On cell resistance and immune response time lag in a model for the HIV infection

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Recently, a cellular automata model has been introduced (Phys. Rev. Lett. 87 (2001) 168102) to describe the spread of the HIV infection among target cells in lymphoid tissues. The model reproduces qualitatively the entire course of the infection displaying, in particular, the two time scales that ch...

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Autor principal: Solovey, G.
Otros Autores: Peruani, F., Dawson, S.P, Dos Santos, R.M.Z
Formato: Capítulo de libro
Lenguaje:Inglés
Publicado: 2004
Acceso en línea:Registro en Scopus
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Biblioteca Central Dr. Luis F. Leloir (FCEN) de Universidad de Buenos Aires
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100 1 |a Solovey, G. 
245 1 3 |a On cell resistance and immune response time lag in a model for the HIV infection 
260 |c 2004 
270 1 0 |m Solovey, G.; Departamento de Física, Fac. de Ciencias Exactas y Naturales, Ciudad Universitaria, Pabellón I, (1428) Buenos Aires, Argentina; email: gsolovey@df.uba.ar 
506 |2 openaire  |e Política editorial 
504 |a Pantaleo, G., Graziozi, C., Fauci, A.S., (1993) N. Engl. J. Med., 328, p. 327 
504 |a Coffin, J.M., (1989) Science, 267, p. 305 
504 |a Daar, E.S., Moudgil, T., Meyer, T.R.D., Ho, D.D., (1991) N. Engl. J. Med., 324, p. 961 
504 |a Clark, S., Saag, M.S., Decker, W.D., (1991) N. Engl. J. Med., 324, p. 954 
504 |a Steckel, D.J., (1997) J. Theor. Biol., 186, p. 491 
504 |a Steckel, D.J., (1997) Immunol. Today, 18, p. 216 
504 |a Perelson, A.S., Nelson, P.W., (1999) SIAM Rev., 41, p. 3 
504 |a Mannion, R., Ruskin, H., Pandey, R.B., (2000) Theor. Biosc., 119, p. 10 
504 |a Mannion, R., Ruskin, H., Pandey, R.B., (2000) Theor. Biosc., 119, p. 94 
504 |a Hershberg, U., Louzoun, Y., Atlan, H., Solomon, S., (2001) Physica A, 289, p. 178 
504 |a Strain, M.C., Wong, J.K., Richman, D.D., Levine, H., (2002) J. Theor. Biol., 218 (1), p. 85 
504 |a Zorzenon Dos Santos, R.M., Coutinho, S., (2001) Phys. Rev. Lett., 87, p. 168102 
504 |a Schinittman, S.M., (1989) Science, 239, p. 617 
504 |a Schinittman, S.M., (1990) Ann. Inter. Med., 113, p. 438 
504 |a Faucci, A.S., (1988) Science, 239, p. 1988 
504 |a P.H. Figueirêdo, S.G. Coutinho, R.M. Zorzenon dos Santos, to be published; Figueirêdo, P.H., (2002), MSc. Thesis, Departamento de Fisica, Universidade Federal de Pernambuco; Solovey, G., (2003), Tesis de Licenciatura, Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires; Nowak, M.A., McMichael, A.J., (1995) Sci. Am., 273, p. 42 
504 |a Nowak, M.A., May, R.M., (2000) Virus Dynamics: Mathematical Principles of Immunology and Virology, , Oxford University Press, Oxford, London 
504 |a Zorzenon Dos Santos, R.M., (2003) Modern Challenges in Statistical Mechanics: Patterns, Noise, and the Interplay of Nonlinearity and Complexity, , N. kenkre, K. Lindenberg (Eds.), AIP, New York 
520 3 |a Recently, a cellular automata model has been introduced (Phys. Rev. Lett. 87 (2001) 168102) to describe the spread of the HIV infection among target cells in lymphoid tissues. The model reproduces qualitatively the entire course of the infection displaying, in particular, the two time scales that characterize its dynamics. In this work, we investigate the robustness of the model against changes in three of its parameters. Two of them are related to the resistance of the cells to get infected. The other one describes the time interval necessary to mount specific immune responses. We have observed that an increase of the cell resistance, at any stage of the infection, leads to a reduction of the latency period, i.e., of the time interval between the primary infection and the onset of AIDS. However, during the early stages of the infection, when the cell resistance increase is combined with an increase in the initial concentration of infected cells, the original behavior is recovered. Therefore we find a long and a short latency regime (eight and one year long, respectively) depending on the value of the cell resistance. We have obtained, on the other hand, that changes on the parameter that describes the immune system time lag affects the time interval during which the primary infection occurs. Using different extended versions of the model, we also discuss how the two-time scale dynamics is affected when we include inhomogeneities on the cells properties, as for instance, on the cell resistance or on the time interval to mount specific immune responses. © 2004 Elsevier B.V. All rights reserved.  |l eng 
536 |a Detalles de la financiación: Umweltbundesamt 
536 |a Detalles de la financiación: National Science Foundation 
536 |a Detalles de la financiación: PICT 03-08133 
536 |a Detalles de la financiación: We thank IUPAB and the program CPG_BA-CAPES for the support received during the development of this work. RMZS thanks CNPq for the grants obtained during this project. SPD acknowldges the financial support of UBA and ANPCyT of Argentina, under grant PICT 03-08133. Part of this work was developed during a stay of RMZS and SPD at the Kavli Institute for Theoretical Physics, UCSB. Their hospitality and support through National Science Foundation Grant No. PHY99-07949 is kindly acknowledged. 
593 |a Departamento de Física, Fac. de Ciencias Exactas y Naturales, Ciudad Universitaria, Pabellón I, (1428) Buenos Aires, Argentina 
593 |a Lab. de Fis. Teor. e Computational, Universidade Federal de Pernambuco, 50670-901, Recife, PE, Brazil 
690 1 0 |a CELLULAR AUTOMATA 
690 1 0 |a DYNAMICAL SYSTEMS 
690 1 0 |a HIV INFECTION 
690 1 0 |a PATTERN FORMATION 
690 1 0 |a ANTIGEN-ANTIBODY REACTIONS 
690 1 0 |a AUTOMATA THEORY 
690 1 0 |a BLOOD 
690 1 0 |a CELLS 
690 1 0 |a PARAMETER ESTIMATION 
690 1 0 |a PATTERN RECOGNITION 
690 1 0 |a PROTEINS 
690 1 0 |a TISSUE 
690 1 0 |a CELL RESISTANCE 
690 1 0 |a CELLULAR AUTOMATA 
690 1 0 |a DYNAMICAL SYSTEMS 
690 1 0 |a HIV INFECTION 
690 1 0 |a PATTERN FORMATION 
690 1 0 |a IMMUNOLOGY 
700 1 |a Peruani, F. 
700 1 |a Dawson, S.P. 
700 1 |a Dos Santos, R.M.Z. 
773 0 |d 2004  |g v. 343  |h pp. 543-556  |k n. 1-4  |p Phys A Stat Mech Appl  |x 03784371  |w (AR-BaUEN)CENRE-280  |t Physica A: Statistical Mechanics and its Applications 
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856 4 0 |u https://doi.org/10.1016/j.physa.2004.06.068  |y DOI 
856 4 0 |u https://hdl.handle.net/20.500.12110/paper_03784371_v343_n1-4_p543_Solovey  |y Handle 
856 4 0 |u https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v343_n1-4_p543_Solovey  |y Registro en la Biblioteca Digital 
961 |a paper_03784371_v343_n1-4_p543_Solovey  |b paper  |c PE 
962 |a info:eu-repo/semantics/article  |a info:ar-repo/semantics/artículo  |b info:eu-repo/semantics/publishedVersion 
963 |a VARI 

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