Literature DB >> 12447006

Modeling the effects of vaccination on chronically infected HIV-positive patients.

Laura E Jones1, Alan S Perelson.   

Abstract

T-cell activation plays a critical role in the initiation and propagation of HIV-1 infection and yet transient activation of the immune system is a normal response to immunization. While it is now considered wise to vaccinate HIV-1-positive patients, it is crucial to anticipate any lasting effects of vaccination on plasma HIV-1 RNA levels and on infected T-cell populations. We extend a simple dynamic model of HIV infection to include T-cell activation by vaccination. We show that the model can reproduce many but not all of the features of the post-tetanus immunization rise in viral load observed and reported on by Stanley et al. in 1966 ( 334:1222-1230). Amplitudes and approximate timing of postimmunization peak viral loads were matched in 10 of 12 cases; in patients with double postimmunization peaks of nearly equal amplitude the later peaks were matched. Furthermore, our simulations suggest that productively infected cell populations track postvaccination increases in plasma viral load, rising and falling in concert over a period of about 4 weeks, whereas chronically infected cells peak later and remain elevated over baseline levels for up to 6 weeks postvaccination.

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Year:  2002        PMID: 12447006     DOI: 10.1097/00126334-200212010-00001

Source DB:  PubMed          Journal:  J Acquir Immune Defic Syndr        ISSN: 1525-4135            Impact factor:   3.731


  12 in total

1.  Host immune responses that promote initial HIV spread.

Authors:  K Wendelsdorf; G Dean; Shuhua Hu; S Nordone; H T Banks
Journal:  J Theor Biol       Date:  2011-08-22       Impact factor: 2.691

2.  Therapeutic immunization in HIV infected Ugandans receiving stable antiretroviral treatment: a Phase I safety study.

Authors:  Cissy Kityo; Stephanie Bousheri; Juliette Akao; Francis Ssali; Rose Byaruhanga; Isaac Ssewanyana; Prossy Muloma; Sula Myalo; Rose Magala; Yichen Lu; Peter Mugyenyi; Huyen Cao
Journal:  Vaccine       Date:  2011-01-04       Impact factor: 3.641

3.  Transient viremia, plasma viral load, and reservoir replenishment in HIV-infected patients on antiretroviral therapy.

Authors:  Laura E Jones; Alan S Perelson
Journal:  J Acquir Immune Defic Syndr       Date:  2007-08-15       Impact factor: 3.731

Review 4.  Modeling HIV persistence, the latent reservoir, and viral blips.

Authors:  Libin Rong; Alan S Perelson
Journal:  J Theor Biol       Date:  2009-06-17       Impact factor: 2.691

5.  Asymmetric division of activated latently infected cells may explain the decay kinetics of the HIV-1 latent reservoir and intermittent viral blips.

Authors:  Libin Rong; Alan S Perelson
Journal:  Math Biosci       Date:  2008-10-17       Impact factor: 2.144

6.  Viral blip dynamics during highly active antiretroviral therapy.

Authors:  Michele Di Mascio; Martin Markowitz; Michael Louie; Christine Hogan; Arlene Hurley; Chris Chung; David D Ho; Alan S Perelson
Journal:  J Virol       Date:  2003-11       Impact factor: 5.103

7.  A stochastic model of latently infected cell reactivation and viral blip generation in treated HIV patients.

Authors:  Jessica M Conway; Daniel Coombs
Journal:  PLoS Comput Biol       Date:  2011-04-28       Impact factor: 4.475

8.  Variable effect of co-infection on the HIV infectivity: within-host dynamics and epidemiological significance.

Authors:  Diego F Cuadros; Gisela García-Ramos
Journal:  Theor Biol Med Model       Date:  2012-03-19       Impact factor: 2.432

9.  Factors associated with HIV viral load "blips" and the relationship between self-reported adherence and efavirenz blood levels on blip occurrence: a case-control study.

Authors:  Aaron Farmer; Xun Wang; Anuradha Ganesan; Robert G Deiss; Brian K Agan; Thomas A O'Bryan; Kevin Akers; Jason F Okulicz
Journal:  AIDS Res Ther       Date:  2016-03-22       Impact factor: 2.250

10.  Modeling latently infected cell activation: viral and latent reservoir persistence, and viral blips in HIV-infected patients on potent therapy.

Authors:  Libin Rong; Alan S Perelson
Journal:  PLoS Comput Biol       Date:  2009-10-16       Impact factor: 4.475

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