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跨物种的脑毛细血管网络:几个简单的组织要求足以重现结构和功能。

Brain Capillary Networks Across Species: A few Simple Organizational Requirements Are Sufficient to Reproduce Both Structure and Function.

作者信息

Smith Amy F, Doyeux Vincent, Berg Maxime, Peyrounette Myriam, Haft-Javaherian Mohammad, Larue Anne-Edith, Slater John H, Lauwers Frédéric, Blinder Pablo, Tsai Philbert, Kleinfeld David, Schaffer Chris B, Nishimura Nozomi, Davit Yohan, Lorthois Sylvie

机构信息

Institut de Mécanique des Fluides de Toulouse (IMFT), Université de Toulouse, CNRS, Toulouse, France.

Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, United States.

出版信息

Front Physiol. 2019 Mar 26;10:233. doi: 10.3389/fphys.2019.00233. eCollection 2019.

Abstract

Despite the key role of the capillaries in neurovascular function, a thorough characterization of cerebral capillary network properties is currently lacking. Here, we define a range of metrics (geometrical, topological, flow, mass transfer, and robustness) for quantification of structural differences between brain areas, organs, species, or patient populations and, in parallel, digitally generate synthetic networks that replicate the key organizational features of anatomical networks (isotropy, connectedness, space-filling nature, convexity of tissue domains, characteristic size). To reach these objectives, we first construct a database of the defined metrics for healthy capillary networks obtained from imaging of mouse and human brains. Results show that anatomical networks are topologically equivalent between the two species and that geometrical metrics only differ in scaling. Based on these results, we then devise a method which employs constrained Voronoi diagrams to generate 3D model synthetic cerebral capillary networks that are locally randomized but homogeneous at the network-scale. With appropriate choice of scaling, these networks have equivalent properties to the anatomical data, demonstrated by comparison of the defined metrics. The ability to synthetically replicate cerebral capillary networks opens a broad range of applications, ranging from systematic computational studies of structure-function relationships in healthy capillary networks to detailed analysis of pathological structural degeneration, or even to the development of templates for fabrication of 3D biomimetic vascular networks embedded in tissue-engineered constructs.

摘要

尽管毛细血管在神经血管功能中起着关键作用,但目前缺乏对脑毛细血管网络特性的全面表征。在这里,我们定义了一系列指标(几何、拓扑、血流、物质传输和鲁棒性),用于量化脑区、器官、物种或患者群体之间的结构差异,同时,通过数字方式生成合成网络,这些网络复制了解剖网络的关键组织特征(各向同性、连通性、空间填充性质、组织域的凸性、特征尺寸)。为了实现这些目标,我们首先构建了一个数据库,其中包含从对小鼠和人类大脑成像获得的健康毛细血管网络的定义指标。结果表明,这两个物种的解剖网络在拓扑上是等效的,并且几何指标仅在缩放方面有所不同。基于这些结果,我们随后设计了一种方法,该方法采用约束Voronoi图来生成3D模型合成脑毛细血管网络,这些网络在局部是随机的,但在网络尺度上是均匀的。通过适当选择缩放比例,这些网络具有与解剖数据等效的特性,这通过对定义指标的比较得到证明。合成复制脑毛细血管网络的能力开启了广泛的应用,从对健康毛细血管网络中结构 - 功能关系的系统计算研究,到对病理结构退化的详细分析,甚至到开发嵌入组织工程构建体中的3D仿生血管网络制造模板。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/623e/6444172/72fe61ba0500/fphys-10-00233-g0001.jpg

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