ArticleBMC veterinary research2025
Establishment and application of a qPCR method for differential detection of Brucella S2 vaccine strain.
Article in BMC veterinary research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- A novel duplex TaqMan qPCR assay for rapid differential diagnosis and co-infection screening of Orf virus and Brucella spp. in goats.Veterinary research communications · 2026Article
- Advances in rapid detection technologies for zoonotic diseases: a one health-oriented review.Frontiers in cellular and infection microbiology · 2026Review
- Innovations, Applications, and Future Trends in Veterinary Diagnostic Technologies.Transboundary and emerging diseases · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundBrucellosis is one of the most serious zoonotic bacterial diseases in the world. The disease has caused serious harm to people and livestock, hindered the healthy development of the breeding industry, and led to serious economic losses.At present, the prevention and control of this kind of disease is still based on vaccine immunization. However, after the widely used vaccine is inoculated to livestock, there is no widely used differential diagnosis method to distinguish vaccine immune antibodies from natural infection antibodies. Quarantine and purification work is difficult to carry out. In addition, there are few studies using real-time PCR(qPCR) methods in the differential diagnosis of natural virulent strains and vaccine strains of brucellosis.The purpose of this study is to establish a rapid, sensitive and accurate differential diagnosis method for Brucella S2 vaccine strain, and to solve the problem of lack of identification of Brucella S2 vaccine strain and natural virulent strain in clinical detection.It avoids the killing of some livestock due to the positive antibody of the Brucella S2 vaccine strain, and can also identify sick animals from immune herds, reducing the economic losses of farms, and providing certain technical support for the quarantine and purification of epidemic diseases.
resultsIn this study, combined with TaqMan probe-based qPCR technology, specific primers and probes were designed according to the specific deletion genes of the Brucella S2 vaccine strain,which could be used as marker genes.The qPCR and duplex qPCR detection methods of Brucella were successfully established.The method has good specificity, sensitivity and repeatability, the lowest limit of detection can reach 1 × 10
conclusionsThis study successfully established a duplex qPCR detection method for the differential diagnosis of the Brucella S2 vaccine strain. From the establishment of the method to the clinical application of the method, it shows that the method can be used for the differential diagnosis of clinical brucellosis.
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.