wang2015_Fig9

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Model Manuscripts

Modeling the Slow CD4+ T Cell Decline in HIV-Infected Individuals.

  • Sunpeng Wang
  • Patricia Hottz
  • Mauro Schechter
  • Libin Rong
PLoS Comput. Biol. 2015; 11 (12): 289-298
Abstract
The progressive loss of CD4+ T cell population is the hallmark of HIV-1 infection but the mechanism underlying the slow T cell decline remains unclear. Some recent studies suggested that pyroptosis, a form of programmed cell death triggered during abortive HIV infection, is associated with the release of inflammatory cytokines, which can attract more CD4+ T cells to be infected. In this paper, we developed mathematical models to study whether this mechanism can explain the time scale of CD4+ T cell decline during HIV infection. Simulations of the models showed that cytokine induced T cell movement can explain the very slow decline of CD4+ T cells within untreated patients. The long-term CD4+ T cell dynamics predicted by the models were shown to be consistent with available data from patients in Rio de Janeiro, Brazil. Highly active antiretroviral therapy has the potential to restore the CD4+ T cell population but CD4+ response depends on the effectiveness of the therapy, when the therapy is initiated, and whether there are drug sanctuary sites. The model also showed that chronic inflammation induced by pyroptosis may facilitate persistence of the HIV latent reservoir by promoting homeostatic proliferation of memory CD4+ cells. These results improve our understanding of the long-term T cell dynamics in HIV-1 infection, and support that new treatment strategies, such as the use of caspase-1 inhibitors that inhibit pyroptosis, may maintain the CD4+ T cell population and reduce the latent reservoir size.
Id Name JWS model
model0_wang2 wang2 wang2
model1_wang2 wang2 wang2
model2_wang2 wang2 wang2
model3_wang2 wang2 wang2
model4_wang2 wang2 wang2
model5_wang2 wang2 wang2
Id Name Source Number of Data Sources
Id Name Model Simulation Simulation Simulation
task0_model0_wang2 wang2 0.0 1825.0 1000
task1_model1_wang2 wang2 0.0 1825.0 1000
task2_model2_wang2 wang2 0.0 1825.0 1000
task3_model3_wang2 wang2 0.0 1825.0 1000
task4_model4_wang2 wang2 0.0 1825.0 1000
task5_model5_wang2 wang2 0.0 1825.0 1000

2D Plots

Id Name Number of Curves
Figure9_patient11 Figure 9 Patient 11 1
Figure9_patient38 Figure 9 Patient 38 1
Figure9_patient44 Figure 9 Patient 44 1
Figure9_patient3055 Figure 9 Patient 3055 1
Figure9_patient_median Figure 9 Patient Median 1
Figure9_MACS_median Figure 9 MACS Median 1

CSV Reports

Id Name Number of Columns