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• W3026785117 abstract "Absolute quantification of microRNAs (miRNAs) or other nucleic acid biomarkers is an important requirement for molecular and clinical biosensing. Emerging technologies with beneficial features concerning simplicity and multiplexing present an attractive route for advancing diagnostic tools toward rapid and low-cost bioanalysis. However, the actual translation into the clinic by miRNA quantification in human samples is often missing. Here, we show that implementing time-gated Förster resonance energy transfer (TG-FRET) into a catalytic hairpin assembly (CHA) can be used for the simultaneous quantification of two miRNAs with a single measurement from total RNA extracts of human tissues. A single terbium–dye FRET pair was conjugated at two specific distances within target-specific CHA hairpin probes, such that each miRNA resulted in distinct amplified photoluminescence (PL) decays that could be distinguished and quantified by TG PL intensity detection. Enzyme-free amplification in a separation-free assay format and the absence of autofluorescence background allowed for simple, specific, and sensitive detection of miR-21 and miR-20a with limits of detection down to 1.8 pM (250 amol). Reliable duplexed quantification of both miRNAs at low picomolar concentrations was confirmed by analyzing total RNA extracts from different colon and rectum tissues with single- and dual-target CHA-TG-FRET and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) for comparison. These simple and multiplexed nucleic acid biomarker assays present a capable method for clinical diagnostics and biomolecular research." @default.
• W3026785117 created "2020-05-29" @default.
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• W3026785117 date "2020-05-22" @default.
• W3026785117 modified "2023-10-14" @default.
• W3026785117 title "Single-Measurement Multiplexed Quantification of MicroRNAs from Human Tissue Using Catalytic Hairpin Assembly and Förster Resonance Energy Transfer" @default.
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• W3026785117 doi "https://doi.org/10.1021/acssensors.0c00432" @default.
• W3026785117 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32438801" @default.
• W3026785117 hasPublicationYear "2020" @default.
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