Ionic mechanisms and Ca<sup>2+</sup>regulation in airway smooth muscle contraction: do the data contradict dogma?
Bibliographic record
Abstract
In general, excitation-contraction coupling in muscle is dependent on membrane depolarization and hyperpolarization to regulate the opening of voltage-dependent Ca(2+) channels and, thereby, influence intracellular Ca(2+) concentration ([Ca(2+)](i)). Thus Ca(2+) channel blockers and K(+) channel openers are important tools in the arsenals against hypertension, stroke, and myocardial infarction, etc. Airway smooth muscle (ASM) also exhibits robust Ca(2+), K(+), and Cl(-) currents, and there are elaborate signaling pathways that regulate them. It is easy, then, to presume that these also play a central role in contraction/relaxation of ASM. However, several lines of evidence speak to the contrary. Also, too many researchers in the ASM field view the sarcoplasmic reticulum as being centrally located and displacing its contents uniformly throughout the cell, and they have focused almost exclusively on the initial single [Ca(2+)] spike evoked by excitatory agonists. Several recent studies have revealed complex spatial and temporal heterogeneity in [Ca(2+)](i), the significance of which is only just beginning to be appreciated. In this review, we will compare what is known about ion channels in ASM with what is believed to be their roles in ASM physiology. Also, we will examine some novel ionic mechanisms in the context of Ca(2+) handling and excitation-contraction coupling in ASM.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.011 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".