Detection and quantification of methicillin-resistant Staphylococcus aureus (MRSA) clones in retail meat products
Bibliographic record
Abstract
AIMS: The objective of the study was to determine the prevalence of methicillin-resistant Staphylococcus aureus (MRSA) contamination of retail meat and to determine the level of contamination. METHODS AND RESULTS: Pork (pork chops and ground pork), ground beef and chicken (legs, wings and thighs) were purchased at retail outlets in four Canadian provinces and tested for the presence of methicillin-resistant Staph. aureus using qualitative and quantitative methods. MRSA was isolated from 9.6% of pork, 5.6% of beef and 1.2% of chicken samples (P = 0.0002). Low levels of MRSA were typically present, with 37% below the detection threshold for quantification and <100 CFU g(-1) present in most quantifiable samples. All isolates were classified as Canadian epidemic MRSA-2 (CMRSA-2) by pulsed field gel electrophoresis (PFGE), with two different PFGE subtypes, and were spa type 24/t242. CONCLUSIONS: MRSA contamination of retail meat is not uncommon. While CMRSA-2, a human epidemic clone, has been found in pigs in Canada, the lack of isolation of livestock-associated ST398 was surprising. SIGNIFICANCE AND IMPACT OF THE STUDY: The relevance of MRSA contamination of meat is unclear but investigation is required because of the potential for exposure from food handling. Sources of contamination require investigation because these results suggest that human or animal sources could be involved.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".