Length oscillation mimicking periodic individual deep inspirations during tidal breathing attenuates force recovery and adaptation in airway smooth muscle
Bibliographic record
Abstract
Airway smooth muscle (ASM) is able to generate maximal force under static conditions, and this isometric force can be maintained over a large length range due to length adaptation. The increased force at short muscle length could lead to excessive narrowing of the airways. Prolonged exposure of ASM to submaximal stimuli also increases the muscle's ability to generate force in a process called force adaptation. To date, the effects of length and force adaptation have only been demonstrated under static conditions. In the mechanically dynamic environment of the lung, ASM is constantly subjected to periodic stretches by the parenchyma due to tidal breathing and deep inspiration. It is not known whether force recovery due to muscle adaptation to a static environment could occur in a dynamic environment. In this study the effect of length oscillation mimicking tidal breathing and deep inspiration was examined. Force recovery after a length change was attenuated in the presence of length oscillation, except at very short lengths. Force adaptation was abolished by length oscillation. We conclude that in a healthy lung (with intact airway-parenchymal tethering) where airways are not allowed to narrow excessively, large stretches (associated with deep inspiration) may prevent the ability of the muscle to generate maximal force that would occur under static conditions irrespective of changes in mean length; mechanical perturbation on ASM due to tidal breathing and deep inspiration, therefore, is the first line of defense against excessive bronchoconstriction that may result from static length and force adaptation.
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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".