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根据血细胞比容和剪切速率对血液粘度进行标准化。

Normalization of Blood Viscosity According to the Hematocrit and the Shear Rate.

作者信息

Trejo-Soto Claudia, Hernández-Machado Aurora

机构信息

Instituto de Física, Pontificia Universidad Católica de Valparaiso, Casilla 4059, Chile.

Departament de Física de la Materia Condensada, Universitat de Barcelona, Av. Diagonal 645, 08028 Barcelona, Spain.

出版信息

Micromachines (Basel). 2022 Feb 24;13(3):357. doi: 10.3390/mi13030357.

DOI:10.3390/mi13030357
PMID:35334649
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8954080/
Abstract

The rheological properties of blood depend highly on the properties of its red blood cells: concentration, membrane elasticity, and aggregation. These properties affect the viscosity of blood as well as its shear thinning behavior. Using an experimental analysis of the interface advancement of blood in a microchannel, we determine the viscosity of different samples of blood. In this work, we present two methods that successfully normalize the viscosity of blood for a single and for different donors, first according to the concentration of erythrocytes and second according to the shear rate. The proposed methodology is able to predict the health conditions of the blood samples by introducing a non-dimensional coefficient that accounts for the response to shear rate of the different donors blood samples. By means of these normalization methods, we were able to determine the differences between the red blood cells of the samples and define a range where healthy blood samples can be described by a single behavior.

摘要

血液的流变学特性高度依赖于其红细胞的特性

浓度、膜弹性和聚集性。这些特性会影响血液的粘度及其剪切变稀行为。通过对微通道中血液界面推进的实验分析,我们测定了不同血液样本的粘度。在这项工作中,我们提出了两种方法,它们成功地对单个和不同献血者的血液粘度进行了归一化,第一种方法是根据红细胞浓度,第二种方法是根据剪切速率。所提出的方法能够通过引入一个无量纲系数来预测血液样本的健康状况,该系数考虑了不同献血者血液样本对剪切速率的响应。通过这些归一化方法,我们能够确定样本中红细胞之间的差异,并定义一个范围,在这个范围内健康血液样本可以用单一行为来描述。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/96baca6db969/micromachines-13-00357-g010a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/8fbeffff5894/micromachines-13-00357-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/f8782c688f95/micromachines-13-00357-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/06a5ddfe7220/micromachines-13-00357-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/97255f589dcc/micromachines-13-00357-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/f9151b319783/micromachines-13-00357-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/3521ced42982/micromachines-13-00357-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/cf7c9891660d/micromachines-13-00357-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/dae3f84ba14a/micromachines-13-00357-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/839fb08f35e5/micromachines-13-00357-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/96baca6db969/micromachines-13-00357-g010a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/8fbeffff5894/micromachines-13-00357-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/f8782c688f95/micromachines-13-00357-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/06a5ddfe7220/micromachines-13-00357-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/97255f589dcc/micromachines-13-00357-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/f9151b319783/micromachines-13-00357-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/3521ced42982/micromachines-13-00357-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/cf7c9891660d/micromachines-13-00357-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/dae3f84ba14a/micromachines-13-00357-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/839fb08f35e5/micromachines-13-00357-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0bb/8954080/96baca6db969/micromachines-13-00357-g010a.jpg

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