Effect of spatial distribution of T-Cells and HIV load on HIV progression

Graziano, Frank M.; Kettoola, Samira Y.; Munshower, Judy; Stapleton, Jack T.; Towfic, George

doi:10.1093/bioinformatics/btn008

Cited by 6 publications

(8 citation statements)

References 12 publications

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“…Many online HIV databases such as (Los Alamos National Laboratory, Rhee et al, 2003;Graziano et. al., 2008; NIAID Division of AIDS, University of California; San Francisco, HIV InSite) are available to obtain mutation frequencies and positions due to drug resistance.…”

Section: Research Objectives and Relevant Analysis Toolsmentioning

confidence: 99%

“…Analyses tools are provided in most online databases to obtain relevant correlations such as genotype-treatment correlations, genotype-clinical correlations, and genotypephenotype correlations. Main objectives for using online databases would be to obtain underlying data and references that show which mutations cause resistance and to which drugs (Rhee et al, 2003), obtain statistical analyses such as correlations between CD4 and RNA levels for considered treatments (Graziano et al, 2008), obtaining rate of change of CD4 and RNA levels based on base CD4 count at the start of a considered patient or a considered therapy, and obtain rate of change CD4 and RNA levels based on preceding CD4 counts for a considered patient or a considered therapy (Graziano et al, 2008).…”

Section: Research Objectives and Relevant Analysis Toolsmentioning

confidence: 99%

See 1 more Smart Citation

Genetic Mutations Affecting the Success and Failure of HIV Regimens

Towfic¹,

Munshower²,

Kettoola³

et al. 2009

J Proteomics Bioinform

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Section: Research Objectives and Relevant Analysis Toolsmentioning

confidence: 99%

Section: Research Objectives and Relevant Analysis Toolsmentioning

confidence: 99%

Genetic Mutations Affecting the Success and Failure of HIV Regimens

Towfic¹,

Munshower²,

Kettoola³

et al. 2009

J Proteomics Bioinform

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Section: Introduction 1inflammation In Viral Infectionsmentioning

confidence: 99%

“…There are various models of immune response that take into account cellular kinetics [8][9][10][11][12][13] and different parts of the innate or adaptive immune response. As such, interferon dynamics is taken into account in [8,10,11,13], while some parts of the adaptive immune response are modeled in references [8,9,12,13]. The influence of inflammatory mediators is indirectly considered in model [14] through the death coefficients in equations for the concentrations of virus and infected cells.…”

Section: Introduction 1inflammation In Viral Infectionsmentioning

confidence: 99%

Modeling of Viral Infection with Inflammation

Mozokhina,

Ait Mahiout,

Volpert

2023

Mathematics

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Viral infection spreads in cell culture or tissue as a reaction–diffusion wave. It is characterized by three main parameters: virus replication number, Rv, which determines whether infection progresses, wave speed, c, which correlates with the virus virulence, and viral load, J(v), which determines the infection transmission rate. In this work, we study how the inflammation triggered by viral infection influences its progression. We obtain analytical expressions for Rv,c, and J(v) and show how they depend on the intensity of inflammation characterized by one or two parameters. Analytical and numerical results show that inflammation decreases the viral replication number, virus virulence, and infectivity, though there are different cases depending on the parameters of the model.

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“…Mathematical modeling is widely used for the investigation of viral infections [8,11,[16][17][18]. It allows the identification of parameters and conditions of the viral infection spreading, which can be difficult to identify in the experiments, and evaluation of the influence of the immune response and of medical treatment on the infection progression.…”

Section: Introductionmentioning

confidence: 99%

The Influence of Immune Response on Spreading of Viral Infection

Mahiout

Mozokhina

Tokarev

et al. 2022

Lobachevskii J Math

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In this work we develop a model of viral infection in host tissues in order to study the influence of the immune response on the infection spreading speed and on the viral load characterizing, respectively, severity of symptoms and infection transmission rate. Dynamics of the interaction between viral infection and the immune response is studied with nonlocal reaction-diffusion equations for the concentrations of virus, interferon, immune cells and antibodies. Analytical results for infection spreading speed and viral load are completed by numerical simulations. At the first stage, progression of viral infection is confronted by the innate immune response mostly determined by the local interferon production. The modeling results show in this case that infection spreading speed does not depend on interferon concentration, while the total viral load decreases with the increase of its concentration. Next, we consider the influence of globally circulating interferon and show that, in contrast to local interferon diffusion, infection spreading speed decreases with increasing of global interferon level, and the total viral load also decreases. At the next stage, adaptive immune response mediated by antibodies and cytotoxic T cells (CTL) further influences infection progression. In this case, the infection propagation speed and the total viral load are decreased by the immune response. The humoral adaptive response (antibodies) increases the global interferon concentration through the viral load, while the cellular adaptive response (CTL) decreases it.

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Effect of spatial distribution of T-Cells and HIV load on HIV progression

Abstract: C++ and Java have been used to simulate the suggested model. A Pentium III or higher platform is recommended.

Cited by 6 publications

References 12 publications

Genetic Mutations Affecting the Success and Failure of HIV Regimens

Genetic Mutations Affecting the Success and Failure of HIV Regimens

Modeling of Viral Infection with Inflammation

The Influence of Immune Response on Spreading of Viral Infection

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