de la Cruz Roberto, Guerrero Pilar, Calvo Juan, Alarcón Tomás
Centre de Recerca Matemàtica, Edifici C, Campus de Bellaterra, 08193 Bellaterra (Barcelona), Spain.
Departament de Matemàtiques, Universitat Autònoma de Barcelona, 08193 Bellaterra (Barcelona), Spain.
J Comput Phys. 2017 Dec 1;350:974-991. doi: 10.1016/j.jcp.2017.09.019.
The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.
混合方法的发展在多尺度建模和随机反应扩散系统中备受关注,因为它们在生物学领域有应用。我们为细胞群体的随机多尺度模型制定了一种混合方法,该方法扩展了现有反应扩散系统混合方法的适用范围。这种方法是针对肿瘤生长的随机多尺度模型开发的,即群体动力学模型,它考虑了影响细胞数量和细胞内动力学的内在噪声的影响。为了制定这种方法,我们为完整的随机模型及其平均场极限开发了一种粗粒度近似。这种近似通过假设群体的年龄分布非常快地达到平衡,从而平均掉年龄结构(这体现了模型的多尺度性质)。然后,我们将粗粒度平均场模型与完整的随机多尺度模型耦合。这样做的话,在平均场区域内,我们忽略了细胞数量(群体)及其出生率(结构)中的噪声。这意味着,除了随机反应扩散系统中出现的问题外,在尝试耦合这两种描述时,我们还需要考虑群体的年龄结构。我们利用粗粒度模型,使得在平均场区域内,年龄分布处于平衡状态且我们知道其显式形式。这使我们能够一致地耦合两个区域,因为当细胞从平均场转移到随机区域时,我们对平衡年龄分布进行采样。此外,我们的方法使我们能够研究细胞内噪声,即出生率的波动,对诸如行波速度等集体性质的影响。我们表明,群体和出生率噪声的组合在前缘区域会导致出生率的大幅波动,而粗粒度模型无法解释这种波动。这种波动对波速有非平凡的影响。因此,除了开发一种新的混合方法外,我们得出结论,出生率波动对于定量准确描述诸如肿瘤生长等侵袭现象至关重要。