Antioxidant capacity of human milk and its association with vitamins A and E and fatty acid composition
Bibliographic record
Abstract
AIM: The antioxidant capacity of human milk reflects the presence and activity of multiple components, which prevent oxidative rancidity. The aim of this study was to use the Oxygen Radical Absorbance Capacity assay to assess human milk antioxidant capacity and find correlations with milk components. METHODS: Milk samples collected from 60 breastfeeding women at 1 month postpartum were assayed for antioxidant capacity, vitamins E and A, and fatty acids. Potential statistical relationships of concentrations of vitamins A and E and polyunsaturated fatty acids on the antioxidant capacity of human milk were determined. RESULTS: Human milk antioxidant capacity was positively attributed to alpha-tocopherol concentration (rho < 0.05). The vitamin A concentration did not significantly contribute to milk antioxidant capacity, but was correlated to milk alpha-tocopherol concentration (r = 0.587; rho < 0.001). There was no evidence of an inverse relationship between polyunsaturated fatty acids concentration and the antioxidant capacity value of milk. CONCLUSION: This study shows that alpha-tocopherol is an important contributor to the oxidative stability of human milk. Moreover, there was no evidence obtained to show that women who have high levels of milk polyunsaturated fatty acids are predisposed to lower milk antioxidant capacity.
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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 | 0.003 |
| 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".