A new in-silico tool for quantifying the impact of blood flow dynamics on cerebral capillary activity

脑功能与血流自动调节密切相关，血流自动调节调节小血管的直径以满足局部脑代谢需要。最近的实验证据表明，血流对毛细血管壁施加的机械力对启动调节的信号的传输具有深远的影响，并且预计这种功能在不同的病理条件下会受到损害，例如高血压，中风和血管老化。到目前为止，这种现象只能通过离体动物实验来研究，其中微血管血流仍然大多不确定。事实上，虽然可以通过荧光显微镜测量血管细胞的活动，直接测量的机械力启动所考虑的血管调节pathways是不可能的。本项目旨在通过使用计算建模来表征在离体制剂中毛细血管壁和血流之间的机械相互作用。我们将计算在不同实验条件下施加在毛细血管网络上的流体机械力，并解释压力依赖性调节机制（这已经在我们以前的作品建模）。开发的工具将是非常有用的实验，因为它将允许重建流体-在不同的实验设置中，动态场和建立用于表征不同的观察到的细胞活性水平的阈值。

The cerebral function is tightly coupled with blood flow autoregulation, which modulates the diameter of small vessels for satisfying the local brain metabolic needs. Recent experimental evidence showed that mechanical forces exerted by blood flow on capillary wall has a profound effect on the transmission of the signal initiating the regulation and this function is expected to be impaired across different pathological conditions such as hypertension, stroke and vascular ageing. So far, this phenomenon can be only studied by means of ex-vivo animal experiments, where the microvascular blood flow remains mostly uncertain. Indeed, although vascular cells activity can be measured through fluorescence microscopy, the direct measurement of the mechanical forces initiating the considered vascular regulatory pathways is not possible.This project aims to characterize the mechanical interaction between capillary wall and blood flow in ex-vivo preparations by using computational modelling. We will compute fluid mechanical forces exerted over capillary networks across different experimental conditions and by accounting for pressure-dependent regulatory mechanisms (which have already been modelled in our previous works).The developed tool will be of great use for experimentalists because it will allow to reconstruct the fluid-dynamic field across different experimental settings and to establish thresholds for characterizing different observed cellular activity levels.