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基于三维计算模型解析叶启发式毛细管网内的流体输运。

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

机构信息

State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, 710049, P. R. China.

NMPA Key Laboratory for Research and Evaluation of Additive Manufacturing Medical Devices, Xi'an Jiaotong University, Xi'an, 710049, P. R. China.

出版信息

Small. 2022 Apr;18(16):e2108102. doi: 10.1002/smll.202108102. Epub 2022 Mar 7.

Abstract

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.

摘要

叶脉为体外工程毛细血管样脉管提供了有前景的模板,因为它具有高效的流体传输能力,并且与天然毛细血管网络具有显著的相似性。探索基于叶片启发的毛细管网络(LICN)的潜在生物学应用的一个关键挑战是准确和定量地了解其内部流体传输特性。在这里,提出了一种基于中心线诱导的分区-组装建模策略来建立 3D 计算模型,该模型可以准确模拟 LICN 中的流动条件。基于 3D 流动模拟,作者展示了 LICN 出色的抗缺陷流体传输能力。有趣的是,主通道中的结构缺陷可以有效地提高整体灌注效率。具有多个缺陷的 LICN 中的流动模式可以通过简单地叠加来自相应单缺陷模型的模拟结果来估计。该 3D 计算模型还用于通过模拟天然微血管流动条件来确定体外形成内皮化毛细血管网络的最佳灌注参数。内皮化网络可以再现血管殖民化过程,并揭示癌细胞黏附和流动诱导剪切力之间的强相关性。这项研究为各种生物医学应用中 LICN 内的流体和生物传输机制提供了一种定量工具。

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