Antimicrobial peptide, cLF36, affects performance and intestinal morphology, microflora, junctional proteins, and immune cells in broilers challenged with E. coli
Bibliographic record
Abstract
This study investigated the effects of an antimicrobial peptide (AMP), cLF36, on growth performance and the histophysiological changes of the intestine in E. coli-challenged broiler chickens. A total number of 360 day old male chicks were randomly assigned to 4 groups of 6 replicates as follows: T1) negative control diet based on corn-soybean meal without E. coli challenge and additives; T2) positive control diet based on corn-soybean meal and challenged with E. coli without any additives; T3) positive control diet challenged with E. coli and supplemented with 20 mg AMP (cLF36)/kg diet; T4) positive control diet challenged with E. coli and supplemented with 45 mg antibiotic (bacitracin methylene disalicylate)/kg diet. Results showed that T3 improved growth performance and the jejunal morphology of E. coli-challenged chickens similar to those of T4. While antibiotic non-selectively decreased the population of ileal bacteria, AMP increased the population of Lactobacillus spp. and decreased harmful bacteria in the ileum of E. coli-challenged chickens. Supplementing E. coli-challenged chickens with AMP improved the gene expression of immune cells and upregulated the expression of tight junction proteins compared to other challenged groups. In conclusion, although cLF36 beneficially affected growth performance and the intestinal morphology of E. coli-challenged chickens similar to those of the antibiotic group, this AMP drastically improved the intestinal microbiome, immune cells, and junctional proteins compared to other E. coli-challenged birds, and can be nominated as an alternative for growth promoter antibiotics.
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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".