Evidence map›Paper›PMID 30223836›Full record

ArticleBMC veterinary research2018

Novel protein chip for the detection of antibodies against infectious bronchitis virus.

Liping Yan, Jianhua Hu, Jing Lei, Zhiyu Shi, Qian Xiao, Zhenwei Bi, Lu Yao, Yuan Li, Yuqing Chen, An Fang and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMC veterinary research, 2018. 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
0.9field-weighted citation impact, top 26% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
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 at 2 institutions in 2 countries.

Liping YanMOE Joint International Research Laboratory of Animal Health and Food Safety, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China. yanliping@njau.edu.cn.ORCID http://orcid.org/0000-0002-7054-1510
Jianhua HuMOE Joint International Research Laboratory of Animal Health and Food Safety, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
Jing LeiMOE Joint International Research Laboratory of Animal Health and Food Safety, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
Zhiyu ShiMOE Joint International Research Laboratory of Animal Health and Food Safety, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
Qian XiaoMOE Joint International Research Laboratory of Animal Health and Food Safety, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
Zhenwei BiMOE Joint International Research Laboratory of Animal Health and Food Safety, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
Lu YaoMOE Joint International Research Laboratory of Animal Health and Food Safety, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
Yuan LiMOE Joint International Research Laboratory of Animal Health and Food Safety, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
Yuqing ChenMOE Joint International Research Laboratory of Animal Health and Food Safety, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
An FangMOE Joint International Research Laboratory of Animal Health and Food Safety, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
Hui LiMOE Joint International Research Laboratory of Animal Health and Food Safety, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
Suquan SongMOE Joint International Research Laboratory of Animal Health and Food Safety, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
Min LiaoKey Laboratory of Animal Virology, Ministry of Agriculture, Zhejiang University, Hangzhou, 310058, People's Republic of China.
Jiyong ZhouMOE Joint International Research Laboratory of Animal Health and Food Safety, Institute of Immunology and College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China. jyzhou@njau.edu.cn.
Nanjing Agricultural University · CNFirst Affiliated Hospital Zhejiang University · CN

Funding

Key Program of Science and Technology Planning of Guangdong Province 2017B020202010National Key Research and Development Program of China 2016YFD0500800National Natural Science Foundation of China 31402150the Agricultural Science & Technology Independent Innovation Fund of Jiangsu Province CX(15)1065the Fundamental Research Funds for the Central Universities Y0201600146
6 · The paper itself

Abstract

backgroundInfectious bronchitis (IB) caused by the IB virus (IBV) can cause acute damage to chickens around the world. Therefore, rapid diagnosis and immune status determination are critical for controlling IBV outbreaks. Enzyme-linked immunosorbent assays (ELISAs) have been widely used in the detection of IBV antibodies in the early infection and continuous infection of IB because they are more sensitive and quicker than other diagnostic methods.

resultsWe have developed two indirect microarray methods to detect antibodies against IBV: a chemiluminescent immunoassay test (CIT) and a rapid diagnostic test (RDT). IBV nonstructural protein 5 (nsp5) was expressed, purified from Escherichia coli, and used to spot the initiator integrated poly(dimethylsiloxane), which can provide a near "zero" background for serological assays. Compared with the IDEXX IBV Ab Test kit, CIT and RDT have a sensitivity and specificity of at least 98.88% and 91.67%, respectively. No cross-reaction was detected with antibodies against avian influenza virus subtypes (H5, H7, and H9), Newcastle disease virus, Marek's disease virus, infectious bursal disease virus, and chicken anemia virus. The coefficients of variation of the reproducibility of the intra- and inter-assays for CIT ranged from 0.8 to 18.63%. The reproducibility of RDT was consistent with the original results. The application of the IBV nsp5 protein microarray showed that the positive rate of the CIT was 96.77%, that of the nsp5 ELISA was 91.40%, and that of the RDT was 90.32%. Furthermore, the RDT, which was visible to the naked eye, could be completed within 15 min. Our results indicated that compared with nsp5 ELISA, the CIT was more sensitive, and the RDT had similar positive rates but was faster. Furthermore, the two proposed methods were specific and stable.

conclusionsTwo microarray assays, which were rapid, specific, sensitive, and relatively simple, were developed for the detection of an antibody against IBV. These methods can be of great value for the surveillance of pathogens and monitoring the efficiency of vaccination.

Indexed as

ChickensAnimalsAntibodies, ViralCoronavirus InfectionsEnzyme-Linked Immunosorbent AssayInfectious bronchitis virusPoultry DiseasesProtein Array AnalysisReproducibility of ResultsAntibodies, ViralAntibody detectionInfectious bronchitisProtein chip

Identifiers

PMID30223836
PMCPMC6142349
OpenAlexW2891815055

What OpenQuestion holds

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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.