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Enhancing efficiency in detection of COVID-19 through AI-driven colorimetric isothermal detection with multiplex primers
•The strategy of using multiplex primers to enhance colorimetric LAMP assay's efficiency was demonstrated with success.•The multiplex primers enhanced the sensitivity of the existing RT-LAMP assay by 10–100 times.•The proposed assay can detect variant of concerns (VoCs) of COVID-19.•The AI-assi...
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Published in: | Diagnostic microbiology and infectious disease 2024-10, Vol.110 (2), p.116446, Article 116446 |
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Main Authors: | , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | •The strategy of using multiplex primers to enhance colorimetric LAMP assay's efficiency was demonstrated with success.•The multiplex primers enhanced the sensitivity of the existing RT-LAMP assay by 10–100 times.•The proposed assay can detect variant of concerns (VoCs) of COVID-19.•The AI-assisted result analysis can analyze approximately 6700 samples/minute, thereby demonstrating its efficiency and scalability in point-of-care screening.
COVID-19 has afflicted millions of lives worldwide. Although there are many rapid methods to detect it based on colorimetric loop-mediated isothermal amplification, there remains room for improvement. This study aims to 1) integrate multiple primers into a singleplex assay to enhance the diagnostic sensitivity, and 2) utilize a high-throughput smartphone-operatable AI-driven color reading tool to enable a rapid result analysis. This setup can improve the sensitivity by 10–100 times and can analyze approximately 6700 samples per minute. The assay is simpler than RT-qPCR, with a turnaround time of less than 75 min. It can detect various types of SARS-CoV-2 by targeting 3 genes, increasing the likelihood that it will remain effective even if the virus undergoes mutations in any single target gene. In summary, it affords potential for adaptation to detection of new/re-emerging diseases with the visual readout for maximum assay simplicity and AI-operated mode for large-scale testing. |
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ISSN: | 0732-8893 1879-0070 1879-0070 |
DOI: | 10.1016/j.diagmicrobio.2024.116446 |