evaluation of red cell membrane cytoskeletal disorders using a flow cytometric method in south iran
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2014
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Abstract
OBJECTIVE: The diagnosis of hereditary red blood cell (RBC) membrane disorders, and in particular hereditary spherocytosis (HS) and Southeast Asian ovalocytosis (SAO), is based on clinical history, RBC morphology, and other conventional tests such as osmotic fragility. However, there are some milder cases of these disorders that are difficult to diagnose. The application of eosin-5’-maleimide (EMA) was evaluated for screening of RBC membrane defects along with some other anemias. We used EMA dye, which binds mostly to band 3 protein and to a lesser extent some other membrane proteins, for screening of some membrane defects such as HS.
METHODS: Fresh RBCs from hematologically normal controls and patients with HS, SAO, hereditary elliptocytosis, hereditary spherocytosis with pincered cells, severe iron deficiency, thalassemia minor, and autoimmune hemolytic anemia were stained with EMA dye and analyzed for mean fluorescent intensity (MFI) using a flow cytometer.
RESULTS: RBCs from patients with HS and iron deficiency showed a significant reduction in MFI compared to those from normal controls (p<0.0001 and p<0.001, respectively), while macrocytic RBCs showed a significant increase in MFI (p<0.01). A significant correlation was shown between mean corpuscular volume and MFI, with the exceptions of HS and thalassemia minor.
CONCLUSION: Our results showed that the flow cytometric method could be a reliable diagnostic method for screening and confirmation, with higher sensitivity and specificity (95% and 93%, respectively) than conventional routine tests for HS patients prior to further specific membrane protein molecular tests.
| Reference Key |
golafshan2014turkishevaluation
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| Authors | ;Habib Alah Golafshan;Reza Ranjbaran;Tahereh Kalantari;Leili Moezzi;Mehran Karimi;Abbas Behzad- Behbahani;Farzaneh Aboualizadeh;Sedigheh Sharifzadeh |
| Journal | proceedings of the international conference on iot in social, mobile, analytics and cloud, i-smac 2017 |
| Year | 2014 |
| DOI |
10.4274/Tjh.2012.0146
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| URL | |
| Keywords |
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