Human milk plasmalogens: an unrecognized pool of novel lipid enriched in long chain polyunsaturated fatty acids (38.1)
Bibliographic record
Abstract
Ethanolamine plasmalogens (EPLas) are unique phospholipids (PL) with potential roles in development of the brain and intestine, where they are present in high amounts. PLas, like arachidonic (20:4n‐6) and docosahexaenoic acid (DHA, 22:6n‐3) are found only in animal lipid. They are present in human milk, but not milk substitutes or intravenous lipid. Their characteristics, including fatty acid composition, are poorly understood in part due to challenges of separation and recovery from diacyl PL which differ from PLas by the lack of a carbonyl group on the sn‐1 glycerol carbon. Our objectives were to develop methodology for separation, recovery and analysis of EPLas from human and cow milk, then determine their composition together with that of milk total lipid, diacyl ethanolamine PL (PE) and phosphatidylcholine (PC). Milk PL were separated using solid phase extraction, then diacyl PE, EPLas and PC separated by HPLC, recovered and their fatty acids determined by GLC for mature milk from 25 women. Human milk EPLas were enriched in long chain n‐6 and n‐3 fatty acids, 20:4n‐6 11.2 ±1.4%, eicosapentanoic (20:5 n‐3) 1.2 ± 0.7%, adrenic acid (22:4n‐6) 2.2 ± 0.5%, and DHA 2.9 ± 1.4 % compared to 3.6 ± 0.8; 0.7 ± 0.3; 0.3 ± 0.2; and 1.5 ± 0.9%, respectively, in PE and 0.47 ± 0.07; 0.14 ± 0.09; 0.08 ± 0.02; and 0.39 ± 0.3%, respectively, in milk total lipid. We found a significant correlation between DHA in milk total lipid and PE (r =0.57) and PC (r=0.42), but not EPLas (r=0.13), suggesting little variability in EPLas with maternal diet. Intriguingly, cow milk colostrum and mature milk show similar patterns. In conclusion, our work raises the question of whether EPLas are a distinct pool of bioactive, tightly regulated milk lipids that contribute to n‐6 and n‐3 fatty acids in the breast‐fed infant.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".