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Spark® multimode microplate reader for high performance cell-based fluorescence assays

By Dr Stefan Haberstock

As we have seen in the previous posts in this series, implementing fluorescence detection will be a quick and effective route to improving the quality and sensitivity of your assays. Achieving optimal fluorescence assays requires an optics system with both sensitivity and flexibility.

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Master the challenges of cell-based fluorescence assays

By Dr Stefan Haberstock

Cell-based assays are giving us deeper insight into cellular mechanisms in a true biological context, and fluorescence assays are playing a leading role. Applications range from cytotoxicity, proliferation, apoptosis and G-protein-coupled receptor (GPCR) signaling assays to high-throughput screening (HTS) drug discovery.

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How to develop an optimal fluorescence assay

By Dr Stefan Haberstock

Fluorescence detection can give you the ability to develop assays with extreme sensitivity, high robustness and a broad dynamic range. Success involves addressing several challenges, such as the careful choice of excitation (Ex) and emission (Em) wavelengths and the selection of flexible and sensitive optics, as we will see here.

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A brighter future with fluorescence-based assays

By Dr Stefan Haberstock

Compared to many other detection technologies, fluorescence provides hard-to-beat performance and flexibility. Fluorescent labels are stable for months, deliver high sensitivity and the diversity in available dyes gives nearly unlimited possibilities in assay design. This and many other advantages make implementing fluorescence detection one of the easiest and safest ways for you to improve the quality and sensitivity of your assays.

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When assessing confluence for cell-based assays, variety is not the spice of life

By Siegfried Sasshofer

Imagine life science research without cell-based assays. Or without cultured cells of all types to power those assays. Healthy, high-quality cells at the right point of confluence are vital for proliferation, kinetics, cytotoxicity, and gene expression studies particularly during long-term experiments. With so many different cell types, assay formats, and detection methods the variability inherent in cell-based assays can be enormous. There’s no room for inconsistency in cell counts and confluence assessments – it’s counterproductive and just wastes time. What’s the best way to improve counting accuracy in your cell-based assays?

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