Characteristics of Escherichia coli Isolated from Bovine Mastitis Exposed to Subminimum Inhibitory Concentrations of Cefalotin or Ceftazidime
Bibliographic record
Abstract
Escherichia coli is a major udder pathogen causing clinical mastitis in dairy cattle and its heat stable endotoxin in powdered infant formula milk is a potential risk factor in neonatal infections. Cephalosporins are frequently used for treatment of mastitis caused by mastitis; however, use of these antimicrobials may induce antimicrobial resistance in E. coli. The objective of this study was to explore the in vitro effect of subminimum inhibitory concentrations (sub-MIC) of cefalotin (CF) and ceftazidime (CAZ) on the morphology, antimicrobial resistance, and endotoxin releasing characteristics of 3 E. coli isolates recovered from bovine clinical mastitis. The parent E. coli isolates, which were susceptible to CF and CAZ, were exposed to CF or CAZ separately at sub-MIC levels to produce 9 generations of induced isolates. Colonies of the CAZ-induced isolates from all 3 parent E. coli were smaller on blood agar and the bacteria became filamentous, whereas the CF-induced isolates did not demonstrate prominent morphological changes. After induction by CF or CAZ, many induced isolates showed resistance to cefoxitin, CAZ, CF, kanamycin, ampicillin, and amoxicillin/clavulanic acid while their parent isolates were susceptible to these antimicrobials. Notably, 5 CAZ-induced isolates from the same parent isolate were found to produce extended-spectrum beta-lactamase (ESBL) though none of the tested ESBL related genes could be detected. All CAZ-induced isolates released more endotoxin with a higher release rate, whereas endotoxin release of CF-induced E. coli isolates was not different from parent isolates. The exposure of cephalosporins at sub-MIC levels induced resistant Escherichia coli. We inferred that cephalosporins, especially CAZ, should be used prudently for treatment of clinical E. coli mastitis.
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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 | 0.000 | 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".