ArticleMicromachines2022
A Digital Microfluidic RT-qPCR Platform for Multiple Detections of Respiratory Pathogens.
Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 21 citations in OpenAlex.
- Epidemic Pattern Changes in Influenza A and B and Mycoplasma pneumoniae Pediatric Respiratory Infections During and After the COVID-19 Pandemic Restrictions in Northwest China.Current microbiology · 2026Article
- Review
- Human metapneumovirus: pathogenesis, epidemiology, diagnostic technologies, and potential intervention strategies.Virology journal · 2025Review
- AI-Enabled Microfluidics for Respiratory Pathogen Detection.Sensors (Basel, Switzerland) · 2025Review
- Nucleic acid amplification tests in digital microfluidics: the promise of next-generation point-of-care diagnostics.Microsystems & nanoengineering · 2025Review
- Review
- The Clinical Value of Novel Inflammatory Biomarkers for Predicting Mycoplasma pneumoniae Infection in Children.Journal of clinical laboratory analysis · 2025Article
- Epidemiology and diagnosis technologies of human metapneumovirus in China: a mini review.Virology journal · 2024Review
- Chlamydophila pneumoniae-associated community-acquired pneumonia in paediatric patients of a tertiary care hospital in Mexico: molecular diagnostic and clinical insights.Scientific reports · 2023Article
- Graphene Oxide Paper Manipulation of Micro-Reactor Drops.Micromachines · 2023Article
- Recent development of microfluidics-based platforms for respiratory virus detection.Biomicrofluidics · 2023Article
- Development of an AlphaLISA assay for sensitive and accurate detection of influenza B virus.Frontiers in medicine · 2023Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.