Evidence map›Paper›PMID 40612150›Full record

ArticleFrontiers in veterinary science2025

An SNP-based diagnostic method for

Xingya Wang, Xiaowei Tian, Wanyang Li, Yuanchao Yang, Shuai Zhang, Hui Wang, Wanru Geng, Jingbo Zhai

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Prevalence and detection ofFrontiers in cellular and infection microbiology · 2026
    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.

Xingya Wang *School of Basic Medical Sciences, Inner Mongolia Minzu University, Tongliao, China.
Xiaowei Tian *Department of Intensive Medicine, Affiliated Hospital of Inner Mongolia Minzu University, Tongliao, China.
Wanyang LiSchool of Basic Medical Sciences, Inner Mongolia Minzu University, Tongliao, China.
Yuanchao YangSchool of Basic Medical Sciences, Inner Mongolia Minzu University, Tongliao, China.
Shuai ZhangSchool of Basic Medical Sciences, Inner Mongolia Minzu University, Tongliao, China.
Hui WangSchool of Basic Medical Sciences, Inner Mongolia Minzu University, Tongliao, China.
Wanru GengDepartment of Intensive Medicine, Affiliated Hospital of Inner Mongolia Minzu University, Tongliao, China.
Jingbo ZhaiSchool of Basic Medical Sciences, Inner Mongolia Minzu University, Tongliao, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Brucellosis, a zoonotic bacterial infection caused by Objective: To develop a diagnostic method capable of specifically detecting S2 vaccine strain infections. Methods: Two probes were designed targeting single nucleotide polymorphism (SNP) loci upstream of the Results: Both types of methods demonstrated high specificity. However, MGB-SNPdd showed greater sensitivity than other detection methods. Reduction of overlap between the probe sequence and the transient stem-loop structure enhanced detection sensitivity. In the clinical applicability analysis, ddPCR methods exhibited higher rates of S2 vaccine strain detection compared with qPCR methods. Conclusion: SNP-based ddPCR methods demonstrate higher sensitivity than qPCR methods and enable specific detection of brucellosis caused by the S2 vaccine strain. Reduction of probe overlap with the transient stem-loop structure improves detection sensitivity, providing valuable insights for enhanced PCR amplification efficiency.

Indexed as

Brucella suis S2brucellosis diagnosisdigital PCRnucleic acid secondary structureqPCRSNP locus

Identifiers

PMID40612150
PMCPMC12221913

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Registered trials

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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.