Browsing by Subject "Red blood cells"

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Open Access
Assessment of stored red blood cells through lab-on-a-chip technologies for precision transfusion medicine
(National Academy of Sciences, 2023-07-26) Isiksacan, Z.; D’Alessandro, A.; Wolf, S. M.; McKenna, D. H.; Tessier, S. N.; Kucukal, E.; Gokaltun, A. A.; William, N.; Sandlin, R. D.; Bischof, J.; Mohandas, N.; Busch, M. P.; Elbüken, Çağlar; Gurkan, U. A.; Toner, M.; Acker, J. P.; Yarmush, M. L.; Usta, O. B.
Transfusion of red blood cells (RBCs) is one of the most valuable and widespread treatments in modern medicine. Lifesaving RBC transfusions are facilitated by the cold storage of RBC units in blood banks worldwide. Currently, RBC storage and subsequent transfusion practices are performed using simplistic workflows. More specifically, most blood banks follow the “first-in-first-out” principle to avoid wastage, whereas most healthcare providers prefer the “last-in-first-out” approach simply favoring chronologically younger RBCs. Neither approach addresses recent advances through -omics showing that stored RBC quality is highly variable depending on donor-, time-, and processing-specific factors. Thus, it is time to rethink our workflows in transfusion medicine taking advantage of novel technologies to perform RBC quality assessment. We imagine a future where lab-on-a-chip technologies utilize novel predictive markers of RBC quality identified by -omics and machine learning to usher in a new era of safer and precise transfusion medicine.
Open Access
Development of an experimental image processing tool and flow-cytometry based electromagnetic scattering analysis for medical diagnosis of red blood cell pathology
(2020-08) Göktaş, Polat
The morphological, biophysical and biochemical properties of biological cells are critical markers for many fields, including life sciences, medical diagnosis, etc. Label-free, high-throughput classification and detection of cellular information at the single-cell level are invaluable for medical diagnostics. In particular, an efficient algorithm for image analytics plays an important role in biomedical research and in vitro diagnostics with grow importance for healthcare. Morphological/biophysical alterations in single biological cells have been associated with hematologic diseases, such as sickle cell disease. Anemia, which has multiple causes, such as iron deficiency, chronic blood loss and hemolysis, is a prevalent health problem affecting an estimated two billion people or 30% of the world’s population. The ability to measure hemoglobin concentration in anemic patients continuously has significant potential to facilitate hemoglobin monitoring, improve the detection of acute anemia, and avoid the complications and expense. Currently, a major challenge in many clinical laboratories, quantification of cellular information at the single-cell level requires complex laboratory sample preparation and data analysis procedures. Here, we demonstrate that the combination of a novel incubation procedure with rapid gas exchange, image-based flow cytometry (IFC) and a computational cell morphology framework, based on the boundary integral equation method (with the use of Muller Boundary Integral Equation Method) is presented to improve the accuracy of classification of red blood cells (RBCs) subtypes (including normal, intermediate and sickled RBCs) as they appear in time under low oxygen. In this dissertation, the results of the following numerical simulations and experiments are presented: We have investigated the changes in time to follow the rate of sickling with IFC as cells undergo deoxygenation. We have proposed a new shape quantification feature criteria as a Sickle Index parameter obtained from a user-defined custom mask in the IFC data to provide better identification of “true” normal, intermediate and sickle cell region boundaries in IFC. Especially, the main merit of the study lies in showing for the first time that the light scattering analysis based on boundary shape structures is correlated with the measured side scattering (SSC-A) pattern realized by IFC to provide the refractive index distribution for each RBC subtypes. Moreover, we applied different ionic strengths and osmolarity conditions to control the ratio of Discocyte/Stomatocyte/Echinocyte (D/S/E) subtypes in murine RBCs. Analysis of samples were performed using conventional and image-based flow cytometry (FC). The predicted cellular information showed good agreement with the expected results of our experimental data extracted from bright-field and dark-field images in IFC. The rich information on the predicted scattering pattern makes our angle-resolved light scattering technique for the purpose of the automatic RBC morphological profile in conventional FC, and discover RBC subpopulation target areas for the label-free analysis of conventional FC data. With this approach, we are able to notably reduce the data analysis procedure to identify RBC subtypes from a cell population in a given experiment through IFC or conventional FC with an angle-resolved light scattering method. Our approach could lead to replacing current manual protocols in the clinical procedure to avoid complex laboratory processes, and manual gating analysis and fluorescent stains in light microscopy or FCs. This study shows that our method has the potential to be used robust and objective characterization, and follow-up care of anemia status, and to provide a rapid action for the conditions that would lead to chronic anemia condition causing to a reduced lifespan, organ damage or painful crisis, and will be useful for the evaluation of anti-sickling agents which are currently proposed or are in clinical trials.
Open Access
Image-Based flow cytometry and angle-resolved light scattering to define the sickling process
(International Society for Advancement of Cytometry, 2019) Göktaş, Polat; Sukharevsky, I.; Larkin, S.; Kuypers, F.; Yalçın, Ö.; Ayhan, Altıntaş
Red blood cells (RBCs) from sickle cell patients exposed to a low oxygen tension reveal highly heterogeneous cell morphologies due to the polymerization of sickle hemoglobin (HbS). We show that angle‐resolved light scattering approach with the use of image‐based flow cytometry provides reliable quantitative data to define the change in morphology of large populations of RBCs from sickle cell patients when the cells are exposed for different times to low oxygen. We characterize the RBC morphological profile by means of a set of morphological and physical parameters, which includes cell shape, size, and orientation. These parameters define the cell as discocyte, sickle, elongated, as well as irregularly or abnormal RBC shaped cells, including echinocytes, holly‐leaf, and granular structures. In contrast to microscopy, quick assessment of large numbers of cells provides statistically relevant information of the dynamic process of RBC sickling in time. The use of this approach facilitates the understanding of the processes that define the propensity of sickle blood samples to change their shape, and the ensuing vaso‐occlusive events in the circulation of the patients. Moreover, it assists in the evaluation of treatments that include the use of anti‐sickling agents, gene therapy‐based hemoglobin modifications, as well as other approaches to improve the quality of life of sickle cell patients. © 2019 International Society for Advancement of Cytometry