A Three-Dimensional Computational Model of the Innate Immune System

  • Pedro Augusto F. Rocha
  • Micael P. Xavier
  • Alexandre B. Pigozzo
  • Barbara de M. Quintela
  • Gilson C. Macedo
  • Rodrigo Weber dos Santos
  • Marcelo Lobosco
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7333)

Abstract

The Human Immune System is a complex system responsible for protecting the organism against diseases. Although understanding how it works is essential to develop better treatments against diseases, its complexity makes this task extremely hard. In this work a three-dimensional mathematical and computational model of part of this system, the innate immune system, is presented. The high computational costs associated to simulations lead the development of a parallel version of the code, which has achieved a speedup of about 72 times over its sequential counterpart.

Keywords

Innate Immune System Parallel Version Human Immune System Endothelium Permeability Neutrophil Apoptosis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Pigozzo, A.B., Macedo, G.C., dos Santos, R.W., Lobosco, M.: Implementation of a Computational Model of the Innate Immune System. In: Liò, P., Nicosia, G., Stibor, T. (eds.) ICARIS 2011. LNCS, vol. 6825, pp. 95–107. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  2. 2.
    Pigozzo, A., Macedo, G., Weber, R., Lobosco, M.: On the computational modelling of the innate immune system. BMC Bioinformatics (2012) (Submitted, review in progress)Google Scholar
  3. 3.
    Pigozzo, A.B., Lobosco, M., dos Santos, R.W.: Parallel implementation of a computational model of the his using openmp and mpi. In: International Symposium on Computer Architecture and High Performance Computing Workshops, pp. 67–72. IEEE Computer Society (2010)Google Scholar
  4. 4.
    Opal, S.M., DePalo, V.A.: Anti-inflammatory cytokines. Chest 117(4), 1162–1172 (2000)CrossRefGoogle Scholar
  5. 5.
    Fiorentino, D., Zlotnik, A., Mosmann, T., Howard, M., O’Garra, A.: Il-10 inhibits cytokine production by activated macrophages. The Journal of Immunology 147(11), 3815–3822 (1991)Google Scholar
  6. 6.
    de Waal Malefyt, R., Abrams, J., Bennett, B., Figdor, C., de Vries, J.: Interleukin 10(il-10) inhibits cytokine synthesis by human monocytes: an autoregulatory role of il-10 produced by monocytes. J. Exp. Med. 174(5), 1209–1220 (1991)CrossRefGoogle Scholar
  7. 7.
    Cassatella, M.A., Meda, L., Bonora, S., Ceska, M., Constantin, G.: Interleukin 10 (il-10) inhibits the release of proinflammatory cytokines from human polymorphonuclear leukocytes. evidence for an autocrine role of tumor necrosis factor and il-1 beta in mediating the production of il-8 triggered by lipopolysaccharide. The Journal of Experimental Medicine 178(6), 2207–2211 (1993)CrossRefGoogle Scholar
  8. 8.
    Marie, C., Pitton, C., Fitting, C., Cavaillon, J.M.: Regulation by anti-inflammatory cytokines (il-4, il-io, il-13, tgf)of interleukin-8 production by lps and/or tnf-activated human polymorphonuclear cells. Mediators of Inflammation 5, 334–340 (1996)CrossRefGoogle Scholar
  9. 9.
    Kennedy, A., DeLeo, F.: Neutrophil apoptosis and the resolution of infection. Immunologic Research 43, 25–61 (2009), 10.1007/s12026-008-8049-6CrossRefGoogle Scholar
  10. 10.
    Lucas, M., Stuart, L., Zhang, A., Hodivala-Dilke, K., Febbraio, M., Silverstein, R., Savill, J., Lacy-Hulbert, A.: Requirements for apoptotic cell contact in regulation of macrophage responses. J. Immunol. 177(6), 4047–4054 (2006)Google Scholar
  11. 11.
    Voll, R.E., Herrmann, M., Roth, E.A., Stach, C., Kalden, J.R., Girkontaite, I.: Immunosuppressive effects of apoptotic cells. Nature 390(6658), 350–351 (1997)CrossRefGoogle Scholar
  12. 12.
    Fachada, N.: Agent-based simulation of the immune system. Master’s thesis, Instituto Superior Tcnico de Lisboa (2008)Google Scholar
  13. 13.
    Cohen, I.R.: Modeling immune behavior for experimentalists. Immunological Reviews 216(1), 232–236 (2007)Google Scholar
  14. 14.
    Moore, K.W., de Waal Malefyt, R., Coffman, R.L., O’Garra, A.: Interleukin-10 and the interleukin-10 receptor. Annual Review of Immunology 19(1), 683–765 (2001)CrossRefGoogle Scholar
  15. 15.
    Borregaard, N., Cowland, J.B.: Granules of the human neutrophilic polymorphonuclear leukocyte. Blood 10, 3503–3521 (1997)Google Scholar
  16. 16.
    Goutelle, S., Maurin, M., Rougier, F., Barbaut, X., Bourguignon, L., Ducher, M., Maire, P.: The hill equation: a review of its capabilities in pharmacological modelling. Fundamental & Clinical Pharmacology 22(6), 633–648 (2008)CrossRefGoogle Scholar
  17. 17.
    LeVeque, R.J.: Finite Difference Methods for Ordinary and Partial Differential Equations. Society for Industrial and Applied Mathematics (2007)Google Scholar
  18. 18.
    Price, T., Ochs, H., Gershoni-Baruch, R., Harlan, J., Etzioni, A.: In vivo neutrophil and lymphocyte function studies in a patient with leukocyte adhesion deficiency type ii. Blood 84(5), 1635–1639 (1994)Google Scholar
  19. 19.
    Su, B., Zhou, W., Dorman, K.S., Jones, D.E.: Mathematical modelling of immune response in tissues. Computational and Mathematical Methods in Medicine: An Interdisciplinary Journal of Mathematical, Theoretical and Clinical Aspects of Medicine 10, 1748–6718 (2009)MathSciNetGoogle Scholar
  20. 20.
    Felder, S., Kam, Z.: Human neutrophil motility: Time-dependent three-dimensional shape and granule diffusion. Cell Motility and the Cytoskeleton 28(4), 285–302 (1994)CrossRefGoogle Scholar
  21. 21.
    Chettibi, S., Lawrence, A., Young, J., Lawrence, P., Stevenson, R.: Dispersive locomotion of human neutrophils in response to a steroid-induced factor from monocytes. J. Cell Sci. 107(11), 3173–3181 (1994)Google Scholar
  22. 22.
    Pennington, S.V., Berzins, M.: New nag library software for first-order partial differential equations. ACM Trans. Math. Softw. 20(1), 63–99 (1994)MATHCrossRefGoogle Scholar
  23. 23.
    Kirk, D., Hwu, W.: Massively Parallel Processors: A Hands-on Approach. Morgan Kaufmann (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Pedro Augusto F. Rocha
    • 1
  • Micael P. Xavier
    • 1
  • Alexandre B. Pigozzo
    • 1
  • Barbara de M. Quintela
    • 1
  • Gilson C. Macedo
    • 2
  • Rodrigo Weber dos Santos
    • 1
  • Marcelo Lobosco
    • 1
  1. 1.Graduate Program in Computational ModellingUFJFJuiz de ForaBrazil
  2. 2.Graduate Program in Biological ScienceUFJFJuiz de ForaBrazil

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