Maternal omega-3 polyunsaturated fatty acids improved levels of DHA-enriched phosphatidylethanolamines and enriched lipid clustering in the neuronal membranes of C57BL/6 mice fetal brains during gestation
Bibliographic record
Abstract
The composition of brain lipids is crucial for neurodevelopment and brain function. Diets enriched in omega (n)-3 polyunsaturated fatty acids (PUFA) can modulate brain lipid composition. However, the influence of maternal n-3 PUFA intake on fetal brain lipidome and neuronal membrane structure during gestation is not well studied. Eight-week-old female C57BL/6 mice were fed low or high n-3 PUFA semi-purified diets for two weeks before mating and during gestation. Fetal brain lipidome and neuronal membrane structure were studied at gestation day (GD) 12.5 (mid) and 18.5 (late) using liquid chromatography high-resolution accurate mass tandem mass spectrometry and computational techniques. Maternal diets high in n-3 PUFA increased fetal brain total phosphoethanolamine, phosphoinositol, phosphoglycerol, and phosphoserine glycerophospholipids, compared to the low n-3 PUFA diet. Docosahexaenoic acid (DHA, 22:6n-3)-enriched phosphatidylethanolamine (PE), phosphatidylcholine (PC), phosphatidylserine (PS), and lyso-PC (LPC) fatty acyl species increased as gestation progressed in the high n-3 PUFA group, compared to low n-3 PUFA. These fatty acyl species and phospholipids promote neurotransmission, memory, and cognition. A high n-3 PUFA diet increased the area per lipid in fetal neuronal membranes as gestation progressed, indicating improved membrane fluidity. Furthermore, a high n-3 PUFA diet increased the clustering of membrane lipids associated with neurotransmission, memory, and cognition (ceramide, PE, and cholesteryl ester) as gestation progressed. Our findings show for the first time that maternal diets high in n-3 PUFA before and during gestation improve fetal brain lipidome and membrane area per lipid that may enhance brain development and function.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".