Evidence map›Paper›PMID 22125606›Full record

ArticlePloS one2011

The prevalences of Salmonella Genomic Island 1 variants in human and animal Salmonella Typhimurium DT104 are distinguishable using a Bayesian approach.

Alison E Mather, Matthew J Denwood, Daniel T Haydon, Louise Matthews, Dominic J Mellor, John E Coia, Derek J Brown, Stuart W J Reid

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.3field-weighted citation impact, top 13% of its field
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

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Ceftiofur-resistantEpidemiology and infection · 2019
    Review
  4. Article
  5. Antimicrobial usage and resistance in beef production.Journal of animal science and biotechnology · 2016
    Review
  6. 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 at 3 institutions in 1 country.

Alison E MatherBoyd Orr Centre for Population and Ecosystem Health, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom.
Matthew J Denwood
Daniel T Haydon
Louise Matthews
Dominic J Mellor
John E Coia
Derek J Brown
Stuart W J Reid
University of Glasgow · GBStobhill Hospital · GBGlasgow Centre for Population Health · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Throughout the 1990 s, there was an epidemic of multidrug resistant Salmonella Typhimurium DT104 in both animals and humans in Scotland. The use of antimicrobials in agriculture is often cited as a major source of antimicrobial resistance in pathogenic bacteria of humans, suggesting that DT104 in animals and humans should demonstrate similar prevalences of resistance determinants. Until very recently, only the application of molecular methods would allow such a comparison and our understanding has been hindered by the fact that surveillance data are primarily phenotypic in nature. Here, using large scale surveillance datasets and a novel Bayesian approach, we infer and compare the prevalence of Salmonella Genomic Island 1 (SGI1), SGI1 variants, and resistance determinants independent of SGI1 in animal and human DT104 isolates from such phenotypic data. We demonstrate differences in the prevalences of SGI1, SGI1-B, SGI1-C, absence of SGI1, and tetracycline resistance determinants independent of SGI1 between these human and animal populations, a finding that challenges established tenets that DT104 in domestic animals and humans are from the same well-mixed microbial population.

Indexed as

Bayes TheoremAnimalsAnti-Bacterial AgentsDrug Resistance, Multiple, BacterialGene FrequencyGenetic VariationGenomic IslandsHumansMarkov ChainsMonte Carlo MethodSalmonella InfectionsSalmonella Infections, AnimalSalmonella typhimuriumSpecies SpecificityAnti-Bacterial Agents

Identifiers

PMID22125606
PMCPMC3220677
OpenAlexW2065925101

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.