Lipase‐Catalyzed Synthesis of Medium‐Long‐Medium Type Structured Lipids Using Tricaprylin and Trilinolenin as Substrate Models
Bibliographic record
Abstract
Abstract The synthesis of medium‐long‐medium type structured lipids (SL) by the interesterification of tricaprylin (TC) and trilinolenin (TLN), using selected commercial lipases from Rhizomucor miehei (Lipozyme RM IM) and Candida antarctica (Novozym 435) was investigated. Although the bioconversion yield (BY) for Lipozyme RM IM (24.7 %) was close to that for Novozym 435 (24.0 %), the initial enzyme activity was 6.3 μmol CLnC/g enzyme/min and 1.6 μmol CLnC/g enzyme/min, respectively. Lipozyme RM IM was subsequently selected for further investigation. The structural analyses of SL indicated that the major products were 1,3‐dicapryl‐2‐linolenyl glycerol (CLnC) and 1(3)‐capryl‐2,3(1)‐dilinolenyl glycerol (CLnLn). In order to optimize the BY, selected parameters were investigated. The experimental results showed that using hexane as the reaction medium, at an initial water activity ( a w ) of 0.06, 10 mg solid enzyme/mL, substrate molar ratio of TC to TLN of 6:1 and a reaction time of 9 h, resulted in the highest BY (73.2 %). Using the optimized conditions, the effects of TLN concentration and other selective parameters, including the denaturation of the enzyme, controlling the a w and the addition of silica gel, on the mass productivity ( P M ), enzymatic productivity ( P E ) and volumetric productivity ( P V ) of the interesterification reaction, were also investigated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".