Evidence map›Paper›PMID 38471226›Full record

ArticlePoultry science2024

Rapid detection of goose megrivirus using TaqMan real-time PCR technology.

Huanru Fu, Shuyu Chen, Jinpeng Zhang, Jinbo Su, Zhongwei Miao, Yu Huang, Chunhe Wan

Open access · goldAbstract read
In one paragraph

Article in Poultry science, 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
1.2field-weighted citation impact, top 24% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  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

7 authors at 1 institution in 1 country.

Huanru FuInstitute of Animal Husbandry and Veterinary Medicine/Fujian Key Laboratory for Avian Diseases Control and Prevention/Fujian Animal Diseases Control Technology Development Centre, Fujian Academy of Agricultural Sciences, Fuzhou 350013, China; School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Shuyu ChenInstitute of Animal Husbandry and Veterinary Medicine/Fujian Key Laboratory for Avian Diseases Control and Prevention/Fujian Animal Diseases Control Technology Development Centre, Fujian Academy of Agricultural Sciences, Fuzhou 350013, China; School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Jinpeng ZhangInstitute of Animal Husbandry and Veterinary Medicine/Fujian Key Laboratory for Avian Diseases Control and Prevention/Fujian Animal Diseases Control Technology Development Centre, Fujian Academy of Agricultural Sciences, Fuzhou 350013, China.
Jinbo SuInstitute of Animal Husbandry and Veterinary Medicine/Fujian Key Laboratory for Avian Diseases Control and Prevention/Fujian Animal Diseases Control Technology Development Centre, Fujian Academy of Agricultural Sciences, Fuzhou 350013, China; School of Future Technology, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Zhongwei MiaoInstitute of Animal Husbandry and Veterinary Medicine/Fujian Key Laboratory for Avian Diseases Control and Prevention/Fujian Animal Diseases Control Technology Development Centre, Fujian Academy of Agricultural Sciences, Fuzhou 350013, China.
Yu HuangInstitute of Animal Husbandry and Veterinary Medicine/Fujian Key Laboratory for Avian Diseases Control and Prevention/Fujian Animal Diseases Control Technology Development Centre, Fujian Academy of Agricultural Sciences, Fuzhou 350013, China.
Chunhe WanInstitute of Animal Husbandry and Veterinary Medicine/Fujian Key Laboratory for Avian Diseases Control and Prevention/Fujian Animal Diseases Control Technology Development Centre, Fujian Academy of Agricultural Sciences, Fuzhou 350013, China. Electronic address: chunhewan@126.com.
Fujian Academy of Agricultural Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to develop an efficient and accurate platform for the detection of the newly identified goose megrivirus (GoMV). To achieve this goal, we developed a TaqMan real-time PCR technology for the rapid detection and identification of GoMV. Our data showed that the established TaqMan real-time PCR assay had high sensitivity, with the lowest detection limit of 67.3 copies/μL. No positive signal can be observed from other goose origin viruses (including AIV, GPV, GoCV, GHPyV, and GoAstV), with strong specificity. The coefficients of variation of repeated intragroup and intergroup tests were all less than 1.5%, with excellent repeatability. Clinical sample investigation data from domestic Minbei White geese firstly provided evidence that GoMV can be transmitted both horizontally and vertically. In conclusion, since the TaqMan real-time PCR method has high sensitivity, specificity, and reproducibility, it can be a useful candidate tool for GoMV epidemiological investigation.

Indexed as

GeesePoultry DiseasesReal-Time Polymerase Chain ReactionAnimalsReproducibility of ResultsRNA Virus InfectionsSensitivity and Specificityepidemiological investigationgoose megrivirusTaqMan real-time PCR technologyvertical transmission

Identifiers

PMID38471226
PMCPMC11067730
OpenAlexW4392454772

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.