Cardiorespiratory fitness, blood pressure, and cerebral oxygenation during a dual-task in healthy young males
Bibliographic record
Abstract
This study aimed to evaluate the effects of cardiorespiratory fitness (CRF) and mean arterial pressure (MAP) on the prefrontal cortex (PFC) oxygenation and dual-task performance in healthy young males. Changes in the concentration of oxygenated (ΔHbO2) and deoxygenated hemoglobin (ΔHHb) in the right and left PFC were examined during a cognitive auditory 2-back task. Cognitive performance (2-back task’s accuracy) and walking motor performances were measured in single-tasks (single motor and single cognitive) and dual-task (2-back task + walking). Thirty-six young males were ranked according to their V˙O2peak. The second tertile was excluded to generate two groups of different CRF (high fit group: n = 12 and V˙O2peak = 56.0 ± 6.7 ml kg−1 min−1; low-fit group: n = 12 and V˙O2peak = 36.7 ± 4.1 ml kg−1 min−1). The CRF groups were further split into two subgroups according to 24-h MAP (higher-MAP, lower-MAP). Two-way ANOVA (CRF x n-back conditions) revealed a significant interaction between the CRF and cognitive task condition on 2-back accuracy (p = .007) and a main effect of CRF on ⊗HHb in the right and left PFC (p < .05). These results suggest that in healthy young males: 1) for CRF, only low-fit individuals demonstrate dual-task costs in accuracy (Dual < Single), and 2) that in comparison to the low-fit group, the high fit-group demonstrated greater changes in PFC oxygenation in ΔHHb, but not ΔHbO2.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 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".