Bioavailability of anthocyanidin-3-glucosides following consumption of red wine and red grape juice
Bibliographic record
Abstract
Pharmacokinetic parameters and the bioavailability of several dietary anthocyanins following consumption of red wine and red grape juice were compared in nine healthy volunteers. They were given a single oral dose of either 400 mL of red wine (279.6 mg total anthocyanins) or 400 mL of red grape juice (283.5 mg total anthocyanins). Within 7 h, the urinary excretion of total anthocyanins was 0.23 and 0.18% of the administered dose following red grape juice and red wine ingestion, respectively. Pharmacokinetic parameters derived from plasma and urine concentrations exhibited higher variability after ingestion of red grape juice. Compared to red grape juice anthocyanins, the relative bioavailability of red wine anthocyanins was calculated to be 65.7, 61.3, 61.9, 291.5, 57.1, and 76.3% for the glucosides of cyanidin, delphinidin, malvidin, peonidin, petunidin, and its sum (referred to as total anthocyanins), respectively. Bioequivalence was established for none of the anthocyanins. On a low level, urinary excretion of anthocyanins was fast, and the excretion rates seem to exhibit monoexponential characteristics over time after ingestion of both red grape juice and red wine. Due to low bioavailability, any significant contribution of anthocyanins to health protecting properties of red wine or red grape juice seems questionable, but the clinical relevance of these findings awaits further investigation.
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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 | 0.001 |
| 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 | 0.000 |
| 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".