Effects of fatty acid glyceride product SILOhealth 104 on the growth performance and carcass composition of broiler chickens
Bibliographic record
Abstract
Butyric acid is the primary energy source for colonocytes, and has shown potential as an alternative to in-feed antibiotics, due to its antimicrobial activity and positive effects on production performance traits of broiler chickens. SILOhealth 104 (SILO S.P.A., Florence, Italy) is a commercial product mainly containing mono- and di-glycerides of butyrate with a small portion of propionic, caprylic, capric, and lauric acid mono- and di-glycerides. Its effects on broiler performance and carcass composition have yet to be evaluated. Four-hundred-eighty day-old male Ross 308 birds were divided into different dietary treatment groups with equal starting weights and fed a diet containing 0, 500, 1,000, 2,000, or 3,000 ppm of SILOhealth 104 for 35 days. There were no significant differences in overall average daily gain or feed: gain ratio with the addition of SILOhealth 104 to the diets (P > 0.05). At 5 wk of age, abdominal fat weight was reduced in birds supplemented with SILOhealth 104 in a dose-responsive manner (P < 0.05), while breast muscle weight increased with supplementation, with significant increases in 2,000 ppm and 3,000 ppm birds compared to controls (P < 0.05). A significant reduction in gene expression of both forkhead box protein O4 and myostatin, 2 factors that can inhibit protein synthesis, was found in the breast muscle of all SILOhealth 104 treated birds (P < 0.05). In addition, gene expression in the adipose tissue, including acetyl-CoA carboxylase alpha and lipoprotein lipase, which are associated with lipid metabolism, was significantly decreased and increased, respectively, by the supplementation of SILOhealth 104 (P < 0.05). These data suggest that the components of SILOhealth 104 can positively affect the deposition of muscle, while reducing abdominal fat deposition in broiler chickens.
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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) | 0.001 | 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".