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高血压中炎症介导的主动脉重塑的多尺度多细胞计算模型

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

作者信息

Estrada Ana C, Humphrey Jay D

机构信息

Department of Biomedical Engineering, Yale University, New Haven, CT, USA.

Electrical and Biomedical Engineering, Fairfield University, Fairfield, CT, USA.

出版信息

Ann Biomed Eng. 2025 Apr;53(4):1014-1023. doi: 10.1007/s10439-025-03685-3. Epub 2025 Feb 4.

Abstract

PURPOSE

Multiple 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.

METHODS

We 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.

RESULTS

We 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.

CONCLUSION

We show the utility of a multi-scale, multi-cell model in delineating effects of different chemo-mechanical stimuli in aortic remodeling in hypertension.

摘要

目的

多种细胞类型在主动脉壁内相互作用,以控制发育、稳态和适应性,并推动疾病进展。鉴于这些相互作用的复杂性及其在组织水平上的表现,迫切需要一类新的跨尺度整合数据的计算模型。

方法

我们融合了血管平滑肌细胞、外膜成纤维细胞和巨噬细胞的基于逻辑的细胞信号模型,并将这个多细胞模型与主动脉生长和重塑的组织水平约束混合模型相结合。使用文献数据对耦合的多尺度模型进行参数化,然后专门针对野生型小鼠中血管紧张素II诱导的胸降主动脉高血压重塑的情况。

结果

我们对比了化学和机械刺激对细胞反应的重要贡献,并确定了募集的巨噬细胞在驱动外膜层非稳态增厚中的关键作用,这种增厚将双轴壁应力降低到设定点值以下。

结论

我们展示了多尺度、多细胞模型在描绘高血压中不同化学-机械刺激对主动脉重塑的影响方面的效用。

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