Molecular and Physiological Effects on the Small Intestine of Weaner Pigs Following Feeding with Deoxynivalenol-Contaminated Feed
Bibliographic record
Abstract
We intended to assess how exposure of piglets to deoxynivalenol (DON)-contaminated feed impacted their growth, immune response and gut development. Piglets were fed traditional Phase I, Phase II and Phase III diets with the control group receiving 0.20–0.40 ppm DON (referred to as the Control group) and treatment group receiving much higher level of DON-contaminated wheat (3.30–3.80 ppm; referred to as DON-contaminated group). Feeding a DON-contaminated diet had no impact on average daily feed intake (ADFI) (p < 0.08) or average daily gain (ADG) (p > 0.10) but it did significantly reduce body weight over time relative to the control piglets (p < 0.05). Cytokine analysis after initial exposure to the DON-contaminated feed did not result in significant differences in serum interleukin (IL) IL1β, IL-8, IL-13, tumor necrosis factor (TNF)-α or interferon (IFN)-γ. After day 24, no obvious changes in jejunum or ileum gut morphology, histology or changes in gene expression for IL-1β, IL-6, IL-10, TNFα, or Toll-like receptor (TLR)-4 genes. IL-8 showed a trend towards increased expression in the ileum in DON-fed piglets. A significant increase in gene expression for claudin (CLDN) 7 gene expression and a trend towards increased CLDN 2-expression was observed in the ileum in piglets fed the highly DON-contaminated wheat. Because CLDN localization was not negatively affected, we believe that it is unlikely that gut permeability was affected. Exposure to DON-contaminated feed did not significantly impact weaner piglet performance or gut physiology.
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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) | 0.000 | 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".