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Modeling Adaptive Regulatory T-Cell Dynamics during Early HIV Infection

Regulatory T-cells (Tregs) are a subset of CD4(+) T-cells that have been found to suppress the immune response. During HIV viral infection, Treg activity has been observed to have both beneficial and deleterious effects on patient recovery; however, the extent to which this is regulated is poorly un...

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Autores principales: Simonov, Michael, Rawlings, Renata A., Comment, Nick, Reed, Scott E., Shi, Xiaoyu, Nelson, Patrick W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3334930/
https://www.ncbi.nlm.nih.gov/pubmed/22536321
http://dx.doi.org/10.1371/journal.pone.0033924
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author Simonov, Michael
Rawlings, Renata A.
Comment, Nick
Reed, Scott E.
Shi, Xiaoyu
Nelson, Patrick W.
author_facet Simonov, Michael
Rawlings, Renata A.
Comment, Nick
Reed, Scott E.
Shi, Xiaoyu
Nelson, Patrick W.
author_sort Simonov, Michael
collection PubMed
description Regulatory T-cells (Tregs) are a subset of CD4(+) T-cells that have been found to suppress the immune response. During HIV viral infection, Treg activity has been observed to have both beneficial and deleterious effects on patient recovery; however, the extent to which this is regulated is poorly understood. We hypothesize that this dichotomy in behavior is attributed to Treg dynamics changing over the course of infection through the proliferation of an ‘adaptive’ Treg population which targets HIV-specific immune responses. To investigate the role Tregs play in HIV infection, a delay differatial equation model was constructed to examine (1) the possible existence of two distinct Treg populations, normal (nTregs) and adaptive (aTregs), and (2) their respective effects in limiting viral load. Sensitivity analysis was performed to test parameter regimes that show the proportionality of viral load with adaptive regulatory populations and also gave insight into the importance of downregulation of CD4(+) cells by normal Tregs on viral loads. Through the inclusion of Treg populations in the model, a diverse array of viral dynamics was found. Specifically, oscillatory and steady state behaviors were both witnessed and it was seen that the model provided a more accurate depiction of the effector cell population as compared with previous models. Through further studies of adaptive and normal Tregs, improved treatments for HIV can be constructed for patients and the viral mechanisms of infection can be further elucidated.
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spelling pubmed-33349302012-04-25 Modeling Adaptive Regulatory T-Cell Dynamics during Early HIV Infection Simonov, Michael Rawlings, Renata A. Comment, Nick Reed, Scott E. Shi, Xiaoyu Nelson, Patrick W. PLoS One Research Article Regulatory T-cells (Tregs) are a subset of CD4(+) T-cells that have been found to suppress the immune response. During HIV viral infection, Treg activity has been observed to have both beneficial and deleterious effects on patient recovery; however, the extent to which this is regulated is poorly understood. We hypothesize that this dichotomy in behavior is attributed to Treg dynamics changing over the course of infection through the proliferation of an ‘adaptive’ Treg population which targets HIV-specific immune responses. To investigate the role Tregs play in HIV infection, a delay differatial equation model was constructed to examine (1) the possible existence of two distinct Treg populations, normal (nTregs) and adaptive (aTregs), and (2) their respective effects in limiting viral load. Sensitivity analysis was performed to test parameter regimes that show the proportionality of viral load with adaptive regulatory populations and also gave insight into the importance of downregulation of CD4(+) cells by normal Tregs on viral loads. Through the inclusion of Treg populations in the model, a diverse array of viral dynamics was found. Specifically, oscillatory and steady state behaviors were both witnessed and it was seen that the model provided a more accurate depiction of the effector cell population as compared with previous models. Through further studies of adaptive and normal Tregs, improved treatments for HIV can be constructed for patients and the viral mechanisms of infection can be further elucidated. Public Library of Science 2012-04-19 /pmc/articles/PMC3334930/ /pubmed/22536321 http://dx.doi.org/10.1371/journal.pone.0033924 Text en Simonov et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Simonov, Michael
Rawlings, Renata A.
Comment, Nick
Reed, Scott E.
Shi, Xiaoyu
Nelson, Patrick W.
Modeling Adaptive Regulatory T-Cell Dynamics during Early HIV Infection
title Modeling Adaptive Regulatory T-Cell Dynamics during Early HIV Infection
title_full Modeling Adaptive Regulatory T-Cell Dynamics during Early HIV Infection
title_fullStr Modeling Adaptive Regulatory T-Cell Dynamics during Early HIV Infection
title_full_unstemmed Modeling Adaptive Regulatory T-Cell Dynamics during Early HIV Infection
title_short Modeling Adaptive Regulatory T-Cell Dynamics during Early HIV Infection
title_sort modeling adaptive regulatory t-cell dynamics during early hiv infection
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3334930/
https://www.ncbi.nlm.nih.gov/pubmed/22536321
http://dx.doi.org/10.1371/journal.pone.0033924
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