4.6 Article

Algorithm-Assisted Detection and Imaging of microRNAs in Living Cancer Cells via the Disassembly of Plasmonic Core-Satellite Probes Coupled with Strand Displacement Amplification

期刊

ACS SENSORS
卷 6, 期 3, 页码 958-966

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acssensors.0c02136

关键词

microRNA detection; plasmonic core-satellite probes; strand displacement amplification; dark-field image; algorithm

资金

  1. National Natural Science Foundation of China [61875062]
  2. Fundamental Research Funds for the Central Universities

向作者/读者索取更多资源

A novel algorithm-assisted system was developed for detecting and imaging miRNAs in living cancer cells by disassembling plasmonic core-satellite probes coupled with strand displacement amplification. The system showed high detection sensitivity and simplicity, presenting potential for inexpensive, intelligent, and rapid screening of cancer cells. Additionally, an application software running on the Android platform demonstrated the potential for remote diagnosis.
Acute detection and high-resolution imaging of microRNAs (miRNAs) in living cancer cells have attracted great attention in clinical diagnosis and therapy. However, current methods suffer from low detection sensitivity or heavy dependence on expensive and sophisticated spectrometers. Herein, a novel algorithm-assisted system of detecting and imaging miRNAs in living cancer cells was developed via the disassembly of plasmonic core-satellite probes coupled with strand displacement amplification (SDA). The target miRNAs in the system could trigger the disassembly of plasmonic core-satellite probes, leading to the color change in the scattering light of the probes, which could be captured by dark-field microscopy (DFM). The concentration of the target miRNAs was obtained by analyzing the dark-field image based on the proposed algorithm with a detection limit of 2 pM for miRNA-21. Thus, the performance in terms of simplicity and sensitivity of the system compared with one of the conventional spectrophotometers was well presented, which could inspire more clinical applications of inexpensive, intelligent, and rapid screening of cancer cells. The application software based on the proposed algorithm running on the Android platform was also developed, demonstrating the potential of remote diagnosis.

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