Response of Nursery Pigs to a Synbiotic Preparation of Starch and an Anti-<i>Escherichia coli</i>K88 Probiotic
Bibliographic record
Abstract
Postweaning diarrhea in pigs is frequently caused by enterotoxigenic Escherichia coli K88 (ETEC). The aim of this study was to test the efficacy of E. coli probiotics (PRO) in young pigs challenged with E. coli K88. We also tested the synbiotic interaction with raw potato starch (RPS), which can be used as a prebiotic. Forty 17-day-old weaned piglets were randomly assigned to four treatments: treatment 1, positive-control diet (C), no probiotics or RPS but containing in-feed antibiotics; treatment 2, probiotic (PRO), no feed antibiotics plus a 50:50 mixture of probiotic E. coli strains UM-2 and UM-7; treatment 3, 14% RPS, no antibiotics (RPS); treatment 4, 14% RPS plus a 50:50 mixture of probiotic E. coli strains UM-2 and UM-7, no antibiotics (PRO-RPS). The pigs were challenged with pathogenic E. coli K88 strains on day 7 of the experiment (24-day-old pigs) and euthanized on day 10 of the experiment (35-day-old pigs). Probiotic and pathogenic E. coli strains were enumerated by selective enrichment on antibiotics, and microbial community analysis was conducted using terminal restriction length polymorphism analysis (T-RFLP) of 16S rRNA genes. The combination of raw potato starch and the probiotic had a beneficial effect on piglet growth performance and resulted in a reduction of diarrhea and increased microbial diversity in the gut. We conclude that the use of E. coli probiotic strains against E. coli K88 in the presence of raw potato starch is effective in reducing the negative effects of ETEC in a piglet challenge model.
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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) | 0.001 | 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".