Courant Institute of Mathematical Sciences, New York University, New York, United States.
Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.
Elife. 2023 Mar 14;12:e78100. doi: 10.7554/eLife.78100.
Veins in vascular networks, such as in blood vasculature or leaf networks, continuously reorganize, grow or shrink, to minimize energy dissipation. Flow shear stress on vein walls has been set forth as the local driver for a vein's continuous adaptation. Yet, shear feedback alone cannot account for the observed diversity of vein dynamics - a puzzle made harder by scarce spatiotemporal data. Here, we resolve network-wide vein dynamics and shear rate during spontaneous reorganization in the prototypical vascular networks of . Our experiments reveal a plethora of vein dynamics (stable, growing, shrinking) where the role of shear is ambiguous. Quantitative analysis of our data reveals that (a) shear rate indeed feeds back on vein radius, yet, with a time delay of 1-3 min. Further, we reconcile the experimentally observed disparate vein fates by developing a model for vein adaptation within a network and accounting for the observed time delay. The model reveals that (b) vein fate is determined by parameters - local pressure or relative vein resistance - which integrate the entire network's architecture, as they result from global conservation of fluid volume. Finally, we observe avalanches of network reorganization events that cause entire clusters of veins to vanish. Such avalanches are consistent with network architecture integrating parameters governing vein fate as vein connections continuously change. As the network architecture integrating parameters intrinsically arise from laminar fluid flow in veins, we expect our findings to play a role across flow-based vascular networks.
血管网络中的静脉,如血管或叶脉网络中的静脉,不断地进行重新组织、生长或收缩,以最小化能量耗散。静脉壁上的流动切应力已被确定为静脉持续适应的局部驱动因素。然而,仅剪切反馈不能解释所观察到的静脉动力学多样性——这一难题因时空数据稀缺而变得更加复杂。在这里,我们在. 的典型血管网络中自发重组期间解决了网络范围的静脉动力学和剪切率问题。我们的实验揭示了大量的静脉动力学(稳定、生长、收缩),其中剪切的作用是模棱两可的。对我们数据的定量分析表明,(a)剪切率确实反馈到静脉半径上,但存在 1-3 分钟的时间延迟。此外,我们通过在网络内开发一种用于静脉适应的模型并考虑观察到的时间延迟,来协调实验观察到的不同静脉命运。该模型表明,(b)静脉命运由参数决定——局部压力或相对静脉阻力——这些参数整合了整个网络的结构,因为它们来自于流体体积的全局守恒。最后,我们观察到网络重组事件的雪崩,导致整个静脉簇消失。这种雪崩与控制静脉命运的网络结构整合参数一致,因为静脉连接不断变化。由于整合控制静脉命运的参数的网络结构本质上源自静脉中的层流,我们预计我们的发现将在基于流动的血管网络中发挥作用。