It's not just leukocytes in cytometry
Attila Tárnok
Abstract
Attila Tárnok
Abstract
THE most common objects of investigation for cytometric analysis, may it be image or flow cytometry, are leukocytes and cells or cell constituents isolated from cells or tissues.However, there are more than just leukocytes to be looked at in the world of cytometry.Erythrocytes, as the transport vehicles for oxygen, are of central relevance in several red blood cell-related diseases.This includes anemia resulting from various acquired or congenital diseases, erythrocytosis, and erythrocyte deformation in sickle cell anemia or spherocytosis, among others.These diseases may lead to altered erythrocyte count, reduced hemoglobin content, shape alterations, or alterations of the cells' elasticity.All of these changes can be analyzed quantitatively on the single erythrocyte level using the cytometry approach.Possibly, the most advanced and challenging methods are those that take advantage of novel optical techniques and perform cytometry in vivo (1).By innovative in vivo flow cytometry technology, many of the abovementioned erythrocyte characteristics can be obtained (2) but it is still a glimpse into the future for most researchers.The image cytometry-based technology developed by Tomaiuolo and colleagues from Napoli, Italy (this issue, page 1040) is presently more accessible.The authors compared two flow-based image cytometry methods to measure the morphology of a large number of erythrocytes flowing through a large (50 lm, unbound) or small (4.7-10 lm, confined) capillary and images being captured by a high-speed camera.The authors report that their technique provides results comparable to standard technologies such as Coulter Counter with regard to erythrocyte volume, area and volume distribution.In addition, it renders additional
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
THE most common objects of investigation for cytometric analysis, may it be image or flow cytometry, are leukocytes and cells or cell constituents isolated from cells or tissues.However, there are more than just leukocytes to be looked at in the world of cytometry.Erythrocytes, as the transport vehicles for oxygen, are of central relevance in several red blood cell-related diseases.This includes anemia resulting from various acquired or congenital diseases, erythrocytosis, and erythrocyte deformation in sickle cell anemia or spherocytosis, among others.These diseases may lead to altered erythrocyte count, reduced hemoglobin content, shape alterations, or alterations of the cells' elasticity.All of these changes can be analyzed quantitatively on the single erythrocyte level using the cytometry approach.Possibly, the most advanced and challenging methods are those that take advantage of novel optical techniques and perform cytometry in vivo (1).By innovative in vivo flow cytometry technology, many of the abovementioned erythrocyte characteristics can be obtained (2) but it is still a glimpse into the future for most researchers.The image cytometry-based technology developed by Tomaiuolo and colleagues from Napoli, Italy (this issue, page 1040) is presently more accessible.The authors compared two flow-based image cytometry methods to measure the morphology of a large number of erythrocytes flowing through a large (50 lm, unbound) or small (4.7-10 lm, confined) capillary and images being captured by a high-speed camera.The authors report that their technique provides results comparable to standard technologies such as Coulter Counter with regard to erythrocyte volume, area and volume distribution.In addition, it renders additional
Key concepts: Cytometry, Flow cytometry, Mass cytometry, Computational biology, Biology, Immunology, Medicine, Genetics