Effect of Cyclolinopeptides on the Oxidative Stability of Flaxseed Oil
Bibliographic record
Abstract
Polar compounds present in flaxseed oil increase its oxidative stability. Flaxseed oil becomes less stable to oxidation when filtered with silica. This observation may be linked to antioxidant compounds present in flaxseed oil. Flaxseed oil was passed over a silica adsorbent column to remove polar compounds. The polar compounds were then eluted from the silica absorbant using a series of increasingly polar solvents. The polar fractions from flaxseed oil were then added back to silica-treated flaxseed oil to determine the impact of fractions containing polar compounds on oxidative stability (induction time) at 100 °C. A polar fraction containing mainly cyclolinopeptide A (CLA, 1), but also containing β/γ- and δ-tocopherol increased the induction time of silica-treated flaxseed oil from 2.36 ± 0.28 to 3.20 ± 0.41 h. When oxidative stability was determined immediately after addition of the polar fractions other flaxseed fractions and solvent controls did not affect oil stability. However, when the oxidative stability index (OSI) test was delayed for three days and oil samples were held at room temperature after the addition of the polar fractions to the flaxseed oil, it was observed that the control oil treated with silica had become highly sensitive to oxidation. A polar fraction containing a mixture of CLs (1, 5, 7, 9, 11), improved the oxidative stability of peptide-free oil with respect to the control when the OSI measurement was made three days after adding the fraction. In addition, effects of 1 on the oxidative stability of peptide-free oil containing divalent metal cations was 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".