Formation Kinetics of Monomeric Cyclic Fatty Acid Methyl Esters of Alpha‐Linolenic Acid: Effects of Mono <i>cis</i>/<i>trans</i> Isomers
Bibliographic record
Abstract
Abstract Cyclic fatty acid monomers (CFAM) are formed at low levels in edible oils during thermal processing operations such as frying or refining, and inevitably become part of the diet. These proatherogenic agents may increase the levels of oxidative stress markers, and induce hepatomegaly and steatosis. However, the kinetics involved in their formation is not well known. The objective of the present study was to evaluate the effects of cis and trans isomers on cyclization reactions involved in the thermal transformation of alpha‐linolenic acid (ALA). Geometrical isomers of ALA were obtained from all‐cis ALA by nitric acid treatment. Mono‐trans isomers were concentrated using silver nitrate‐silica gel chromatography. All‐cis ALA, isomerized ALA, and a fraction at 85% mono‐trans isomers were heat treated at 275 °C in hexadecane for periods up to 24 hours, and the formation of geometrical isomers and CFAM was monitored by GC. The results show that mono‐trans isomers at carbon 9 and carbon 15 form CFAM at an accelerated rate, compared to the corresponding cis isomers, resulting in the formation of higher levels of CFAM over shorter time periods. The validation of the kinetic model was performed by solving simultaneously and nonlinearly fitting the system of coupled differential equations with experimental data. Good agreement was found between the experimental data and the predicted values. This work suggests that the use of polyunsaturated vegetable oils over extended periods for thermal processing of food may result in the formation of CFAM, in particular, if mono‐trans isomers are present in the oil.
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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".