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

机译:跨物种的大脑毛细血管网络:一些简单的组织要求足以重现结构和功能

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摘要

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.
机译:尽管毛细血管在神经血管功能中起着关键作用,但目前仍缺乏对脑毛细血管网络特性的全面表征。在这里,我们定义了一系列度量(几何,拓扑,流量,传质和鲁棒性),用于量化大脑区域,器官,物种或患者群体之间的结构差异,同时,以数字方式生成可复制密钥的合成网络解剖网络的组织特征(各向同性,连通性,空间填充性质,组织域凸度,特征尺寸)。为了实现这些目标,我们首先构建一个从小鼠和人脑成像获得的健康毛细血管网络定义指标的数据库。结果表明,两个物种之间的解剖网络在拓扑上是等效的,并且几何度量仅在比例上有所不同。基于这些结果,我们然后设计一种方法,该方法使用约束Voronoi图来生成3D模型合成脑毛细血管网络,该网络在本地范围内是随机的,但在网络规模上是同质的。通过适当选择缩放比例,这些网络具有与解剖数据等效的属性,通过比较定义的量度可以证明。合成性复制脑毛细血管网络的能力开辟了广泛的应用范围,从健康毛细血管网络中结构-功能关系的系统计算研究到病理性结构退化的详细分析,甚至开发用于制造3D仿生血管的模板嵌入组织工程结构中的网络。

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