Phenolics from Winemaking By‐Products Better Decrease VLDL‐Cholesterol and Triacylglycerol Levels than Those of Red Wine in Wistar Rats
Bibliographic record
Abstract
Winemaking by-products account for more than 30% of the grape production, but this inexpensive feedstock has not yet been fully exploited. Accordingly, we evaluated the potential biological activity of winemaking by-products produced with Syrah grapes in comparison with those of the wine produced using the same grape cultivar. Winemaking by-products showed higher contents of total anthocyanins, flavonols, stilbenes, and flavanols than red wine as evaluated by HPLC-DAD-FD (on a dry weight basis). In contrast, red wine was a better source of phenolic acids. However, the contribution of phenolic acids was minor for both samples. Furthermore, equivalent concentration of winemaking by-products (100 mg/kg/d) showed greater biological activity by than that of red wine by decreasing the levels of VLDL-cholesterol and triacylglycerols in Wistar rats. Therefore, this study supports the use of winemaking by-products as an economical source of bioactive phenolics with potential use in the food and nutraceutical industries.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".