4.8 Article

Polychromatic Quantum Dot Array to Compose a Community Signal Ensemble for Multiplexed miRNA Detection

期刊

ACS NANO
卷 -, 期 -, 页码 -

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acsnano.2c03806

关键词

miRNA detection; multiplexing; transfer printing; duplex-specific nuclease; quantum dot

资金

  1. Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [2020R1A6A3A01095785]
  2. Global Frontier Program of the Global Frontier Hybrid Interface Materials (GFHIM) - Ministry of Science and ICT (MSIT) of Korea [2013M3A6B1078874]
  3. Midcareer Researcher Support Program - MSIT of Korea [NRF-2021R1A2B5B03001739]
  4. National Research Foundation of Korea [2020R1A6A3A01095785] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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In this study, a polychromatic quantum dot array (PQDA) was developed for accurate quantification of multiple miRNAs. The PQDA, manufactured using advanced patterning techniques, showed a wide dynamic range and high specificity, enabling the identification of target miRNAs with high sensitivity.
We herein describe a polychromatic quantum dot array (PQDA) to compose a community signal ensemble enabling accurate and precise quantification of miRNAs in a multiplexed manner. Advanced multicomponent ultrahighresolution patterning technique achieved by capsulationassisted transfer printing following self-assembly-based poly(methyl methacrylate) (PMMA) patterning is utilized to manufacture the PQDA, which is designed to discharge a target miRNAs-specific set of fluorescent quantum dots (QDs) through the activity of duplex-specific nuclease (DSN). On the basis of the community signal ensemble produced by the discharged QD profiles, target miRNAs are very specifically identified down to a femtomolar level (1.27 fM) in a multiplexed manner over a wide dynamic range of up to 6 orders of magnitude. The practical diagnostic capability of this strategy is also demonstrated by reliably identifying breast cancer-specific miRNAs from heterogeneous cancer cell lysates.

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