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1.
Journal of Tropical Medicine ; 22(11):1487-1492, 2022.
Article in Chinese | GIM | ID: covidwho-2316552

ABSTRACT

Objective: Provide a digital microfluidic RT-qPCR chip for rapid detection of several upper respiratory diseases. Methods: Several specific primer-probe sets were designed according to the conserved sequences of 2019 novel corona virus(2019-n COV), influenza A virus(Flu A), influenza B virus(Flu B), severe acute respiratory syndrome corona virus(SARS-Co V), Middle East respiratory syndrome corona virus(MERS-Co V), and then packaged into a digital microfluidic chip which allowed simultaneous detection of five upper respiratory tract pathogens with the help of reverse transcription quantitative PCR(RT-q PCR)technology. In the meanwhile, the detection limit, specificity and sensitivity of this digital microfluidic chip were evaluated base on the clinical specimens, plasmids and unrelated pathogens. Results: The established digital microfluidic RT-q PCR chip for 2019-n COV, Flu A, Flu B,SARS-Co V,MERS-Co V had a detection limit of 12 copies/reaction, while the detection limit of the RT-q PCR method without digital microfluidics was 15 copy/reaction;the detection limit of the two methods was basically the same. For nucleic acid samples extracted from clinical samples, the detection results of digital microfluidic RT-q PCR chips were all negative without non-specific amplification. At the same time, the RT-qPCR method and the digital microfluidic RT-qPCR chip method were used to carry out clinical comparative tests of 5 items in 20 clinical samples, total 100 tests. The results showed that the sensitivity of the digital microfluidic RT-q PCR chip reached 94%, the specificity was 100%. SPSS was used to analyze the consistency of the two methods, and the results showed that the two methods had a high degree of consistency(Kappa=0.962, P<0.05). Conclusion: Based on digital microfluidic RT-q PCR chip technology,a multi-target rapid detection method of upper respiratory tract susceptible virus was established, which could provide a new detection method for early clinical identification of respiratory pathogens.

2.
Micromachines (Basel) ; 13(10)2022 Sep 30.
Article in English | MEDLINE | ID: covidwho-2066262

ABSTRACT

The coronavirus disease 2019 pandemic has spread worldwide and caused more than six million deaths globally. Therefore, a timely and accurate diagnosis method is of pivotal importance for controlling the dissemination and expansions. Nucleic acid detection by the reverse transcription-polymerase chain reaction (RT-PCR) method generally requires centralized diagnosis laboratories and skilled operators, significantly restricting its use in rural areas and field settings. The digital microfluidic (DMF) technique provides a better option for simultaneous detections of multiple pathogens with fewer specimens and easy operation. In this study, we developed a novel digital microfluidic RT-qPCR platform for multiple detections of respiratory pathogens. This method can simultaneously detect eleven respiratory pathogens, namely, mycoplasma pneumoniae (MP), chlamydophila pneumoniae (CP), streptococcus pneumoniae (SP), human respiratory syncytial virus A (RSVA), human adenovirus (ADV), human coronavirus (HKU1), human coronavirus 229E (HCoV-229E), human metapneumovirus (HMPV), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus (FLUA) and influenza B virus (FLUB). The diagnostic performance was evaluated using positive plasmids samples and clinical specimens compared with off-chip individual RT-PCR testing. The results showed that the limit of detections was around 12 to 150 copies per test. The true positive rate, true negative rate, positive predictive value, negative predictive value, and accuracy of DMF on-chip method were 93.33%, 100%, 100%, 99.56%, and 99.85%, respectively, as validated by the off-chip RT-qPCR counterpart. Collectively, this study reported a cost-effective, high sensitivity and specificity on-chip DMF RT-qPCR system for detecting multiple respiratory pathogens, which will greatly contribute to timely and effective clinical management of respiratory infections in medical resource-limited settings.

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