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Stochastic nonlinear model for somatic cell population dynamics during ovarian follicle activation
Journal of Mathematical Biology ( IF 2.2 ) Pub Date : 2021-02-02 , DOI: 10.1007/s00285-021-01561-x
Frédérique Clément 1 , Frédérique Robin 1 , Romain Yvinec 1, 2
Affiliation  

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.



中文翻译:

卵泡激活过程中体细胞群动态的随机非线性模型

在哺乳动物中,雌性生殖细胞被保护在称为卵泡的体细胞结构中,在整个生殖生命中,卵泡在被激活之前一直处于静止状态。我们研究了在卵泡激活后发生的体细胞事件序列,从前体体细胞的觉醒开始,并将它们转化为增殖细胞。我们引入了一个非线性随机模型来解释两种细胞类型的联合动力学,并允许我们研究增殖细胞反馈对前体细胞的潜在影响。为了解决细胞增殖是伴随细胞还是在细胞觉醒之后的关键问题,我们评估了所有前体细胞觉醒所需的时间,以及总细胞数相对于初始细胞数的相应增加。使用首次通过时间的概率理论,我们设计了一个基于严格有限状态投影和耦合技术的数值方案,以计算平均消光时间和消光时的细胞数。我们发现反馈项明显降低了灭绝时增殖细胞的数量。我们使用精确似然方法校准模型参数。我们对初始模型和一系列子模型进行了全面比较,这有助于选择激活过程中发生的关键细胞事件,并表明觉醒比增殖更为突出。我们发现反馈项明显降低了灭绝时增殖细胞的数量。我们使用精确似然方法校准模型参数。我们对初始模型和一系列子模型进行了全面比较,这有助于选择激活过程中发生的关键细胞事件,并表明觉醒比增殖更为突出。我们发现反馈项明显降低了灭绝时增殖细胞的数量。我们使用精确似然方法校准模型参数。我们对初始模型和一系列子模型进行了全面比较,这有助于选择激活过程中发生的关键细胞事件,并表明觉醒比增殖更为突出。

更新日期:2021-02-02
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