Evidence map›Paper›PMID 36296002›Full record

ArticleMicromachines2022

A Digital Microfluidic RT-qPCR Platform for Multiple Detections of Respiratory Pathogens.

Huitao Huang, Kaisong Huang, Yun Sun, Dasheng Luo, Min Wang, Tianlan Chen, Mingzhong Li, Junwei Duan, Liqun Huang, Cheng Dong

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.5field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 21 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Huitao HuangZhuhai Center for Disease Control and Prevention, Zhuhai 519087, China.
Kaisong HuangZhuhai Center for Disease Control and Prevention, Zhuhai 519087, China.
Yun SunDigifluidic Biotech Ltd., Zhuhai 519000, China.
Dasheng LuoDigifluidic Biotech Ltd., Zhuhai 519000, China.
Min WangDigifluidic Biotech Ltd., Zhuhai 519000, China.
Tianlan ChenDigifluidic Biotech Ltd., Zhuhai 519000, China.
Mingzhong LiState Key Laboratory of Analog and Mixed-Signal VLSI, University of Macau, Macao 999078, China.
Junwei DuanCollege of Information Science and Technology, Jinan University, Guangzhou 510632, China.ORCID 0000-0002-2388-0149
Liqun HuangZhuhai Center for Disease Control and Prevention, Zhuhai 519087, China.
Cheng DongSchool of Intelligent Systems Science and Engineering/JNU-Industry School of Artificial Intelligence, Jinan University, Zhuhai 519000, China.ORCID 0000-0003-2019-6517
Zhuhai People's Hospital · CNJinan University · CNUniversity of Macau · MO

Funding

Guangdong Basic and Applied Basic Research Foundation 2021A1515110623 and 2021A1515011999Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization 2021B1212040007National Key Research and Development Program of China No. 2018YFC2002500Zhuhai Industry-university-research Cooperation Project ZH22017002200012PWCZhuhai "COVID-19 infection prevention" Emergency Science and Technology Research Project ZH22036302200052PWC
6 · The paper itself

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.

Indexed as

digital microfluidicon-chiprespiratory pathogensRT-qPCR

Identifiers

PMID36296002
PMCPMC9611846
OpenAlexW4303857010

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.