Literature DB >> 25858229

Imaging flow cytometry for the study of erythroid cell biology and pathology.

Leigh Samsel1, J Philip McCoy1.   

Abstract

Erythroid cell maturation and diseases affecting erythrocytes are frequently accompanied by morphologic and immunophenotypic changes to these cells. In the past, these changes have been assessed primarily through the use of manual microscopy, which substantially limits the statistical rigor, throughput, and objectivity of these studies. Imaging flow cytometry provides a technology to examine both the morphology of cells as well as to quantify the staining intensity and signal distribution of numerous fluorescent markers on a cell-by-cell basis with high throughput in a statistically robust manner, and thus is ideally suited to studying erythroid cell biology. To date imaging flow cytometry has been used to study erythrocytes in three areas: 1) erythroid cell maturation, 2) sickle cell disease, and 3) infectious diseases such as malaria. In the maturation studies, imaging flow cytometry can closely recapitulate known stages of maturation and has led to the identification of a new population of erythroid cell precursors. In sickle cell disease, imaging flow cytometry provides a robust method to quantify sickled erythrocytes and to identify cellular aggregates linked to morbidities, and in malaria, imaging flow cytometry has been used to screen for new chemotherapeutic agents. These studies have demonstrated the value of imaging flow cytometry for investigations of erythrocyte biology and pathology. Published by Elsevier B.V.

Entities:  

Keywords:  Erythrocyte; Imaging flow cytometry; Malaria; Red blood cell; Sickle cell

Mesh:

Year:  2015        PMID: 25858229      PMCID: PMC4522225          DOI: 10.1016/j.jim.2015.03.019

Source DB:  PubMed          Journal:  J Immunol Methods        ISSN: 0022-1759            Impact factor:   2.303


  25 in total

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3.  Imaging flow cytometry documents incomplete resistance of human sickle F-cells to ex vivo hypoxia-induced sickling.

Authors:  Kleber Yotsumoto Fertrin; Eduard J van Beers; Leigh Samsel; Laurel G Mendelsohn; Rehan Saiyed; James S Nichols; David A Hepp; Christine A Brantner; Mathew P Daniels; J Philip McCoy; Gregory J Kato
Journal:  Blood       Date:  2014-07-24       Impact factor: 22.113

4.  Imaging flow cytometry for automated detection of hypoxia-induced erythrocyte shape change in sickle cell disease.

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Journal:  PLoS Genet       Date:  2016-08-01       Impact factor: 5.917

Review 5.  Techniques for the Detection of Sickle Cell Disease: A Review.

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  6 in total

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