ArticleJournal of virological methods2010
Development of universal SYBR Green real-time RT-PCR for the rapid detection and quantitation of bovine and porcine toroviruses.
Article in Journal of virological methods, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Identification of a new goat torovirus strain: first detection and genomic analysis in China.Irish veterinary journal · 2025Article
- Development and use of a reverse transcription insulated isothermal PCR assay for detection and characterization of bovine torovirus in yaks.Archives of virology · 2021Article
- Porcine Torovirus (PToV)-A Brief Review of Etiology, Diagnostic Assays and Current Epidemiology.Frontiers in veterinary science · 2019Review
- Molecular epidemiology of Porcine torovirus (PToV) in Sichuan Province, China: 2011-2013.Virology journal · 2014Article
- An overview of calf diarrhea - infectious etiology, diagnosis, and intervention.Journal of veterinary science · 2014Review
- Case-control study of microbiological etiology associated with calf diarrhea.Veterinary microbiology · 2013Article
- Molecular detection of porcine torovirus in piglets with diarrhea in southwest China.TheScientificWorldJournal · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Toroviruses (ToVs) are a group of emerging viruses that cause gastroenteritis in domestic animals and humans. Currently, methods such as real-time reverse transcription-polymerase chain reaction (real-time RT-PCR) have not yet been developed for the rapid detection and quantitation of bovine (BToV) and porcine (PToV) toroviruses. Using BToV and PToV RNA standards generated by in vitro transcription, the detection limit of the SYBR Green real-time RT-PCR assay was 2.54 x 10(2) BToV and 2.17 x 10(3) PToV copies/reaction (correlation coefficiency=0.99 and 0.97, respectively), whereas those of RT-PCR and nested PCR were 2.54 x 10(5) and 2.54 x 10(4) (BToV) and 2.17 x 10(7) and 2.17 x 10(5) (PToV) cRNA viral copies/reaction, respectively. Archived diarrhea specimens of calves (n=121) and piglets (n=86) were subjected to RT-PCR, nested PCR and SYBR Green real-time RT-PCR. By conventional RT-PCR, 1 (0.8%) bovine and 7 (8.1%) porcine samples tested positive to BToV and PToV, respectively. With nested PCR, 13 (10.7%) bovine and 17 (19.8%) porcine samples tested positive. SYBR Green real-time RT-PCR assay detected BToV and PToV in 22 of 121 (18.2%) bovine and 31 of 86 (36.0%) porcine samples. These results indicate that SYBR Green real-time RT-PCR (P<0.05) is a more sensitive assay, which can be reproduced as a reliable, sensitive, and rapid tool for the detection and quantitation of toroviruses.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.