ResourceLife Sciences
New Tools for Drug Discovery: Multiplexing the Monitoring of Ca2+ and cAMP Signaling in Primary Cells Using the FDSS®/µCELL
27 Jan 2015This application note demonstrates the suitability of primary cells for signaling assays in compound screenings using primary and stem cells expressing luminescent biosensor proteins specific for Ca2+ and cAMP. These assay formats are used on the FDSS®/µCELL plate reader to generate pharmacologically relevant data for GPCR ligands.
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Microplate Readers / DetectorsMicroplate readers are used to automate the detection and analysis of labeled or label-free components in microplates during assays or live-cell monitoring. Microplate readers are generally distinguished by their mode of detection. Types include absorbance, luminescence, fluorescence intensity, fluorescence polarization, TRF / FRET and multimode microplate readers. Microplate readers deliver a high throughput of samples by reading multiple wells simultaneously, with the 96-well format the most commonly used. As a result, microplate readers are often used in the drug discovery, bioassays, research and pharmaceutical industries for screening applications. Microplate loading can also be automated, with robotic microplate stackers to increase throughput. Find the best microplate readers in our peer-reviewed product directory: compare products, check customer reviews and receive pricing direct from manufacturers.Cell-Based AssaysCell-based assays are used to monitor the presence, quantity and activities of a desired cellular analyte including drug molecules or biomarkers. This can reveal information on cell health (apoptosis, cytotoxicity, viability and proliferation assays), cell metabolism, cell migration and cell signaling mechanisms. Find the best cell-based assay products, kits and equipment with our peer reviewed product directory: compare products, check customer reviews and receiving pricing direct from manufacturers.High ThroughputHigh throughput experiments allow the simultaneous processing of several samples. This parallelization reduces the cost per experiment and increases reproducibility and output volume of data.