Evidence map›Paper›PMID 41847197›Full record

ArticleFrontiers in microbiology2026

Development of a point-of-care dual one-step recombinase-aided PCR assay for rapid identification of

Xingyu Liu, Kenan Peng, Yuanrui Li, Shihao Jiao, Jianing Wu, Duoxiao Zhang, Shijue Gao, Yujie Xiang, Junkai Ren, Qian Ma and 6 more

Abstract read
In one paragraph

Article in Frontiers in 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

16 authors.

Xingyu LiuHebei Medical University, Shijiazhuang, Hebei, China.
Kenan PengDepartment of Clinical Laboratory, Hebei General Hospital, Shijiazhuang, Hebei, China.
Yuanrui LiHealth Science Center, Ningbo University, Ningbo, Zhejiang, China.
Shihao JiaoDepartment of Clinical Laboratory, Hebei General Hospital, Shijiazhuang, Hebei, China.
Jianing WuDepartment of Clinical Laboratory, Hebei General Hospital, Shijiazhuang, Hebei, China.
Duoxiao ZhangDepartment of Clinical Laboratory, Hebei General Hospital, Shijiazhuang, Hebei, China.
Shijue GaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Yujie XiangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Junkai RenNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Qian MaDepartment of Clinical Laboratory, Hebei General Hospital, Shijiazhuang, Hebei, China.
Xinxin LiDepartment of Clinical Laboratory, Hebei General Hospital, Shijiazhuang, Hebei, China.
Zijin ZhaoDepartment of Clinical Laboratory, Hebei General Hospital, Shijiazhuang, Hebei, China.
Zhiqiang HanDepartment of Clinical Laboratory, Hebei General Hospital, Shijiazhuang, Hebei, China.
Xinxin ShenNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Xuejun MaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Yanqing TieDepartment of Clinical Laboratory, Hebei General Hospital, Shijiazhuang, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Fluoroquinolone (FQ) resistance in Methods: A cartridge-based POCT dual one-step recombinase-aided PCR (POCT-DO-RAP) assay was established for rapid detection of FQ resistance-associated mutations in MTB. Locked nucleic acid (LNA) probes were designed to enhance single-nucleotide discrimination for Results: The optimized POCT-DO-RAP assay achieved limits of detection of 1 copy/reaction for the wild-type (WT) tube and 10 CFU/mL for the mutant-type (MT) tube, representing a 10-fold increase in sensitivity compared with conventional qPCR. The assay reliably detected mutant alleles even when they represented only 1% of mixed templates. Among 128 clinical isolates, the assay accurately differentiated 50 wild-type and 78 resistant strains, showing complete concordance with Sanger sequencing and no cross-reactivity. In clinical validation,9 samples negative by qPCR were confirmed as positive by both DO-RAP assay and nested PCR followed by Sanger sequencing. Conclusion: The POCT-DO-RAP assay developed in this study achieves a fully integrated "sample-in, result-out" workflow on a single device, offering ultra-high sensitivity, precise mutation discrimination, and excellent clinical concordance. This approach provides a promising molecular diagnostic tool for rapid detection of drug-resistant tuberculosis, particularly suitable for primary healthcare and resource-limited settings.

Indexed as

fluoroquinolone resistancegyrAmolecular diagnosticsMycobacterium tuberculosispoint-of-care testingrecombinase-aided PCR

Identifiers

PMID41847197
PMCPMC12989489

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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.