Ruslan M. Medzhitov

The paper shows macrophages remove protein aggregates from other cells via trogocytosis, driven by lysosomal stress and tmCSF1 signaling.

The paper identifies a conserved tissue-level stress response to proteolytic damage, characterized by heme release and oxidative stress, and shows how alveolar macrophages and fibroblasts respond to mitigate damage.

The paper uses spatial transcriptomics to analyze thyroid heterogeneity, identifying a damage-response thyrocyte state that balances with hormone-producing states across scales.

The paper develops a mathematical model to study how immune responses and metabolic pathway adaptations interact during infection, finding that glucose redistribution and cytokine regulation are critical for effective pathogen clearance.

This study identifies macrophage-derived Oncostatin M as a critical regulator of type I interferon responses during viral respiratory infection, preventing excessive inflammation.

The paper models a macrophage-myofibroblast circuit to predict fibrosis types and shows targeting the myofibroblast autocrine loop reduces fibrosis after myocardial infarction.

The paper develops a framework to analyze developmental circuits using single-cell gene expression data from the human intestine, revealing design principles of developmental programs.

This study develops an engineered whole-lung tissue model to study tissue organization and alveolar barrier function, showing improved barrier function with alveolar macrophages.

The paper develops a computational framework to study division of labor in tissues by analyzing cell interactions and spatial cues using single-cell RNA-seq and spatial transcriptomics data.

This study identifies a cell-circuit framework for wound healing and fibrosis, revealing three fibrosis outcomes and parameters that control the transition from healing to fibrosis.