J. M. Irish

EV Fingerprinting uses flow cytometry to resolve EV heterogeneity and detect tumor-derived EVs in plasma.

This study shows that glioblastomas contacting the lateral ventricle have distinct immune features, including elevated T cell checkpoint receptors and suppressive myeloid cells, suggesting new therapeutic targets.

This study identifies how STAT1 gain-of-function variants alter T cell prevalence, metabolism, and IL-6 sensitivity in patients, revealing their role in immune dysregulation.

The paper assesses monocyte subsets in DLBCL patients, finding that nonclassical monocytes are decreased in peripheral blood and prone to migrate into tumors, correlating with adverse outcomes.

The paper identifies two new immature and dysfunctional neutrophil subsets that serve as an early blood signature for sepsis, detectable by routine flow cytometry.

This paper introduces RAPID, an unsupervised machine learning algorithm that identifies single cell phenotypes and assesses clinical risk stratification in glioblastoma patients using single cell mass cytometry data.