Peaks and valleys: oscillatory cerebral blood flow at high altitude protects cerebral tissue oxygenation
Bibliographic record
Abstract
Abstract Introduction. Oscillatory patterns in arterial pressure and blood flow (at ∼0.1 Hz) may protect tissue oxygenation during conditions of reduced cerebral perfusion and/or hypoxia. We hypothesized that inducing oscillations in arterial pressure and cerebral blood flow at 0.1 Hz would protect cerebral blood flow and cerebral tissue oxygen saturation during exposure to a combination of simulated hemorrhage and sustained hypobaric hypoxia. Methods. Eight healthy human subjects (4 male, 4 female; 30.1 ± 7.6 year) participated in two experiments at high altitude (White Mountain, California, USA; altitude, 3800 m) following rapid ascent and 5–7 d of acclimatization: (1) static lower body negative pressure (LBNP, control condition) was used to induce central hypovolemia by reducing chamber pressure to −60 mmHg for 10 min (0 Hz) , and; (2) oscillatory LBNP where chamber pressure was reduced to −60 mmHg, then oscillated every 5 s between −30 mmHg and −90 mmHg for 10 min (0.1 Hz) . Measurements included arterial pressure, internal carotid artery (ICA) blood flow, middle cerebral artery velocity (MCAv), and cerebral tissue oxygen saturation (ScO 2 ). Results. Forced 0.1 Hz oscillations in mean arterial pressure and mean MCAv were accompanied by a protection of ScO 2 (0.1 Hz: −0.67% ± 1.0%; 0 Hz: −4.07% ± 2.0%; P = 0.01). However, the 0.1 Hz profile did not protect against reductions in ICA blood flow (0.1 Hz: −32.5% ± 4.5%; 0 Hz: −19.9% ± 8.9%; P = 0.24) or mean MCAv (0.1 Hz: −18.5% ± 3.4%; 0 Hz: −15.3% ± 5.4%; P = 0.16). Conclusions. Induced oscillatory arterial pressure and cerebral blood flow led to protection of ScO 2 during combined simulated hemorrhage and sustained hypoxia. This protection was not associated with the preservation of cerebral blood flow suggesting preservation of ScO 2 may be due to mechanisms occurring within the microvasculature.
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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 | 0.000 | 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".