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Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth

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 hybri...

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Detalles Bibliográficos
Autores principales: de la Cruz, Roberto, Guerrero, Pilar, Calvo, Juan, Alarcón, Tomás
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5656096/
https://www.ncbi.nlm.nih.gov/pubmed/29200499
http://dx.doi.org/10.1016/j.jcp.2017.09.019
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author de la Cruz, Roberto
Guerrero, Pilar
Calvo, Juan
Alarcón, Tomás
author_facet de la Cruz, Roberto
Guerrero, Pilar
Calvo, Juan
Alarcón, Tomás
author_sort de la Cruz, Roberto
collection PubMed
description 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.
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spelling pubmed-56560962017-12-01 Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth de la Cruz, Roberto Guerrero, Pilar Calvo, Juan Alarcón, Tomás J Comput Phys Article 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. Academic Press 2017-12-01 /pmc/articles/PMC5656096/ /pubmed/29200499 http://dx.doi.org/10.1016/j.jcp.2017.09.019 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
de la Cruz, Roberto
Guerrero, Pilar
Calvo, Juan
Alarcón, Tomás
Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth
title Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth
title_full Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth
title_fullStr Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth
title_full_unstemmed Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth
title_short Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth
title_sort coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5656096/
https://www.ncbi.nlm.nih.gov/pubmed/29200499
http://dx.doi.org/10.1016/j.jcp.2017.09.019
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