Evidence map›Paper›PMID 37762237›Full record

ArticleInternational journal of molecular sciences2023

Identification of a Monoclonal Antibody against Porcine Deltacoronavirus Membrane Protein.

Huiguang Wu, Chen Li, Xian Sun, Yue Cheng, Zhenhai Chen

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 18% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Huiguang WuCollege of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China.ORCID 0000-0001-7724-7835
Chen LiCollege of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China.ORCID 0000-0002-0955-3707
Xian SunCollege of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China.
Yue ChengCollege of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China.
Zhenhai ChenCollege of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China.
Yangzhou University · CN

Funding

111 Project D18007Agricultural Science and Technology Independent Innovation Fund of Jiangsu Province CX (21) 2014Guangxi Key Research and Development Plan AB21238003Natural Science Foundation Projects of Jiangsu Province BK20211120Priority Academic Program Development of Jiangsu Higher Education Institutions PAPDYangzhou City and Yangzhou University corporation YZ2022187
6 · The paper itself

Abstract

Porcine deltacoronavirus (PDCoV) is an emerging virus that poses a significant threat to the global swine industry. Its membrane (M) protein is crucial for virion assembly and virus-host interactions. We selected the hydrophilic region of M protein for prokaryotic expression, purification, and recombinant protein production. Utilizing hybridoma technology, we prepared the monoclonal antibody (mAb) 24-A6 against M protein. The mAb 24-A6 was shown to be suitable for use in immunofluorescence assays, western blotting, and immunoprecipitation, with specificity for PDCoV and no cross-reactivity with other five porcine viruses. The M protein was observed to be expressed as early as 3 h after PDCoV infection, increasing its expression over the duration of infection. Notably, the antigenic epitope of the M protein identified as

Indexed as

Antibodies, MonoclonalMembrane ProteinsAnimalsDeltacoronavirusEpitopesSwineAntibodies, MonoclonalEpitopesMembrane Proteinsantigenic epitopemembrane proteinmonoclonal antibodyporcine deltacoronavirus

Identifiers

PMID37762237
PMCPMC10530725
OpenAlexW4386602658

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.