STRUCTURED LIPIDS: ACIDOLYSIS OF GAMMA‐LINOLENIC ACID‐RICH OILS WITH n‐3 POLYUNSATURATED FATTY ACIDS
Bibliographic record
Abstract
ABSTRACT Structured lipids were synthesized by acidolysis of γ‐linolenic acid‐rich oils and n‐3 polyunsaturated fatty acids (PUFA), namely eicosapentaenoic acid (EPA; 20:5n‐3) and docosahexaenoic acid (DHA, 22:6n‐3), using different lipases. Lipase PS‐30 from Pseudomonas sp. was chosen over the other enzymes to catalyze the acidolysis reaction owing to higher incorporation of n‐3 PUFA. Effects of mole ratio, reaction time, incubation temperature, enzyme load, and solvent type on acidolysis reactions were studied. At 250 enzyme activity units, incorporation of n‐3 PUFA reached optimal values of 29.9 and 30.7% for the reactions with borage and evening primrose oils, respectively. For the time course reaction, incorporation of n‐3 PUFA increased up to 34.1 and 31.5% (in 30 h), in borage and evening primrose oils, respectively. After 24 h incubation in hexane, n‐3 PUFA (EPA+DHA) incorporated into borage and evening primrose oils was 31.8 and 32.7%, respectively. The highest n‐3 PUFA incorporation in both oils occurred at a mole ratio of 1:2:2 (oil/EPA/DHA). Among the solvents tested, n‐hexane was found to be highly effective; total n‐3 PUFA incorporation of 33.3 and 27.8% in borage and evening primrose oils, respectively, was achieved in hexane. However, the solvent‐free reaction afforded products with a total of 23.4–28.8% n‐3 fatty acids (EPA and DHA).
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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) | 0.001 | 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".