Evidence map›Paper›PMID 31119068›Full record

ArticlePeerJ2019

Molecular epidemiology of coagulase-negative

Stephen N Jenkins, Emmanuel Okello, Paul V Rossitto, Terry W Lehenbauer, John Champagne, Maria C T Penedo, Andréia G Arruda, Sandra Godden, Paul Rapnicki, Patrick J Gorden and 2 more

Abstract read
In one paragraph

Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Staphylococcal mastitis in dairy cows.Frontiers in veterinary science · 2024
    Review
  10. Virulence Mechanisms of Staphylococcal Animal Pathogens.International journal of molecular sciences · 2023
    Review
  11. Article
  12. Comparative Genomics ofVeterinary sciences · 2023
    Article
  13. Review
  14. Article
  15. Article
  16. Molecular epidemiology and characterization of antimicrobial-resistantFrontiers in cellular and infection microbiology · 2023
    Article
  17. Article
  18. Genotypic characterization ofVeterinary world · 2022
    Article
  19. Article
  20. Review
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

12 authors.

Stephen N JenkinsVeterinary Medicine Teaching and Research Center, School of Veterinary Medicine, University of California, Davis, Tulare, CA, United States of America.
Emmanuel OkelloVeterinary Medicine Teaching and Research Center, School of Veterinary Medicine, University of California, Davis, Tulare, CA, United States of America.
Paul V RossittoVeterinary Medicine Teaching and Research Center, School of Veterinary Medicine, University of California, Davis, Tulare, CA, United States of America.
Terry W LehenbauerVeterinary Medicine Teaching and Research Center, School of Veterinary Medicine, University of California, Davis, Tulare, CA, United States of America.
John ChampagneVeterinary Medicine Teaching and Research Center, School of Veterinary Medicine, University of California, Davis, Tulare, CA, United States of America.
Maria C T PenedoVeterinary Genetics Laboratory, University of California, Davis, CA, United States of America.
Andréia G ArrudaDepartment of Veterinary Preventive Medicine, College of Veterinary Medicine, The Ohio State University, Columbus, OH, United States of America.
Sandra GoddenDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States of America.
Paul RapnickiDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States of America.
Patrick J GordenVeterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States of America.
Leo L TimmsDepartment of Animal Science, College of Agriculture and Life Sciences, Iowa State University, Ames, IA, United States of America.
Sharif S AlyVeterinary Medicine Teaching and Research Center, School of Veterinary Medicine, University of California, Davis, Tulare, CA, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoagulase negative METHODOLOGY: A total of 604 CNS isolates were cultured from milk samples collected during a dry-cow treatment clinical trial conducted on 6 dairy herds in 4 states in the US. All the study cows were randomized to receive 1 of the 3 different intra-mammary antimicrobial infusions (Quatermaster, Spectramast DC or ToMorrow Dry Cow) at dry-off. Milk samples were collected at dry-off, calving (0-6 days in milk, DIM), post-calving (7-13 DIM) and at mastitis events within the first 100 DIM. The CNS isolates were identified to species level by partial sequencing of the

resultsThe major CNS species identified were DISCUSSION: The observed association between genetic and epidemiological distributions indicated animal-adapted nature of four CNS species, suggesting possible host-adapted and environmental transmission of these species. Multi-stage isolation of the same udder quarter strain was evidence for chronic intra-mammary infection.

conclusionThe different CNS species and strains circulating on US dairy herds were genetically diverse. Four species identified were likely udder-adapted pathogens, 2 of which caused persistent infection. Our findings are important in guiding the design of effective mastitis control strategies.

Indexed as

Coagulase negative Staphylococcus (CNS)EpidemiologyGenetic relatednessMastitis pathogensPhylogenyPulse-field gel electrophoresis (PFGE)

Identifiers

PMID31119068
PMCPMC6507897

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.