Skip to main content
SpringerLink
Log in

Optimal control of the immune response synchronizing the various regulatory compartments of the immune system. I. Mathematical analysis of the risk of pathological disorders in the organism

  • System Analysis
  • Published:
Cybernetics and Systems Analysis Aims and scope

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  1. V. M. Glushkov, V. V. Ivanov, and V. M. Yanenko, Modeling Evolving Systems [in Russian], Nauka, Moscow (1983).

    Google Scholar 

  2. V. S. Mikhalevich, V. V. Ivanov, V. M. Yanenko, et al., “Integro-functional model of blood-formation regulation,” Kibernetika, No. 3, 69–77 (1986).

    Google Scholar 

  3. V. S. Mikhalevich, V. M. Janenko, and K. L. Atoev, “System analysis of mechanisms of organism's defensive function regulation (MODER),” in: Selected Topics on Mathematical Models in Immunology and Medicine, Proc. Int. Workshop, Kiev, Aug. 28–Sept. 7, 1989, IIASA, Laxenburg (1990), pp. 137–145.

    Google Scholar 

  4. V. S. Mikhalevich, V. M. Yanenko, K. L. Atoev, et al., “Mathematical modeling of immune system regulatory mechanisms traced by 2″–5″ adenyl acid oligonucleotides,” Preprint 90-47, Inst. Kibern. im. V. M. Glushkova, AN UkrSSR, Kiev (1990).

    Google Scholar 

  5. V. M. Yanenko and V. A. Mazurenko, “Increasing the effectiveness of computer-aided diagnosis of acute leucosis,” in: M. L. Bykhovskii (ed.), Mathematical and Technical Aspects of Medical Cybernetics [in Russian], VPI, Voronezh (1978), pp. 84–97.

    Google Scholar 

  6. V. M. Yanenko, “Modeling the dynamics of precursor clone cells and tumor growth,” in: Z. A. Butenko (ed.), The Trunk Cell and Tumor Growth [in Russian], Naukova Dumka, Kiev (1984), pp. 247–251.

    Google Scholar 

  7. V. M. Yanenko and V. A. Mazurenko, “Increasing the effectiveness of computer-aided differential diagnosis and therapy of some forms of acute leucosis,” in: Application of Mathematical Methods for Processing of Medical-Biological Data and Computers in Medical Practice [in Russian], Part 2, VNIIMP MZ SSSR (1984), pp. 247–251.

  8. R. V. Petrov and K. A. Lebedev, “New techniques in clinical immunology,” Klinich. Medits.,63, No. 3, 5–13 (1985).

    Google Scholar 

  9. G. I. Marchuk, Mathematical Models in Immunology [in Russian], Nauka, Moscow (1985).

    Google Scholar 

  10. H. Frimel and I. Brok, Fundamentals of Immunology [Russian translation], Mir, Moscow (1986).

    Google Scholar 

  11. K. L. Atoev and V. M. Yanenko, “Immune status of the organism: synergism and antagonism of effector and suppressor lymphocyte populations. A mathematical study,” Kibernetika, No.4, 115–125 (1988).

    MathSciNet  Google Scholar 

  12. V. M. Janenko and K. L. Atoev, “Mathematical simulation of the immunomodulating role of energy metabolism in support of synergism and antagonism of compartments of an immune system,” Acta Appl. Mathem.,14, 167–178 (1989).

    MathSciNet  Google Scholar 

  13. V. S. Mikhalevich, V. M. Yanenko, and K. L. Atoev, “An information system for assessing the risk of ecological catastrophes,” in: Modeling the Functional State of the Organism and Its Control [in Russian], Inst. Kibern. im. V. M. Glushkova NAN Ukr., Kiev (1993), pp. 52–74.

    Google Scholar 

  14. K. L. Atoev, “A computer-aided technology for assessing the risk of irreversible changes at various levels of biosystem organization,” in: Modeling the Functional State of the Organism and Its Control [in Russian], Inst. Kibern. im. V. M. Glushkova NAN Ukr., Kiev (1993), pp. 4–30.

    Google Scholar 

  15. R. J. DeBoer, P. Hogeweg, H. F. J. Dullens, and others, “Macrophage T-lymphocyte interactions in the anti-tumor immune response: A mathematical model,” J. Immun.,134, 2748–2758 (1985).

    Google Scholar 

  16. K. S. Lee and R. R. Mohler, “On tumor modeling and control,” in: Selected Topics on Mathematical Models in Immunology and Medicine, Proc. Int. Workshop, Kiev, Aug. 28–Sept. 7, 1989, IIASA, Laxenburg (1990), pp. 71–82.

    Google Scholar 

  17. J. Folkman, R. Langer, R. J. Lindhart, et al., “Angiogenesis inhibition caused by heparin or fragment in the presence of cortisone,” Science,221, 719–725 (1983).

    Google Scholar 

  18. N. M. Berezhnaya and S. I. Yalkut, Biological Role of Immunoglobulin-E [in Russian], Naukova Dumka, Kiev (1983).

    Google Scholar 

  19. M. Chum, M. Krim, A. Grinelli-Piperno, et al., “Enhancement of cytotoxic activity of natural killer cells by interleukin-2 and antagonism between interleukin-2 and cyclic monophosphate,” Scand. J. Immun.,22, No. 4, 375–381 (1985).

    Google Scholar 

  20. A. S. Gukovskaya, “The role of ions in lymphocyte activation,” Usp. Sovrem. Biol.,97, No. 2, 179–192 (1984).

    Google Scholar 

  21. K. G. Chandy, T. E. DeCoersey, M. D. Cahalan, et al., “Electroimmunology: the physiological role of ion channels in the immune system,” J. Immun.,132, No. 2, 787–791 (1985).

    Google Scholar 

  22. W. G. Nayler, P. A. Pool-Wilson, and A. Williams, “Hypoxia and calcium,” J. Mol. Cell. Cardiol.,11, 683–706 (1979).

    Google Scholar 

  23. K. L. Atoev, V. V. Ivanov, and V. M. Yanenko, “Interrelationship of processes of energy synthesis and consumption in tissues infected by viral infection. A mathematical model,” Kibernetika, No. 3, 90–96 (1986).

    Google Scholar 

  24. K. L. Atoev, “A mathematical model of regulation by energy metabolism of ion transport to myocardial cells,” Kibern. Vychisl. Tekhn., No. 82, 56–60 (1989).

    MATH  Google Scholar 

  25. K. L. Atoev, “A study of the role of cyclic nucleotides in regulation of calcium transport, myocardial energy metabolism, and biosynthesis under extreme loads on the heart,” Kibern. Vychisl. Tekhn., No. 90, 100–106 (1991).

    Google Scholar 

  26. I. V. Sergienko and M. F. Kaspshitskaya, Models and Methods for Computer Solution, of Combinatorial Optimization Problems [in Russian], Naukova Dumka, Kiev (1985).

    Google Scholar 

  27. I. V. Sergienko, Mathematical Models and Methods for Discrete Optimization Problems [in Russian], Naukova Dumka, Kiev (1985).

    Google Scholar 

  28. V. S. Mikhalevich and I. V. Sergienko, “Analysis of problem-solving methods and their applications,” Kibernetika, No. 4, 89–113 (1981).

    MathSciNet  Google Scholar 

  29. R. M. Baevskii, “Evaluation and classification of health levels from the point of view of adaptation theory,” Vestnik AMN SSSR, No. 8, 73–78 (1989).

    Google Scholar 

  30. Yu. I. Zhuravlev, “Correct algebras over the set of incorrect (heuristic) algorithms, I, II, III,” Kibernetika, No. 4, 14–21 (1977); No. 6, 21–27 (1977); No. 2, 35–43 (1978).

    MATH  Google Scholar 

Download references

Authors
  1. I. V. Sergienko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. M. Yanenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. K. L. Atoev
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 83–99, March–April, 1995.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sergienko, I.V., Yanenko, V.M. & Atoev, K.L. Optimal control of the immune response synchronizing the various regulatory compartments of the immune system. I. Mathematical analysis of the risk of pathological disorders in the organism. Cybern Syst Anal 31, 225–239 (1995). https://doi.org/10.1007/BF02366922

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02366922

Keywords

Search

Navigation