Epidemiology and molecular characterization of Staphylococcus aureus causing bovine mastitis in water buffaloes from the Hazara division of Khyber Pakhtunkhwa, Pakistan
Bibliographic record
Abstract
Buffalo represent a major source of milk in Pakistan. However, production is impacted by the disease bovine mastitis. Mastitis causes significant economic losses, with Staphylococcus aureus (S. aureus) being one of its major causative agents. While much work has been done understanding the epidemiology of bovine mastitis in Pakistan, detailed molecular characterization of the associated S. aureus is unavailable. In the current study both the epidemiological and molecular characterization of S. aureus from bovine mastitis in the Hazara division of Pakistan are examined. S. aureus was isolated from 18.41% of the animals, and left quarters more prone to infection (69.6%) than right quarters (30.4%). Sub-clinical mastitis (75.31%) was more prevalent than clinical mastitis (24.69%), with infections evenly distributed amongst the eight districts. Molecular characterization revealed that only 19.6% of the isolates were methicillin-resistant, and four strains types identified, including ST9-t7867-MSSA, ST9-MSSA, ST101-t2078-MSSA, and ST22-t8934-MRSA-IVa. Antiseptic resistance genes were not detected in the isolates, and low levels of antibiotic resistance were also noted, however the methicillin-resistant strains had higher overall antibiotic resistance. This study represents the most complete molecular typing data for S. aureus causing bovine mastitis in the Hazara district of Pakistan, and the country as a whole.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".