Flaxseed Cyclolinopeptides: Analysis and Storage Stability
Bibliographic record
Abstract
Abstract Fourteen cyclolinopeptides (CLPs) from flaxseed oil and meal were separated, identified and quantified by HPLC coupled to an Orbitrap MS. The oxidative stability of the cyclolinopeptides was assessed during storage of flaxseed oil and meal. A significant decrease in the amounts of the methionine containing CLPs, namely CLP‐B, CLP‐J and CLP‐M, and a concurrent increase in the amounts of methionine sulfoxide containing CLPs, such as CLP‐C, CLP‐E and CLP‐G were observed. The cyclolinopeptides with two methionine units, CLP‐L and CLP‐M, exhibited the greatest decrease, followed by CLP‐J, the major flaxseed oil bitter taste precursor, and CLP‐B, a biologically active cyclolinopeptide. At the end of the storage period, the amount of the bitter CLP‐E increased fourfold in the oil while the immunosuppressive cyclolinopeptides A remained unchanged. No significant changes in the amount of each of the CLPs were observed in the stored flaxseed meals. A fast and reliable procedure has been developed for quantitative analysis of cyclolinopeptides. Due to the high predisposition of methionine containing cyclolinopeptides to oxidation and the easiness of CLPs’ quantification with the proposed method, it is possible to reliably assess the extent of flaxseed meal and oil oxidation.
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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".