues and finds that spatial chromatin states predict resistance to neoadjuvant chemotherapy.

This study develops a computational pipeline for analyzing spatial proteomics data to identify tissue states associated with chemotherapy response in TNBC, revealing distinct spatial patterns and predictive markers.

The paper introduces SMART, a spatio-molecular atlas of TNBC response trajectories, revealing distinct epithelial archetypes and tumor-immune microenvironments associated with treatment response and prognosis.

This paper develops a three-color Cascade-FRET system to measure force-dependent interactions between RIAM and vinculin in focal adhesions, revealing force-independent binding and tension-sensing capabilities.

The paper uses spatial multiomic profiling to identify distinct fibrotic epithelial niches in IPF, revealing a KRT5low/KRT17 epithelial population and its association with SPP1 macrophages.

The paper shows how in vivo topology transforms competition for cell-matrix adhesion into directional migration through Sdf1 and Sema3A interactions.