Mono- and dioleyl p-coumarate phenolipids and their antioxidant activity in a muscle food model system
Bibliographic record
Abstract
Abstract Response surface methodology (RSM) was used to optimize the degree of esterification of p-coumaric acid to triolein via lipase-catalyzed acidolysis, and enzyme load, reaction time and mole ratio of substrates were selected as variables in the experimental design. The results showed that the model employed was highly sufficient for determining the effectiveness and interaction of three selected variables, enzyme load, reaction time and the mole ratio of substrates, on the dependent variable, the degree of esterification. Although the optimization point was not found in the selected range of the three variables, the steepest ascent analysis suggested that an increase of these three variables might lead to a stationary point. However, based on the limitations on increasing the range of tested variables, including possible oxidation of synthesized lipids and increased cost, the degree of esterification so yielded in the designed central composite design should be the one closest to the possible ideal optimized degree. The p-coumarates so produced exhibited varying antioxidant performance in the tested muscle food model, which could be explained by their different lipophilicity. Moreover, the potential health benefits of synthesized phenolic lipids have been discussed. Graphical Abstract
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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) | 0.001 | 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".