Stochastic nonlinear model for somatic cell population dynamics during ovarian follicle activation - Inria - Institut national de recherche en sciences et technologies du numérique
Journal Articles Journal of Mathematical Biology Year : 2021

Stochastic nonlinear model for somatic cell population dynamics during ovarian follicle activation

Abstract

In mammals, female germ cells are sheltered within somatic structures called ovarian follicles, which remain in a quiescent state until they get activated, all along reproductive life. We investigate the sequence of somatic cell events occurring just after follicle activation, starting by the awakening of precursor somatic cells, and their transformation into proliferative cells. We introduce a nonlinear stochastic model accounting for the joint dynamics of the two cell types, and allowing us to investigate the potential impact of a feedback from proliferative cells onto precursor cells. To tackle the key issue of whether cell proliferation is concomitant or posterior to cell awakening, we assess both the time needed for all precursor cells to {awake}, and the corresponding increase in the total cell number with respect to the initial cell number. Using the probabilistic theory of first passage times, we design a numerical scheme based on a rigorous Finite State Projection and coupling techniques to compute the mean extinction time and the cell number at extinction time. We find that the feedback term clearly lowers the number of proliferative cells at the extinction time. We calibrate the model parameters using an exact likelihood approach. We carry out a comprehensive comparison between the initial model and a series of submodels, which helps to select the critical cell events taking place during activation, and suggests that awakening is prominent over proliferation.
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Dates and versions

hal-02057983 , version 1 (13-01-2021)

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Frédérique Clément, Frédérique Robin, Romain Yvinec. Stochastic nonlinear model for somatic cell population dynamics during ovarian follicle activation. Journal of Mathematical Biology, 2021, 82 (3), pp.1-52. ⟨10.1007/s00285-021-01561-x⟩. ⟨hal-02057983⟩
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