Effects of Omega-3 Fatty Acids on Inflammatory Markers in Cerebrospinal Fluid and Plasma in Alzheimer’s Disease: The OmegAD Study
Bibliographic record
Abstract
BACKGROUND: omega-3 fatty acids (omega-3 FAs) found in dietary fish or fish oils are anti-inflammatory agents that may influence Alzheimer's disease (AD). OBJECTIVE: To study the effects of dietary omega-3 FA supplementation on inflammatory markers in cerebrospinal fluid (CSF) and plasma from patients with mild to moderate AD. METHODS: Thirty-five patients (70.3 +/- 8.2 years) were randomized to a daily intake of 2.3 g omega-3 FAs or placebo for 6 months. The inflammatory markers interleukin (IL)-6, tumour necrosis factor-alpha and soluble interleukin-1 receptor type II (sIL-1RII) were analysed in CSF and plasma at baseline and at 6 months. The AD markers tau-protein, hyperphosphorylated tau-protein and beta-amyloid (Abeta(1-42)) were assessed in CSF. High-sensitivity C-reactive protein was assessed in plasma. A possible relation to the APOE genotype was investigated. RESULTS: There was no significant treatment effect of omega-3 FAs on inflammatory and AD biomarkers in CSF or on inflammatory markers in plasma, nor was there any relation with APOE. A significant correlation was observed at baseline between sIL-1RII and Abeta(1-42) levels in CSF. CONCLUSIONS: Treatment of AD patients with omega-3 FAs for 6 months did not influence inflammatory or biomarkers in CSF or plasma. The correlation between sIL-1RII and Abeta(1-42) may reflect the reciprocal interactions between IL-1 and Abeta peptides.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".