Distribution of Abnormal Hemoglobins in Puerto Rico and Survival Studies of Red Blood Cells Using Cr51

Abstract 1. A survey of the incidence of abnormal hemoglobins in different racial groups distributed over the island of Puerto Rico was performed. The relation of the rate of destruction of red cells to the presence of abnormal hemoglobin patterns in the affected population was also studied. 2. The abnormal hemoglobins were classified by the difference in paper electrophoretic mobility. Fetal hemoglobin was measured by its resistance to alkaline denaturation. The red cell life span was determined by measuring the survival of erythrocytes labelled with radioactive sodium chromate. 3. A total of 2,089 inhabitants were studied. There were 1,487 white subjects and 602 Negroes. Forty-two individuals were found to harbor abnormal hemoglobins. All but one were Negroes or Negroid of African descent, and their relative numbers agreed closely with the geographical distribution of ethnic groups in the island. Abnormal hemoglobins were found in 2.01 per cent of the entire series of 2,089 persons, but in those considered Negroes or Negroids the incidence of abnormal hemoglobins was 6.8 per cent. Of the 42 persons showing abnormal hemoglobins, thirty-four or 81 per cent, had hemoglobin S; only two of these had sickle cell anemia. The incidence of the sickle cell trait among the Puerto Rican Negro population was 5.2 per cent; and the incidence of hemoglobin S disease among those harboring the trait was 5.9 per cent. Eight, or 19 per cent of the abnormal cases had hemoglobin C; only one of these had hemoglobin C disease with clinical hemolytic anemia. The incidence of the hemoglobin C trait among the Puerto Rican Negro population is 1.3 per cent; and the incidence of hemoglobin C disease among those harboring the trait may reach 12.5 per cent. 4. All 42 cases harboring abnormal hemoglobins showed very small quantities of fetal or alkali-resistant hemoglobin ranging from 0.45 per cent to 3.25 per cent, averaging 1.12 per cent. 5. The "apparent" half-life of the red blood cells was found to be 10 days in sickle cell anemia, 7 days in SC disease, 20.6 days in cases of hemoglobin SA, 18.5 days in one case of hemoglobin C disease and 21.5 days in 2 cases of the combination CA. The normal "apparent" half-life in our laboratory is 24.5 days.

Download Full-text

More Efficient Exchange of Sickle Red Blood Cells Can be Achieved By Exchanging the Densest Red Blood Cells

Blood ◽

10.1182/blood.v128.22.3856.3856 ◽

2016 ◽

Vol 128 (22) ◽

pp. 3856-3856

Author(s):

Suzanne Thibodeaux ◽

Leah Irwin ◽

Lita Jamensky ◽

Kevin Schell ◽

Una O'Doherty

Keyword(s):

Sickle Cell Disease ◽

Red Blood Cells ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Blood Cells ◽

Wild Type ◽

Cell Disease ◽

Hemoglobin S ◽

And Control ◽

Exchange Parameters

Abstract Background: In sickle cell disease, it is well established that cells containing two mutated hemoglobins (SS) are denser than cells containing wild-type hemoglobin. We asked whether we could more efficiently exchange red blood cells (RBCs) in sickle cell anemia patients by exploiting the denser property of RBCs containing hemoglobin SS compared to wild-type RBCs. Methods: To probe this question, we performed a series of experiments using the waste bags from sickle cell patients as simulated patients. We exchanged the simulated patient with one RBC volume using recently expired ABO compatible RBC units on a COBE Spectra apheresis instrument. We measured hematocrit and hemoglobin S levels in the simulated and control patient bag before and after the exchange. In the experimental scenario, we programmed the COBE Spectra to exchange the bottom half of the RBCs by indicating that the hematocrit was half of the true hematocrit (e.g. 21% when the hematocrit of the bag was 42%). For control exchanges we programmed the COBE Spectra to exchange the entire RBC volume by programing the hematocrit to be the true one (for this example 42%). Results: The percentage of hemoglobin S was more effectively diminished in our modified exchanges that targeted dense RBCs than in control exchanges. Our experimental exchanges were also more effective than expected for a 1 red blood cell volume exchange by Poisson calculation (n=5). In an optimized experiment, hemoglobin S was reduced from 23.7% to 1.3 % after exchanging 1 RBC volume using our modified approach while it was reduced from 23.2 to 5.4% using the control or routine exchange parameters. The same volume of donor RBCs (1 RBC volume) was used to exchange our experimental and control simulations. We obtained a 95% reduction of hemoglobin S in our experimental conditions and a 77% reduction in our control conditions. The instrument was programmed to compensate for RBC depletion with the modified RBC exchange. The compensation is necessary to maintain a constant hematocrit since more RBCs are present in the bottom half than top half of the centrifuged RBCs. Conclusions: It is possible to exchange sickle cell anemia patients more effectively by taking advantage of the fact that RBCs containing hemoglobin SS are denser than normal RBCs. Using waste products from sickle cell anemia exchanges provides an opportunity to safely optimize exchange parameters. This approach should allow us to: 1) achieve a higher reduction in hemoglobin S in patients, 2) achieve the previous levels of reduction using fewer donor units and/or 3) combine red cell exchange with other therapies for sickle cell disease, such as hydroxyurea, by taking advantage of the differential densities and selective depletion of red blood cells containing different levels of hemoglobin F. Disclosures No relevant conflicts of interest to declare.

Download Full-text

Fascicles of hemoglobin S fibers

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100142505 ◽

1986 ◽

Vol 44 ◽

pp. 176-177

Author(s):

William A. McDade ◽

Robert J. Vassar ◽

Robert Josephs

Keyword(s):

Glutamic Acid ◽

Red Blood Cells ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Blood Cells ◽

Mutant Protein ◽

Hemoglobin S

The substitution of valine for glutamic acid at the β 6 position of hemoglobin results in a mutant protein whose solubility is dramatically decreased in the deoxygenated form. The deoxygenated protein polymerizes to form long, solid helical rods called fibers. The red blood cells of sickle cell anemia patients are filled with these fibers that distort the cell into the rigid shapes pathognomonic for the disease. In stirred solutions of purified HbS, fibers are the first of a series of metastable intermediates that ultimately crystallize. Fibers have the potential to form either larger particles, called macrofibers, or bundles, called fascicles.

Download Full-text

STUDIES ON THE DESTRUCTION OF RED BLOOD CELLS. XII. FACTORS INFLUENCING THE ROLE OF S HEMOGLOBIN IN THE PATHOLOGIC PHYSIOLOGY OF SICKLE CELL ANEMIA AND RELATED DISORDERS 1

Journal of Clinical Investigation ◽

10.1172/jci103489 ◽

1957 ◽

Vol 36 (6 Pt 1) ◽

pp. 833-843 ◽

Cited By ~ 42

Author(s):

Mortimer S. Greenberg ◽

Edward H. Kass ◽

William B. Castle

Keyword(s):

Red Blood Cells ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Blood Cells ◽

Factors Influencing ◽

Pathologic Physiology

Download Full-text

Elastic property of sickle cell anemia and sickle cell trait red blood cells

Journal of Biomedical Optics ◽

10.1117/1.jbo.26.9.096502 ◽

2021 ◽

Vol 26 (09) ◽

Author(s):

Endris Muhammed ◽

James Cooper ◽

Daniel Devito ◽

Robert Mushi ◽

Maria del Pilar Aguinaga ◽

...

Keyword(s):

Elastic Property ◽

Red Blood Cells ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Blood Cells ◽

Sickle Cell Trait

Download Full-text

The effect of the antisickling compoundGBT1118 on the permeability of red blood cells from patients with sickle cell anemia

Physiological Reports ◽

10.14814/phy2.14027 ◽

2019 ◽

Vol 7 (6) ◽

pp. e14027 ◽

Cited By ~ 2

Author(s):

Halima Al Balushi ◽

Kobina Dufu ◽

David C. Rees ◽

John N. Brewin ◽

Anke Hannemann ◽

...

Keyword(s):

Red Blood Cells ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Blood Cells

Download Full-text

Peripheral Red Blood Cell Split Chimerism as a Consequence of Intramedullary Selective Apoptosis of Recipient Red Blood Cells in a Case of Sickle Cell Disease

Mediterranean Journal of Hematology and Infectious Diseases ◽

10.4084/mjhid.2014.066 ◽

2014 ◽

Vol 6 (1) ◽

pp. e2014066 ◽

Cited By ~ 1

Author(s):

Marco Marziali ◽

Antonella Isgrò ◽

Pietro Sodani ◽

Javid Gaziev ◽

Daniela Fraboni ◽

...

Keyword(s):

Bone Marrow ◽

Red Blood Cells ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Blood Cells ◽

Marrow Transplant ◽

Mixed Chimerism ◽

Radical Cure ◽

Hematopoietic Stem ◽

Hematopoietic Chimerism

Allogeneic cellular gene therapy through hematopoietic stem cell transplantation is the only radical cure for congenital hemoglobinopathies like thalassemia and sickle cell anemia. Persistent mixed hematopoietic chimerism (PMC) has been described in thalassemia and sickle cell anemia. Here, we describe the clinical course of a 6-year-old girl who had received bone marrow transplant for sickle cell anemia. After the transplant, the patient showed 36% donor hematopoietic stem cells in the bone marrow, whereas in the peripheral blood there was evidence of 80% circulating donor red blood cells (RBC). The analysis of apoptosis at the Bone Marrow level suggests that Fas might contribute to the cell death of host erythroid precursors. The increase in NK cells and the regulatory T cell population observed in this patient suggests that these cells might contribute to the condition of mixed chimerism.

Download Full-text

Deep Learning Models for Classification of Red Blood Cells in Microscopy Images to Aid in Sickle Cell Anemia Diagnosis

Electronics ◽

10.3390/electronics9030427 ◽

2020 ◽

Vol 9 (3) ◽

pp. 427 ◽

Cited By ~ 11

Author(s):

Laith Alzubaidi ◽

Mohammed A. Fadhel ◽

Omran Al-Shamma ◽

Jinglan Zhang ◽

Ye Duan

Keyword(s):

Deep Learning ◽

Red Blood Cells ◽

Transfer Learning ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Blood Cells ◽

Learning Models ◽

Sickle Cells ◽

Microscopy Images

Sickle cell anemia, which is also called sickle cell disease (SCD), is a hematological disorder that causes occlusion in blood vessels, leading to hurtful episodes and even death. The key function of red blood cells (erythrocytes) is to supply all the parts of the human body with oxygen. Red blood cells (RBCs) form a crescent or sickle shape when sickle cell anemia affects them. This abnormal shape makes it difficult for sickle cells to move through the bloodstream, hence decreasing the oxygen flow. The precise classification of RBCs is the first step toward accurate diagnosis, which aids in evaluating the danger level of sickle cell anemia. The manual classification methods of erythrocytes require immense time, and it is possible that errors may be made throughout the classification stage. Traditional computer-aided techniques, which have been employed for erythrocyte classification, are based on handcrafted features techniques, and their performance relies on the selected features. They also are very sensitive to different sizes, colors, and complex shapes. However, microscopy images of erythrocytes are very complex in shape with different sizes. To this end, this research proposes lightweight deep learning models that classify the erythrocytes into three classes: circular (normal), elongated (sickle cells), and other blood content. These models are different in the number of layers and learnable filters. The available datasets of red blood cells with sickle cell disease are very small for training deep learning models. Therefore, addressing the lack of training data is the main aim of this paper. To tackle this issue and optimize the performance, the transfer learning technique is utilized. Transfer learning does not significantly affect performance on medical image tasks when the source domain is completely different from the target domain. In some cases, it can degrade the performance. Hence, we have applied the same domain transfer learning, unlike other methods that used the ImageNet dataset for transfer learning. To minimize the overfitting effect, we have utilized several data augmentation techniques. Our model obtained state-of-the-art performance and outperformed the latest methods by achieving an accuracy of 99.54% with our model and 99.98% with our model plus a multiclass SVM classifier on the erythrocytesIDB dataset and 98.87% on the collected dataset.

Download Full-text