Cerebral and myocardial blood flow responses to hypercapnia and hypoxia in humans
Bibliographic record
Abstract
In humans, cerebrovascular responses to alterations in arterial Pco(2) and Po(2) are well documented. However, few studies have investigated human coronary vascular responses to alterations in blood gases. This study investigated the extent to which the cerebral and coronary vasculatures differ in their responses to euoxic hypercapnia and isocapnic hypoxia in healthy volunteers. Participants (n = 15) were tested at rest on two occasions. On the first visit, middle cerebral artery blood velocity (V(P)) was assessed using transcranial Doppler ultrasound. On the second visit, coronary sinus blood flow (CSBF) was measured using cardiac MRI. For comparison with V(P), CSBF was normalized to the rate pressure product [an index of myocardial oxygen consumption; normalized (n)CSBF]. Both testing sessions began with 5 min of euoxic [end-tidal Po(2) (Pet(O(2))) = 88 Torr] isocapnia [end-tidal Pco(2) (Pet(CO(2))) = +1 Torr above resting values]. Pet(O(2)) was next held at 88 Torr, and Pet(CO(2)) was increased to 40 and 45 Torr in 5-min increments. Participants were then returned to euoxic isocapnia for 5 min, after which Pet(O(2)) was decreased from 88 to 60, 52 and 45 Torr in 5-min decrements. Changes in V(P) and nCSBF were normalized to isocapnic euoxic conditions and indexed against Pet(CO(2)) and arterial oxyhemoglobin saturation. The V(P) gain for euoxic hypercapnia (%/Torr) was significantly higher than nCSBF (P = 0.030). Conversely, the V(P) gain for isocapnic hypoxia (%/%desaturation) was not different from nCSBF (P = 0.518). These findings demonstrate, compared with coronary circulation, that the cerebral circulation is more sensitive to hypercapnia but similarly sensitive to hypoxia.
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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".