Evidence map›Paper›PMID 41767673›Full record

ArticleFrontiers in veterinary science2026

Distribution and antimicrobial resistance profiles of vaginal bacteria in healthy dairy cows.

Brandi M Macleod, Theodoros Ntallaris, Jane M Morrell, Ingrid Hansson, Csaba Varga

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Brandi M Macleod *College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, United States.
Theodoros Ntallaris *Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Jane M MorrellDepartment of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Ingrid HanssonDepartment of Animal Biosciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Csaba VargaDepartment of Pathobiology, College of Veterinary Medicine, University of Illinois Urbana-Champaign, Urbana, IL, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Evaluating the vaginal bacterial isolates of dairy cows and their antimicrobial resistance patterns can improve animal health management practices and reduce the risk of transmitting antimicrobial-resistant pathogens within animal populations and from animals to humans. Materials and methods: This study characterized the culturable bacterial composition and antimicrobial resistance (AMR) profiles of vaginal bacteria isolated from healthy dairy cows at the Swedish Livestock Research Centre, Lövsta, Sweden. Unsupervised machine learning techniques, including Partitioning Around Medoids clustering and co-occurrence network analysis, investigated bacterial co-occurrences in the vaginal microbiota. Bacterial isolates were classified as resistant or wild type based on the epidemiological breakpoint values for inhibition zone diameters in the disk diffusion method defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST). Results: A total of 127 bacterial isolates representing 34 different species were isolated from the samples collected from the anterior vagina of 40 cows. Conclusion: Our study highlights the importance of including commensal reproductive tract bacteria in AMR monitoring programs, as these species may serve as reservoirs of resistance genes and contribute to the spread of AMR within dairy herds.

Indexed as

antimicrobial resistanceclusteringdairy cowsmicrobiotavaginal bacteria

Identifiers

PMID41767673
PMCPMC12945782

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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.