Dietary essential fatty acids and brain function: a developmental perspective on mechanisms
Bibliographic record
Abstract
Brain development is a complex interactive process in which early disruptive events can have long-lasting effects on later functional adaptation. It is a process that is dependent on the timely orchestration of external and internal inputs through sophisticated intra- and intercellular signalling pathways. Long-chain polyunsaturated fatty acids (LCPUFA), specifically arachidonic acid and docosahexaenoic acid (DHA), accrue rapidly in the grey matter of the brain during development, and brain fatty acid (FA) composition reflects dietary availability. Membrane lipid components can influence signal transduction cascades in various ways, which in the case of LCPUFA include the important regulatory functions mediated by the eicosanoids, and extend to long-term regulation through effects on gene transcription. Our work indicates that FA imbalance as well as specific FA deficiencies can affect development adversely, including the ability to respond to environmental stimulation. For example, although the impaired water-maze performance of mice fed a saturated-fat diet improved in response to early environmental enrichment, the brains of these animals showed less complex patterns of dendritic branching. Dietary n-3 FA deficiency influences specific neurotransmitter systems, particularly the dopamine systems of the frontal cortex. We showed that dietary deficiency of n-3 FA impaired the performance of rats on delayed matching-to-place in the water maze, a task of the type associated with prefrontal dopamine function. We did not, however, find an association over a wider range of brain DHA levels and performance on this task. Some, but not all, studies of human infants suggest that dietary DHA may play a role in cognitive development as well as in some neurodevelopmental disorders; this possibility has important implications for population health.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".