Docosahexaenoic and Arachidonic Acids as Neuroprotective Nutrients throughout the Life Cycle
Bibliographic record
Abstract
The role of docosahexaenoic acid (DHA) and arachidonic acid (AA) in neurogenesis and brain development throughout the life cycle is fundamental. DHA and AA are long-chain polyunsaturated fatty acids (LCPUFA) vital for many human physiological processes, such as signaling pathways, gene expression, structure and function of membranes, among others. DHA and AA are deposited into the lipids of cell membranes that form the gray matter representing approximately 25% of the total content of brain fatty acids. Both fatty acids have effects on neuronal growth and differentiation through the modulation of the physical properties of neuronal membranes, signal transduction associated with G proteins, and gene expression. DHA and AA have a relevant role in neuroprotection against neurodegenerative pathologies such as Alzheimer's disease and Parkinson's disease, which are associated with characteristic pathological expressions as mitochondrial dysfunction, neuroinflammation, and oxidative stress. The present review analyzes the neuroprotective role of DHA and AA in the extreme stages of life, emphasizing the importance of these LCPUFA during the first year of life and in the developing/prevention of neurodegenerative diseases associated with aging.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".