Mutant prevention and minimum inhibitory concentration drug values for enrofloxacin, ceftiofur, florfenicol, tilmicosin and tulathromycin tested against swine pathogens Actinobacillus pleuropneumoniae, Pasteurella multocida and Streptococcus suis
Bibliographic record
Abstract
Actinobacillus pleuropneumoniae, Pasteurella multocida and Streptococcus suis are prevalent bacterial causes of swine infections. Morbidity, mortality and positively impacting the financial burden of infection occurs with appropriate antimicrobial therapy. Increasing antimicrobial resistance complicates drug therapy and resistance prevention is now a necessity to optimize therapy and prolong drug life. Mutant bacterial cells are said to arise spontaneously in bacterial densities of 107-109 or greater colony forming units/ml. Antibiotic drug concentration inhibiting growth of the least susceptible cell in these high density populations has been termed the mutant prevention concentration (MPC). In this study MPC and minimum inhibitory concentration (MIC) values of ceftiofur, enrofloxacin, florfenicol, tilmicosin and tulathromycin were determined against the swine pathogens A. pleuropneumoniae, P.multocida and S. suis. The following MIC90/MPC90 values (mg/L) for 67 A. pleuropneumoniae and 73 P. multocida strains respectively were as follows: A. pleuropneumoniae 0.031/0.5, ≤0.016/0.5, 0.5/2, 4/32, 2/32; P. multocida 0.004/0.25, 0.016/0.125, 0.5/0.5, 8/16, 0.5/1. For 33 S. suis strains, MIC90 values (mg/L) respectively were as follows: 1, 0.25, 4, ≥8 and ≥8. A total of 16 S. suis strains with MIC values of 0.063-0.5 mg/L to ceftiofur and 0.25-0.5 mg/L to enrofloxacin were tested by MPC; MPC values respectively were 0.5 and 1 mg/L respectively. MPC concentrations provide a dosing target which may serve to reduce amplification of bacterial subpopulations with reduced antimicrobial susceptibility. Drug potency based on MIC90 values was ceftiofur > enrofloxacin >florfenicol = tulathromycin > tilmicosin; based on MPC90 values was enrofloxacin > ceftiofur > tulathromycin > florfenicol ≥ tilmicosin.
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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 | 0.000 |
| 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".