Staphylococcus aureus Genotypes of Subclinical Bovine Mastitis Milk in the Middle Western Anatolia
Bibliographic record
Abstract
Background: Staphylococcus aureus is the most common etiological pathogen of bovine mastitis. Subclinical mastitis is characterised by a non-alteration of the milk but can cause food poisoning by production of enterotoxins in milk. Knowledge about the genetic variability within different S. aureus populations would help in the design of efficient treatments to prevent subclinical mastitis and provide useful data for epidemiological studies. The aim of this study was to characterize the genetic nature of the S. aureus cultured from subclinical bovine mastitis occurring in 16 farms in the middle western Anatolia. Methods: Two hundred sixty eight milk samples positive with California Mastitis Test (CMT) suggesting the subclinical mastitis of lactating cows in 16 different farms in the Middle Western Anatolia were collected and S. aureus were isolated. Identification was carried out by traditional tests and ribotyping confirmed the identification. Staphylococcal Enterotoxins (SE) were detected and typed by Staphylococcal Enterotoxin Test Reversed Passive Latex Agglutination (SET-RPLA) test kit. Genetic characterisation of the isolates was carried out by both ribotyping and pulsed field gel electrophoresis (PFGE). Results: A total of 77 isolates of S. aureus were purified and analysed by both biochemical identification and genotyping. Only 4 isolates (5.19 %) of S. aureus were recorded as enterotoxin positive. Genetic characterisation of the isolates was carried out by ribotyping revealed eight ribotypes while pulsed field gel electrophoresis (PFGE) was more discriminative representing 19 pulsotypes. Conclusion: This study shows no significant association between enterotoxin production, ribogroup and pulsotype profile of the S. aureus isolates collected from the Middle Western Anatolia.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".