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Tytuł artykułu

Numerical modelling of the competition between the adaptive immune system and virus

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
We present and analyze numerically a mathematical model of interactions between adaptive immune system and viral infection. The model is a bilinear system of partial integro-differential equations of Boltzmann type. It is a generalization of the recently proposed kinetic models that consider particular (namely, the cellmediated and the humoral) immune mechanisms used in the fight against viral infections. We use Matlab to solve complicated system of equations, present the results of computer simulations and explain their immunological meaning. The results show that the model can describe in a better way (in comparison with the previous kinetic models) real biological situations and is able to illustrate various methods of therapy.
Rocznik
Strony
763--778
Opis fizyczny
Bibliogr. 37 poz., wykr.
Twórcy
autor
  • Faculty of Mathematics and Computer Science, University of Warmia and Mazury Słoneczna 54, 10-710 Olsztyn, Poland, kolev@matman.uwm.edu.pl
Bibliografia
  • Abbas, A. and Lichtman, A. (2004) Basic Immunology. Functions and Disorders of the Immune System. Elsevier, Philadelphia.
  • Arkeryd, L. (1972) On the Boltzmann equation. Arch. Rat. Mech. Anal. 45 (1), 1-34.
  • Arlotti, L., Bellomo, N., De Angelis, E. and Lachowicz, M. (2003) Generalized Kinetic Models in Applied Sciences. World Sci., New Jersey.
  • Arlotti,L., Bellomo,N. and Lachowicz,M. (2000) Kinetic equations modelling population dynamics. Transport Theory Statist. Phys. 29 (1-2), 125-139.
  • Arlotti, L., Gamba, A. and Lachowicz, M. (2002) A kinetic model of tumour/ immune system cellular interactions. J. Theoret. Medicine 4(1), 39-50.
  • Arlotti, L. and Lachowicz, M. (1996) Qualitative analysis of an equation modelling tumor-host dynamics. Math. Comput. Modelling 23 (6), 11-29.
  • Asquith, B. and Bangham, Ch. (2003) An introduction to lymphocyte and viral dynamics: the power and limitations of mathematical analysis. Proc. R. Soc. Lond. B, 270 (1525), 1651-1657.
  • Bellomo, N. (2008) Modelling complex living systems-a kinetic theory and stochastic game approach. Birkhäuser, Boston.
  • Belleni-Morante, A. (1979) Applied Semigroups and Evolution Equations. Oxford Univ. Press, Oxford.
  • Bellomo, N., Bianca, C. and Delitala, M. (2009) Complexity analysis and mathematical tools towards the modelling of living systems. Physics of Life Reviews 6 (3), 144-175.
  • Bellomo, N. and Delitala, M. (2008) From the mathematical kinetic, and stochastic game theory to modelling mutations, onset, progression and immune competition of cancer cells. Physics of Life Reviews 5 (4), 183-206.
  • Bellomo, N. and Forni, G. (1994) Dynamics of tumor interaction with the host immune system. Math. Comput. Modelling 20 (1), 107-122.
  • Bellomo, N. and Forni, G. (2008) Complex multicellular systems and immune competition: New paradigms looking for a mathematical theory. Curr. Top. Dev. Biol. 81, 485-502.
  • Bellomo, N., Li, N. and Maini, P. (2008) On the foundations of cancer modelling: Selected topics, speculations, and perspectives. Math. Models Methods Appl. Sci. 18 (4), 593-646.
  • Bellomo, N. and Preziosi, L. (2000) Modelling and mathematical problems related to tumor evolution and its interaction with the immune system. Math. Comput. Modelling 32 (3-4), 413-452.
  • Bellouquid,A. and Delitala,M. (2005) Mathematical methods and to ols of kinetic theory towards modelling complex biological systems. Math. Models Methods Appl. Sci. 15 (11), 1639-1666.
  • Bellouquid, A. and Delitala, M. (2006) Modelling Complex Biological Systems. A Kinetic Theory Approach. Birkhäuser, Boston.
  • Calvo, A., Xiao, N., Kang, J., Best, C., Leiva, I., Emmert-Buck, M., Jorcyk, C. and Green, J. (2002) Alterations in gene expression profiles during prostate cancer progression: functional correletions to tumorigenicity and down-regulation of selenoprotein-P in mouse and human tumors. Cancer Research 62 (18), 5325-5335.
  • De Angelis, E. and Lodz, B. (2008) On the kinetic theory for active particles: A model for tumor-immune system competition. Math. Comput. Modelling 47 (1-2), 96-209.
  • De Lillo, S., Salvatori, M. and Bellomo, N. (2007) Mathematical to ols of the kinetic theory of active particles with some reasoning on the model ling progression and heterogeneity. Math. Comput. Modelling 45 (5-6), 564-578.
  • Drucis, K., Kolev, M., Majda,W. and Zubik-Kowal, B. (2010) Nonlinear modeling with mammographic evidence of carcinoma. Nonlinear Analysis: Real World Applications 11 (5), 4326-4334.
  • Gautschi,W. (1997) Numerical Analysis: An Introduction. Birkhäuser, Boston.
  • Jackiewicz, Z., Jorcyk, C., Kolev, M. and Zubik-Kowal, B. (2009) Correlation between animal and mathematical models for prostate cancer progression. Comput. Math. Methods Med. 10 (4), 241-252.
  • Kagi, D., Seiler, P., Pavlovic, J., Ledermann, B., Burki, K., Zinkernagel, R. and Hengartner, H. (1995) The roles of perforin-dependent and Fas-dependent cytotoxicity in protection against cytopathic and noncytopathic viruses. Eur. J. Immunol. 25 (12), 3256-3262.
  • Kolev, M. (2008a) Mathematical modelling of the interactions between antibodies and virus. Proc. of the IEEE Conf. on Human System Interactions. IEEE, ieeexplore.ieee.org, 365-368.
  • Kolev, M. (2008b) Mathematical modelling of the humoral immune response to virus. Proc. of the Fourteenth National Conf. on Application of Mathematics in Biology and Medicine. Department of Mathematics, Informatics and Mechanics, University of Warsaw, 63-68.
  • Kolev, M. (2009) Numerical modelling of cellular immune response to virus. In: S. Magrenov, L. Vulkov and J. Waśniewski, eds., Numerical Analysis and Applications. LNCS 5434, Springer, 361-368.
  • Kolmogorov, A. and Fomin, S. (1975) Itroductory Real Analysis. Dover Publ. Inc., New York.
  • Kuby, J. (1997) Immunology. W.H. Freeman, New York.
  • Lydyard, P., Whelan, A. and Fanger, M. (2000) Instant Notes in Immunology. BIOS Sci. Publ. Ltd., Oxford.
  • Pinchuk, G. (2002) Schaum’s Outline of Theory and Problems of Immunology. McGraw-Hill, New York.
  • Shampine, L. and Reichelt, M. (1997) The Matlab ODE suite. SIAM J. Sci. Comput. 18 (1), 1-22.
  • Volkov, E. (1990) Numerical Methods. Hemisphere/Mir, New York/Moscow.
  • Wodarz, D. (2007) Killer Cell Dynamics. Springer, Berlin-New York.
  • Wodarz, D. and Bangham, C. (2000) Evolutionary dynamics of HTLV-I. J. Mol. Evol. 50 (5), 448-455.
  • Wodarz, D. and Krakauer, D. (2000) Defining CTL-induced pathology: implication for HIV. Virology 274 (1), 94-104.
  • Wodarz, D., May, R. and Nowak, M. (2000) The role of antygen-independent persistence of memory cytotoxic T lymphocytes. Intern. Immun. 12 (4), 467-477.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BATC-0009-0010
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