Maternal n-3 PUFA deficiency alters brain fatty acid and oxylipin profiles across perinatal development in offspring
Bibliographic record
Abstract
Abstract Long-chain polyunsaturated fatty acids (LC-PUFAs), particularly arachidonic acid (AA, 20:4n-6) and docosahexaenoic acid (DHA, 22:6n-3), are essential for optimal neurodevelopment through their effect on neuronal proliferation, neurite outgrowth and synaptogenesis. Emerging evidence highlights that brain PUFAs are metabolized in oxylipins, the bioactive oxidized PUFA metabolites known to regulate inflammatory processes. Recent data highlighted that both PUFA and oxylipin profiles are modulated in the adult male brain by dietary PUFA content. However, little is known on the impact of maternal dietary n-3 PUFA intake during the perinatal period and the neurodevelopmental profile of brain fatty acids and associated oxylipins in offspring, and whether these effects differ between sexes. To address this question, we first measured fatty acid levels in the placenta and embryonic brain of male and female offspring of mothers fed a sufficient or deficient diet in n-3 PUFAs at embryonic day (E)17.5. Then, fatty acids and oxylipins were measured at different post-natal stages, in the brain at P0 and P7, and in the hippocampus at P14 and P21, in both male and female offspring. Our results show that maternal n-3 PUFA dietary deficiency alters fatty acid profiles as early as E17.5 in both the placenta and the brain. Furthermore, dietary intervention affects both fatty acid and oxylipin profiles throughout postnatal brain development, with notable sex-specific differences. These findings underscore the critical importance of adequate maternal n-3 PUFA intake during the perinatal period for maintaining an optimal PUFA and oxylipin profiles, with potential implications for fetal and postnatal brain development.
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 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) | 0.000 | 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) | 0.001 | 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".