Evidence map›Paper›PMID 37771940›Full record

ArticleFrontiers in veterinary science2023

Establishment and application of multiplex droplet digital polymerase chain reaction assay for bovine enterovirus, bovine coronavirus, and bovine rotavirus.

Junzhen Chen, Dan Li, Yafang Xu, Zeyu Li, Siqi Ma, Xinyi Liu, Yuanyuan Yuan, Chengyuan Zhang, Qiang Fu, Huijun Shi

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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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

11 citing papers in PubMed.

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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

10 authors.

Junzhen ChenCollege of Veterinary Medicine, Xinjiang Agricultural University, Ürümqi, China.
Dan LiCollege of Veterinary Medicine, Xinjiang Agricultural University, Ürümqi, China.
Yafang XuCollege of Veterinary Medicine, Xinjiang Agricultural University, Ürümqi, China.
Zeyu LiCollege of Veterinary Medicine, Xinjiang Agricultural University, Ürümqi, China.
Siqi MaCollege of Veterinary Medicine, Xinjiang Agricultural University, Ürümqi, China.
Xinyi LiuCollege of Veterinary Medicine, Xinjiang Agricultural University, Ürümqi, China.
Yuanyuan YuanCollege of Veterinary Medicine, Xinjiang Agricultural University, Ürümqi, China.
Chengyuan ZhangCollege of Veterinary Medicine, Xinjiang Agricultural University, Ürümqi, China.
Qiang FuCollege of Veterinary Medicine, Xinjiang Agricultural University, Ürümqi, China.
Huijun ShiCollege of Veterinary Medicine, Xinjiang Agricultural University, Ürümqi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bovine enterovirus (BEV), bovine coronavirus (BCoV), and bovine rotavirus (BRV) are still the major worldwide concerns in the health care of cattle, causing serious economic losses in the livestock industry. It is urgent to establish specific and sensitive methods to detect viruses for the early control of diseases. Droplet digital PCR (ddPCR) has been proposed to effectively detect viral particles, and it does not involve Ct values or standard curves. In this study, we designed specific primers and probes, based on conserved regions of viral genomes, to optimize protocols for a dual ddPCR assay for detecting BCoV and BRV and a multiplex ddPCR assay for BEV, BCoV, and BRV. Sensitivity assays revealed that the lower limit of detection for qPCR was 1,000 copies/μL and for ddPCR for BEV, BCoV, and BRV, 2.7 copies/μL, 1 copy/μL and 2.4 copies/μL, respectively. Studying 82 samples collected from diarrheal calves on a farm, our dual ddPCR method detected BCoV, BRV, and co-infection at rates of 18.29%, 14.63%, and 6.1%, respectively. In contrast, conventional qPCR methods detected BCoV, BRV, and co-infection at rates of 10.98%, 12.2%, and 3.66%, respectively. On the other hand, studying 68 samples from another farm, qPCR detected BCoV, BRV, BEV, and co-infection of BCoV and BEV at rates of 14.49%, 1.45%, 5.80%, and 1.45%, respectively. Our multiplex ddPCR method detected BCoV, BRV, BEV, co-infection of BCoV and BEV, and co-infection of BRV and BEV. at rates of 14.49%, 2.9%, 8.7%, 2.9%, and 1.45%, respectively. Studying 93 samples from another farm, qPCR detected BCoV, BRV, BEV, and co-infection of BCoV and BEV was detected at rates of 5.38%, 1.08%, 18.28%, and 1.08%, respectively. Co-infection of BCoV, BRV, BEV, BCoV, and BEV, and co-infection of BRV and BEV, were detected by multiplex ddPCR methods at rates of 5.38%, 2.15%, 20.45%, 1.08%, and 1.08%, respectively. These results indicated that our optimized dual and multiplex ddPCR methods were more effective than conventional qPCR assays to detect these viral infections.

Indexed as

bovine coronavirusbovine enterovirusbovine rotavirusdroplet digital PCRreal-time quantitative PCR

Identifiers

PMID37771940
PMCPMC10523346

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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.