Diaphragmatic neuromechanical coupling and mechanisms of hypercapnia during inspiratory loading
Bibliographic record
Abstract
We hypothesized that improved diaphragmatic neuromechanical coupling during inspiratory loading is not sufficient to prevent alveolar hypoventilation and task failure, and that the latter results primarily from central-output inhibition of the diaphragm and air hunger rather than contractile fatigue. Eighteen subjects underwent progressive inspiratory loading. By task failure all developed hypercapnia. Tidal transdiaphragmatic pressure (ΔPdi) and diaphragmatic electrical activity (ΔEAdi) increased during loading - the former more than the latter; thus, neuromechanical coupling (ΔPdi/ΔEAdi) increased during loading. Progressive increase in extra-diaphragmatic muscle contribution to tidal breathing, expiratory muscle recruitment, and decreased end-expiratory lung volume contributed to improved neuromechanical coupling. At task failure, subjects experienced intolerable breathing discomfort, at which point mean ΔEAdi was 74.9±4.9% of maximum, indicating that the primary mechanism of hypercapnia was submaximal diaphragmatic recruitment. Contractile fatigue was an inconsistent finding. In conclusion, hypercapnia during acute loading primarily resulted from central-output inhibition of the diaphragm suggesting that acute loading responses are controlled by the cortex rather than bulbopontine centers.
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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 | 0.001 |
| 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".