Acute cocoa flavanol improves cerebral oxygenation without enhancing executive function at rest or after exercise
Bibliographic record
Abstract
Acute exercise-induced improvements in cognitive function are accompanied by increased (cerebral) blood flow and increased brain-derived neurotrophic factor (BDNF) levels. Acute cocoa flavanol (CF) intake may improve cognitive function, cerebral blood flow (in humans), and BNDF levels (in animals). This study investigated (i) the effect of CF intake in combination with exercise on cognitive function and (ii) cerebral hemodynamics and BDNF in response to CF intake and exercise. Twelve healthy men participated in this randomized, double-blind, crossover study. Participants performed a cognitive task (CT) at 100 min after acute 903-mg CF or placebo (PL) intake, followed by a 30-min time-trial. Immediately after this exercise, the same CT was performed. Prefrontal near-infrared spectroscopy was applied during CT and exercise to measure changes in oxygenated (ΔHbO 2 ), deoxygenated (ΔHHb), and total haemoglobin (ΔHb tot ) and blood samples were drawn and analyzed for BDNF. Reaction time was faster postexercise, but was not influenced by CF. ΔHbO 2 during the resting CT was increased by CF, compared with PL. ΔHbO 2 , ΔHHb, and ΔHb tot increased in response to exercise without any effect of CF. During the postexercise cognitive task, there were no hemodynamic differences between CF or PL. Serum BDNF was increased by exercise, but was not influenced by CF. In conclusion, at rest, CF intake increased cerebral oxygenation, but not BDNF concentrations, and no impact on executive function was detected. This beneficial effect of CF on cerebral oxygenation at rest was overruled by the strong exercise-induced increases in cerebral perfusion and oxygenation.
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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) | 0.001 | 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".