Accumulation of Dietary Docosahexaenoic Acid in the Brain Attenuates Acute Immune Response and Development of Postischemic Neuronal Damage
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Consumption of fish has been shown to reduce risk of coronary heart disease and, possibly, of ischemic stroke. Because docosahexaenoic acid (DHA) is the most likely neuroactive component within fish oil, we hypothesized that exposing mice to a DHA-enriched diet may reduce inflammation and protect neurons against ischemic injury. METHODS: To visualize the effects of DHA on neuroinflammation after stroke, TLR2-fluc-GFP transgenic mice were exposed to either a control diet, a diet depleted in n-3 polyunsaturated fatty acid, or a diet enriched in DHA during 3 months. Real-time biophotonic/bioluminescence imaging of the TLR2 response was performed before and after middle cerebral artery occlusion, whereas cytokines concentrations and stroke area analyses were performed at 3 and 7 days after middle cerebral artery occlusion, respectively. RESULTS: We show that a 3-month DHA treatment prevented microglial activation after ischemic injury, reduced the ischemic lesion size, and increased levels of the antiapoptotic molecule Bcl-2 in the brain. Additional analysis revealed a significant decrease in the levels of COX2 and IL-1β, but not in other proinflammatory cytokines. Importantly, long-term DHA supplementation significantly changed the n-3:n-6 polyunsaturated fatty acid ratio in the brain. CONCLUSIONS: Collectively, these data indicate that diet-induced accumulation of DHA in the brain protects against postischemic inflammation and injury. Because DHA is widely available at low cost and has an excellent safety profile, our data suggest that increased DHA intake may provide protection against acute immune response/brain damage in ischemic stroke.
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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 | 0.001 | 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 | 0.000 |
| 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".