Cerebral blood flow response to acute hypoxic hypoxia
Bibliographic record
Abstract
Hypoxic hypoxia (inspiratory hypoxia) stimulates an increase in cerebral blood flow (CBF) maintaining oxygen delivery to the brain. However, this response, particularly at the tissue level, is not well characterised. This study quantifies the CBF response to acute hypoxic hypoxia in healthy subjects. A 20-min hypoxic (mean P(ET)o(2)=52 mmHg) challenge was induced and controlled by dynamic end-tidal forcing whilst CBF was measured using pulsed arterial spin labelling perfusion MRI. The rate constant, temporal delay and magnitude of the CBF response were characterised using an exponential model for whole-brain and regional grey matter. Grey matter CBF increased from 76.1 mL/100 g/min (95% confidence interval (CI) of fitting: 75.5 mL/100 g/min, 76.7 mL/100 g/min) to 87.8 mL/100 g/min (95% CI: 86.7 mL/100 g/min, 89.6 mL/100 g/min) during hypoxia, and the temporal delay and rate constant for the response to hypoxia were 185 s (95% CI: 132 s, 230 s) and 0.0035 s(-1) (95% CI: 0.0019 s(-1), 0.0046 s(-1)), respectively. Recovery from hypoxia was faster with a delay of 20 s (95% CI: -38 s, 38 s) and a rate constant of 0.0069 s(-1) (95% CI: 0.0020 s(-1), 0.0103 s(-1)). R-2*, an index of blood oxygenation obtained simultaneously with the CBF measurement, increased from 30.33 s(-1) (CI: 30.31 s(-1), 30.34 s(-1)) to 31.48 s(-1) (CI: 31.47 s(-1), 31.49 s(-1)) with hypoxia. The delay and rate constant for changes in R-2* were 24 s (95% CI: 21 s, 26 s) and 0.0392 s(-1) (95% CI: 0.0333 s(-1), 0.045 s(-1) ), respectively, for the hypoxic response, and 12 s (95% CI: 10 s, 13 s) and 0.0921 s(-1) (95% CI: 0.0744 s(-1), 0.1098 s(-1)/) during the return to normoxia, confirming rapid changes in blood oxygenation with the end-tidal forcing system. CBF and R-2* reactivity to hypoxia differed between subjects, but only R-2* reactivity to hypoxia differed significantly between brain regions. (c) 2013 The Authors. NMR in Biomedicine published by John Wiley & Sons, Ltd.
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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) | 0.000 | 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".