ArticleScientific reports2017
Population mechanics: A mathematical framework to study T cell homeostasis.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 20 citations in OpenAlex.
- Quiescence Multiverse.Biomolecules · 2025Review
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- The coordination of anti-phage immunity mechanisms in bacterial cells.Nature communications · 2022Article
- Killing the competition: a theoretical framework for liver-stage malaria.Open biology · 2022Article
- Modeling the effect of boost timing in murine irradiated sporozoite prime-boost vaccines.PloS one · 2018Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Unlike other cell types, T cells do not form spatially arranged tissues, but move independently throughout the body. Accordingly, the number of T cells in the organism does not depend on physical constraints imposed by the shape or size of specific organs. Instead, it is determined by competition for interleukins. From the perspective of classical population dynamics, competition for resources seems to be at odds with the observed high clone diversity, leading to the so-called diversity paradox. In this work we make use of population mechanics, a non-standard theoretical approach to T cell homeostasis that accounts for clone diversity as arising from competition for interleukins. The proposed models show that carrying capacities of T cell populations naturally emerge from the balance between interleukins production and consumption. These models also suggest remarkable functional differences in the maintenance of diversity in naïve and memory pools. In particular, the distribution of memory clones would be biased towards clones activated more recently, or responding to more aggressive pathogenic threats. In contrast, permanence of naïve T cell clones would be determined by their affinity for cognate antigens. From this viewpoint, positive and negative selection can be understood as mechanisms to maximize naïve T cell diversity.
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