Regulation of the Cerebral Circulation by Arterial Carbon Dioxide
Bibliographic record
Abstract
ABSTRACT Intact, coordinated, and precisely regulated cerebrovascular responses are required for the maintenance of cerebral metabolic homeostasis, adequate perfusion, oxygen delivery, and acid‐base balance during deviations from homeostasis. Increases and decreases in the partial pressure of arterial carbon dioxide (PaCO 2 ) lead to robust and rapid increases and decreases in cerebral blood flow (CBF). In awake and healthy humans, PaCO 2 is the most potent regulator of CBF, and even small fluctuations can result in large changes in CBF. Alterations in the responsiveness of the cerebral vasculature can be detected with carefully controlled stimulus‐response paradigms and hold relevance for cerebrovascular risk in steno‐occlusive disease. As changes in PaCO 2 do not typically occur in isolation, the integrative influence of physiological factors such as intracranial pressure, arterial oxygen content, cerebral perfusion pressure, and sympathetic nervous activity must be considered. Further, age and sex, as well as vascular pathologies are also important to consider. Following a brief summary of key historical events in the development of our understanding of cerebrovascular physiology and an overview of the measurement techniques to index CBF this review provides an in‐depth description of CBF regulation in response to alterations in PaCO 2 . Cerebrovascular reactivity and regional flow distribution are described, with further consideration of how differences in reactivity of parallel networks can lead to the “steal” phenomenon. Factors that influence cerebrovascular reactivity are discussed and the mechanisms and regulatory pathways mediating the exquisite sensitivity of the cerebral vasculature to changes in PaCO 2 are outlined. Finally, topical avenues for future research are proposed. © 2019 American Physiological Society. Compr Physiol 9:1101‐1154, 2019.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".