Evidence map›Paper›PMID 36979622›Full record

ReviewBiosensors2023

Multiplex Detection of Infectious Diseases on Microfluidic Platforms.

Fumin Chen, Qinqin Hu, Huimin Li, Yi Xie, Leshan Xiu, Yuqian Zhang, Xiaokui Guo, Kun Yin

Open access · goldFull text readReview
In one paragraph

Review in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
3.9field-weighted citation impact, top 6% 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

20 citing papers in PubMed, 36 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

8 authors at 2 institutions in 2 countries.

Fumin ChenSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, No. 227 Chongqing South Road, Shanghai 200025, China.ORCID 0000-0002-9046-3361
Qinqin HuSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, No. 227 Chongqing South Road, Shanghai 200025, China.
Huimin LiSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, No. 227 Chongqing South Road, Shanghai 200025, China.
Yi XieSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, No. 227 Chongqing South Road, Shanghai 200025, China.ORCID 0000-0003-4838-4114
Leshan XiuSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, No. 227 Chongqing South Road, Shanghai 200025, China.
Yuqian ZhangDepartment of Surgery, Division of Surgery Research, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0002-2800-6100
Xiaokui GuoSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, No. 227 Chongqing South Road, Shanghai 200025, China.
Kun YinSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, No. 227 Chongqing South Road, Shanghai 200025, China.
Shanghai Jiao Tong University · CNMayo Clinic · US

Funding

National Natural Science Foundation of China 22104090Natural Science Foundation of Shanghai 22ZR1436200
6 · The paper itself

Abstract

Infectious diseases contribute significantly to the global disease burden. Sensitive and accurate screening methods are some of the most effective means of identifying sources of infection and controlling infectivity. Conventional detecting strategies such as quantitative polymerase chain reaction (qPCR), DNA sequencing, and mass spectrometry typically require bulky equipment and well-trained personnel. Therefore, mass screening of a large population using conventional strategies during pandemic periods often requires additional manpower, resources, and time, which cannot be guaranteed in resource-limited settings. Recently, emerging microfluidic technologies have shown the potential to replace conventional methods in performing point-of-care detection because they are automated, miniaturized, and integrated. By exploiting the spatial separation of detection sites, microfluidic platforms can enable the multiplex detection of infectious diseases to reduce the possibility of misdiagnosis and incomplete diagnosis of infectious diseases with similar symptoms. This review presents the recent advances in microfluidic platforms used for multiplex detection of infectious diseases, including microfluidic immunosensors and microfluidic nucleic acid sensors. As representative microfluidic platforms, lateral flow immunoassay (LFIA) platforms, polymer-based chips, paper-based devices, and droplet-based devices will be discussed in detail. In addition, the current challenges, commercialization, and prospects are proposed to promote the application of microfluidic platforms in infectious disease detection.

Indexed as

Biosensing TechniquesCommunicable DiseasesNucleic AcidsHumansImmunoassayMicrofluidicsNucleic Acidsimmunosensorsinfectious disease diagnosismicrofluidic platformsmultiplex detectionnucleic acid sensors

Identifiers

PMID36979622
PMCPMC10046538
OpenAlexW4353091002

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read7
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.