Biofilm Formation in Dairy: A Food Safety Concern—Effect of biofilm production on antimicrobial susceptibility of Staphylococcus aureus bovine mastitis strains from the most prevalent Canadian spa types
Bibliographic record
Abstract
Staphylococcus aureus intramammary infections often leads to clinical and subclinical mastitis in dairy cattle. Prediction of disease evolution and treatment efficacy based on the characteristics of disease-causing strains of S. aureus would significantly improve management of dairy herds. To study the effect of biofilm production and the influence of genetic lineage, we selected S. aureus isolates from the most prevalent Canadian spa types associated with bovine mastitis. Antimicrobial susceptibility in planktonic growth and for bacteria embedded in biofilm was compared. PCR was used to detect the bap gene responsible for atypical biofilm formation. All Canadian spa types from dairy cattle were susceptible to the 8 antimicrobial agents tested. Only strain sa3493 from spa type t267 showed a resistance to pirlimycin. However, bacteria producing larger amounts of biofilms better survived the bactericidal action of antimicrobial agents even when exposed to concentrations 64 folds higher than the minimal inhibitory concentration determined for planktonic cultures. Pirlimycin was more effective on bacteria producing low to moderate levels of biofilm compared with vancomycin or ceftiofur. Antimicrobial agents did not affect the viability of spa types t13401 and t605 that were high biofilm producers. Although both these spa types produced high amounts of biofilm, only t605 possessed the bap gene. We also found a close relationship between DIM at sampling and the presence of spa type t605 isolates. These results suggest that detection of S. aureus spa type may help predict the effectiveness of antimicrobial therapy and that some spa types are more likely to be retrieved toward the end of the lactation.
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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 | 0.000 | 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".