[en] This paper studies the influence of apoptosis in the dynamics of the HIV infection. A new modeling of the healthy CD4+ T-cells activation-induced apoptosis is used. The parameters of this model are identified by using clinical data generated by monitoring patients starting Highly Active Anti-Retroviral Therapy (HAART). The sampling of blood tests is performed to satisfy the constraints of dynamical system parameter identification. The apoptosis parameter, which is inferred from clinical data, is then shown to play a key role in the early diagnosis of immunological failure.
Disciplines :
Immunology & infectious disease Computer science
Author, co-author :
Mhawej, Marie-José
Brunet-Francois, Cécile
Fonteneau, Raphaël ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Ernst, Damien ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Ferré, Virginie
Stan, Guy-Bart
Raffi, François
Moog, Claude H.
Language :
English
Title :
Apoptosis characterizes immunological failure of HIV infected patients
scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.
Bibliography
Adams B.M., Banks H.T., Kwon H.-D., and Tran H.T. Dynamic multidrug therapies for HIV: Optimal and STI approaches. Mathematical Biosciences and Engineering 1 2 (2004)
Ahr B., Robert-Hebmann V., Devaux C., and Biard-Piechaczyk M. Apoptosis of uninfected cells induced by HIV envelope glycoproteins. Retrovirology 1 (2004)
Badley A.D. Cell death during HIV infection (2005), CRC Press, Boca Raton, FL. http://www.vonl.com/chips/cellhiv.htm 〈http://www.vonl.com/chips/cellhiv.htm〉
Berger A., et al. Comparative evaluation of the COBAS Amplicor HIV-1 MonitorTM Ultrasensitive Test, the new COBAS AmpliPrep/COBAS Amplicor HIV-1 MonitorTM and the Versant HIV RNA 3.0 assays for quantitation of HIV-1 RNA in plasma samples. Journal of Clinical Virology 33 (2005) 43-51
Chang, H., & Astolfi, A. (2007). Immune response's enhancement via controlled drug scheduling. In 46th IEEE conference on decision and control, December, New Orleans, LA, USA.
Delfraissy, J. F. (2005). Monitoring of HIV infected patients: experts recommendations, Flammarion edition, Médecine Science, Paris. Available at 〈www.ladocumentationfrancaise.fr/brp/notices/044000467.shtml〉, (in French).
Estaquier J., et al. Programmed cell death and AIDS: Significance of T-cell apoptosis in pathogenic and nonpathogenic primate lentiviral infections. Proceedings of the National Academic of Sciences of the United States of America 91 (1994) 9431-9435
Fiches Techniques de la Firme Roche (2003). Available at 〈http://www.roche-diagnostics.fr〉.
Filter, R. A., & Xia, X. (2003). A penalty function to HIV/AIDS model parameter estimation. In 13th IFAC Symposium on System Identification, Rotterdam.
Galli R., Merrick L., Friesenhahn M., and Ziermann R. Comprehensive comparison of the Versant® HIV-1 RNA 3.0 (bDNA) and COBAS Amplicor HIV-1 Monitor® 1.5 assays on 1000 clinical specimens. Journal of Clinical Virology 34 (2005) 245-252
Gougeon M.-L., and Montagnier L. Programmed cell death as a mechanism of CD4 and CD8 T cell depletion in AIDS: Molecular control and effect of highly active anti-retroviral therapy. Annals of the New York Academy of Sciences 887 1 (1999) 199-212. http://www.blackwell-synergy.com/doi/abs/10.1111/j.1749-6632.1999.tb0793 4.x 〈http://www.blackwell-synergy.com/doi/abs/10.1111/j.1749-6632.1999. tb07934.x〉
Heffernan J.M., and Wahl L.M. Treatment interruptions and resistance: A review. In: Tan W.-Y., and Wu H. (Eds). Deterministic and stochastic models for AIDS epidemics and HIV infection with interventions (2005), World Scientific, Hackensack, NJ 425-455
Herbein G., Mahlknecht U., Batliwalla F., Gregersen P., Pappas T., Butler J., et al. Apoptosis of CD 8 + T cells is mediated by macrophages through interaction of HIV gp120 with chemokine receptor CXCR4. Nature 395 6698 (1998) 189-194. http://dx.doi.org/10.1038/26026 〈http://dx.doi.org/10.1038/26026〉
Ho D.D., et al. Rapid turnover of plasma virion and CD4 lymphocytes in HIV-1 infection. Nature 373 (1995) 123-126
Israel-Ballard K., et al. TaqMan RT-PCR and Versant® HIV-1 RNA 3.0 (bDNA) assay quantification of HIV-1 RNA viral load in breast milk. Journal of Clinical Virology 34 (2005) 253-256
Khalili S., and Armaou A. Sensitivity analysis of HIV infection response to treatment via stochastic modeling. Chemical Engineering Science 63 (2008) 1330-1340
Moog C.H., Ouattara D.A., and Mhawej M.J. Analysis of the HIV dynamics. Proceedings of the seventh IFAC symposium on nonlinear control systems, Pretoria, South Africa, August 22-24 (2007)
Nowak M.A., and May R.M. Virus dynamics: Mathematical principles of immunology and virology (2002), Oxford University Press, Oxford
Ouattara, D. A. (2005). Mathematical analysis of the HIV-1 infection: Parameter estimation, therapies effectiveness, and therapeutical failures. In 27th annual international conference of the IEEE engineering in medicine and biology society, September, Shanghai, China.
Ouattara, D. A. (2006). Modeling of the HIV infection, identification and aid for the diagnosis. Ph.D. thesis, Ecole Centrale de Nantes & Université de Nantes, Nantes, France, (in French).
Ouattara, D. A., Mhawej, M.-J., & Moog, C. H. (2007). IRCCyN Web software for the computation of HIV infection parameters. Available at 〈http://www.hiv.irccyn.ec-nantes.fr〉.
Ouattara, D. A., Mhawej, M. J., & Moog, C. (2008). Clinical tests of therapeutical failures based on mathematical modeling of the HIV infection, Joint special issue of IEEE transactions on circuits and systems and IEEE transactions on Automatic Control, Special issue on systems biology, January, 230-241.
Ouattara, D. A., & Moog, C. H. (2007). Modelling of the HIV/AIDS infection : An aid for an early diagnosis of patients, Biology and control theory: Current challenges. In Lecture notes in control and information sciences (LNCIS), Springer, Berlin.
Pantaleo G., and Fauci A.S. Apoptosis in HIV infection. Nature Medicine 1 2 (1995) 118-120. http://dx.doi.org/10.1038/nm0295-118 〈http://dx.doi.org/10.1038/nm0295-118〉
Perelson A.S., and Nelson P.W. Mathematical analysis of HIV-1 dynamics in vivo. SIAM Review 41 1 (1999) 3-44
Perelson A.S., et al. Decay characteristics of HIV-1 infected compartment during combination therapy. Nature 387 (1997) 188-191
Prud'homme I.T., et al. Amplicor HIV Monitor, NASBA HIV-1 RNA QT and Quantiplex HIV RNA version 2.0 viral load assays: A Canadian evaluation. Journal of Clinical Virology 11 (1998) 189-202
Smith R.J. Adherence to antiretroviral HIV drugs: How many doses can you miss before resistance emerges?. Proceedings of the Royal Society B 273 (2006) 617-624
Smith R.J., and Wahl M. Distinct effects of protease and reverse transcriptase inhibition in an immunological model of HIV-1 infection with impulsive drug effects. Bulletin of Mathematical Biology 66 (2004) 1259-1283
Stan G.B., Belmudes F., Fonteneau R., Zeggwagh F., Lefebvre M.A., Michelet C., et al. Modelling the influence of activation-induced apoptosis of CD 4 + and CD 8 + T-cells on the immune system response of a HIV infected patient. IET Systems Biology 2 2 (2008) 94-102
Stewart S.A., Poon B., Song J.Y., and Chen I.S.Y. Human immunodeficiency virus Type 1 Vpr induces apoptosis through caspase activation. The Journal of Virology 74 (2000) 3105-3111
Tan W.Y., and Wu H. Deterministic and stochastic models for AIDS epidemics and HIV infection with interventions (2005), World Scientific, Singapore
U.S. Department of Health and Human Services, (2006). Guidelines for the Use of Antiretroviral Agents in HIV-1-Infected Adults and Adolescents, May. Available at 〈http://www.aidsinfo.nih.gov/guidelines〉.
Vassena, L., Proschan, M., Fauci, A. S., & Lusso, P. (2007). Interleukin 7 reduces the level of spontaneous apoptosis in CD 4 + and CD 8 + T cells from HIV-1 infected individuals. Proceedings of the National Academy of Sciences of the United States of America 2355-2360.
Wang J., Guan E., Roderiquez G., and Norcross M.A. Synergistic induction of apoptosis in primary CD 4 + T cells by macrophage-tropic HIV-1 and TGF-beta1. The Journal of Immunology 167 (2001) 3360-3366
Wei X., et al. Viral dynamics in human immunodeficiency virus type 1 infection. Nature 373 (1995) 117-122
Wodarz D., and Nowak M. Specific therapy regimes could lead to long term immunological control of HIV. Proceedings of the National Academy of Sciences of the United States of America (PNAS) 96 25 (1999) 14464-14469
Xia X., and Moog C.H. Identifiability of nonlinear systems with application to HIV/AIDS models. IEEE Transactions on Automatic Control 48 2 (2003) 330-336
Yun Yue F., Kovacs C., Dimayuga R., Xiao J.G., Parks P., Kaul R., et al. Preferential apoptosis of HIV-1 Specific CD 4 + T cells. The Journal of Immunology 174 (2005) 2196-2204
Zauli G., Gibellini D., Secchiero P., Dutartre H., Olive D., Capitani S., et al. Human immunodeficiency virus type 1 Nef protein sensitizes CD 4 + T lymphoid cells to apoptosis via functional upregulation of the CD95/CD95 ligand pathway. Blood 93 (1999) 1000-1010
Zurakowski, R., & Teel, R. A (2006). A model predictive control based scheduling method for HIV therapy. Journal of Theoretical Biology, July, 368-382.
Zurakowski, R., & Wodarz, D. (2007). Treatment interruptions to decrease risk of resistance emerging during therapy switching in HIV treatment, 46th IEEE conference on decision and control, December, New Orleans, LA, USA.
Similar publications
Sorry the service is unavailable at the moment. Please try again later.
This website uses cookies to improve user experience. Read more
Save & Close
Accept all
Decline all
Show detailsHide details
Cookie declaration
About cookies
Strictly necessary
Performance
Strictly necessary cookies allow core website functionality such as user login and account management. The website cannot be used properly without strictly necessary cookies.
This cookie is used by Cookie-Script.com service to remember visitor cookie consent preferences. It is necessary for Cookie-Script.com cookie banner to work properly.
Performance cookies are used to see how visitors use the website, eg. analytics cookies. Those cookies cannot be used to directly identify a certain visitor.
Used to store the attribution information, the referrer initially used to visit the website
Cookies are small text files that are placed on your computer by websites that you visit. Websites use cookies to help users navigate efficiently and perform certain functions. Cookies that are required for the website to operate properly are allowed to be set without your permission. All other cookies need to be approved before they can be set in the browser.
You can change your consent to cookie usage at any time on our Privacy Policy page.