Evidence map›Paper›PMID 41304291›Full record

ArticleMicroorganisms2025

Development of a Blocking ELISA for Detection of Serum Neutralizing Antibodies Against Duck Adenovirus Type 3.

Mei Tang, Xiaona Shi, Yifei Xiong, Chunxiu Yuan, Qinmin Zhu, Minfan Huang, Bangfeng Xu, Qinfang Liu, Xue Pan, Zhifei Zhang and 4 more

Abstract read
In one paragraph

Article in Microorganisms, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

14 authors.

Mei TangDepartment of Avian Infectious Diseases, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China.
Xiaona ShiDepartment of Avian Infectious Diseases, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China.
Yifei XiongCollege of Animal Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Chunxiu YuanDepartment of Avian Infectious Diseases, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China.
Qinmin ZhuDepartment of Avian Infectious Diseases, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China.
Minfan HuangCollege of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China.
Bangfeng XuDepartment of Avian Infectious Diseases, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China.
Qinfang LiuDepartment of Avian Infectious Diseases, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China.ORCID 0000-0001-9516-2130
Xue PanDepartment of Avian Infectious Diseases, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China.
Zhifei ZhangDepartment of Avian Infectious Diseases, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China.
Qiaoyang TengDepartment of Avian Infectious Diseases, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China.
Minghao YanDepartment of Avian Infectious Diseases, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China.ORCID 0009-0005-9037-5328
Dawei YanDepartment of Avian Infectious Diseases, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China.ORCID 0000-0001-8039-4668
Zejun LiDepartment of Avian Infectious Diseases, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China.

Funding

the National Key Research and Development Program of China 2023YFD1800601the National Key Research and Development Program of China 2024YFD1800102the National Natural Science Foundation of China 32573347
6 · The paper itself

Abstract

In 2014, Duck Adenovirus type 3 (DAdV-3) emerged in Muscovy ducks and has since spread rapidly across China, causing significant economic losses to the duck industry. Given this situation, the development of reliable diagnostic tools is crucial for effective disease control. In this study, a neutralizing monoclonal antibody (mAb) 2F12 specific to DAdV-3 was generated, which showed a blocking rate of over 70% and a neutralization titer of up to 1:794. A blocking enzyme-linked immunosorbent assay (b-ELISA) was further developed based on mAb 2F12 to efficiently detect neutralizing antibodies against DAdV-3. The cut-off values of percent inhibition (PI) were set based on testing 84 negative duck serum samples, with a value below 16.79% (mean (X¯) + 2 standard deviations (SD)) for negative sera and over 21.62% (X¯ + 3SD) for positive sera. The b-ELISA exhibited a high specificity, reacting exclusively with DAdV-3 positive serum and showing no cross-reactivity with other representative positive sera tested. Additionally, the b-ELISA showed significantly higher sensitivity than the serum neutralization test (SNT), detecting antibodies 16-fold greater than the endpoint dilution of the SNT. The established b-ELISA, validated with 90 field serum samples from six duck farms, was well-suited for clinical detection of DAdV-3 antibodies and for monitoring post-vaccination antibody levels, representing a significant advancement in DAdV-3 detection and prevention.

Indexed as

blocking ELISAdetectionduck adenovirus type 3 (DAdV-3)monoclonal antibody

Identifiers

PMID41304291
PMCPMC12654197

What OpenQuestion holds

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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.