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Deciphering Fluid Transport Within Leaf-Inspired Capillary Networks Based on a 3D Computational Model.

Mao MaoPengyu ChenJiankang HeGuangyu ZhuXiao LiDichen Li
Published in: Small (Weinheim an der Bergstrasse, Germany) (2022)
Leaf venation provides a promising template for engineering capillary-like vasculature in vitro due to its highly efficient fluid transport capability and remarkable similarities to native capillary networks. A key challenge in exploring the potential biological applications of leaf-inspired capillary networks (LICNs) is to accurately and quantitively understand its internal fluid transport characteristics. Here, a centerline-induced partition-assembly modeling strategy is proposed to establish a 3D computational model, which can accurately simulate the flow conditions in LICNs. Based on the 3D flow simulation, the authors demonstrate the excellent defect-resistant fluid transport capability of LICNs. Interestingly, structural defects in the primary channel can effectively accelerate the overall perfusion efficiency. Flow patterns in LICNs with multiple defects can be estimated by simple superposition of the simulation results derived from the corresponding single-defect models. The 3D computational model is further used to determine the optimal perfusion parameter for the in-vitro formation of endothelialized capillary networks by mimicking native microvascular flow conditions. The endothelialized networks can recapitulate the vascular colonization process and reveal a strong correlation between cancer cell adhesion and flow-induced shear stress. This study offers a quantitative tool to scrutinize the fluid and biological transport mechanisms within LICNs for various biomedical applications.
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