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SUMMARY:Distribution-modeling quantifies collective Th cell decision circu
 its in chronic inflammation - Kevin Thurley (University of Bonn)
DTSTART:20231107T160000Z
DTEND:20231107T163000Z
UID:TALK203953@talks.cam.ac.uk
DESCRIPTION:Immune responses are tightly regulated by a diverse set of int
 eracting immune cell populations. Alongside decision-making processes such
  as differentiation into specific effector cell types\, immune cells initi
 ate proliferation at the beginning of an inflammation\, forming two layers
  of complexity. Here\, we developed a general mathematical framework for t
 he data-driven analysis of collective immune-cell dynamics\, based on a no
 n-Markovian distribution modeling approach. We identified qualitative and 
 quantitative properties of generic network motifs\, and we specified diffe
 rentiation dynamics by analysis of kinetic transcriptome data. Further\, w
 e derived a specific\, data-driven mathematical model for Th1 vs. Tfh cell
  fate-decision dynamics in acute and chronic LCMV infections in mice. Mode
 l simulations predict different windows of opportunity for perturbation in
  acute and chronic infection scenarios\, with potential implications for o
 ptimization of targeted immunotherapy.
LOCATION:Seminar Room 1\, Newton Institute
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