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Record W2906133922 · doi:10.3168/jds.2018-15136

Molecular epidemiology and distribution of antimicrobial resistance genes of Staphylococcus species isolated from Chinese dairy cows with clinical mastitis

2018· article· en· W2906133922 on OpenAlexaff
Yue Qu, Huanan Zhao, Diego B. Nóbrega, Eduardo R. Cobo, Bo Han, Zhonghua Zhao, Shumei Li, Mengyue Li, Herman W. Barkema, Jian Gao

Bibliographic record

VenueJournal of Dairy Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMastitisStaphylococcus aureusBiologyMicrobiologyAntibiotic resistanceStaphylococcus epidermidisStaphylococcusSCCmecGenotypeRAPDVeterinary medicineAntibioticsMethicillin-resistant Staphylococcus aureusGenetic diversityBacteriaGeneticsGeneMedicinePopulation

Abstract

fetched live from OpenAlex

Staphylococcus species, categorized into Staphylococcus aureus and non-aureus staphylococci (NAS), are frequent causes of mastitis in dairy cattle around the world. Current treatments using antimicrobials are under increasing scrutiny due to rising prevalence of multi-drug resistance in S. aureus. Objectives of this study were to determine: (1) genetic diversity of Staphylococcus species isolated from clinical mastitis in cows from large Chinese dairy farms; and (2) prevalence and distribution of antimicrobial resistance genes (ARG) in these isolates. Staphylococcus aureus (n = 96) were isolated from 26 herds located in 12 provinces of China, whereas NAS (n = 112) were isolated from 59 herds located in 18 provinces of China. The NAS were identified at the species level using a partial 16S rRNA sequencing method, whereas random amplification of polymorphic DNA (RAPD) PCR was done to determine genetic relationships of isolates. Finally, PCR was used to detect resistance and biofilm formation genes. Staphylococcus chromogenes (33%) was the most common NAS species, followed by Staphylococcus sciuri (17%) and Staphylococcus epidermidis (8%). Staphylococcus aureus was grouped in 12 genotypes, of which 2 types represented 56% of isolates. Staphylococcus chromogenes (n = 37) clustered into 8 RAPD types, with 2 prevalent types containing 73% of isolates. The most prevalent ARG in S. aureus isolates was blaZ (95%), followed by tetM (33%), tetK (31%), ermT (26%), and aacA-aphD (23%). The mecA and vanA were detected in 16 and 4% of isolates, respectively. In NAS, blaZ (100%), mecA (73%), tetK (79%), tetM (96%), mphC (63%), and msrA (54%) were frequently detected. Antimicrobial resistance genes mecA, tetK, tetL, tetM, dfrG, ermB, msrA, mphC, aadD, and aphA3 were more commonly detected in NAS than in S. aureus. Biofilm formation genes (icaA and icaD) were frequently detected in staphylococci isolated from bovine clinical mastitis. The existence of predominant RAPD types in S. aureus and S. chromogenes isolates across Chinese dairy farms indicated that specific genotypes had disseminated within herds and become more udder-adapted. High prevalence of ARG, especially in NAS, highlighted the risk of selection of multi-drug resistant staphylococci with potential as a reservoir of ARG.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.630
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.293
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations68
Published2018
Admission routes1
Has abstractyes

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