Nutritional interventions to modulate immune competence in broilers and correlation to quantitative disease phenotype after Necrotic enteritis challenge
Bibliographic record
Abstract
This study investigated the effect of four different nutritional interventions, applied during the first week of life, on immune competence parameters of broiler chickens. The four (dietary) interventions were antibiotics in the drinking water, 25% inclusion of rye in the feed, beta-glucans from Saccharomyces cerevisiae, and coated butyrate. Broiler chickens (between 1 and 2 weeks of age) were subjected to a Necrotic Enteritis (NE) challenge. A positive and negative control treatment (challenged vs. non-challenged chickens, respectively) was included to estimate the effect of the NE challenge. It was hypothesized that applying a nutritional intervention in the first week of life would affect the microbiota colonization, immune system programming, and consequently the quantitative disease phenotype (lesions scores as a result of the NE challenge). The NE challenge did affect the overall performance during the first 2 weeks post-challenge. The antibiotics group showed significant effects on different biological levels: (temporary) increased performance, deviating microbiota composition, increased gene expression in barrier function processes, whereas decreased gene expression in immune related processes, and a higher villi to crypt ratio compared to the (un)challenged control treatment. In the other treatments only significant differences in bacterial genera were observed. In conclusion, this study has shown that it is probable to disturb the gut system development, whereby giving antibiotics (amoxicillin) gives an effect on multiple biological levels. In addition, the other dietary perturbations, i.e. change in feed composition (25% inclusion of rye), feed additives (beta-glucans or coated butyrate) only affected the microbiota composition to some extent.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".