Role of CO<sub>2</sub> in the cerebral hyperemic response to incremental normoxic and hyperoxic exercise
Bibliographic record
Abstract
Cerebral blood flow (CBF) is temporally related to exercise-induced changes in partial pressure of end-tidal carbon dioxide (PetCO2 ); hyperoxia is known to enhance this relationship. We examined the hypothesis that preventing PetCO2 from rising (isocapnia) during submaximal exercise with and without hyperoxia [end-tidal Po2(PetO2 ) = 300 mmHg] would attenuate the increases in CBF. Additionally, we aimed to identify the magnitude that breathing, per se, influences the CBF response to normoxic and hyperoxic exercise. In 14 participants, CBF (intra- and extracranial) measurements were measured during exercise [20, 40, 60, and 80% of maximum workload (Wmax)] and during rest while ventilation (V̇e) was volitionally increased to mimic volumes achieved during exercise (isocapnic hyperpnea). While V̇ewas uncontrolled during poikilocapnic exercise, during isocapnic exercise and isocapnic hyperpnea, V̇ewas increased to prevent PetCO2 from rising above resting values (∼40 mmHg). Although PetCO2 differed by 2 ± 3 mmHg during normoxic poikilocapnic and isocapnic exercise, except for a greater poikilocapnic compared with isocapnic increase in blood velocity in the posterior cerebral artery at 60% Wmax, the between condition increases in intracranial (∼12-15%) and extracranial (15-20%) blood flow were similar at each workload. The poikilocapnic hyperoxic increases in both intra- and extracranial blood-flow (∼17-29%) were greater compared with poikilocapnic normoxia (∼8-20%) at intensities >40% Wmax(P< 0.01). During both normoxic and hyperoxic conditions, isocapnia normalized both the intracranial and extracranial blood-flow differences. Isocapnic hyperpnea did not alter CBF. Our findings demonstrate a differential effect of PetCO2 on CBF during exercise influenced by the prevailing PetO2.
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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 | 0.001 |
| 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 | 0.000 | 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".