Enhanced task-related brain activation and resting perfusion in healthy older adults after chronic blueberry supplementation
Bibliographic record
Abstract
Blueberries are rich in flavonoids, which possess antioxidant and anti-inflammatory properties. High flavonoid intakes attenuate age-related cognitive decline, but data from human intervention studies are sparse. We investigated whether 12 weeks of blueberry concentrate supplementation improved brain perfusion, task-related activation, and cognitive function in healthy older adults. Participants were randomised to consume either 30 mL blueberry concentrate providing 387 mg anthocyanidins (5 female, 7 male; age 67.5 ± 3.0 y; body mass index, 25.9 ± 3.3 kg·m−2) or isoenergetic placebo (8 female, 6 male; age 69.0 ± 3.3 y; body mass index, 27.1 ± 4.0 kg·m−2). Pre- and postsupplementation, participants undertook a battery of cognitive function tests and a numerical Stroop test within a 1.5T magnetic resonance imaging scanner while functional magnetic resonance images were continuously acquired. Quantitative resting brain perfusion was determined using an arterial spin labelling technique, and blood biomarkers of inflammation and oxidative stress were measured. Significant increases in brain activity were observed in response to blueberry supplementation relative to the placebo group within Brodmann areas 4/6/10/21/40/44/45, precuneus, anterior cingulate, and insula/thalamus (p < 0.001) as well as significant improvements in grey matter perfusion in the parietal (5.0 ± 1.8 vs –2.9 ± 2.4%, p = 0.013) and occipital (8.0 ± 2.6 vs –0.7 ± 3.2%, p = 0.031) lobes. There was also evidence suggesting improvement in working memory (2-back test) after blueberry versus placebo supplementation (p = 0.05). Supplementation with an anthocyanin-rich blueberry concentrate improved brain perfusion and activation in brain areas associated with cognitive function in healthy older adults.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".