Antioxidant activity of monooleyl and dioleyl <i>p</i>‐coumarates in in vitro and biological model systems
Bibliographic record
Abstract
Lipase‐catalysed acidolysis of p‐coumaric acid with triolein was carried out, followed by separation of the synthesized phenolipids using column chromatography. The identification of synthesized phenolipids was conducted by using HPLC–MS. The antioxidant activities of the purified phenolipids were assessed in in vitro assays and biological systems. Monooleyl and dioleyl p‐coumarates were identified as the phenolipid species present. The prepared phenolipids exhibited varying antioxidant activities in 1,1‐diphenyl‐2‐picrylhydrazyl (DPPH) and peroxyl radical scavenging, reducing power, β‐carotene/linoleate bleaching, human low‐density lipoprotein (LDL) cholesterol oxidation as well as hydroxyl and peroxyl radical‐induced DNA cleavage assays. Practical applications: In this study, the antioxidant activity of synthesized phenolipids, monooleyl and dioleyl p‐coumarates obtained from p‐coumaric acid and triolein, was investigated and confirmed in a number of commonly employed assays. The synthesized model phenolipids containing p‐coumaric acid moiety and fatty acid chains exhibited improved lipophilicity and antioxidant activity. Extension of this work to marine omega‐3 oils as starting materials is expected to produce novel phenolipids that may be used as nutraceuticals and functional food ingredients with unique stability characteristics and potentially improved health benefits.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".