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DOI 10.1098/rspa.2023.0116

Медицинская библиотека · Proceedings. Mathematical, physical, and engineering sciences · 2023

Computational modelling distinguishes diverse contributors to aneurysmal progression in the Marfan aorta.

Li David S, Cavinato Cristina, Latorre Marcos, Humphrey Jay D

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Аннотация

Thoracic aortic aneurysms are characterized by a progressive loss of biomechanical functionality resulting from degenerative changes in wall composition, microstructure, and mechanical properties. Among the many causes of these lesions, Marfan syndrome is the most common heritable condition, resulting from mutations to the gene that codes the elastin-associated glycoprotein fibrillin-1. Key histopathological features of the aneurysmal Marfan aorta include extensive degradation of elastic fibres, significant remodelling of fibrillar collagens and compromised smooth muscle cell function. Computational growth and remodelling models have confirmed the importance of compromised elastic fibre integrity in aneurysmal dilatation, but we show here that this contributor alone is not sufficient to describe biomechanical data collected from the two most common mouse models of Marfan syndrome. Rather, our simulations suggest that compromised mechanosensing and mechanoregulation of extracellular matrix by mural cells also play central roles in the natural history. Determination of optimal disease-contributing parameters further suggests a rapid reduction in cellular mechanosensing and mechanoregulation relative to diminished elastic fibre integrity, highlighting the importance of inter- and intra-lamellar elastin in the Marfan aorta. Aneurysmal dilatation in Marfan syndrome thus results from multiple contributors to progressive degeneration of the aortic wall, and computational mechanobiological models can help disentangle these contributions.

Для цитирования: Li David S, Cavinato Cristina, Latorre Marcos, Humphrey Jay D. Computational modelling distinguishes diverse contributors to aneurysmal progression in the Marfan aorta.. Proceedings. Mathematical, physical, and engineering sciences. 2023. DOI: 10.1098/rspa.2023.0116.
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