Aggregate Counting
Aggregate Counting - Related Videos
06:49
Monitoring Protein Aggregation Kinetics In Vivo using Automated Inclusion Counting in Caenorhabditis elegans
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Cited by 1 •
2021
Here, a method is presented for the analysis of protein aggregation kinetics in the nematode Caenorhabditis elegans. Animals from an age-synchronized population are imaged at different time points, followed by semiautomated inclusion counting in CellProfiler and fitting to a mathematical model in AmyloFit.
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...
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.
10:10
Aggregates for Concrete and Asphaltic Mixes
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2023
Source: Roberto Leon, Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA Concrete and asphalt are by far the most common construction materials used today. Concrete is a composite material consisting of cement, water, air, coarse aggregate, and fine aggregates. Fine aggregates are typically sands and coarse aggregates are natural or crushed rocks. Chemical admixtures to modify certain specific properties are also commonly used (i.e., superplasticizers to make the...
FAQs
Size and shape criteria help analysis distinguish true clustered units from single cells, debris, or irregular objects in an image. Applying the same thresholds across samples makes object classification more consistent and reduces reliance on visual judgment. These criteria are especially useful when cultures contain a mixture of aggregates and individual units with different physical appearances.
Aggregates and single units represent different organizational states, so combining them can distort both the total count and the observed distribution. Separating these categories allows researchers to determine whether a sample contains predominantly individual units, clustered structures, or a mixture. That distinction supports more meaningful comparisons of growth, aggregation behavior, and culture quality.
The reported distribution depends on how objects are identified and classified, including the selected size and shape criteria. Differences in culture conditions or treatment may also change the relative presence of single units and clustered structures. Consistent imaging and analysis settings are therefore important when comparing samples, because procedural variation can otherwise be mistaken for a biological effect.
A typical workflow begins by imaging the suspension or culture, followed by identifying objects in the resulting image. Researchers then separate aggregates from single units and apply size or shape criteria before calculating counts and distributions. Using the same workflow for each sample produces quantitative measurements that can be compared across experiments and used to monitor culture changes.
Aggregate counting can reveal whether a treatment changes the number, distribution, or organization of clustered biological units. Comparing treated and untreated samples with the same counting criteria provides quantitative evidence of treatment-associated changes rather than relying only on visual impressions. This makes the approach useful for assessing effects on growth, aggregation, and overall culture quality.
In three-dimensional cultures, aggregate measurements provide quantitative information about the formation and distribution of clustered structures. Researchers can use these data to compare culture conditions, standardize seeding densities, and identify settings that produce more consistent preparations. The resulting counts also support reproducible downstream biological analysis by documenting the starting organization of the culture.