Development of a perfusable, hierarchical microvasculature-on-a-chip model

开发一种可灌注的、分级微血管芯片模型

阅读:1

Abstract

Several methods have been developed for generating 3D, in vitro, organ-on-chip models of human vasculature to study vascular function, transport, and tissue engineering. However, many of these existing models lack the hierarchical nature of the arterial-to-capillary-to-venous architecture that is key to capturing a more comprehensive view of the human microvasculature. Here, we present a perfusable, multi-compartmental model that recapitulates the three microvascular compartments to assess various physiological properties such as vessel permeability, vasoconstriction dynamics, and circulating cell arrest and extravasation. Viscous finger patterning and passive pumping create the larger arterial and venular lumens, while the smaller diameter capillary bed vessels are generated through self-assembly. These compartments anastomose and form a perfusable, hierarchical system that portrays the directionality of blood flow through the microvasculature. The addition of collagen channels reduces the apparent permeability of the central capillary region, likely by reducing leakage from the side channels, enabling more accurate measurements of vascular permeability-an important motivation for this study. Furthermore, the model permits modulation of fluid flow and shear stress conditions throughout the system by using hydrostatic pressure heads to apply pressure differentials across either the arteriole or the capillary. This is a pertinent system for modeling circulating tumor or T cell dissemination and extravasation. Circulating cells were found to arrest in areas conducive to physical trapping or areas with the least amount of shear stress, consistent with hemodynamic or mechanical theories of metastasis. Overall, this model captures more features of human microvascular beds and is capable of testing a broad variety of hypotheses.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。