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对比相应的常微分方程系统,刻画细胞周期结构化偏微分方程模型的行为。

Characterising the Behaviour of a Structured PDE Model of the Cell Cycle in Contrast to a Corresponding ODE System.

作者信息

Nixson Ruby E, Byrne Helen M, Pitt-Francis Joe M, Maini Philip K

机构信息

Wolfson Centre for Mathematical Biology, University of Oxford, Oxford, UK.

Ludwig Institute for Cancer Research, University of Oxford, Oxford, UK.

出版信息

Bull Math Biol. 2025 Jun 8;87(7):93. doi: 10.1007/s11538-025-01472-8.

Abstract

Experimental results have shown that anti-cancer therapies, such as radiotherapy and chemotherapy, can modulate the cell cycle and generate cell cycle phase-dependent responses. As a result, obtaining a detailed understanding of the cell cycle is one possible path towards improving the efficacy of many of these therapies. Here, we consider a basic structured partial differential equation (PDE) model for cell progression through the cell cycle, and derive expressions for key quantities, such as the population growth rate and cell phase proportions. These quantities are shown to be periodic and, as such, we compare the PDE model to a corresponding ordinary differential equation (ODE) model in which the parameters are linked by ensuring that the long-term ODE behaviour agrees with the average PDE behaviour. By design, we find that the ODE model does an excellent job of representing the mean dynamics of the PDE model within just a few cell cycles. However, by probing the parameter space we find cases in which this mean behaviour is not a good measure of the PDE population growth. Our analytical comparison of two caricature models (one PDE and one ODE system) provides insight into cases in which the simple ODE model is an appropriate approximation to the PDE model.

摘要

实验结果表明,放疗和化疗等抗癌疗法能够调节细胞周期并产生细胞周期阶段依赖性反应。因此,详细了解细胞周期是提高许多此类疗法疗效的一条可行途径。在此,我们考虑一个用于描述细胞在细胞周期中进展的基本结构化偏微分方程(PDE)模型,并推导关键量的表达式,如种群增长率和细胞阶段比例。这些量被证明是周期性的,因此,我们将PDE模型与相应的常微分方程(ODE)模型进行比较,在该ODE模型中,通过确保长期ODE行为与平均PDE行为一致来关联参数。通过设计,我们发现ODE模型在仅仅几个细胞周期内就能出色地表示PDE模型的平均动态。然而,通过探索参数空间,我们发现了一些情况,其中这种平均行为并不是PDE种群增长的良好度量。我们对两个简化模型(一个PDE模型和一个ODE系统)的分析比较,为简单ODE模型何时是PDE模型的合适近似提供了见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42bf/12146229/c5d3e15c96dc/11538_2025_1472_Fig1_HTML.jpg

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