A maturational model for the study of airway smooth muscle adaptation to mechanical oscillation
Bibliographic record
Abstract
It has been shown that mechanical stretches imposed on airway smooth muscle (ASM) by deep inspiration reduce the subsequent contractile response of the ASM. This passive maneuver of lengthening and retraction of the muscle is beneficial in normal subjects to counteract bronchospasm. However, it is detrimental to hyperresponsive airways because it triggers further bronchoconstriction. Although the exact mechanisms for this contrary response by normal and hyperresponsive airways are unclear, it has been suggested that the phenomenon is related to changes in ASM adaptability to mechanical oscillation. Healthy immature airways of both human and animal exhibit hyperresponsiveness, but whether the adaptative properties of hyperresponsive airway differ from normal is still unknown. In this article, we review the phenomenon of ASM adaptation to mechanical oscillation and its relevance and implication to airway hyperresponsiveness. We demonstrate that the age-specific expression of ASM adaptation is prominent using an established maturational animal model developed in our laboratory. Our data on immature ASM showed potentiated contractile force shortly after a length oscillation compared with the maximum force generated before oscillation. Several potential mechanisms such as myogenic response, changes in actin polymerization, or changes in the quantity of the cytoskeletal regulatory proteins plectin and vimentin, which may underlie this age-specific force potentiation, are discussed. We suggest a working model of the structure of smooth muscle associated with force transmission, which may help to elucidate the mechanisms responsible for the age-specific expression of smooth muscle adaptation. It is important to study the maturational profile of ASM adaptation as it could contribute to juvenile hyperresponsiveness.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".