Differential sensitivities of cerebral and brachial blood flow to hypercapnia in humans
Bibliographic record
Abstract
Although it is known that the vasculatures of the brain and the forearm are sensitive to changes in arterial Pco(2), previous investigations have not made direct comparisons of the sensitivities of cerebral blood flow (CBF) (middle cerebral artery blood velocity associated with maximum frequency of Doppler shift; Vp) and brachial blood flow (BBF) to hypercapnia. We compared the sensitivities of Vp and BBF to hypercapnia in humans. On the basis of the critical importance of the brain for the survival of the organism, we hypothesized that Vp would be more sensitive than BBF to hypercapnia. Nine healthy males (30.1 +/- 5.2 yr, mean +/- SD) participated. Euoxic hypercapnia (end-tidal Po(2) = 88 Torr, end-tidal Pco(2) = 9 Torr above resting) was achieved by using the technique of dynamic end-tidal forcing. Vp was measured by transcranial Doppler ultrasound as an index of CBF, whereas BBF was measured in the brachial artery by echo Doppler. Vp and BBF were measured during two 60-min trials of hypercapnia, each trial separated by 60 min. Since no differences in the responses were found between trials, data from both trials were averaged to make comparisons between Vp and BBF. During hypercapnia, Vp and BBF increased by 34 +/- 8 and 14 +/- 8%, respectively. Vp remained elevated throughout the hypercapnic period, but BBF returned to baseline levels by 60 min. The Vp CO(2) sensitivity was greater than BBF (4 +/- 1 vs. 2 +/- 1%/Torr; P < 0.05). Our findings confirm that Vp has a greater sensitivity than BBF in response to hypercapnia and show an adaptive response of BBF that is not evident in Vp.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".