Evidence map›Paper›PMID 40018702›Full record

ArticleFrontiers in veterinary science2025

Epidemiological investigation of goose circovirus based on a newly developed indirect ELISA method.

Jialong Chen, Wenchang Xue, Zhanxin Yao, Chao Wang, Wanjun Zhu, He Wang, Jipei Zhang, Yi Tang, Rongchang Liu, Jidang Chen

Abstract read
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In one paragraph

Article in Frontiers in veterinary science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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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

10 authors.

Jialong Chen *School of Animal Science and Technology, Foshan University, Foshan, China.
Wenchang Xue *School of Animal Science and Technology, Foshan University, Foshan, China.
Zhanxin YaoSchool of Animal Science and Technology, Foshan University, Foshan, China.
Chao WangSchool of Animal Science and Technology, Foshan University, Foshan, China.
Wanjun ZhuWANMUZHOU Biotechnology Limited Company, Foshan, China.
He WangSchool of Animal Science and Technology, Foshan University, Foshan, China.
Jipei ZhangSchool of Animal Science and Technology, Foshan University, Foshan, China.
Yi TangCollege of Animal Science and Veterinary Medicine, Shandong Agricultural University, Taian, China.
Rongchang LiuInstitute of Animal Husbandry and Veterinary, Fujian Academy of Agricultural Sciences, Fuzhou, China.
Jidang ChenSchool of Animal Science and Technology, Foshan University, Foshan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Goose circovirus (GoCV) is a recently identified pathogen in geese that is known to cause slow growth, feather disorder syndrome, and immunosuppression. Infection with GoCV may increase the risk of coinfections with multiple pathogens, leading to significant economic losses in the goose industry. However, due to a lack of serological detection methods, analysis of viral nucleic acids has been widely used in GoCV epidemiological surveys, which has limited accurate monitoring of the prevalence of GoCV. In this study, we developed and optimized an indirect ELISA method based on the prokaryotic-expressed recombinant GoCV capsid protein (△Cap-iELISA). The △Cap-iELISA was then used to test 349 goose serum samples collected from Guangdong, Shandong, and Fujian provinces during 2023 and 2024. The results showed that the positive rate of GoCV antibodies in the sampled geese was 71.06%. Further analysis indicated that the positive rate of GoCV antibodies increased with the age of the geese. In conclusion, we have developed a novel iELISA method that is well-suited for large-scale clinical detection and early diagnosis of GoCV infection. Notably, a significant correlation between age and the positive rate of GoCV antibodies among geese was observed based on this newly established method.

Indexed as

capsid proteingoose circovirusindirect ELISAprokaryotic expressionserological detection methods

Identifiers

PMID40018702
PMCPMC11866481

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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.