Liver regeneration after partial hepatectomy: the upper optimality estimate

Keywords: mathematical model of regeneration processes, partial hepatectomy, dynamic programming, optimality criterion

Abstract

This publication investigates one of the fundamental problems of mathematical biology, specifically the development of mathematical models for the dynamics of complex biosystems that have a satisfactory explanatory and predictable power. A necessary condition for the development of such models is to find a solution for the problem of identifying the objective principles and rules of regulation of the "cellular system", which determines among all the possibilities exactly the "real path" of its dynamics observed in the experiment.

One of the promising approaches to solving this problem is based on the hypothesis that the regulation of processes for support/restoration of the dynamic homeostasis of tissues and organs of the body occurs according to certain principles, and criteria of optimality, which have developed due to the natural selection of the body during its previous evolution.

It is quite difficult to solve this problem at the current time due to the many uncertainties in the paths of the previous evolution of the organism, the dynamics of changes in external conditions, as well as the high computational complexity of solving such a problem.

Instead of this, we have proposed a simplified formulation of the problem of searching for regulation control strategies, which gives us an upper estimate of optimality for the processes of maintaining/restoring dynamic homeostasis of the liver. The upper estimate of the optimality of regulation and testing of hypotheses for the model of liver regeneration was considered in the case of partial hepatectomy and was solved by Python software methods.

The result shows that in the case of partial hepatectomy, the liver regeneration strategies obtained in numerous experiments for the problem of the upper optimality estimate qualitatively coincide with the processes of liver regeneration that can be observed during biological experiments.

In plenty of experiments following hypotheses were also tested: how significant is the contribution of the process of controlled apoptosis, and how other processes (polyploidy, division, and formation of binuclear hepatocytes) affect the strategy of liver regeneration.

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References

N. Kiani, D. Gomez-Cabrero, G. Bianconi. Networks of Networks in Biology: Concepts, Tools and Applications. 2021. Cambridge: Cambridge University Press. 214 p. DOI: https://doi.org/10.1017/9781108553711

O. Wolkenhauer, M. Mesarovic. Feedback dynamics and cell function: why systems biology is called systems biology. Mol BioSyst. - 2005. - Vol. 1(1). - P.14--16. DOI: https://doi.org/10.1039/B502088N

E.T. Liu. Systems biology, integrative biology, predictive biology. Cell. - 2005. - Vol. 121(4). - P.505--506. DOI: https://doi.org/10.1016/j.cell.2005.04.021

W.J. Sutherland. The best solution. Nature. - 2005. - Vol. 435. - P. 569. DOI: https://doi.org/10.1038/435569a

N. Rashevsky. Mathematical principles in biology and their applications. 1961. Springfield, LA. 128 p.

R. Rosen. Optimality Principles in biology. 1967. Springer New York, NY. 198 p. DOI: https://doi.org/10.1007/978-1-4899-6419-9

N. Tsiantis, J.R. Banga. OUsing optimal control to understand complex metabolic pathways. BMC Bioinformatics. - 2020. - Vol. 21:472. - P.1-33. DOI: https://doi.org/10.1186/s12859-020-03808-8

E. Todorov. Optimality principles in sensorimotor control. Nature neuroscience. - 2004. - Vol. 7(9). - P.907-915. DOI: https://doi.org/10.1038/nn1309

M. G. J. de Vos, F. J. Poelwijk, S. J. Tans. Optimality in evolution: new insights from synthetic biology. Current opinion in biotechnology. - 2013. - Vol. 24(4). - P.797-802. DOI: https://doi.org/10.1016/j.copbio.2013.04.008

J.M. Smith. Optimization theory in evolution. Annu Rev Ecol Syst. - 1978. - Vol. 9(1). - P.31-56. DOI: https://doi.org/10.1146/annurev.es.09.110178.000335

G.A. Parker, J.M. Smith et al. Optimality theory in evolutionary biology. Nature. - 1990. - Vol. 348(6296). - P.27-33. DOI: https://doi.org/10.1038/348027a0

I. Yegorov, F. Mairet, H. De Jong, J.L. Gouze. Optimal control of bacterial growth for the maximization of metabolite production. J Math Biol. - 2019. - Vol. 78(4). - P.985-1032. DOI: https://doi.org/10.1007/s00285-018-1299-6

L. Bayon, P.F. Ayuso, J. Otero, P. Suarez, C. Tasis. Influence of enzyme production dynamics on the optimal control of a linear unbranched chemical process. J Math Chem. - 2019. - Vol. 57(5). - P.1330-1343. DOI: https://doi.org/10.1007/s10910-018-0969-3

M.D. Petkova, G. Tkacik, W. Bialek, E.F. Wieschaus, T. Gregor. Optimal decoding of cellular identities in a genetic network. Cell. - 2019. - Vol. 176(4). - P.844-855. DOI: https://doi.org/10.1016/j.cell.2019.01.007

V. V. Karieva, S. V. Lvov. Mathematical model of liver regeneration processes: homogeneous approximation, Visnyk of V.N.Karazin Kharkiv National University. Ser. ``Mathematics, Applied Mathematics and Mechanics''. - 2018. -Vol. 87. - P.29-41. DOI: https://doi.org/10.26565/2221-5646-2018-87-03

V. V. Karieva, S. V. Lvov, L. P. Artyukhova. Different strategies in the liver regeneration processes. Numerical experiments on the mathematical model. Visnyk of V.N.Karazin Kharkiv National University. Ser. ``Mathematics, Applied Mathematics and Mechanics''. - 2020. - Vol. 31. - P.~36--44. DOI: https://doi.org/10.26565/2221-5646-2020-91-03

G. Y. Minuk. Hepatic regeneration. If it ain’t broke, don’t fix it. Can. J. Gastroenterol.- 2003. - Vol. 17. - P.~418-424. DOI: https://doi.org/10.1155/2003/615403

R. Taub. R. Liver Regeneration: From Myth to Mechanism. Nature Reviews Molecular Cell Biology. - 2004. - Vol. 5. - P.836-847. DOI: http://dx.doi.org/10.1038/nrm1489

T. Itoh, A. Miyajima. Liver regeneration by stem/progenitor cells. Hepatology. - 2014. - Vol. 59(4)- P.1617-1626. DOI: http://dx.doi.org/10.1002/hep.26753

G. M. Higgins, R. M. Anderson. Experimental pathology of the liver. Restoration of the liver of the white rat following partial surgical removal, Archives of Pathology. - 1931. - Vol. 12. - P.186-202.

K. Nishiyama, H. Nakashima, M. Ikarashi, M. Kinoshita, M. Nakashima, S. Aosasa et al. Mouse CD11b+Kupffer cells recruited from bone marrow accelerate liver regeneration after partial hepatectomy. PLOS ONE. - 2015. - Vol. 10(9). - P.e0136774. DOI: https://doi.org/10.1371/journal.pone.0136774

Y. Miyaoka, A. Miyajima. To divide or not to divide: revisiting liver regeneration. Cell Division.- 2013. - Vol. 8:8. - P. 1-12. DOI: https://doi.org/10.1186/1747-1028-8-8

Y. Miyaoka, K. Ebato, H. Kato, S. Arakawa, S. Shimizu, A. Miyajima. Hypertrophy and unconventional cell division of hepatocytes underlie liver regeneration. Curr Biol. - 2012. - Vol. 22. - P. 1166-1175. DOI: https://doi.org/10.1016/j.cub.2012.05.016

G. Gentric, S. Celton-Morizur, C. Desdouets. Polyploidy and liver proliferation. Clin Res Hepatol Gastroenterol. - 2012. - Vol. 36. - P.29-34. DOI: https://doi.org/10.1016/j.clinre.2011.05.011

H.W. Beams, R.L. King. The origin of binucleate and large mono nucleate cells in the liver of the rat. Anat Rec. - 1942. - Vol. 83. - P.281-297. DOI: https://doi.org/10.1002/ar.1090830207

P. M. G. St. Aubin, N. L. R. Bucher. A study of binucleate cell counts in resting and regenerating rat liver employing a mechanical method for the separation of liver cells. Anat Rec. - 1952. - Vol. 112. - P.797-809. DOI: https://doi.org/10.1002/ar.1091120406

J. Nelder, R. Mead. A simplex method for function minimization. Computer Journal. - 1965. - Vol. 7 (4). - P.308-313. DOI: https://doi.org/10.1093/comjnl/7.4.308

F. Gao, L. Han. Implementing the Nelder-Mead simplex algorithm with adaptive parameters. Computational Optimization and Applications. - 2012. - Vol. 51. - P.259-277. DOI: https://doi.org/10.1007/s10589-010-9329-3

Published
2023-06-07
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How to Cite
Karieva, V. V., & Lvov, S. (2023). Liver regeneration after partial hepatectomy: the upper optimality estimate. Visnyk of V. N. Karazin Kharkiv National University. Ser. Mathematics, Applied Mathematics and Mechanics, 97, 41-58. https://doi.org/10.26565/2221-5646-2023-97-04
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