Maria Carolina Florian

The paper uses single-cell RNA sequencing to analyze somatic mutations in HSCs and finds age-related clonal expansion and transcriptional divergence.

This paper develops a deep learning model to predict haematopoietic stem cell ageing from 3D chromatin images, achieving an AUROC of 0.77 and identifying key chromatin features as predictive markers.

The paper uses deep learning to link TP53 genotype with expression-defined transcriptional programs in AML, finding a strong correlation between p53-low expression and TP53-inactive genotypes.

This study shows that reducing RhoA activity in aged HSCs lowers nuclear tension, restores chromatin structure, and improves regenerative capacity and lineage balance.

The paper identifies NOTCH1-JAG1 cis interactions regulated by RADICAL FRINGE that maintain hematopoietic stem cell fate during development.

This study identifies a Cdc42-Borg4-Sep7 axis that regulates HSC polarity and function by controlling the polar distribution of these proteins and affecting engraftment potential and LMPP frequency.

This study develops an in-silico model to explore how hematopoietic stem cells (HSCs) respond to varying demands and aging, showing that internal feedback between HSCs and progenitors explains homeostasis and aging-related changes.