Evidence map›Paper›PMID 42315622›Full record

ArticleCurrent microbiology2026

Validation of a Qualitative Detection Method for Influenza A Virus RNA Based on the RT-RPA-CRISPR/Cas13a System.

Cong Peng, Cheng Zhang, Tong Jiang

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in Current microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Cong PengSuzhou Ninth People's Hospital, Suzhou, 215200, Jiangsu, China.
Cheng ZhangSuzhou Ninth People's Hospital, Suzhou, 215200, Jiangsu, China.
Tong JiangDepartment of Clinical Laboratory, Suzhou TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Suzhou, 215000, Jiangsu, China. jt18269857923@163.com.

Funding

Suzhou Municipal Science and Technology Bureau No. SYWD2025119
6 · The paper itself

Abstract

Seasonal influenza A virus (IAV) frequently causes outbreaks, creating an urgent need for rapid, cost-effective detection. Existing methods have limitations: antigen tests lack sensitivity, RT-qPCR (the gold standard) requires bulky thermal cyclers, isothermal techniques like LAMP suffer from complex primer design and non-specific amplification, and many CRISPR-based diagnostics integrate nanotechnology or microfluidics, increasing cost and complexity without systematic clinical validation. To address these issues, we adapted RT-RPA combined with CRISPR-Cas13a into a simplified qualitative IAV detection platform. The workflow uses isothermal RT-RPA for amplification, Cas13a for specific recognition and trans-cleavage, and a lateral flow strip for visual readout. A rapid nucleic acid release reagent simplifies sample pretreatment. This approach retains the high sensitivity and specificity of nucleic acid testing while eliminating complex equipment. Preliminary performance evaluation showed that the platform produced a clear signal at 10¹ copies/mL of viral genome and exhibited no cross-reactivity with other respiratory viruses. Using RT-qPCR as the gold standard, testing of 78 clinical samples achieved 100% concordance. In summary, this study provides a practical simplification of an established RT-RPA-CRISPR/Cas13a workflow for IAV detection, supported by preliminary clinical validation, and demonstrates its suitability for rapid testing in low-resource settings.

Indexed as

CRISPR-Cas SystemsInfluenza A virusInfluenza, HumanMolecular Diagnostic TechniquesNucleic Acid Amplification TechniquesRNA, ViralHumansRapid Diagnostic TestsSensitivity and SpecificityRNA, Viral

Identifiers

What OpenQuestion holds

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Registered trials

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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.