The effects of graded changes in oxygen and carbon dioxide tension on coronary blood velocity independent of myocardial energy demand
Bibliographic record
Abstract
In humans, coronary blood flow is tightly regulated by microvessels within the myocardium to match myocardial energy demand. However, evidence regarding inherent sensitivity of the microvessels to changes in arterial partial pressure of carbon dioxide and oxygen is conflicting because of the accompanied changes in myocardial energy requirements. This study aimed to investigate the changes in coronary blood velocity while manipulating partial pressures of end-tidal CO2 (Petco2) and O2 (Peto2). It was hypothesized that an increase in Petco2 (hypercapnia) or decrease in Peto2 (hypoxia) would result in a significant increase in mean blood velocity in the left anterior descending artery (LADVmean) due to an increase in both blood gases and energy demand associated with the concomitant cardiovascular response. Cardiac energy demand was assessed through noninvasive measurement of the total left ventricular mechanical energy. Healthy subjects (n = 13) underwent a euoxic CO2 test (Petco2 = -8, -4, 0, +4, and +8 mmHg from baseline) and an isocapnic hypoxia test (Peto2 = 64, 52, and 45 mmHg). LADVmean was assessed using transthoracic Doppler echocardiography. Hypercapnia evoked a 34.6 ± 8.5% (mean ± SE; P < 0.01) increase in mean LADVmean, whereas hypoxia increased LADVmean by 51.4 ± 8.8% (P < 0.05). Multiple stepwise regressions revealed that both mechanical energy and changes in arterial blood gases are important contributors to the observed changes in LADVmean (P < 0.01). In summary, regulation of the coronary vasculature in humans is mediated by metabolic changes within the heart and an inherent sensitivity to arterial blood gases.
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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) | 0.000 | 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".