Separation of dietary omega‐3 and omega‐6 fatty acids in food by capillary electrophoresis
Bibliographic record
Abstract
A lower dietary omega-6/omega-3 (n-6/n-3) fatty acid ratio (<4) has been shown to be beneficial in preventing a number of chronic illnesses. Interest exists in developing more rapid and sensitive analytical methods for profiling fatty acid levels in foods. An aqueous CE method was developed for the simultaneous determination of 15 n-3 and n-6 relevant fatty acids. The effect of pH and concentration of buffer, type and concentration of organic modifier, and additive on the separation was investigated in order to determine the best conditions for the analysis. Baseline separations of the 15 fatty acids were achieved using 40 mM borate buffer at pH 9.50 containing 50 mM SDS, 10 mM β-cyclodextrin, and 10% acetonitrile. The developed CE method has LODs of <5 mg/L and good linearity (R(2) > 0.980) for all fatty acids studied. The proposed method was successfully applied to the determination of n-3 and n-6 fatty acids in flax seed, Udo® oils and a selection of grass-fed and grain-fed beef muscle samples.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".