Synthesis of Structured Lipids Containing Medium-Chain and Omega-3 Fatty Acids
Bibliographic record
Abstract
The ability of different lipases to incorporate omega3 fatty acids, namely, eicosapentaenoic acid (EPA, C20:5n-3), docosapentaenoic acid (DPA, C22:5n-3), and docosahexaenoic acid (DHA, C22:6n-3), into a high-laurate canola oil, known as Laurical 35, was studied. Lipases from Mucor miehei (Lipozyme-IM), Pseudomonas sp. (PS-30), and Candida rugosa (AY-30) catalyzed optimum incorporation of EPA, DPA, and DHA into Laurical 35, respectively. Other lipases used were Candida anatrctica (Novozyme-435) and Aspergillus niger (AP-12). Response surface methodology (RSM) was used to obtain a maximum incorporation of EPA, DPA, and DHA into high-laurate canola oil. The process variables studied were the amount of enzyme (2-6%), reaction temperature (35-55 degrees C), and incubation time (12-36 h). The amount of water added and mole ratio of substrates (oil to n-3 fatty acids) were kept at 2% and 1:3, respectively. The maximum incorporation of EPA (62.2%) into Laurical 35 was predicted at 4.36% of enzyme load and 43.2 degrees C over 23.9 h. Under optimum conditions (5.41% enzyme; 38.7 degrees C; 33.5 h), the incorporation of DPA into high-laurate canola oil was 50.8%. The corresponding maximum incorporation of DHA (34.1%) into Laurical 35 was obtained using 5.25% enzyme, at 43.7 degrees C, over 44.7 h. Thus, the number of double bonds and the chain length of fatty acids had a marked effect on the incorporation omega3 fatty acids into Laurical 35. EPA and DHA were mainly esterified to the sn-1,3 positions of the modified oils, whereas DPA was randomly distributed over the three positions of the triacylglycerol molecules. Meanwhile, lauric acid remained esterified mainly to the sn-1 and sn-3 positions of the modified oils. Enzymatically modified Laurical 35 with EPA, DPA, or DHA had higher conjugated diene (CD) and thiobarbituric acid reactive substance (TBARS) values than their unmodified counterpart. Thus, enzymatically modified oils were more susceptible to oxidation than their unmodified counterparts, when both CD and TBARS values were considered.
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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".