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• W4366201631 abstract "MicroRNAs (miRNAs) are a family of conserved small noncoding RNAs whose expression is associated with many diseases, including cancer. Salivary miRNAs are gaining popularity as noninvasive diagnostic biomarkers for cancer and other systemic disorders, but their use is limited by their low abundance and complicated detection procedure. Herein, we present a novel self-assembly approach based on rolling circle amplification (RCA) and graphene oxide (GO) for the ultrasensitive detection of miRNA21 and miRNA16 (miRNA oral cancer biomarkers in human saliva). First, target miRNA hybridizes with the RCA template. In the presence of DNA polymerase, the RCA reaction is induced and sequences matching the template are generated. Then, a nicking enzyme cuts the long ssDNA product into tiny pieces to obtain the amplified products. The DNA-decorated GO sensor was fabricated by preabsorbing the ssDNA fluorescence-labeled probe on the GO surface, resulting in fluorescence quenching. The DNA-decorated GO sensor could detect the amplified product via the self-assembly of dsDNA, leading to the desorption and recovery of the fluorescence-labeled probe. Under optimal conditions, the proposed system exhibited ultrasensitive detection; the detection limits of miRNA16 and miRNA21 were 8.81 and 3.85 fM, respectively. It showed a wide range of detection between 10 fM and 100 pM for miRNA16 and between 10 fM and 1 nM for miRNA16. It demonstrated high selectivity, distinguishing between 1- and 3-mismatch nucleotides in target miRNA. Overall, our proposed DNA-decorated GO sensor can accurately detect the salivary miRNAs and may potentially be used for the diagnosis and screening of early-stage oral cancer." @default.
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• W4366201631 date "2023-04-17" @default.
• W4366201631 modified "2023-09-25" @default.
• W4366201631 title "Ultrasensitive Detection of MicroRNA in Human Saliva via Rolling Circle Amplification Using a DNA-Decorated Graphene Oxide Sensor" @default.
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• W4366201631 doi "https://doi.org/10.1021/acsomega.3c00411" @default.
• W4366201631 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37151566" @default.
• W4366201631 hasPublicationYear "2023" @default.
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