Mechanopharmacology and Synergistic Relaxation of Airway Smooth Muscle
Bibliographic record
Abstract
Asthmatic airways are stiffer than normal. We have shown that the cytoskeletal passive stiffness of airway smooth muscle (ASM) can be regulated by intracellular signaling pathways, especially those associated with Rho kinase (ROCK). We have also shown that an oscillatory strain reduces the passive stiffness of ASM and its ability to generate force. Here, we investigated the combined effect of inhibiting the ASM contraction with β2 agonist and decreasing the ASM cytoskeletal stiffness with ROCK inhibitor and/or force oscillation (FO) on the relaxation of contracted ASM. We hypothesize that the ASM relaxation can be synergistically enhanced by the combination of these interventions, because drug-induced softening of the cytoskeleton enhances the FO-induced relaxation and vice versa. Sheep tracheal strips were isotonically contracted to acetylcholine (3 × 10−5 M). At the plateau of shortening, β2 agonist salbutamol (10−7 M), ROCK inhibitor H1152 (10−7 M), and FO (square wave, 1 Hz, amplitude 6% maximal active force) were applied either alone or in combination. After adjusting for nonspecific time-dependent variation, relengthening by individual interventions with low-dose salbutamol or H1152, or small amplitude FO was not significantly different from zero. However, significant relengthening was observed in all combination treatments. The relengthening was greater than the mathematical sum of relengthening caused by individual treatments thereby demonstrating synergistic relaxation. The ASM stiffness did not change with salbutamol or H1152 treatments, but was lower with FO in combination with H1152. The results suggest that the mechanopharmacological treatment can be an effective therapy for asthma.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".