Maxim Kuznetsov

Mr. Maxim Kuznetsov

P.N. Lebedev Physical Institute of the Russian Academy of Sciences
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Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2021 in Physics of Life Reviews
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MKMaxim Kuznetsov
Maxim Kuznetsov
JCJ. Clairambault
J. Clairambault
Vitaly VolpertVitaly Volpert
Vitaly Volpert

12 May 2017 in Physical Review E
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MKMaxim Kuznetsov
Maxim Kuznetsov
AKAndrey Kolobov
Andrey Kolobov
APAndrey Polezhaev
Andrey Polezhaev
We investigate numerically the behavior of a two-component reaction-diffusion system of Fitzhugh-Nagumo type before the onset of subcritical Turing bifurcation in response to local rigid perturbation. In a large region of parameters, the initial perturbation evolves into a localized structure. In a part of that region, closer to the bifurcation line, this structure turns out to be unstable and covers all the available space over the course of time in a process of self-completion. Depending on the parameter values in two-dimensional (2D) space, this process happens either through generation and evolution of new peaks on oscillatory tails of the initial pattern, or through the elongation, deformation, and rupture of initial structure, leading to space-filling nonbranching snakelike patterns. Transient regimes are also possible. Comparison of these results with 1D simulations shows that the prebifurcation region of parameters where the self-completion process is observed is much larger in the 2D case.


30 November 2022 in Journal of Theoretical Biology
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MKMaxim Kuznetsov
Maxim Kuznetsov
AKAndrey Kolobov
Andrey Kolobov

1 October 2019 in Journal of Mathematical Biology
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MKMaxim Kuznetsov
Maxim Kuznetsov
AKAndrey Kolobov
Andrey Kolobov

22 July 2020 in Mathematics
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MKMaxim Kuznetsov
Maxim Kuznetsov
AKAndrey Kolobov
Andrey Kolobov
A spatially-distributed continuous mathematical model of solid tumor growth and treatment by fractionated radiotherapy is presented. The model explicitly accounts for three time and space-dependent factors that influence the efficiency of radiotherapy fractionation schemes—tumor cell repopulation, reoxygenation and redistribution of proliferative states. A special algorithm is developed, aimed at finding the fractionation schemes that provide increased tumor cure probability under the constraints of maximum normal tissue damage and maximum fractional dose. The optimization procedure is performed for varied radiosensitivity of tumor cells under the values of model parameters, corresponding to different degrees of tumor malignancy. The resulting optimized schemes consist of two stages. The first stages are aimed to increase the radiosensitivity of the tumor cells, remaining after their end, sparing the caused normal tissue damage. This allows to increase the doses during the second stages and thus take advantage of the obtained increased radiosensitivity. Such method leads to significant expansions in the curative ranges of the values of tumor radiosensitivity parameters. Overall, the results of this study represent the theoretical proof of concept that non-uniform radiotherapy fractionation schemes may be considerably more effective that uniform ones, due to the time and space-dependent effects.