ReviewJournal of immunological methods2015
Imaging flow cytometry for the study of erythroid cell biology and pathology.
Review in Journal of immunological methods, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 38 citations in OpenAlex.
- Cardiac immunity and heart repair: Mechanism, challenge, and future direction.Chinese medical journal · 2026Review
- Translation of the Morphological Hallmarks of Dyserythropoiesis to Objective Morphometric Parameters by Imaging Flow Cytometry.International journal of laboratory hematology · 2025Article
- Current understanding of eryptosis: mechanisms, physiological functions, role in disease, pharmacological applications, and nomenclature recommendations.Cell death & disease · 2025Review
- Article
- Phenotypic analysis of erythrocytes in sickle cell disease using imaging flow cytometry.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2022Article
- Differential and targeted vesiculation: pathologic cellular responses to elevated arterial pressure.Molecular and cellular biochemistry · 2022Review
- Human erythrocyte fragmentation during ex-vivo pig organ perfusion.Xenotransplantation · 2022Article
- Techniques for the Detection of Sickle Cell Disease: A Review.Micromachines · 2021Review
- Blood rheology biomarkers in sickle cell disease.Experimental biology and medicine (Maywood, N.J.) · 2020Review
- Fluorescence Exclusion: A Simple Method to Assess Projected Surface, Volume and Morphology of Red Blood Cells Stored in Blood Bank.Frontiers in medicine · 2018Article
- Exploiting Single-Cell Quantitative Data to Map Genetic Variants Having Probabilistic Effects.PLoS genetics · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.