Bibliographic record
Abstract
The contribution of airway smooth muscle (ASM) to asthma is critical but the multiple ways in which it may contribute to its pathobiology is still an active area of exploration. Contractile, proliferative and secretory properties relevant to asthma have been assessed. To date, studies of the contractile properties of isolated ASM have failed to demonstrate alterations in contractile properties that could explain excessive airway narrowing and airway hyperresponsiveness [1, 2], however tempting it is to attribute these features of asthma to intrinsic abnormalities of the muscle. In contrast to studies of tissue strips, cultured ASM cells demonstrate a range of “pro-asthmatic” properties that differ between cells derived from asthmatic subjects and healthy controls. For example, cultured ASM cells show enhanced stiffening when stimulated with contractile agonists [3] and proliferate more rapidly when treated with growth factors [4, 5], a property that would potentially favour a predisposition to remodelling. The pro-inflammatory phenotype is manifest as the expression of cytokines such as the neutrophilic chemoattractant CXCL8, attributable to enhanced NF-κB binding to the promoter site of CXCL8 [6]. Matrix proteins affecting ASM function and other cellular phenotypes are also secreted by ASM and are determinant of the ASM phenotype (reviewed in [7]). New insights into a potential property of airway smooth muscle cells with relevance to 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.015 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".