IL-2 Regulates Expansion of CD4+ T Cell Populations by Affecting Cell Death: Insights from Modeling CFSE Data

Ganusov, Vitaly V.; Milutinović, Dejan; Boer, Rob J. de

doi:10.4049/jimmunol.179.2.950

Cited by 51 publications

(91 citation statements)

References 51 publications

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“…This phenomenon is in accordance with previous literature reports involving T cell response to anti-CD3 stimulation with high concentrations of exogenous IL-2 (26).…”

Section: Cd4ϩ T Cells Divide In Response To Paapcs Releasing Il-2 Andsupporting

confidence: 93%

“…This is consistent with previous results demonstrating that CD4ϩ T cell expansion by IL-2 is largely regulated by the rate of cell death. IL-2 has the most dramatic influence on the rate at which the death rate increases with the division number (26). This suggests that physiologically, the mode of T cell exposure to IL-2 has a significant role in FIGURE 5.…”

Section: Discussionmentioning

confidence: 97%

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An Artificial Antigen-presenting Cell with Paracrine Delivery of IL-2 Impacts the Magnitude and Direction of the T Cell Response

Steenblock

Fadel

Labowsky

et al. 2011

Journal of Biological Chemistry

104

116

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“…This phenomenon is in accordance with previous literature reports involving T cell response to anti-CD3 stimulation with high concentrations of exogenous IL-2 (26).…”

Section: Cd4ϩ T Cells Divide In Response To Paapcs Releasing Il-2 Andsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 97%

An Artificial Antigen-presenting Cell with Paracrine Delivery of IL-2 Impacts the Magnitude and Direction of the T Cell Response

Steenblock

Fadel

Labowsky

et al. 2011

Journal of Biological Chemistry

104

116

View full text Add to dashboard Cite

“…where it is assumed that A −1 (t) = 0 for all t. It should be noted that one may alternatively compute the number of cells in the B phase as [41] …”

Section: Smith-martin Modelsmentioning

confidence: 99%

“…While the delayed gamma distribution can be derived from assumptions regarding a two-step activation process and permits the analytic solution of the model, the authors find that a lognormal distribution (3.7) is a more accurate description of cellular activation as measured by thymidine incorporation [53] and that is what is used here. The Smith-Martin model can be generalized further by considering a cell death rate which increases with division number, β i = β + (i − 1)m, for i ≥ 1 [41,53] or by considering a B phase duration which increases with division number, ∆ n = ∆ + (i − 1)m [53].…”

Section: Smith-martin Modelsmentioning

confidence: 99%

Mathematical Models of Dividing Cell Populations: Application to CFSE Data

Banks

Thompson

2012

Math. Model. Nat. Phenom.

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Abstract. Flow cytometric analysis using intracellular dyes such as CFSE is a powerful experimental tool which can be used in conjunction with mathematical modeling to quantify the dynamic behavior of a population of lymphocytes. In this survey we begin by providing an overview of the mathematically relevant aspects of the data collection procedure. We then present an overview of the large body of mathematical models, along with their assumptions and uses, which have been proposed to describe the dynamics of proliferating cell populations. While much of this body of work has been aimed at modeling the generation structure (cells per generation) of the proliferating population, several recent models have considered the more fundamental task of modeling CFSE histogram data directly. Such models are analyzed and recent results are discussed. Finally, directions for future research are suggested.

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“…There are a large number of publications in this area in which different models describe these interactions on many different scales and with differing levels of detail. For example, some people have developed large-scale (e.g., individualbased) models that describe explicitly the interactions between particular types of cells (e.g., the model of Ganusov et al [18], that captures how IL-2 regulates the expansion of the CD4+T cell population). However, in order to analyse these models it is often necessary to rely on simulation rather than analytical solutions [32].…”

Section: Introductionmentioning

confidence: 99%

Using process algebra to develop predator–prey models of within-host parasite dynamics

McCaig

Fenton

Graham

et al. 2013

Journal of Theoretical Biology

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As a first approximation of immune-mediated within-host parasite dynamics we can consider the immune response as a predator, with the parasite as its prey. In the ecological literature of predator-prey interactions there are a number of different functional responses used to describe how a predator reproduces in response to consuming prey. Until recently most of the models of the immune system that have taken a predator-prey approach have used simple mass action dynamics to capture the interaction between the immune response and the parasite. More recently Fenton and Perkins (2010) employed three of the most commonly used functional response terms from the ecological literature.In this paper we make use of a technique from computing science, process algebra, to develop mathematical models. The novelty of the process algebra approach is to allow stochastic models of the population (parasite and immune cells) to be developed from rules of individual cell behaviour. By using this approach in which individual cellular behaviour is captured we have derived a ratio-dependent response similar to that seen in previous models of immunemediated parasite dynamics, confirming that, whilst this type of term is controversial in ecological predator-prey models, it is appropriate for models of the immune system.

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IL-2 Regulates Expansion of CD4+ T Cell Populations by Affecting Cell Death: Insights from Modeling CFSE Data

Cited by 51 publications

References 51 publications

An Artificial Antigen-presenting Cell with Paracrine Delivery of IL-2 Impacts the Magnitude and Direction of the T Cell Response

An Artificial Antigen-presenting Cell with Paracrine Delivery of IL-2 Impacts the Magnitude and Direction of the T Cell Response

Mathematical Models of Dividing Cell Populations: Application to CFSE Data

Using process algebra to develop predator–prey models of within-host parasite dynamics

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