Positional distribution of FA in TAG of enzymatically modified borage and evening primrose oils
Bibliographic record
Abstract
Stereospecific analysis was carried out to establish positional distribution of FA in the TAG of DHA, EPA, and (EPA + DHA)-enriched oils. In this study, TAG of enzymatically modified oils were purified using a silicic acid column. The TAG were then subjected to positional distribution analysis using a modified procedure involving reductive cleavage with Grignard reagent. The results showed that in DHA-enriched borage oil (BO), DHA was randomly distributed over the three positions of TAG, whereas gamma-linolenic acid (GLA) was mainly esterified at the sn-2 and -3 positions. In DHA-enriched evening primrose oil (EPO), however, DHA and GLA were concentrated in the sn-2 position. In EPA-enriched BO, EPA was randomly distributed over the three positions of TAG, similar to that observed for DHA. In EPA-enriched EPO, however, this FA was mainly located at the primary positions (sn-1 and sn-3) of TAG. In both oils, GLA was preferentially esterified at the sn-2 position. In (EPA + DHA)-enriched BO, EPA and DHA were mainly esterified at the sn-1 and -3 positions of TAG, whereas GLA was mainly located at the sn-2 position. In (EPA + DHA)-enriched EPO, GLA was mainly located at the sn-2 and -3 positions; EPA was preferentially esterified at the sn-1 and -3 positions, and DHA was found mainly at the sn-3 position.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".