Feeding Rats Diets Enriched in Lowbush Blueberries for Six Weeks Decreases Ischemia-induced Brain Damage
Bibliographic record
Abstract
Oxidative stress is an important element in the etiology of ischemic stroke. Lowbush blueberries (Vaccinium angustifolium Aiton) have a high antioxidant capacity and thus we determined whether consumption of lowbush blueberries would protect neurons from stroke-induced damage. Rats were fed AIN-93G diets containing 0 or 14.3% blueberries (g fresh weight/100 g feed) for 6 weeks. Stroke was then simulated by ligation of the left common carotid artery (ischemia), followed by hypoxia. One week later, plasma and urine were collected, and neuronal damage in the hippocampus was determined histologically. In control rats, hypoxia-ischemia resulted in 40 +/- 2% loss of neurons in the hippocampus of the left cerebral hemisphere, as compared to the right hemisphere. Rats on blueberry-supplemented diets lost only 17 +/- 2% of neurons in the ischemic hippocampus. Neuroprotection was observed in the CA1 and CA2 regions, but not CA3 region, of the hippocampus. The blueberry diet had no detectable effects on the plasma or urine oxygen radical absorbance capacity (ORAC) or plasma lipids. We conclude that consumption of lowbush blueberries by rats confers protection to the brain against damage from ischemia, suggesting that inclusion of blueberries in the diet may improve ischemic stroke outcomes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".