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Biophysics  2014 

HIV感染–免疫动力学的元胞自动机模拟研究
Cellular Automata Modeling of HIV-Immune System

DOI: 10.12677/BIPHY.2014.21001, PP. 1-13

Keywords: HIV;AIDS;元胞自动机
HIV
, AIDS, Cellular Automata

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Abstract:

自1981年发现首例人类获得性免疫缺失综合症(艾滋病,AIDS)至今已有30多年,然而人们至今未能找到治疗这种危及人类生命健康的可怕疾病的方法。建立正确的艾滋病病毒HIV与免疫系统相互作用数学模型,有助于发现HIV的感染机理,帮助我们找到治疗AIDS的方法。在这篇报告中,我们综述了利用元胞自动机模型来揭示HIV与免疫系统相互作用的研究,包括模拟HIV感染后病人出现三个典型的特征期(急性期、潜伏期和AIDS发病期)的动力学过程,以及对应的药物治疗理论研究。
 It is more than 30 years since the first case of Acquired Immune Deficiency Syndrome (AIDS) has been reported. However, we still cannot find the effective treatment though this terrible sickness kills approximately two million patients per year. Using mathematical model for approaching the dynamics of human immunodeficiency virus (HIV) infection was and still is one of most important methods among the numerous studies of the treatments of AIDS. Constructing a correct mathematical model of HIV infection will help us to investigate the interaction between HIV and immune and shed light on AIDS treatment. In this article, we review the recent development of cellular automata model to discuss the interaction mechanism between HIV and immune cells, and the drug treatment.

References

[1]  Becker, M.H. and Joseph, J.G. (1988) AIDS and behavioral change to reduce risk: A review. American Journal of Public Health, 78, 394-410.
[2]  Barre-Sinoussi, F., Chermann, J.C., Rey, F., et al. (1983) Isolation of a T-lymphotropic retrovirus from a patient at risk for acquired immune deficiency syndrome (AIDS). Science, 220, 868871.
[3]  Gallo, R.C., Salahuddin, S.Z., Popovic, M., et al. (1984) Frequent detection and isolation of cytopathic retroviruses (HTLVIII) from patients with AIDS and at risk for AIDS. Science, 224, 500-503.
[4]  Levy, J.A., Hoffman, A.D., Kramer, S.M., et al. (1984) Isolation of lymphocytopathic retroviruses from San Francisco patients with AIDS. Science, 225, 840-842.
[5]  Chun, T.W., Engel, D., Mizell, S.B., et al. (1999) Effect of interleukin-2 on the pool of latently infected, resting CD4+T cells in HIV-1-infected patients receiving highly active anti-retroviral therapy. Nature Medicine, 5, 651-655.
[6]  Uenishi, R., Hase, S., Keng, T.K., et al. (2007) HIV/AIDS in Asia: The shape of epidemics and their molecular epide-miology. Virologica Sinica, 6, 004.
[7]  Mayer, K.H. and Beyrer, C. (2007) HIV epidemiology update and transmission factors: Risks and risk contexts—16th International AIDS Conference epidemiology plenary. Clinical Infectious Diseases, 44, 981-987.
[8]  钟进彦, 张栗, 柳建发 (2010) 艾滋病的流行研究进展. 地方病通报, 6, 72-74.
[9]  Wei, X., Ghosh, S.X., Taylor, M.E., et al. (1995) Viral dynamics in human immunodeficiency virus type 1 infection. Nature, 373, 117-122.
[10]  Finzi, D., Hermankova, M., Pierson, T., et al. (1997) Identification of a reservoir for HIV-1 in patients on highly active antiretroviral therapy. Science, 278, 1295-1300.
[11]  Bassetti, S., Battegay, M., Furrer, H., et al. (1999) Why is highly active an-ti-retroviral therapy (HAART) not prescribed or discontinued. JAIDS Journal of Acquired Immune Deficiency Syndromes, 21, 114-119.
[12]  Sharkey, M.E., Teo, I., Greenough, T., et al. (2000) Persistence of episomal HIV-1 infection intermediates in patients on highly active anti-retroviral therapy. Nature Medicine, 6, 76-81.
[13]  Bassetti, S., Battegay, M., Furrer, H., et al. (1999) Why is highly active anti-retroviral therapy (HAART) not prescribed or dis-continued? Journal of Acquired Immune Deficiency Syndromes, 21, 114-119.
[14]  Dinoso, J.B., Kim, S.Y., Wiegand, A.M., et al. (2009) Treatment intensification does not reduce residual HIV-1 viremia in patients on highly active antiretroviral therapy. PNAS, 106, 94039408.
[15]  Sharkey, M.E., Teo, I., Greenough, T., et al. (2000) Persistence of episomal HIV-1 infection intermediates in patients on highly active anti-retroviral therapy. Nature Medicine, 6, 76-81.
[16]  Dean, M., Carrington, M., Winkler, C., Huttley, G.A., Smith, M.W., Allikmets, R., et al. (1996) Genetic restriction of HIV-1 infection and progression to AIDS by a deletion allele of the CKR5 structural gene. Science, 273, 1856-1862.
[17]  Rosenberg, E.S., Altfeld, M., Poon, S.H., Phillips, M.N., Wilkes, B.M., Eldridge, R.L., Robbins, G.K., D’Aquila, R.T., Goulder, P.J. and Walker, B.D. (2000) Immune control of HIV-1 after early treatment of acute infection. Nature, 407, 523-526.
[18]  Novina, C.D., Murray, M.F., Dykxhoorn, D.M., Beresford, P.J., Riess, J., Lee, S.K., Collman, R.G., Lieberman, J., Shankar, P. and Sharp, P.A. (2002) siRNA-directed inhibition of HIV-1 infection. Nature Medicine, 8, 681-686.
[19]  Pantaleo, G., Graziosi, C. and Fauci, A.S. (1993) The immunopathogenesis of human immunodeficiency virus infection. New England Journal of Medicine, 328, 327-335.
[20]  Kaplan, E.H. (1990) An overview of AIDS modeling. New Directions for Program Evaluation, 46, 23-36.
[21]  Phillips, A.N. (1996) Reduction of HIV concentration during acute infection: Independence from a specific immune response. Science, 271, 497-499.
[22]  Perelson, A.S. and Weisbuch, G. (1997) Immunology for physicists. Reviews of Modern Physics, 69, 1219.
[23]  Perelson, A.S. and Nelson, P.W. (1999) Mathematical analysis of HIV-1 dynamics. SIAM Review, 41, 3-44.
[24]  Cohn, M. and Mata, J. (2007) Quantitative modeling of immune responses. Immunological Reviews, 216, 5-8.
[25]  Chavali, A.K., Gianchandani, E.P., Tung, K.S., Lawrence, M.B., Peirce, S.M. and Papin, J.A. (2008) Characterizing emergent properties of immunological systems with multi-cellular rulebased computational modeling. Trends in Immunol-ogy, 29, 589599.
[26]  Li, X.H., Wang, Z.X., Lu, T.Y. and Che, X.J. (2009) Modelling immune system: Principles, models, analysis and perspectives. Journal of Bionic Engineering, 6, 77-85.
[27]  Nowak, M.A., May, R.M. and Anderson, R.M. (1990) The evolutionary dy-namics of HIV-1 quasispecies and the development of immunodefi-ciency disease. AIDS, 4, 1095-1103.
[28]  Coffin, J.M. (1995) HIV population dynamics in vivo: Implications for genetic variation, pathogenesis, and therapy. Science, 267, 483-489.
[29]  Nowak, M. and May, R.M. (2000) Virus dynamics: Mathematical principles of immunology and virology. Oxford University Press, Oxford.
[30]  Perelson, A.S. (2002) Modelling viral and immune system dynamics. Nature Reviews Immunology, 2, 28-36.
[31]  Wang, G. and Deem, M.W. (2006) Physical theory of the competition that allows HIV to escape from the immune system. Physical Review Letters, 97, Article ID: 188106.
[32]  Wodarz, D. (2007) Kill cell dynamics: Mathematical and computational approaches to immunology. Springer, Berlin.
[33]  Hernandez-Vargas, E.A. and Middleton, R.H. (2013) Modeling the three stages in HIV infection. Journal of Theoretical Biology, 320, 33-40.
[34]  Hershberg, U., Louzoun, Y., Atlan, H. and Solomon, S. (2001) HIV time hierarchy: Winning the war while, loosing all the battles. Physica A, 289, 178-190.
[35]  Lin, H. and Shuai, J.W. (2010) A stochastic spatial model of HIV dynamics with an asymmetric battle between the virus and the immune system. New Journal of Physics, 12, 043051.
[36]  Weisbuch, G. and Atlan, H. (1988) Control of the im-mune response. Journal of Physics A: Mathematical and General, 21, L189-L192.
[37]  Dayan, I., Stauffer, D. and Havlin, S. (1988) Cellu-lar automata generalization of the Weisbuch-Atlan model for immune response. Journal of Physics A: Mathematical and General, 21, 2473-2476.
[38]  Pandey, R.B. and Stauffer, D. (1990) Metastability with probabilistic cellular automata in an HIV infection. Journal of Statistical Physics, 61, 235-240.
[39]  Pandey, R.B. (1991) Cellular automata approach to interacting cellular network models for the dynamics of cell population in an early HIV infection. Physica A, 179, 442-470.
[40]  Zorzenon dos Santos, R.M. and Coutinho, S. (2001) Dynamics of HIV infection: A cellular automata approach. Physical Review Letters, 87, 168102.
[41]  Codd, E.F. (1968) Cellular automata. Academic Press, Inc., Waltham.
[42]  Gardner, M. (1970) Mathematical games: The fantastic combinations of John Conway’s new solitaire game “life”. Scientific American, 223, 120-123.
[43]  Wolfram, S. (1983) Statistical mechanics of cellular automata. Reviews of Modern Physics, 55, 601.
[44]  Wolfram, S. (1984) Cellular automata as models of complexity. Nature, 311, 419-424.
[45]  Wolfram, S. (1994) Cellular automata and complexity: Collected papers. Addison-Wesley, Reading.
[46]  Maerivoet, S. and De Moor, B. (2005) Cellular automata models of road traffic. Physics Reports, 419, 1-64.
[47]  Chopard, B. and Droz, M. (1998) Cellular automata modeling of physical systems. Cambridge University Press, Cambridge.
[48]  Mei, S.S., Billings, S.A. and Guo, L.Z. (2005) A neighborhood selection method for cellular automata models. International Journal of Bifurcation and Chaos, 15, 383-393.
[49]  Toffoli, T. and Margolus, N. (1987) Cellular automata machines: A new environment for modeling. MIT Press, Cambridge.
[50]  Coveney, P.V. and Fowler, P.W. (2005) Modelling biological complexity: A physical scientist’s perspective. Journal of the Royal Society Interface, 2, 267-280.
[51]  Celada, F. and Seiden, P.E. (1992) A computer model of cellular interactions in the immune system. Immunology Today, 13, 5662.
[52]  Strain, M.C. and Levine, H. (2002) Comment on “dynamics of HIV infection: A cellular automata approach. Physical Review Letters, 89, Article ID: 219805.
[53]  Solovey, G., Peruani, F., Ponce Dawson, S. and Zorzenon dos Santos, R.M. (2004) On cell resistance and immune response time lag in a model for the HIV infection. Physica A: Statistical Mechanics and Its Applications, 343, 543-556.
[54]  Figueirêdo, P.H., Coutinho, S. and Zorzenon dos Santos, R.M. (2008) Robustness of a cellular automata model for the HIV infection. Physica A: Statistical Mechanics and Its Applications, 387, 6545-6552.
[55]  González, R.E.R., de Figueirêdo, P.H. and Coutinho, S. (2013) Cellular automata approach for the dynamics of HIV infection under antiretrovial therapies: The role of the virus diffusion. Physica A, 392, 4717-4725.
[56]  Strain, M.C., Richman, D.D., Wong, J.K. and Levine, H. (2002) Spatiotemporal dynamics of HIV propagation. Journal of Theoretical Biology, 218, 85-96.
[57]  Mielke, A. and Pandey, R.B. (1998) A computer simulation study of cell population in a fuzzy interaction model for mutating HIV. Physica A, 251, 430-438.
[58]  Corne, D.W. and Frisco, P. (2008) Dynamics of HIV infection studies with cellular automata and conformon-P systems. BioSystems, 91, 531-544.
[59]  Precharattana, M., Triampo, W., Mod-chang, C., Triampo, D. and Lenbury, Y. (2010) Investigation of spatial formation involving CD4+ T cells in HIV/AIDS dynamics by a sto-chastic cellular automata model. International Journal of Mathematics and Computers in Simulation, 4, 135-143.
[60]  Precharattana, M. and Triampo, W. (2014) Modeling dynamics of HIV infected cells using stochastic cellular automaton. Physica A, 407, 303-311.
[61]  Mannion, R., Ruskin, H.J. and Pandey, R.B. (2002) Effects of viral mutation on cellular dynamics in a Monte Carlo simulation of HIV immune response model in three dimensions. Theory in Biosciences, 121, 237-245.
[62]  Mo, Y.B., Ren, B., Yang, W.C. and Shuai, J.W. (2014) The 3-dimensional cellular automata for HIV infection. Physica A, 399, 31-39.
[63]  Moonchai, S., Lenbury, Y. and Triampo, W. (2010) Cellular automata simulation modeling of HIV infection in lymph node and peripheral blood compartments. International Journal of Mathematics and Computers in Simulation, 4, 124-134.
[64]  Sloot, P., Chen, F. and Boucher, C. (2002) Cellular automata model of drug therapy for HIV infection. In: Cellular Automata, Springer, Berlin, 282-293.
[65]  Benyoussef, A., El HafidAllah, N., ElKenz, A., Ez-Zahraouy, H. and Loulidi, M. (2003) Dynamics of HIV infection on 2D cellular automata. Physica A, 322, 506-520.
[66]  Shi, V., Tridane, A. and Kuang, Y. (2008) A viral load-based cellular automata approach to modeling HIV dynamics and drug treatment. Journal of Theoretical Biology, 252, 24-35.
[67]  Precharattana, M., Nokkeaw, A., Triampo, W., Triampo, D. and Lenbury, Y. (2011) Stochastic cellular automata model and Monte Carlo simulations of CD4+ T cell dynamics with a proposed alternative leukapheresis treatment for HIV/AIDS. Computers in Biology and Medicine, 41, 546-558.
[68]  Burkhead, E.G., Hawkins, J.M. and Molinek, D.K. (2009) A dynamical study of a cellular automata model of the spread of HIV in a lymph node. Bulletin of Mathematical Biology, 71, 2574.
[69]  Bacelar, F.S., Andrade, R.F.S. and Santos, R.M. (2010) The dynamics of the HIV infection: A time-delay differential equation approach.
[70]  Hecquet, D., Ruskin, H.J. and Crane, M. (2007) Optimisation and parallelization strategies for Monte Carlo simulation of HIV infection. Computers in Biology and Medicine, 37, 691-699.
[71]  Baldazzi, V., Castiglione, F. and Bernaschi, M. (2006) An enhanced agent based model of the immune system response. Cellular Immunology, 244, 77-79.
[72]  Beauchemin, C., Samuel, J. and Tuszynski, J. (2005) A simple cellular automaton model for influenza A viral infections. Journal of Theoretical Biology, 232, 223-234.
[73]  Santos, L.B., Costa, M.C., Pinho, S.T.R. and Andrade, R.F.S. (2009) Periodic forcing in a three level cellular automata model for a vector-transmitted disease. Physical Review E, 80, 016102.
[74]  Xiao, X., Shao, S.H. and Chou, K.C. (2006) A probability cellular automaton model for hepatitis B viral infections. Biochemical and Biophysical Research Communications, 342, 605-610.
[75]  Gharib-Zahedi, M.R. and Ghaemi, M. (2012) Kinetics of hepatitis B virus infection: A cellular automaton model study. Journal of Paramedical Sciences, 3, 2008-4978.

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