Multi-Scale Multi-Cell Computational Model of Inflammation-Mediated Aortic Remodeling in Hypertension

被引:0
作者
Estrada, Ana C. [1 ,2 ]
Humphrey, Jay D. [1 ]
机构
[1] Yale Univ, Dept Biomed Engn, New Haven, CT 06520 USA
[2] Fairfield Univ, Elect & Biomed Engn, Fairfield, CT USA
基金
美国国家卫生研究院;
关键词
Fibroblast; Macrophage; Logic based; Constrained mixture; Fibrosis; RECEPTORS CONTRIBUTE; ARTERIAL STIFFNESS; ADVENTITIA; MECHANISMS; WALL; REGULATOR; FIBROSIS; GROWTH; RISK;
D O I
10.1007/s10439-025-03685-3
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
PurposeMultiple cell types interact within the aortic wall to control development, homeostasis, and adaptation as well as to drive disease progression. Given the complexity of these interactions and their manifestations at the tissue level, there is a pressing need for a new class of computational models that integrate data across scales.MethodsWe meld logic-based cell signaling models of vascular smooth muscle cells, adventitial fibroblasts, and macrophages and couple this multi-cell model with a tissue level-constrained mixture model of aortic growth and remodeling. The coupled multi-scale model is parameterized using data from the literature and then specialized for the case of angiotensin II-induced hypertensive remodeling of the descending thoracic aorta in wild-type mice.ResultsWe contrast important contributions of chemo- and mechano-stimulation of cell responses and identify critical roles of recruited macrophages in driving the non-homeostatic thickening of the adventitial layer that reduces biaxial wall stress below setpoint values.ConclusionWe show the utility of a multi-scale, multi-cell model in delineating effects of different chemo-mechanical stimuli in aortic remodeling in hypertension.
引用
收藏
页码:1014 / 1023
页数:10
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