New Insights into the French Paradox: Free Radical Scavenging by Resveratrol Yields Cardiovascular Protective Metabolites
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Resveratrol was subjected to a diversity-oriented synthesis using oxidative transformations by various biorelevant, biomimetic, or biomimetic-related chemical reagents. Using a combined strategy of ultrahigh-resolution profiling, bioactivity screening, and bioactivity-guided isolation, 19 metabolites were obtained. The compounds were tested for their in vitro enzyme inhibitory activity on angiotensin-1 converting enzyme (ACE), cyclooxygenase-1 and -2, and 15-lipoxygenase (LOX), and evaluated for their relevant drug-like properties in silico . The compounds demonstrated a generally increased cardiovascular protective and anti-inflammatory potential and better drug-likeness compared to resveratrol. Trans -δ-viniferin ( 6 ) was identified as a competitive, C-domain-selective ACE inhibitor that is over 20 times more potent than resveratrol. Further, trans -ε-viniferin ( 2 ) acted as an over 40 times stronger LOX inhibitor than resveratrol. While our results cannot be directly translated to the health benefits of dietary resveratrol consumption without further studies, it is demonstrated that biologically relevant oxidative environments transform resveratrol into potent cardiovascular protective and anti-inflammatory metabolites.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".