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脑淋巴系统中的蠕动流。

Peristaltic flow in the glymphatic system.

机构信息

Univ. Lille, CNRS, ONERA, Arts et Métiers Institute of Technology, Centrale Lille, UMR 9014 - LMFL - Laboratoire de Mécanique des Fluides de Lille - Kampé de Fériet, 59000, Lille, France.

Auckland Bioeng. Inst. and Dept. Eng. Sci., University of Auckland, 70 Symonds Street, Bldg 439, Auckland, 1010, New Zealand.

出版信息

Sci Rep. 2020 Dec 3;10(1):21065. doi: 10.1038/s41598-020-77787-4.

DOI:10.1038/s41598-020-77787-4
PMID:33273489
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7713425/
Abstract

The flow inside the perivascular space (PVS) is modeled using a first-principles approach in order to investigate how the cerebrospinal fluid (CSF) enters the brain through a permeable layer of glial cells. Lubrication theory is employed to deal with the flow in the thin annular gap of the perivascular space between an impermeable artery and the brain tissue. The artery has an imposed peristaltic deformation and the deformable brain tissue is modeled by means of an elastic Hooke's law. The perivascular flow model is solved numerically, discovering that the peristaltic wave induces a steady streaming to/from the brain which strongly depends on the rigidity and the permeability of the brain tissue. A detailed quantification of the through flow across the glial boundary is obtained for a large parameter space of physiologically relevant conditions. The parameters include the elasticity and permeability of the brain, the curvature of the artery, its length and the amplitude of the peristaltic wave. A steady streaming component of the through flow due to the peristaltic wave is characterized by an in-depth physical analysis and the velocity across the glial layer is found to flow from and to the PVS, depending on the elasticity and permeability of the brain. The through CSF flow velocity is quantified to be of the order of micrometers per seconds.

摘要

采用第一性原理方法对血管周围空间(PVS)内的流动进行建模,以研究脑脊液(CSF)如何通过可渗透的神经胶质细胞层进入大脑。利用润滑理论来处理在不可渗透的动脉和脑组织之间的血管周围空间的薄环形间隙内的流动。动脉受到强制蠕动变形,可变形的脑组织通过弹性胡克定律进行建模。对血管周围流动模型进行数值求解,发现蠕动波会引起向大脑的稳定流动/从大脑流出的稳定流动,这强烈依赖于脑组织的刚性和渗透性。对于与生理相关条件的大参数空间,获得了穿过神经胶质边界的透流量的详细量化。这些参数包括大脑的弹性和渗透性、动脉的曲率、长度和蠕动波的幅度。由于蠕动波引起的透流的稳定流动分量通过深入的物理分析进行了描述,并且发现穿过神经胶质层的流速取决于大脑的弹性和渗透性,从 PVS 流出并流向 PVS。穿过 CSF 的流速被量化为每秒几微米的量级。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4e/7713425/92f898d287f2/41598_2020_77787_Fig10_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4e/7713425/92f898d287f2/41598_2020_77787_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4e/7713425/184619d2f386/41598_2020_77787_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4e/7713425/dfc76744a6a6/41598_2020_77787_Fig2_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4e/7713425/d36999cdcb75/41598_2020_77787_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4e/7713425/b19ce9f5c42d/41598_2020_77787_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4e/7713425/85ff270e32d4/41598_2020_77787_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4e/7713425/61135c7cc030/41598_2020_77787_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4e/7713425/aaeab9f563a8/41598_2020_77787_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4e/7713425/92f898d287f2/41598_2020_77787_Fig10_HTML.jpg

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J Theor Biol. 2022 Jun 7;542:111103. doi: 10.1016/j.jtbi.2022.111103. Epub 2022 Mar 23.
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Cerebrovascular Smooth Muscle Cells as the Drivers of Intramural Periarterial Drainage of the Brain.脑血管平滑肌细胞作为脑壁内动脉周围引流的驱动因素。
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Flow of cerebrospinal fluid is driven by arterial pulsations and is reduced in hypertension.
Sci Rep. 2025 Apr 21;15(1):13798. doi: 10.1038/s41598-025-97631-x.
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magnetic resonance imaging of the interstitial pressure gradients (pgMRI) using a pulsatile poroelastic computational model.使用脉动多孔弹性计算模型对间质压力梯度进行磁共振成像(pgMRI)
Interface Focus. 2025 Apr 4;15(1):20240044. doi: 10.1098/rsfs.2024.0044.
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Cerebrospinal Fluid Flow.脑脊液流动
Annu Rev Fluid Mech. 2023;55:237-264. doi: 10.1146/annurev-fluid-120720-011638. Epub 2022 Sep 28.
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