Stability of cerebral metabolism and substrate availability in humans during hypoxia and hyperoxia
Bibliographic record
Abstract
Characterization of the influence of oxygen availability on brain metabolism is an essential step toward a better understanding of brain energy homoeostasis and has obvious clinical implications. However, how brain metabolism depends on oxygen availability has not been clearly examined in humans. We therefore assessed the influence of oxygen on CBF (cerebral blood flow) and CMRO2 (cerebral metabolic rates for oxygen) and carbohydrates. PaO2 (arterial partial pressure of oxygen) was decreased for 15 min to ~60, ~44 and ~35 mmHg [to target a SaO2 (arterial oxygen saturation) of 90, 80 and 70% respectively], and elevated to ~320 and ~430 mmHg. Isocapnia was maintained during each trial. At the end of each stage, arterial-jugular venous differences and volumetric CBF were measured to directly calculate cerebral metabolic rates. During progressive hypoxaemia, elevations in CBF were correlated with the reductions in both SaO2 (R2=0.54, P<0.05) and CaO2 (arterial oxygen content) (R2=0.57, P<0.05). Despite markedly reduced CaO2, cerebral oxygen delivery was maintained by increased CBF. Cerebral metabolic rates for oxygen, glucose and lactate remained unaltered during progressive hypoxia. Consequently, cerebral glucose delivery was in excess of that required, and net lactate efflux increased slightly in severe hypoxia, as reflected by a small increase in jugular venous lactate. Progressive hyperoxia did not alter CBF, CaO2, substrate delivery or cerebral metabolism. In conclusion, marked elevations in CBF with progressive hypoxaemia and related reductions in CaO2 resulted in a well-maintained cerebral oxygen delivery. As such, cerebral metabolism is still supported almost exclusively by carbohydrate oxidation during severe levels of hypoxaemia.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".