Evidence map›Paper›PMID 40839293›Full record

ArticleAMB Express2025

Autonomous microfluidic influenza A/B subtyping system using on-chip multiplex isothermal amplification for field-deployable surveillance.

Si-Ming Lu, Jia-Long Wang, Yang Li, Ling Zhang, Hang-Ping Yao, Li-Guo Liang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in AMB Express, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Review
  2. Review
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

6 authors.

Si-Ming Lu *Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Jia-Long Wang *State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Yang Li *State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Ling ZhangDepartment of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Hang-Ping YaoState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. yaohangping@zju.edu.cn.
Li-Guo LiangCentre for Clinical Laboratory, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China. lianglg@zju.edu.cn.

Funding

Major Project of Hangzhou Health Science and Technology Program Z20250271National Key Research and Development Program of China 2024YFC2309900Science and Technology Program for Disease Prevention and Control in Zhejiang Province 2025JK021Zhejiang Provincial Health Major Science and Technology Programme WKJ-ZJ-2434Zhejiang Provincial Natural Science Foundation of China LTGY23H160001
6 · The paper itself

Abstract

Influenza viruses present significant challenges to global health. A rapid recombinase polymerase amplification (RPA)-based detection system for multiple influenza strains (A, H1N1/H2N2/H3N2/H5N1/H7N9 and B) has been developed to address the limitations of 2-h Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) tests. By using optimized primers targeting key viral proteins (M, NA, HA, PA), the method achieves detection in 10 min with 0.99 log linearity (1-10

Indexed as

Influenza A and B subtypesLow-resource settingsMicrofluidic devicePoint-of-care diagnosticsRNA detectionRPA

Identifiers

PMID40839293
PMCPMC12370608

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.