Irons Linda, Latorre Marcos, Humphrey Jay D
Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
Ann Biomed Eng. 2021 Jul;49(7):1701-1715. doi: 10.1007/s10439-020-02713-8. Epub 2021 Jan 7.
Tissue-level biomechanical properties and function derive from underlying cell signaling, which regulates mass deposition, organization, and removal. Here, we couple two existing modeling frameworks to capture associated multiscale interactions-one for vessel-level growth and remodeling and one for cell-level signaling-and illustrate utility by simulating aortic remodeling. At the vessel level, we employ a constrained mixture model describing turnover of individual wall constituents (elastin, intramural cells, and collagen), which has proven useful in predicting diverse adaptations as well as disease progression using phenomenological constitutive relations. Nevertheless, we now seek an improved mechanistic understanding of these processes; we replace phenomenological relations in the mixture model with a logic-based signaling model, which yields a system of ordinary differential equations predicting changes in collagen synthesis, matrix metalloproteinases, and cell proliferation in response to altered intramural stress, wall shear stress, and exogenous angiotensin II. This coupled approach promises improved understanding of the role of cell signaling in achieving tissue homeostasis and allows us to model feedback between vessel mechanics and cell signaling. We verify our model predictions against data from the hypertensive murine infrarenal abdominal aorta as well as results from validated phenomenological models, and consider effects of noisy signaling and heterogeneous cell populations.
组织水平的生物力学特性和功能源自潜在的细胞信号传导,该信号传导调节质量沉积、组织和清除。在此,我们将两个现有的建模框架结合起来,以捕捉相关的多尺度相互作用——一个用于血管水平的生长和重塑,另一个用于细胞水平的信号传导——并通过模拟主动脉重塑来说明其效用。在血管水平,我们采用一个约束混合模型来描述单个壁成分(弹性蛋白、壁内细胞和胶原蛋白)的更新,该模型已被证明在使用唯象本构关系预测各种适应性变化以及疾病进展方面很有用。然而,我们现在寻求对这些过程有更深入的机制理解;我们用基于逻辑的信号模型取代混合模型中的唯象关系,该模型产生一个常微分方程组,可预测胶原蛋白合成、基质金属蛋白酶和细胞增殖在壁内应力改变、壁面剪应力和外源性血管紧张素II作用下的变化。这种耦合方法有望更好地理解细胞信号传导在实现组织稳态中的作用,并使我们能够对血管力学和细胞信号传导之间的反馈进行建模。我们将模型预测结果与来自高血压小鼠肾下腹主动脉的数据以及经过验证的唯象模型的结果进行了验证,并考虑了噪声信号和异质细胞群体的影响。