Voluntary activation of the diaphragm after inspiratory pressure threshold loading
Bibliographic record
Abstract
Abstract After a bout of isolated inspiratory work, such as inspiratory pressure threshold loading (IPTL), the human diaphragm can exhibit a reversible loss in contractile function, as evidenced by a decrease in transdiaphragmatic twitch pressure (P DI,TW ). Whether or not diaphragm fatigability after IPTL is affected by neural mechanisms, measured through voluntary activation of the diaphragm (D‐VA) in addition to contractile mechanisms, is unknown. It is also unknown if changes in D‐VA are similar between sexes given observed differences in diaphragm fatigability between males and females. We sought to determine whether D‐VA decreases after IPTL and whether this was different between sexes. Healthy females ( n = 11) and males ( n = 10) completed an IPTL task with an inspired duty cycle of 0.7 and targeting an intensity of 60% maximal transdiaphragmatic pressure until task failure. P DI,TW and D‐VA were measured using cervical magnetic stimulation of the phrenic nerves in combination with maximal inspiratory pressure maneuvers. At task failure, P DI,TW decreased to a lesser degree in females vs. males (87 ± 15 vs. 73 ± 12% baseline, respectively, p = 0.016). D‐VA decreased after IPTL but was not different between females and males (91 ± 8 vs. 88 ± 10% baseline, respectively, p = 0.432). When all participants were pooled together, the decrease in P DI,TW correlated with both the total cumulative diaphragm pressure generation ( R 2 = 0.43; p = 0.021) and the time to task failure (TTF, R 2 = 0.40; p = 0.30) whereas the decrease in D‐VA correlated only with TTF ( R 2 = 0.24; p = 0.041). Our results suggest that neural mechanisms can contribute to diaphragm fatigability, and this contribution is similar between females and males following IPTL.
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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".