Toxic Oxygenated α,β-Unsaturated Aldehydes and their Study in Foods: A Review
Bibliographic record
Abstract
The oxidation of lipids containing polyunsaturated omega-3 or omega-6 acyl groups, such as docosahexenoic, eicosapentenoic, linolenic, arachidonic, or linoleic groups, and of the corresponding fatty acids, generates among other compounds alpha,beta -unsaturated aldehydes supporting different functional groups containing oxygen, which can be named oxygenated alpha,beta -unsaturated aldehydes (OalphabetaUAs). These compounds can be produced in cells and tissues of living organisms or in foods during processing or storage, and from these latter can be absorbed through the diet. In the last few years, OalphabetaUAs are receiving a great deal of attention because they are being considered as possible causal agents of numerous diseases, such as chronic inflammation, neurodegenerative diseases, adult respiratory distress syndrome, atherogenesis, diabetes, and different types of cancer. This review deals with the nature of the different kinds of OalphabetaUAs detected until now, their reactivity and consequent biological activity; the several pathways proposed for their formation; the current knowledge about the influence of both oxidative conditions and lipids nature in the rate of formation and yield of each kind of OalphabetaUAs in edible oils; the methods described until now to determine the presence in foods of some of these compounds, such as 4-hydroxy-trans-2-nonenal, 4-hydroxy-trans-2-octenal, 4-hydroxy-trans-2-hexenal and 4-oxo-trans-2-hexenal; and finally, the levels found of some of them in several foods.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".