Evaluating the <i>trans</i> Fatty Acid, CLA, PUFA and Erucic Acid Diversity in Human Milk from Five Regions in China
Why this work is in the frame
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Bibliographic record
Abstract
Human milk was obtained from 97 healthy lactating women from five different regions in China. Twenty-four hour dietary questionnaire identified the foods consumed that showed distinct differences in food types between cities. The southern and central regions had higher levels of total trans fatty acids (TFA) and conjugated linoleic acids (CLA) in human milk than the northern region. The major isomers in human milk from the northern region were vaccenic and rumenic acids, whereas the other regions had a random distribution of these isomers. This was consistent with the isomer distribution in the refined vegetable oils used and their increased formation during high temperature stir-frying. The human milk composition showed little evidence that partially hydrogenated fats were consumed, except eight mothers in Guangzhou who reported eating crackers, plus four other mothers. The TFA concentration in these human milk samples was higher (2.06-3.96%). The amount of n-6 (1.70-2.24%) and n-3 (0.60-1.47%) highly unsaturated fatty acids (HUFA) in human milk and the resultant ratio (1.43-2.95) showed all mothers in China had an adequate supply of HUFA in their diet. Rapeseed oil was consumed evidenced by erucic acids in human milk. The levels of erucic acid were below internationally accepted limits for human consumption. The levels of undesirable TFA and CLA isomers in human milk are a concern. Efforts to decrease the practice of high temperature stir-frying using unsaturated oils, and a promotion to increase consumption of dairy and ruminant products should be considered in China.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it