Evidence map›Paper›PMID 42100657›Full record

ArticleFrontiers in cellular and infection microbiology2026

Development of an indirect enzyme-linked immunosorbent assay based on the nucleocapsid protein of bovine parainfluenza virus type 3.

Juan Liao, Xue Yang, Ruiqi Li, Aoyuntuya Zhang, Yu Han, Shanhui Ren, Shijun Bao, Jinxin Xie

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2026. 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
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  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

8 authors.

Juan LiaoCollege of Veterinary Medicine, Gansu Agricultural University, Lanzhou, Gansu, China.
Xue YangCollege of Veterinary Medicine, Gansu Agricultural University, Lanzhou, Gansu, China.
Ruiqi LiCollege of Veterinary Medicine, Xinjiang Agricultural University, Urumqi, Xinjiang, China.
Aoyuntuya ZhangCollege of Veterinary Medicine, Xinjiang Agricultural University, Urumqi, Xinjiang, China.
Yu HanCollege of Advanced Agricultural Sciences, Yulin University, Yulin, Shaanxi, China.
Shanhui RenLanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Lanzhou, Gansu, China.
Shijun BaoCollege of Veterinary Medicine, Gansu Agricultural University, Lanzhou, Gansu, China.
Jinxin XieCollege of Veterinary Medicine, Xinjiang Agricultural University, Urumqi, Xinjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Bovine parainfluenza virus type 3 (BPIV3) is an important pathogen in the bovine respiratory disease complex. The purpose of this study was to develop an efficient and rapid serological detection method, an indirect enzyme-linked immunosorbent assay (iELISA), for BPIV3. Methods: The full-length N gene of BPIV3 was amplified from reverse-transcribed BPIV3 cDNA and ligated into the pET-28a prokaryotic expression vector. The recombinant target N protein was correctly expressed. After purification, the target N protein was used to immunize BALB/c mice to prepare polyclonal antibodies. After experimental optimization, an iELISA for detecting antibodies against the BPIV3 N protein was established using purified protein and prepared polyclonal antibodies. Results: The recombinant N protein was efficiently expressed after induction with isopropyl β-D-1-thiogalactopyranoside at 32°C for 16 h. Immunization of BALB/c mice with the purified recombinant N protein elicited polyclonal antibodies that specifically reacted with BPIV3, with an antibody titer of 1:256000. The optimized iELISA conditions were as follows. Microtiter plates were coated with antigen at 5× 10 Conclusion: The N protein polyclonal antibody prepared in this study provides an important biological basis for research on the mechanism of BPIV3 infection. The establishment of an iELISA can enable the rapid screening of clinical samples, thereby providing reliable technical support for the epidemiological investigation of BPIV3.

Indexed as

Antibodies, ViralCattle DiseasesNucleocapsid ProteinsParainfluenza Virus 3, BovineRespirovirus InfectionsAnimalsCattleEnzyme-Linked Immunosorbent AssayFemaleMiceMice, Inbred BALB CRecombinant ProteinsSensitivity and SpecificityAntibodies, ViralNucleocapsid ProteinsRecombinant Proteinsbovine parainfluenza virus type 3indirect enzyme-linked immunosorbent assaynucleocapsid proteinpolyclonal antibodyserological detection

Identifiers

PMID42100657
PMCPMC13143965

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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.