Literature DB >> 10973282

A cellular calculus for signal integration by T cells.

A V Gett1, P D Hodgkin.   

Abstract

During an immune response numerous receptor-mediated signals delivered to T cells direct their proliferation, survival and differentiation. Here, we describe a quantitative model and in vitro methods for assessing the "calculus" used by T cells to process these multiple signals. The model reveals how T cells convert independently received signals into linear additive effects on division times which, in turn, amplify T cell number exponentially. These results explain why so many ligands can each appear obligatory for T cell activation and argue for a re-examination of the two-signal theory as the basis for decisions between tolerance and activation.

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Year:  2000        PMID: 10973282     DOI: 10.1038/79782

Source DB:  PubMed          Journal:  Nat Immunol        ISSN: 1529-2908            Impact factor:   25.606


  79 in total

1.  Toward rigorous comprehension of biological complexity: modeling, execution, and visualization of thymic T-cell maturation.

Authors:  Sol Efroni; David Harel; Irun R Cohen
Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

2.  Kinetics of virus-specific CD8+ T cells and the control of human immunodeficiency virus infection.

Authors:  Miles P Davenport; Ruy M Ribeiro; Alan S Perelson
Journal:  J Virol       Date:  2004-09       Impact factor: 5.103

Review 3.  Mapping the life histories of T cells.

Authors:  Ton N M Schumacher; Carmen Gerlach; Jeroen W J van Heijst
Journal:  Nat Rev Immunol       Date:  2010-08-06       Impact factor: 53.106

Review 4.  Immunology and mathematics: crossing the divide.

Authors:  Robin E Callard; Andrew J Yates
Journal:  Immunology       Date:  2005-05       Impact factor: 7.397

5.  Quantifying lymphocyte kinetics in vivo using carboxyfluorescein diacetate succinimidyl ester (CFSE).

Authors:  Becca Asquith; Christophe Debacq; Arnaud Florins; Nicolas Gillet; Teresa Sanchez-Alcaraz; Angelina Mosley; Luc Willems
Journal:  Proc Biol Sci       Date:  2006-05-07       Impact factor: 5.349

6.  Modelling cell lifespan and proliferation: is likelihood to die or to divide independent of age?

Authors:  Mark R Dowling; Dejan Milutinović; Philip D Hodgkin
Journal:  J R Soc Interface       Date:  2005-12-22       Impact factor: 4.118

7.  Computational analysis of CFSE proliferation assay.

Authors:  Tatyana Luzyanina; Sonja Mrusek; John T Edwards; Dirk Roose; Stephan Ehl; Gennady Bocharov
Journal:  J Math Biol       Date:  2006-11-09       Impact factor: 2.259

Review 8.  mTOR at the crossroads of T cell proliferation and tolerance.

Authors:  Anna Mondino; Daniel L Mueller
Journal:  Semin Immunol       Date:  2007-03-23       Impact factor: 11.130

9.  Determining the expected variability of immune responses using the cyton model.

Authors:  Vijay G Subramanian; Ken R Duffy; Marian L Turner; Philip D Hodgkin
Journal:  J Math Biol       Date:  2007-11-03       Impact factor: 2.259

10.  A model of immune regulation as a consequence of randomized lymphocyte division and death times.

Authors:  E D Hawkins; M L Turner; M R Dowling; C van Gend; P D Hodgkin
Journal:  Proc Natl Acad Sci U S A       Date:  2007-03-14       Impact factor: 11.205

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