Chemomechanical regulation of growing tissues from a thermodynamically-consistent framework and its application to tumor spheroid growth.

IF 2.3 4区 数学 Q2 BIOLOGY
Nonthakorn Olaranont, Chaozhen Wei, John Lowengrub, Min Wu
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引用次数: 0

Abstract

It is widely recognized that reciprocal interactions between cells and their microenvironment, via mechanical forces and biochemical signaling pathways, regulate cell behaviors during normal development, homeostasis and disease progression such as cancer. However, how exactly cells and tissues regulate growth in response to chemical and mechanical cues is still not clear. Here, we propose a framework for the chemomechanical regulation of growth based on thermodynamics of continua and growth-elasticity to predict growth patterns. Combining the elastic and chemical energies, we use an energy variational approach to derive a novel formulation that isolates the mass-conserving tissue rearrangement from the mass-accretion volumetric growth, and incorporates independent energy-dissipating stress relaxation and biochemomechanical regulation of the volumetric growth rate respectively. We validate the model using experimental data from growth of tumor spheroids in confined environments. We also investigate the influence of model parameters, including tissue rearrangement rate, tissue compressibility, strength of mechanical feedback and external mechanical stimuli, on the growth patterns of tumor spheroids.

基于热力学一致框架的组织生长的化学力学调控及其在肿瘤球体生长中的应用。
人们普遍认为,细胞与其微环境之间的相互作用,通过机械力和生化信号通路,调节细胞在正常发育、体内平衡和疾病进展(如癌症)过程中的行为。然而,细胞和组织究竟是如何根据化学和机械信号来调节生长的,目前还不清楚。在此,我们提出了一个基于连续热力学和生长弹性的生长化学力学调节框架,以预测生长模式。结合弹性能和化学能,我们使用能量变分方法推导出一种新的公式,该公式将质量守恒的组织重排从质量增加的体积增长中分离出来,并分别纳入独立的能量耗散应力松弛和体积增长速率的生化力学调节。我们用封闭环境中肿瘤球体生长的实验数据验证了该模型。我们还研究了模型参数,包括组织重排率、组织可压缩性、机械反馈强度和外部机械刺激对肿瘤球体生长模式的影响。
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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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