Glial Cell Count
Glial Cell Count - Related Videos
10:19
Using a Hemacytometer to Count Cells
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2023
Many biomedical experiments require manipulation of a known quantity of cells, in order to achieve accurate, reproducible, and statistically-relevant data. Therefore, learning how to count cells is a particularly essential technique for any successful biomedical scientist. The most common way to count cells is by using a hemacytometer - an instrument that bears two laser-etched grids, which aid in the enumeration of an aliquot cells under a simple light microscope. This data can then be used to...
01:04
Glial Cells
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2025
Overview Glial cells are one of the two main types of cells in the nervous system. Glia cells comprise astrocytes, oligodendrocytes, microglia, and ependymal cells in the central nervous system, and satellite and Schwann cells in the peripheral nervous system. These cells do not communicate via electrical signals like neurons do, but they contribute to virtually every other aspect of nervous system function. In humans, the number of glial cells is roughly equal to the number of neurons in the...
05:47
Counting and Determining the Viability of Cultured Cells
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Cited by 19 •
2008
Determining the number of cells in culture is important in standardization of culture conditions and in performing accurate quantitation experiments. In this video, we demonstrate how cells are counted using a hemacytometer.
06:37
Counting Human Neural Stem Cells
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Cited by 14 •
2007
Knowledge of the exact number of viable cells is required for many tissue culture manipulations. This protocol describes how to differentiate between live and dead cells and quantify cells using a hemacytometer. Although it describes counting human neural stem/precursor cells (hNSPCs), it can be used for other cell types.
09:19
Study Glial Cell Heterogeneity Influence on Axon Growth Using a New Coculture Method
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Cited by 5 •
2010
In this protocol, we described a new method to study the influence of glial cell heterogeneity on axon growth with an in vitro co-culture system. Rat cortical glial cells were cultured to confluence and cocultured with highly purified rat dorsal root ganglia neurons. Different glial cell influence on neurons adhesion and axon growth was compared directly in the same culture. This method provides a new way to directly study the glial cell heterogeneity influence on neuron adhesion and axon...
FAQs
The chosen sampling area or volume sets the context for the result and determines how many cells are evaluated relative to the tissue examined. Counts from a small imaging field, defined tissue region, or larger volume may describe different aspects of nervous-system organization. Keeping the sampling unit consistent supports meaningful comparisons across specimens or conditions.
Reliable identification depends on the criterion used to recognize glia. Researchers may distinguish cells by morphology or by cell-specific labeling, then apply that criterion to the selected sample. This choice affects which cells enter the count and therefore shapes the resulting density estimate, making the identification approach important when comparing healthy, diseased, or treated tissue.
Normalization expresses the observed number in relation to tissue size, rather than treating every sample or field as equivalent. Reporting a count per defined area or volume can make measurements from differently sized regions more comparable. This is especially useful when tissue architecture or the amount of examined material varies between specimens.
Manual counting relies on direct assessment of the selected sample, whereas image-analysis methods use analysis of captured fields or tissue images to obtain the measurement. Both approaches depend on a defined region and a consistent method for recognizing glial cells. The choice affects how counts are generated and should match the study’s sampling and comparison needs.
A typical workflow begins by defining the tissue region, sampling area, or volume to be examined. The investigator then identifies glial cells using morphology or cell-specific labeling, counts them manually or through image analysis, and relates the result to tissue size when normalization is needed. This sequence produces a quantitative endpoint for tissue comparison.
In medicine, these measurements can support studies of neuroinflammation, nervous-system injury, and tumors. By quantifying glial cells within specified tissue regions, investigators can characterize pathological organization and compare affected tissue with healthy tissue. The resulting values also serve as endpoints in neuropathology and disease-model research, where cell-number changes may accompany the condition under study.
Treatment studies can use these measurements as quantitative endpoints rather than relying only on descriptive observations. Researchers may compare counts between healthy and diseased tissue or across study conditions to characterize changes associated with pathology or intervention. The resulting values provide a numerical basis for evaluating treatment-related comparisons within the study design.