Literature DB >> 7832188

Sickle cell rheology is determined by polymer fraction--not cell morphology.

H Hiruma1, C T Noguchi, N Uyesaka, S Hasegawa, E J Blanchette-Mackie, A N Schechter, G P Rodgers.   

Abstract

Sickle cell disease pathophysiology is mediated by acute and chronic impairment of cell flexibility due to the formation of intracellular sickle hemoglobin (Hb S) polymer as cells are partially deoxygenated in the microcirculation. We have recently developed a method to measure the relationship between the formation of intracellular polymerized Hb S and cell filtration. In this study, we have used this method to examine whether sickle cell morphology, independent of Hb S polymer fraction, had an effect on cell rheology. We primarily use sickle trait (AS) and Hb S-beta(+)-thalassemia (S-beta(+)-thal) erythrocytes with low hemoglobin F levels, which have normal membranes and few or no dense cells, to remove these confounding effects. We find that the relationship between filtration and the percentages of each "type" of morphological deformation of AS erythrocytes was different from that of the S-beta(+)-thal erythrocytes. In addition, we find that while the filtration of AS erythrocytes as a function of oxygen saturation was similar, whether measured during deoxygenation or reoxygenation, the relationship between the percentages of each type of deformed erythrocyte and oxygen saturation demonstrated hysteresis during oxygenation-deoxygenation experiments. Transmission electron microscopy, for both elongated and irregularly shaped cells, showed that similarly distorted cells could have very different amounts and alignment of polymer. These results suggests that cell morphology per se is not strongly related to filtration, whereas calculated intracellular Hb S polymer fraction predicts loss of filtration of AS and S-beta(+)-thal erythrocytes well. Measured or calculated polymer fraction values would appear to be a better parameter for the study of sickle cell disease pathophysiology and response to treatment than cell morphology studies.

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Year:  1995        PMID: 7832188     DOI: 10.1002/ajh.2830480105

Source DB:  PubMed          Journal:  Am J Hematol        ISSN: 0361-8609            Impact factor:   10.047


  8 in total

1.  High-throughput assessment of hemoglobin polymer in single red blood cells from sickle cell patients under controlled oxygen tension.

Authors:  Giuseppe Di Caprio; Ethan Schonbrun; Bronner P Gonçalves; Jose M Valdez; David K Wood; John M Higgins
Journal:  Proc Natl Acad Sci U S A       Date:  2019-11-25       Impact factor: 11.205

2.  Effects of short supramaximal exercise on hemorheology in sickle cell trait carriers.

Authors:  Philippe Connes; Fagnété Sara; Marie-Dominique Hardy-Dessources; Laurent Marlin; Frantz Etienne; Laurent Larifla; Christian Saint-Martin; Olivier Hue
Journal:  Eur J Appl Physiol       Date:  2006-02-28       Impact factor: 3.078

3.  Kinetics of sickle cell biorheology and implications for painful vasoocclusive crisis.

Authors:  E Du; Monica Diez-Silva; Gregory J Kato; Ming Dao; Subra Suresh
Journal:  Proc Natl Acad Sci U S A       Date:  2015-01-20       Impact factor: 11.205

4.  Optical measurement of biomechanical properties of individual erythrocytes from a sickle cell patient.

Authors:  HeeSu Byun; Timothy R Hillman; John M Higgins; Monica Diez-Silva; Zhangli Peng; Ming Dao; Ramachandra R Dasari; Subra Suresh; YongKeun Park
Journal:  Acta Biomater       Date:  2012-07-20       Impact factor: 8.947

5.  The effect of rigid cells on blood viscosity: linking rheology and sickle cell anemia.

Authors:  Antonio Perazzo; Zhangli Peng; Y-N Young; Zhe Feng; David K Wood; John M Higgins; Howard A Stone
Journal:  Soft Matter       Date:  2022-01-19       Impact factor: 3.679

6.  Universal metastability of sickle hemoglobin polymerization.

Authors:  Weijun Weng; Alexey Aprelev; Robin W Briehl; Frank A Ferrone
Journal:  J Mol Biol       Date:  2008-02-05       Impact factor: 5.469

7.  Treatment of homozygous sickle cell disease with pentoxifylline.

Authors:  A Sacerdote
Journal:  J Natl Med Assoc       Date:  1999-08       Impact factor: 1.798

8.  A deep convolutional neural network for classification of red blood cells in sickle cell anemia.

Authors:  Mengjia Xu; Dimitrios P Papageorgiou; Sabia Z Abidi; Ming Dao; Hong Zhao; George Em Karniadakis
Journal:  PLoS Comput Biol       Date:  2017-10-19       Impact factor: 4.475

  8 in total

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