Regulation of cerebral blood flow in mammals during chronic hypoxia: a matter of balance
Bibliographic record
Abstract
Respiratory-induced changes in the partial pressures of arterial carbon dioxide (PaCO2) and oxygen (PaO2) play a major role in cerebral blood flow (CBF) regulation. Elevations in PaCO2 (hypercapnia) lead to vasodilatation and increases in CBF, whereas reductions in PaCO2 (hypocapnia) lead to vasoconstriction and decreases in CBF. A fall in PaO2 (hypoxia) below a certain threshold (<40-45 mmHg) also produces cerebral vasodilatation. Upon initial exposure to hypoxia, CBF is elevated via a greater relative degree of hypoxia compared with hypocapnia. At this point, hypoxia-induced elevations in blood pressure and loss of cerebral autoregulation, stimulation of neuronal pathways, angiogenesis, release of adenosine, endothelium-derived NO and a variety of autocoids and cytokines are additional factors acting to increase CBF. Following 2-3 days, however, the process of ventilatory acclimatization results in a progressive rise in ventilation, which increases PaO2 and reduces PaCO2, collectively acting to attenuate the initial rise in CBF. Other factors acting to lower CBF include elevations in haematocrit, sympathetic nerve activity and local and endothelium-derived vasoconstrictors. Hypoxia-induced alterations of cerebrovascular reactivity, autoregulation and pulmonary vascular tone may also affect CBF. Thus, the extent of change in CBF during exposure to hypoxia is dependent on the balance between the myriad of vasodilators and constrictors derived from the endothelium, neuronal innervations and perfusion pressure. This review examines the extent and mechanisms by which hypoxia regulates CBF. Particular focus will be given to the marked influence of hypoxia associated with exposure to high altitude and chronic lung disease. The associated implications of these hypoxia-induced integrative alterations for the regulation of CBF are discussed, and future avenues for research are proposed.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".