Feed supplementation with winery by-products improves the physiological status of juvenile Liza aurata during a short-term feeding trial and hypoxic challenge
Bibliographic record
Abstract
The search of bioactive compounds obtained from natural sources with beneficial effects in growth and health is an increasing trend in aquaculture. Wine by-products are an excellent source of such compounds, mostly phenolics, with demonstrated antioxidant and immunostimulant activities in vertebrates. The present study evaluated the effects of dietary inclusion (100 g/kg) of two wine by-products (grape pomace and lees) on growth, immune status and metabolism of juvenile golden gray mullet (Liza aurata), as well as the potential protective effect of compounds present in the two by products against induced stress produced by moderate hypoxia. Results evidenced a significant positive effect of grape pomace on feed efficiency, as well as in different indicators of metabolic and immunological status of the fish. Also, a significant negative effect of wine lees on the functional diversity of intestinal microbiota was evidenced. Fish fed on diets containing any of the two by-products evidenced significantly lower levels of cortisol when challenged by hypoxia, this pointing to a protective effect mediated by their contents in phenolic compounds and suggesting an interesting and practical application for these agricultural by-products.
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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) | 0.001 | 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".