Evidence map›Paper›PMID 41472204›Full record

ReviewViruses2025

Diagnostic Methods for Bovine Coronavirus: A Review of Recent Advancements and Challenges.

Jie Dong, Xiaoxiao He, Shijun Bao, Zhanyong Wei

Abstract readReview
In one paragraph

Review in Viruses, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Jie DongCollege of Veterinary Medicine, Gansu Agricultural University, Lanzhou 730070, China.
Xiaoxiao HeCollege of Veterinary Medicine, Gansu Agricultural University, Lanzhou 730070, China.
Shijun BaoCollege of Veterinary Medicine, Gansu Agricultural University, Lanzhou 730070, China.ORCID 0000-0001-7557-5069
Zhanyong WeiCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou 450002, China.

Funding

Gansu Provincial Department of Agriculture and Rural Affairs Science and Technology Support Project KJZC-2024-15
6 · The paper itself

Abstract

Bovine coronavirus(BCoV) is a significant pathogen causing substantial economic losses in the cattle industry through increased calf mortality, reduced growth performance, and decreased milk yield. Rapid and accurate diagnostic methods are therefore essential for controlling BCoV transmission. Current diagnostic methods comprise two primary categories: conventional techniques and cutting-edge innovations. Conventional approaches, including molecular methods like RT-PCR/qRT-PCR and immunological assays such as ELISA and neutralization tests, remain the main diagnostic methods. However, they are limited by laboratory dependency as well as the necessary balance between speed and sensitivity. These limitations have promoted the development of innovative methods, including isothermal amplification, CRISPR/Cas systems, droplet digital PCR, and integrated platforms. This review comprehensively analyzes the advantages, limitations, and applications of current diagnostic methods, highlighting integrated platforms such as RPA-CRISPR-LFA and microfluidics-based LFA. These innovations bridge critical performance gaps by enhancing sensitivity and specificity while enabling field application, demonstrating significant potential as next-generation point-of-care diagnostics for managing this economically critical pathogen.

Indexed as

Cattle DiseasesCoronavirus, BovineCoronavirus InfectionsMolecular Diagnostic TechniquesAnimalsCattleCRISPR-Cas SystemsNucleic Acid Amplification TechniquesSensitivity and SpecificityBCoVCRISPR/Casimmunological methodsintegrated platformslateral flow assay (LFA)moleculardiagnostic methods

Identifiers

PMID41472204
PMCPMC12737541

What OpenQuestion holds

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LicenceCC BY
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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.