Neural substrate of perceptual and semantic priming : multi-channel event-related potential study
Bibliographic record
Abstract
Omega (n)-3 polyunsaturated fatty acids (PUFA) are known to regulate lipid metabolism and inflammation; however, the regulation of maternal lipid metabolism and cytokines profile by n-3 PUFA during different gestation stages, and its impact on fetal sustainability is not known. We investigated the effects of maternal diet varying in n-3 PUFA prior to, and during gestation, on maternal metabolic profile, placental inflammatory cytokines, and fetal outcomes. Female C57BL/6 mice were fed either a high, low or very low (9, 3 or 1% w/w n-3 PUFA) diet, containing n-6:n-3 PUFA of 5:1, 20:1 and 40:1, respectively for two weeks before mating, and throughout pregnancy. Animals were sacrificed prior to mating (NP), and during pregnancy at gestation days 6.5, 12.5 and 18.5. Maternal metabolic profile, placental cytokines and fetal outcomes were determined. Our results show for the first time that a maternal diet high in n-3 PUFA prevented dyslipidemia in NP mice, and maintained the expected lipid profile during pregnancy. However, females fed the very low n-3 PUFA diet became hyperlipidemic prior to pregnancy, and carried this profile into pregnancy. Maternal diet high in n-3 PUFA maintained maternal plasma progesterone and placental pro-inflammatory cytokines profile, and sustained fetal numbers throughout pregnancy, while females fed the low and very-low n-3 PUFA diet had fewer fetuses. Our findings demonstrate the importance of maternal diet before, and during pregnancy, to maintain maternal metabolic profile and fetus sustainability. These findings are important when designing dietary strategies to optimize maternal metabolism during pregnancy for successful pregnancy outcome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".