In vivo therapeutic efficacy and pharmacokinetics of colistin sulfate in an experimental model of enterotoxigenic Escherichia coli infection in weaned pigs
Bibliographic record
Abstract
Enterotoxigenic Escherichia coli (ETEC: F4) associated with post-weaning diarrhea (PWD) in pigs has developed resistance against several antimicrobial families, leading to increased use of colistin sulfate (CS) for the treatment of this disease. The objective of this study was to determine the efficacy of oral CS treatment in experimental PWD due to ETEC: F4 challenge and determine the effect of this challenge on CS intestinal absorption. In this study, 96 pigs were divided into two trials based on CS dose (100 000 or 50 000 IU/kg). Fecal shedding of ETEC: F4, total E. coli, and CS-resistant E. coli, diarrhea scores, and weight changes were evaluated. Colistin sulfate plasma concentrations were determined by HPLC-MS/MS. Regardless of the dose, CS treatment resulted in a reduction of fecal ETEC: F4 and total E. coli shedding, and in diarrhea scores but only during the treatment period. However, CS treatment resulted in a slight increase in fecal shedding of CS resistant E. coli and did not prevent weight loss in challenged pigs. In addition, challenge with ETEC: F4 resulted in an increase of CS intestinal absorption. Our study is among the first to demonstrate that under controlled conditions, CS was effective in reducing fecal shedding of ETEC: F4 and total E. coli in experimental PWD. However, CS treatment was associated with a slight selection pressure on E. coli and did not prevent pig weight loss. Further studies are needed in field conditions, to better characterize CS therapeutic regimen efficacy and bacterial resistance dissemination.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".