Impact of Capsaicinoid Supplementation in Health and Performance of Broiler Chickens Subjected to Lipopolysaccharide Challenge
Bibliographic record
Abstract
This study investigated the effects of dietary capsaicinoid (CAP) supplementation on broiler chickens subjected to an inflammatory challenge induced by lipopolysaccharide (LPS). A total of 144 Cobb500™ male broilers (Rivelli Alimentos SA, Matheus Leme, Brazil), raised from 1 to 21 days, were randomly assigned to three treatments, with eight replicates of six birds. Treatments were a control diet (CON), a control diet with LPS administration (CON+LPS), and a control diet supplemented with 1 mg CAP/kg feed and LPS (CAP+LPS). LPS was administered intraperitoneally on days 14, 16, 18, and 20. Performance, intestinal morphometry, serum metabolites, and jejunal gene expression related to oxidative and inflammatory responses were evaluated. Slaughter was at 20 days. Data were subjected to ANOVA and means compared by Tukey’s test at 0.05 significance. CON broilers exhibited the highest feed intake and a better feed conversion ratio (p < 0.05) compared to CON+LPS. CAP+LPS broilers showed higher body weight gain than CON+LPS but lower than CON broilers (p < 0.001). CON+LPS broilers had the highest crypt depth (p = 0.002). Higher mRNA expression of superoxide dismutase and catalase (p > 0.05) was observed in CON broilers. In conclusion, supplementation with a 1 mg CAP/kg diet improves the growth performance and intestinal morphometry of LPS-challenged broiler chickens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".