Literature DB >> 9176641

Modeling T-cell proliferation: an investigation of the consequences of the Hayflick limit.

S Pilyugin1, J Mittler, R Antia.   

Abstract

Somatic cells, including immune cells such as T-cells have a limited capacity for proliferation and can only replicate for a finite number of generations (known as the Hayflick limit) before dying. In this paper we use mathematical models to investigate the consequences of introducing a Hayflick limit on the dynamics of T-cells stimulated with specific antigen. We show that while the Hayflick limit does not alter the dynamics of T-cell response to antigen over the short term, it may have a profound effect on the long-term immune response. In particular we show that over the long term the Hayflick limit may be important in determining whether an immune response can be maintained to a persistent antigen (or parasite). The eventual outcome is determined by the magnitude of the Hayflick limit, the extent to which antigen reduces the input of T-cells from the thymus, and the rate of antigen-induced proliferation of T-cells. Counter to what might be expected we show that the persistence of an immune response (immune memory) requires the density of persistent antigen to be less than a defined threshold value. If the amount of persistent antigen (or parasite) is greater than this threshold value then immune memory will be relatively short lived. The consequences of this threshold for persistent mycobacterial and HIV infections and for the generation of vaccines are discussed.

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Year:  1997        PMID: 9176641     DOI: 10.1006/jtbi.1996.0319

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  7 in total

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6.  Within-host mechanisms of immune regulation explain the contrasting dynamics of two helminth species in both single and dual infections.

Authors:  Chiara Vanalli; Lorenzo Mari; Lorenzo Righetto; Renato Casagrandi; Marino Gatto; Isabella M Cattadori
Journal:  PLoS Comput Biol       Date:  2020-11-23       Impact factor: 4.475

7.  Influenza Virus Infection Model With Density Dependence Supports Biphasic Viral Decay.

Authors:  Amanda P Smith; David J Moquin; Veronika Bernhauerova; Amber M Smith
Journal:  Front Microbiol       Date:  2018-07-10       Impact factor: 5.640

  7 in total

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