Nucleated Cell Classification
Nucleated Cell Classification - Related Videos
09:41
Visualization of Cell Cycle Variations and Determination of Nucleation in Postnatal Cardiomyocytes
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Cited by 5 •
2017
To distinguish cell division from cell cycle variations in cardiomyocytes, we present protocols using two transgenic mouse lines: Myh6-H2B-mCh transgenic mice, for the unequivocal identification of cardiomyocyte nuclei, and CAG-eGFP-anillin mice, for distinguishing cell division from cell cycle variations.
09:53
Automated Microfluidic Blood Lysis Protocol for Enrichment of Circulating Nucleated Cells
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Cited by 4 •
2009
An automated microfluidic device was developed for circulating nucleated cell enrichment from peripheral blood via erythrocyte lysis that ensures isolation of high quality sample without cell loss.
10:10
Synthesis of Compound Giant Unilamellar Vesicles: A Biomimetic Model of Nucleate Cells
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2025
This article presents a method for preparing compound Giant Unilamellar Vesicles (cGUVs) with a vesicle-in-vesicle structure, with customized electrical conductivity in inner, annular, and outer regions. Electroformation synthesizes simple GUVs, which are transformed into stomatocytes and cGUVs via osmotic shock, providing a valuable model for studying the biophysics of nucleated cells.
09:36
The Use of High-resolution Infrared Thermography (HRIT) for the Study of Ice Nucleation and Ice Propagation in Plants
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Cited by 27 •
2015
Here we present a protocol that allows one to visualize sites of ice formation and avenues of ice propagation in plants utilizing high resolution infrared thermography (HRIT).
07:02
Studying the Effects of Temperature on the Nucleation and Growth of Nanoparticles by Liquid-Cell Transmission Electron Microscopy
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Cited by 12 •
2021
Temperature control during liquid-phase electron microscopy experiments opens up new perspectives of studying the dynamic of nanoparticles in liquid environments mimicking their formation or application media. Using recently developed heating liquid cells, we directly observed the influence of temperature on the nucleation and growth processes of gold nanoparticles in water.
FAQs
Reliable classification combines several observable features rather than relying on a single visual trait. Nuclear shape and size provide important distinctions, while chromatin pattern and cytoplasmic appearance add further evidence. Considering these characteristics together helps organize cells more consistently and supports interpretation of cellular composition in blood, tissue, and biomedical research samples.
Nuclear shape, size, and chromatin pattern capture structural differences that may separate one cell population from another. These features are especially useful when visual examination is performed with microscopy or image analysis. Evaluating them systematically can improve differential cell counts and help identify cellular patterns that warrant closer medical or research interpretation.
Molecular markers provide an additional classification layer when nuclear and cytoplasmic appearance alone does not adequately distinguish cells. They can be measured with flow-based methods and incorporated into cell-population analysis. This added information supports more detailed immune-cell profiling and helps researchers compare cellular groups using both observable structure and molecular characteristics.
Microscopy and image analysis emphasize observable morphology, including nuclear structure and cytoplasmic appearance. Flow-based methods can incorporate molecular markers to characterize cell populations through measured signals. The choice of approach affects which evidence is available for classification, so method selection should match whether the investigation prioritizes cellular appearance, molecular features, or both.
A practical workflow begins by examining the sample with an appropriate microscopy, image-analysis, or flow-based method. The observer or analysis system then evaluates nuclear shape, size, chromatin pattern, cytoplasmic appearance, and, when needed, molecular markers. Cells are grouped according to these features, producing information that can support differential counts or broader population analysis.
In medicine, the approach supports differential cell counts, blood and tissue evaluation, and immune-cell profiling. It can also help recognize abnormal cellular patterns associated with disease. By organizing nucleated cells according to standardized observable or molecular characteristics, the resulting assessment can provide a clearer basis for interpreting patient samples and comparing cellular findings.
Standardized classification promotes consistency in how cellular features and populations are evaluated. This consistency helps clinicians and researchers compare results across patients, samples, and experimental conditions. It also makes differential counts, tissue assessments, and immune-cell profiles easier to interpret, while supporting recognition of abnormal patterns that may have medical relevance.