Issue 2 (188), article 4


Kibern. vyčisl. teh., 2017, Issue 2 (188), pp.

Grygoryan R.D., Dr (in biology),
Chief of Department of human systems modeling and reliability
Aksenova T.V., Junior-researcher
Degoda A.G., Senior-researcher, PhD (in math.)
Institute of software systems of National Аcademy of Sciences of Ukraine,
40, Acad.Glushkov ave., corp.5, Kiev, 052187, Ukraine


Introduction. Human organism is a too complex system to be empirically examined and comprehended: there is no method for simultaneously measuring or integrally analyzing of billions of multi-scale life variables. Experts need models and information technologies that causally incorporate cell-scale and organism-scale biophysical and physiological data.

The purpose of the article is to describe a specialized simulator (SS) providing users of additional information concerning scenarios and multi-level mechanisms of energy optimization in the human organism.

Results. Multi-scale mechanisms providing cell energy balance (CEB) are in the basis of SS. At cell-level, providers of CEB form a battery of autonomous mechanisms (BAM). Under energy lack (EL), BAM increases the rate of ATP synthesis using local opportunities. If EL remains, extracellular providers of aerobic synthesis of ATP enlarge current potentials of the EL-cell. The SS provides simulation scenarios increasing the lung ventilation, the erythropoiesis, blood concentrations of carbohydrates, and of other nutrients for biogenesis of mitochondria. The role of the cardiovascular system is in regulating of blood incomes to EL-cells.

Conclusion. The SS is a novel informational technology of dual goals. Explaining the function of mechanisms-providers of CEB, the SS also can be used by applied physiologists and physicians for the planning of optimal scenarios for physical empowering of healthy people.

Keywords: mathematical models, mitochondria, glucose, integrative physiology, medicine.

Download full text (ru)!


1 Skulachev V.A.,Bogachev A.V., Kasparinsky F.O. Principles of Bioenergetics. Springer-Verlag, Berlin Heidelberg, 2013. 436 p.

2 Michiels C. Physiological and Pathological Responses to Hypoxia. Am J Pathol. 2004. No164. P. 1875–1882.

3 Kandel J., Angelin A.A., Wallace D.C. Mitochondrial respiration is sensitive to cytoarchitectural breakdown. Integr. Biol. (Camb). 2016, 8 (11). P. 1170–1182.

4 Finsterer J. Hematological manifestations of primary mitochondrial disorders. Acta Haematol. 2007. 118 (2). P. 88–98.

5 Mali V.R., pan G., Deshpande M. Cardiac Mitochondrial Respiratory Dysfunction and Tissue Damage in Chronic Hyperglycemia Correlate with Reduced Aldehyde Dehydrogenase-2 Activity. PLoS One. 2016.11 (10):e0163158.

6 Grygoryan R.D. The Energy Basis of Reversible Adaptation. N.Y.: Nova Science, 2012. 252 p.

7 Grygoryan R.D., Lyabakh K.G. Arterial pressure: a comprehension. Kyiv: ISS of National Academy of Sciences of Ukraine. 2015. 458 p. (In Russian).

8 Grygoryan R.D. The “floating” arterial pressure paradigm: a concept of physiological supersystems. Dusseldorf: Palmarium Academic Publishing. 2016. 417 p. (In Russian).

9 Grygoryan R.D., Deriev I.I., Aksionova T.V. A software simulator of aerobe cell’s responses to energy imbalance. Problems in programming. 2014. No 1. P. 90–98. (In Russian).

10 Grygoryan R.D., Aksionova T.V., Markevich R.A. A software simulator of pancreas. Problems in programming. 2013. No 1. P. 100–106. (In Russian).

11 Grygoryan R.D., Aksionova T.V., Degoda A.G. Modeling of mechanisms and hemodynamic effects of heart hypertrophy. Cybernetics and computer engineering. 2016. Issue.184. P. 72–83. (In Russian).

12 Grygoryan R.D., Aksionova T.V. Modeling of organism-scale mechanisms fighting against energy shortage in cells. Bulletin of University “Ukraine”. Series: Informatics, computers, and cybernetics. 2016. P. 91–99. (In Russian).

13 Aksionova T.V. A software technology providing simulations of mathematical models of physiological systems. Problems in programming. 2012. No1. P. 110–120. (In Russian).

14 Chada S.R., Hollenbeck P.J. Nerve growth factor signaling regulates motility and docking of axonal mitochondria. Curr. Biol. 2004. V.14. P. 1272–1276.

15 Ramamurthy S., Ronnett G. AMP-activated protein kinase (AMPK) and energy-sensing in the brain. Neurobiol. 2012. 21, No 2. P. 52–60.

Recieved 15.03.2017