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Record W2909466667 · doi:10.3168/jds.2018-15135

Antimicrobial resistance profiles of 5 common bovine mastitis pathogens in large Chinese dairy herds

2019· article· en· W2909466667 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Dairy Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversity of Calgary
FundersNational Natural Science Foundation of China
KeywordsEnrofloxacinTetracyclineMastitisMicrobiologyPenicillinClindamycinAmoxicillinAntibiotic resistanceStaphylococcus aureusBiologyBroth microdilutionStreptococcus agalactiaeKlebsiellaMultiple drug resistanceAntimicrobialVeterinary medicineAntibioticsStreptococcusMedicineMinimum inhibitory concentrationBacteriaEscherichia coliCiprofloxacin

Abstract

fetched live from OpenAlex

The prevalence of antimicrobial resistance (AMR) is increasing in human and animal pathogens, becoming a concern worldwide. However, prevalence and characteristics of AMR of bovine mastitis pathogens in large Chinese dairy herds are still unclear. Therefore, our objective was to determine the AMR profile of bacteria isolated from clinical mastitis in large (>500 cows) Chinese dairy herds. A total of 541 isolates of the 5 most common species, Staphylococcus aureus (n = 103), non-aureus staphylococci (NAS; n = 107), Streptococcus species (n = 101), Klebsiella species (n = 130), and Escherichia coli (n = 100), isolated from bovine clinical mastitis on 45 dairy farms located in 10 provinces of China were included. Presence of AMR was determined by minimum inhibitory concentrations using the microdilution method. Prevalence of multidrug resistance (resistance to >2 antimicrobials) was 27% (148/541). A very wide distribution of minimum inhibitory concentrations was screened in all isolates, including Staph. aureus isolates, which were resistant to penicillin (66%). In addition, NAS (30%) were more resistant than Staph. aureus to oxacillin (84%), penicillin (62%), tetracycline (34%), and clindamycin (33%). Prevalence of resistance to tetracycline was high (59%) in Streptococcus spp. Additionally, prevalence of resistance of both E. coli and Klebsiella spp. was high to amoxicillin/clavulanate potassium (81 and 38%, respectively), followed by tetracycline (only Klebsiella spp. 32%). A high proportion (27%) of isolates were multidrug resistant; the most frequent combinations were clindamycin-cefalexin-tetracycline or enrofloxacin-cefalexin-penicillin patterns for Staph. aureus; enrofloxacin-oxacillin-penicillin-tetracycline patterns for NAS; clindamycin-enrofloxacin-tetracycline patterns for Streptococcus spp.; amoxicillin/clavulanate potassium-ceftiofur-polymyxin B patterns for Klebsiella spp.; and amoxicillin/clavulanate potassium-ceftiofur-polymyxin B patterns for E. coli. Resistance for 4 kinds of antimicrobials highly critical for human medicine, including daptomycin, vancomycin, imipenem, and polymyxin B, ranged from 0 to 24%. In conclusion, prevalence of AMR in mastitis pathogens was high on large Chinese dairy farms, potentially jeopardizing both antimicrobial efficacy and public health. Results of this study highlighted the need for improvements in antimicrobial stewardship and infection control programs in large Chinese dairy farms to reduce emergence of AMR.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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