The effect of hypoxia on the ventilatory and cerebral blood flow (CBF) responses to CO2
Bibliographic record
Abstract
Objectives This study examines the proposed approach to a standard measurement regime for characterizing the respiratory chemoreflexes as detailed by Duffin (2007) and develops a similar approach to characterize cerebrovascular responsiveness to hypoxia and CO 2 . We measured the effect of hypoxia on the isoxic modified rebreathing ventilatory and CBF responses to CO 2 in terms of sensitivity, ventilatory recruitment threshold and wakefulness ventilation at 2 levels of isoxia (PO 2 = 50 mmHg & 150 mmHg). We also measured the effect of hypercapnia on the isocapnic steady‐state (SS) ventilatory and CBF responses to hypoxia at 3 levels of hypercapnia (PCO2 = 4, 7 & 10 mmHg above resting). Finally we compared the isoxic rebreathing measurements with the SS isocapnic measurements. Method Custom designed software controlling a specialized gas blending device (RespirAct™; Thornhill Research) was used to implement the steady state and modified rebreathing protocols. Ventilation (VE), PetCO2 and PetO2, middle cerebral artery velocity (MCAv), and blood pressure (BP) were recorded. Results 9 subjects completed the tests (6 male). This graph displays the SS response of VE, MCAv and BP to CO 2 (PCO2 = 50 mmHg) first in hyperoxia (PO2 = 150 mmHg) and then in hypoxia (PO2 = 50 mmHg). We compared the SS and rebreathing ventilation and CBF responses. Rebreathing analysis (figures above) gives us interesting results. Ventilation shows a higher slope (increase of sensitivity) as well as a lower threshold during the Hypoxic phase as expected. For the MCAv, the interindividual variability is larger than expected. This example shows same slope, as expected. Comparison with SS method is more complex. Some subjects might have limitations of the MCAv increase. Further analysis still need to be done.
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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".