Smooth muscle length adaptation and actin filament length: a network model of the cytoskeletal dysregulation
Bibliographic record
Abstract
Length adaptation of the airway smooth muscle cell is attributable to cytoskeletal remodeling. It has been proposed that dysregulated actin filaments may become longer in asthma, and that such elongation would prevent a parallel-to-series transition of contractile units, thus precluding the well-known beneficial effects of deep inspirations and tidal breathing. To test the potential effect that actin filament elongation could have in overall muscle mechanics, we present an extremely simple model. The cytoskeleton is represented as a 2-D network of links (contractile filaments) connecting nodes (adhesion plaques). Such a network evolves in discrete time steps by forming and dissolving links in a stochastic fashion. Links are formed by idealized contractile units whose properties are either those from normal or elongated actin filaments. Oscillations were then imposed on the network to evaluate both the effects of breathing and length adaptation. In response to length oscillation, a network with longer actin filaments showed smaller decreases of force, smaller increases in compliance, and higher shortening velocities. Taken together, these changes correspond to a network that is refractory to the effects of breathing and therefore approximates an asthmatic scenario. Thus, an extremely simple model seems to capture some relatively complex mechanics of airway smooth muscle, supporting the idea that dysregulation of actin filament length may contribute to excessive airway narrowing.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".