Evidence map›Paper›PMID 37576781›Full record

ArticleVeterinary world2023

Single-step multiplex reverse transcription-polymerase chain reaction for the detection and differentiation of QX-like infectious bronchitis virus from the Thai variant and vaccine strains H120, Ma5, and 4/91.

Sucheeva Junnu, Tawatchai Pohuang

Open access · goldAbstract read
In one paragraph

Article in Veterinary world, 2023. 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, top 94% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

2 authors at 1 institution in 1 country.

Sucheeva JunnuDivision of Livestock Medicine, Faculty of Veterinary Medicine, Khon Kaen University, Khon Kaen 40002, Thailand.
Tawatchai PohuangDivision of Livestock Medicine, Faculty of Veterinary Medicine, Khon Kaen University, Khon Kaen 40002, Thailand.
Khon Kaen University · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aim: QX-like infectious bronchitis virus (IBV) is a highly infectious avian coronavirus that causes respiratory and kidney disease. It is linked to increased mortality and loss of performance in infected chickens worldwide, including Thailand. Thus, a simple and rapid diagnostic method for the diagnosis of QX-like IBV is needed. This study aimed to develop a single-step multiplex reverse transcription-polymerase chain reaction (mRT-PCR) assay to detect and differentiate QX-like IBV from Thai IBV and vaccine strains used in the poultry industry (H120, Ma5, and 4/91). Materials and Methods: Primer sets specific for QX-like and Thai IBV were designed to target the S1 gene. The specificity of the technique was verified using nine isolates of QX-like IBV, four isolates of Thai IBV, and other avian viral respiratory pathogens. The detection limit was evaluated using a serial ten-fold dilution of QX-like and Thai IBV. Results: The results showed that single-step mRT-PCR could detect QX-like IBV and differentiate it from Thai IBV and the vaccine strains H120, Ma5, and 4/91. The limit of detection of the developed assay was 10 Conclusion: The single-step mRT-PCR assay developed in this study can potentially discriminate QX-like IBV from Thai IBV and the vaccine strains H120, Ma5, and 4/91 in a single reaction. It is also suitable for use in all laboratories with access to conventional PCR equipment.

Indexed as

detectionQX-like infectious bronchitis virussingle-step multiplex reverse transcription-polymerase chain reactionspecificity

Identifiers

PMID37576781
PMCPMC10420694
OpenAlexW4378574561

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LicenceCC BY
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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.