Literature DB >> 1576733

Redistribution of red blood cell flow in microcirculatory networks by hemodilution.

A R Pries1, A Fritzsche, K Ley, P Gaehtgens.   

Abstract

The effect of isovolemic hemodilution on red blood cell flow distribution was studied in complete self-contained microvessel networks of the rat mesentery. Hematocrit, diameter, and length of all vessel segments as well as the topological structure were determined in control networks (systemic hematocrit, 0.54) and after hemodilution (systemic hematocrit, 0.30). Hemodilution was performed by exchanging blood with hydroxyethyl starch (MW 450,000; 6%) or homologous plasma. With hemodilution, the decrease of microvessel hematocrit exceeded that of systemic hematocrit. The average discharge hematocrit in capillaries was 79% of systemic hematocrit in the control group and 73% with hemodilution (p less than 0.001). The heterogeneity of capillary hematocrit within the network, expressed by the coefficient of variation, increased from 0.4 to 0.7. By using the morphological and topological data of four networks, the distribution of hematocrits was also calculated using a hydrodynamic flow model. The modeling results were found to be in close agreement with the experimental data. This indicates that the observed changes can be deduced from established rheological phenomena, most of all phase separation at arteriolar bifurcations. The changes in hematocrit distribution after hemodilution are accompanied by a redistribution of red blood cell flow within the network: relative to total red blood cell flow, red blood cell flow in the distal capillaries of the network increases by about 40% at the expense of the proximal capillaries that are close to the feeding arteriole and that exhibit the highest red blood cell flow under control conditions.(ABSTRACT TRUNCATED AT 250 WORDS)

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Year:  1992        PMID: 1576733     DOI: 10.1161/01.res.70.6.1113

Source DB:  PubMed          Journal:  Circ Res        ISSN: 0009-7330            Impact factor:   17.367


  15 in total

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2.  Shear-induced non-monotonic viscosity dependence for model red blood cell suspensions in microvessels.

Authors:  Chih-Tang Liao; Yeng-Long Chen
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4.  The development of peripheral microvasculopathy with chronic metabolic disease in obese Zucker rats: a retrograde emergence?

Authors:  Brayden D Halvorson; Nithin J Menon; Daniel Goldman; Stephanie J Frisbee; Adam G Goodwill; Joshua T Butcher; Phoebe A Stapleton; Steven D Brooks; Alexandre C d'Audiffret; Robert W Wiseman; Julian H Lombard; Robert W Brock; I Mark Olfert; Paul D Chantler; Jefferson C Frisbee
Journal:  Am J Physiol Heart Circ Physiol       Date:  2022-07-29       Impact factor: 5.125

5.  Structural Features of Microvascular Networks Trigger Blood Flow Oscillations.

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Journal:  Bull Math Biol       Date:  2022-07-08       Impact factor: 3.871

6.  Modeling the hematocrit distribution in microcirculatory networks: A quantitative evaluation of a phase separation model.

Authors:  Peter M Rasmussen; Timothy W Secomb; Axel R Pries
Journal:  Microcirculation       Date:  2018-04       Impact factor: 2.628

7.  Cerebral microcirculation shear stress levels determine Neisseria meningitidis attachment sites along the blood-brain barrier.

Authors:  Emilie Mairey; Auguste Genovesio; Emmanuel Donnadieu; Christine Bernard; Francis Jaubert; Elisabeth Pinard; Jacques Seylaz; Jean-Christophe Olivo-Marin; Xavier Nassif; Guillaume Duménil
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Review 8.  Effects of impaired microvascular flow regulation on metabolism-perfusion matching and organ function.

Authors:  Tuhin K Roy; Timothy W Secomb
Journal:  Microcirculation       Date:  2020-12-21       Impact factor: 2.679

9.  Red blood cell dynamics in biomimetic microfluidic networks of pulmonary alveolar capillaries.

Authors:  Hagit Stauber; Dan Waisman; Netanel Korin; Josué Sznitman
Journal:  Biomicrofluidics       Date:  2017-01-10       Impact factor: 2.800

10.  Flow of Red Blood Cells in Stenosed Microvessels.

Authors:  Koohyar Vahidkhah; Peter Balogh; Prosenjit Bagchi
Journal:  Sci Rep       Date:  2016-06-20       Impact factor: 4.379

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