Evidence map›Paper›PMID 39450337›Full record

ArticleFrontiers in cellular and infection microbiology2024

Duplex recombinase aided amplification-lateral flow dipstick assay for rapid distinction of

Ke Chen, Junze Zhang, Simeng Wang, Zhengjun Yi, Yurong Fu

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Ke ChenDepartment of Medical Microbiology, School of Basic Medicine, Shandong Second Medical University, Weifang, Shandong, China.
Junze ZhangDepartment of Medical Microbiology, School of Basic Medicine, Shandong Second Medical University, Weifang, Shandong, China.
Simeng WangSchool of Medical Laboratory, Shandong Second Medical University, Weifang, Shandong, China.
Zhengjun YiSchool of Medical Laboratory, Shandong Second Medical University, Weifang, Shandong, China.
Yurong FuDepartment of Medical Microbiology, School of Basic Medicine, Shandong Second Medical University, Weifang, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aims to develop a novel diagnostic approach using the recombinase aided amplification-lateral flow dipstick(RAA-LFD) assay for the distinction of Methods: Our study established a duplex RAA-LFD assay capable of discriminating between MTB and MAC. Based on the principles of RAA primer and probe design, specific primers and probes were developed targeting the MTB Results: The complete workflow allows for the effective amplification of the MTB Conclusions: Our study introduces a rapid, specific, and sensitive duplex RAA-LFD assay for the discriminatory diagnosis of MTB and MAC. This method represents a significant advancement in the field of infectious disease diagnostics, offering a valuable tool for rapid detection and management of MTB and MAC infections. The implementation of this approach in point-of-care settings could greatly enhance TB control and prevention efforts, especially in resource-limited environments.

Indexed as

Mycobacterium avium ComplexMycobacterium tuberculosisNucleic Acid Amplification TechniquesSensitivity and SpecificityDNA, BacterialDNA PrimersHumansMolecular Diagnostic TechniquesMycobacterium avium-intracellulare InfectionRecombinasesReproducibility of ResultsTuberculosisDNA, BacterialDNA PrimersRecombinaseslateral flow dipstick (LFD)Mycobacterium avium complex (MAC)Mycobacterium tuberculosis (MTB)rapid distinctionrecombinase-aided amplification (RAA)

Identifiers

PMID39450337
PMCPMC11499229

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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.