Quantification of hexanal as an index of lipid oxidation in human milk and association with antioxidant components
Bibliographic record
Abstract
Hexanal, a secondary product of lipid oxidation, was identified as the major volatile aldehyde generated from lipid peroxidation in human milk. Hexanal was quantified in human milk using solid phase microextraction-gas chromatography/flame ionization detection that required correction for recovery based on the fat content of human milk. Alpha-tocopherol was the only tocopherol isomer in human milk found to be significantly correlated with hexanal (R = -0.374, p<0.05) and the total antioxidant capacity of human milk (ORAC(Fl) (R = 0.408, p<0.01)). Ascorbic acid content was negatively correlated (R = -0.403, p<0.05) with hexanal, but not to ORAC(Fl) in human milk. The effect of Holder pasteurization on oxidative status of human milk was determined using multiple parameters that included, hexanal level and malondialdehyde as markers of lipid oxidation, vitamins C and E content and antioxidant capacity (e.g. ORAC(Fl)). Pasteurization did not affect the oxidative status of milk as measured by hexanal level, ORAC(Fl) and malondialdehyde content. We conclude that hexanal is a sensitive and useful chemical indicator for assessing peroxidation reactions in human milk and that alpha tocopherol and ascorbic acid are two key antioxidant components in milk that contribute to protection against oxidation of milk lipids.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".