Cell Viability Multiplexing
Cell Viability Multiplexing - 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.
08:27
Use of a Caspase Multiplexing Assay to Determine Apoptosis in a Hypothalamic Cell Model
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Cited by 20 •
2014
Multiplex assays can provide beneficial information for basic cellular mechanisms and eliminate waste of reagents and unnecessary repetitive experiments. We describe here a multiplex caspase-3/7 activity assay, using fluorescent- and luminescent-based methods, to determine cell viability in an in vitro hypothalamic model following oxidative challenge with palmitic acid.
08:43
Highly Multiplexed, Super-resolution Imaging of T Cells Using madSTORM
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Cited by 5 •
2017
We demonstrate a method to image multiple molecules within heterogeneous nano-structures at single molecule accuracy using sequential binding and elution of fluorescently labeled antibodies.
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.
FAQs
The approach pairs compatible fluorescent, luminescent, or colorimetric assays so that several cellular features can be measured from the same sample. Depending on the assay combination, signals may reflect metabolic activity, ATP levels, membrane integrity, or cell death. Collecting these readouts together preserves relationships between endpoints and provides more context than measuring each feature in separate experiments.
These measurements represent different aspects of cellular status, so they can separate reduced viability from changes in a particular cellular process. For example, a treatment may affect metabolic activity or proliferation without producing the same pattern as direct cell death. Comparing multiple signals helps researchers interpret treatment effects more precisely instead of assigning one endpoint to overall cytotoxicity.
A single viability endpoint can conceal differences among cells or treatment responses because distinct cellular changes may produce similar overall measurements. Multiplexed readouts expose patterns across viability, function, and death-related signals within the same sample. In cancer research, these patterns can help identify varied responses to a drug or combination and support more informative dose-response analysis.
Researchers should select fluorescent, luminescent, or colorimetric assays whose signals can be collected and analyzed together. The selected readouts should address the biological questions of interest, such as metabolic activity, ATP levels, membrane integrity, or cell death. Aligning assay choice with the intended interpretation helps ensure that the resulting measurements provide complementary rather than redundant information.
It is especially useful when researchers need to characterize how candidate drugs affect cancer cells beyond a single survival measurement. The method supports drug screening and combination screening by linking viability-related signals with effects on proliferation, apoptosis, or cellular function. This broader profile can improve interpretation of treatment activity and help distinguish different response patterns across tested conditions.
Multiple readouts add biological context to changes observed across treatment doses. Instead of evaluating only whether viability rises or falls, researchers can compare dose-related effects on metabolic activity, ATP levels, membrane integrity, or cell death. This can clarify whether a response reflects cytotoxicity, altered proliferation, apoptosis, or another cellular-function change, strengthening interpretation of treatment effects.