Cell Viability
Cell Viability - Related Videos
12:03
Viability Assays for Cells in Culture
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Cited by 39 •
2014
Therapeutic compounds are often first examined in vitro with viability assays. Blind cell counts by a human observer can be highly sensitive to small changes in cell number but do not assess function. Computerized viability assays, as described here, can assess both structure and function in an objective manner.
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.
07:28
Imaging Cell Viability on Non-transparent Scaffolds — Using the Example of a Novel Knitted Titanium Implant
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Cited by 6 •
2016
Here we present a fluorophore based imaging technique to detect cell viability on a non-transparent titanium scaffold as well as to detect glimpses of the scaffold impurities. This protocol troubleshoots the drawback of imaging cell-cell or cell-metal interactions on non-transparent scaffolds.
07:23
Fluorescence Microscopy Methods for Determining the Viability of Bacteria in Association with Mammalian Cells
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Cited by 82 •
2013
Central to the field of bacterial pathogenesis is the ability to define if and how microbes survive after exposure to eukaryotic cells. This article outlines protocols for the use of fluorescent dyes that reveal the viability of individual bacteria inside and associated with host cells.
07:05
Viability of Bioprinted Cellular Constructs Using a Three Dispenser Cartesian Printer
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Cited by 6 •
2015
A Cartesian bioprinter was designed and fabricated to allow multi-material deposition in precise, reproducible geometries, while also allowing control of environmental factors. Utilizing the three-dimensional bioprinter, complex and viable constructs may be printed and easily reproduced.
FAQs
Different assay signals report different cellular properties. Plasma membrane integrity indicates whether the cell boundary remains intact, whereas dye exclusion reflects whether cells prevent entry of a viability-associated dye. ATP production and metabolic activity instead indicate energetic or biochemical function. Because these readouts are not identical, selecting one depends on the cellular change or treatment being investigated.
That distinction matters because a lower assay signal does not automatically identify the biological cause. Reduced ATP production or metabolic activity can indicate impaired function, while changes in membrane integrity or dye exclusion provide another type of evidence about cell damage. Recognizing these differences prevents researchers from treating every signal change as equivalent to irreversible cell death.
Different assays can disagree because they measure different indicators rather than one universal property. A treatment might alter ATP production, metabolic activity, membrane integrity, or dye exclusion to different extents, producing distinct signals in the same sample. The difference is informative because it encourages researchers to interpret each result according to the assay’s specific biological readout.
A basic assessment begins by choosing a readout that matches the question, such as membrane integrity, ATP production, metabolic activity, or dye exclusion. Researchers then measure the selected signal in the cell system and interpret changes in relation to injury, death, or treatment. This approach keeps the assay aligned with the biological outcome of interest.
Cell viability data can guide optimization of cell culture conditions because changes in the measured signals reveal whether cells are maintaining essential functions under a given setup. Rather than treating culture performance as a single observation, researchers can monitor viability-related readouts and use them to identify conditions associated with healthier, more reproducible cell behavior.
Researchers apply these measurements in cytotoxicity studies and drug testing to determine whether a potential treatment damages cells or changes their functional state. The same approach supports disease research by showing how cellular injury or death varies across experimental conditions. Results can help compare treatments and identify effects that warrant further investigation.