Impacts of colistin sulfate on fecal Escherichia coli resistance and on growth performance of piglets in a post-weaning diarrhea model
Bibliographic record
Abstract
Colistin sulfate (CS) is used in Canada for the treatment of post weaning diarrhea (PWD), to overcome conventional therapeutic antibiotics failures.The aim of the present study was to determine the effect of a conventional oral regimen of CS for the treatment of PWD, on the development of E. coli CS resistance and to evaluate the effect of ETEC: F4 infection on CS intestinal absorption.A total of 48 pigs were used, challenge was carried out by oral administration of 10 9 CFU of a hemolytic ETEC: F4 strain resistant to nalidixic acid.CS was administered at a dose of 50.000UI/kg twice a day for 5 days.Feces were examined clinically and bacteriologically before and after challenge to evaluate presence of diarrhea and E. coli fecal excretion.ETEC: F4 virulence factors were monitored and CS plasma concentrations were quantified by an HPLC-MS/MS.From one until six days after CS administration, a significant reduction in the fecal excretion of ETEC: F4, total E. coli, ETEC: F4 virulence factors and in diarrhea scores was observed in the challenged treated group compared to the challenged untreated group (p<0.0001).No significant difference in growth performances was observed in treated compared to non-treated pigs (p>0.71).A significant selection pressure on E. coli total population was observed following CS treatment (p<0.0001).Challenge with ETEC: F4 resulted in an increase in intestinal absorption of CS.Our study is the first to demonstrate in an experimental model of PWD, that CS at a dose of 50,000 IU/kg is effective in reducing fecal excretion of E. coli.However, this regimen was associated with a selection pressure on E. coli CS resistance, and did not improve growth performance in challenged pigs.Thus, the use of this antibiotic in pig should be revised.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 | 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".