3D-DNA walking nanomachine based on catalytic hairpin assembly and copper nanoclusters for sensitive detection of hepatitis C virus
Talanta, ISSN: 0039-9140, Vol: 269, Page: 125478
2024
- 4Citations
- 2Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations4
- Citation Indexes4
- Captures2
- Readers2
Article Description
Rapid and accurate detection of the hepatitis C virus (HCV) is essential for early diagnosis and prevention of virus transmission. This study presents a novel approach that combines the three-dimensional (3D)-DNA walking nanomachine with catalytic hairpin assembly (CHA) and copper nanoclusters (CuNCs). By integrating CHA with the 3D DNA walking nanomachine, efficient target amplification on 3D surfaces was achieved, leading to improved reaction speed and detection performance. Terminal deoxynucleotidyl transferase (TdT) was utilized to generate T-rich DNA sequences. These sequences served as templates for the formation of CuNCs, which functioned as the readout signal. The optimized 3D-DNA walking nanomachine exhibited excellent sensitivity in detecting HCV, with a detection limit of 42.4 pM and a linear range of 100 pM to 2 nM. The biosensor demonstrated excellent selectivity and reproducibility, with a recovery rate ranging from 94% to 108% for the detection of real samples. This design holds great potential for sensitive, label-free, and reliable detection of HCV in clinical settings. Furthermore, the versatility of this approach allows for the customization of target sequences, thereby facilitating the detection of various nucleic acid targets. Therefore, this method has the potential to advance personalized medicine, disease management, and genetic analysis in the field of molecular diagnosis.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0039914023012298; http://dx.doi.org/10.1016/j.talanta.2023.125478; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85178324696&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/38039675; https://linkinghub.elsevier.com/retrieve/pii/S0039914023012298; https://dx.doi.org/10.1016/j.talanta.2023.125478
Elsevier BV
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