Effect of Inspiratory Resistive Loading on Expiratory Muscle Fatigue
Bibliographic record
Abstract
Expiratory resistive loading elicits inspiratory as well as expiratory muscle fatigue, suggesting parallel co-activation of the inspiratory muscles during expiration. It is unknown whether the expiratory muscles are similarly co-activated to the point of fatigue during inspiratory resistive loading (IRL). PURPOSE: To determine whether IRL elicits expiratory as well as inspiratory muscle fatigue. METHODS: Healthy male subjects (n=9) underwent isocapnic IRL to task failure (60% maximal inspiratory pressure, 15 breaths/min, 0.7 inspiratory duty cycle). Abdominal and diaphragm contractile function was assessed at baseline and at 3, 15 and 30 min post-IRL by measuring gastric twitch pressure (Pga,tw) and transdiaphragmatic twitch pressure (Pdi,tw) in response to potentiated magnetic stimulation of the thoracic and phrenic nerves, respectively. Electromyographic activity of the diaphragm, rectus abdominis, and external oblique was monitored to ensure consistency of stimulation. Fatigue was defined as >15% reduction from baseline in Pga,tw or Pdi,tw. RESULTS: During IRL (mean±SE;15.0±2.5 min), mean arterial pressure (MAP) and heart rate (HR) increased in a time-dependent manner (13 mmHg and 50 beats/min for the final min, respectively). Peak Pdi was significantly lower during the final min of IRL than during the first min (p<0.05). Peak Pga did not change significantly throughout IRL. Pdi,tw was significantly lower than baseline (34.3±3.2 cmH2O) at 3 min (23.2±1.9 cmH2O, p<0.001), 15 min (24.2±1.7 cmH2O, p<0.001) and 30 min post-IRL (26.3±2.0 cmH2O, p<0.001). Pga,tw was not significantly different from baseline (37.6±5.7 cmH2O) at 3 min (36.5±4.9 cmH2O), 15 min (33.7±4.13 cmH2O) and 30 min post-IRL (32.9±3.8 cmH2O). CONCLUSION: IRL elicits objective evidence of diaphragm, but not abdominal, muscle fatigue. Agonist-antagonist interactions for the respiratory muscles appear to be more important during expiratory versus inspiratory loading. Funding: NSERC
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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) | 0.002 | 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".