Lipophilization of Resveratrol and Effects on Antioxidant Activities
Bibliographic record
Abstract
Resveratrol (R), a polyphenol, was structurally modified via esterification with selected fatty acids to expand its potential application in lipophilic foods, drugs, and cosmetics. The esterification was carried out using 12 different fatty acids with varying chain lengths and degrees of unsaturation (C3:0-C22:6). Two monoesters, two diesters, and one triester were identified by high-performance liquid chromatography-mass spectrometry, and the monoesters (R-3-O-monodocosahexaenoate and R-4'-O-monodocosahexaenoate) were structurally confirmed by nuclear magnetic resonance. The lipophilicity of resveratrol and its alkyl esters was calculated using ALOGPS 2.1. Resveratrol exhibited greater antioxidant activity in both 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical cation scavenging assays. Resveratrol esters with long-chain fatty acids (C18:0 and C18:1) showed higher antioxidant activity in the DPPH radical scavenging assay, whereas short-chain fatty acid (C3:0, C4:0, and C6:0) showed higher antioxidant activity in the ABTS radical cation scavenging assay. The results may imply that resveratrol derivatives could be used in lipophilic media as health beneficial antioxidants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".