Administration of probiotics influences F4 (K88)-positive enterotoxigenic Escherichia coli attachment and intestinal cytokine expression in weaned pigs
Bibliographic record
Abstract
This study evaluated the effect of the probiotics Pediococcus acidilactici and Saccharomyces cerevisiae boulardii on the intestinal colonization of O149 enterotoxigenic Escherichia coli harbouring the F4 (K88) fimbriae (ETEC F4) and on the expression of ileal cytokines in weaned pigs. At birth, different litters of pigs were randomly assigned to one of the following treatments: 1) control without antibiotics or probiotics (CTRL); 2) reference group in which chlortetracycline and tiamulin were added to weanling feed (ATB); 3) P. acidilactici; 4) S. cerevisiae boulardii; or 5) P. acidilactici + S. cerevisiae boulardii. Probiotics were administered daily (1 × 10(9) CFU per pig) during the lactation period and after weaning (day 21). At 28 days of age, all pigs were orally challenged with an ETEC F4 strain, and a necropsy was performed 24 h later. Intestinal segments were collected to evaluate bacterial colonization in the small intestine and ileal cytokine expressions. Attachment of ETEC F4 to the intestinal mucosa was significantly reduced in pigs treated with P. acidilactici or S. cerevisiae boulardii in comparison with the ATB group (P = 0.01 and P = 0.03, respectively). In addition, proinflammatory cytokines, such as IL-6, were upregulated in ETEC F4 challenged pigs treated with P. acidilactici alone or in combination with S. cerevisiae boulardii compared with the CTRL group. In conclusion, the administration of P. acidilactici or S. cerevisiae boulardii was effective in reducing ETEC F4 attachment to the ileal mucosa, whereas the presence of P. acidilactici was required to modulate the expression of intestinal inflammatory cytokines in pigs challenged with ETEC F4.
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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".