Spectroscopy and Spectral Analysis, Volume. 44, Issue 8, 2111(2024)

Research Progress of Surface-Enhance Raman Scatting Spectrum for miRNAs Detection

LIU Hui-qiao1...2,*, FU Jin-jin1, WANG Si-tian1, ZHANG Jia-kun1, HE Ya-nan1 and CAO Kang-zhe1 |Show fewer author(s)
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    Surface-enhance Raman scatting (SERS) has been widely used in biomedical detection due to its high sensitivity, non-invasive, multi-channel detection and other characteristics. The abnormal expression of microribonucleic acid (miRNAs) has been found to be associated with a variety of diseases, and miRNAs have become a novel biomarker. The development of simple, sensitive and reliable miRNAs detection methods is of great significance for studying biological function, medical diagnosis, disease treatment and targeted drug research of miRNAs. Nano-SERS probes combined with nucleic acid signal amplification strategy showed high sensitivity for miRNAs detection. However, the components in the actual samples are complex, resulting in background signal interference detection results, and the tedious separation and purification process increases the detection time. Researchers have recently combined other techniques to optimize detection, improve sample throughput, simplify operations, reduce analysis time, and improve resolution. This paper mainly introduces the latest progress in miRNAs detection method based on SERS technology, discusses the advantages and necessity of technology fusion, and summarises the existing problems of miRNAs detection based on SERS technology for clinical detection, aiming to provide a reference for the design of a new fast, sensitive and reliable miRNAs detection platform.

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    LIU Hui-qiao, FU Jin-jin, WANG Si-tian, ZHANG Jia-kun, HE Ya-nan, CAO Kang-zhe. Research Progress of Surface-Enhance Raman Scatting Spectrum for miRNAs Detection[J]. Spectroscopy and Spectral Analysis, 2024, 44(8): 2111

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    Paper Information

    Received: Nov. 16, 2022

    Accepted: --

    Published Online: Oct. 11, 2024

    The Author Email: Hui-qiao LIU (liuhq@xynu.edu.cn)

    DOI:10.3964/j.issn.1000-0593(2024)08-2111-09

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