Th17‐associated cytokines promote human airway smooth muscle cell proliferation
Bibliographic record
Abstract
Increased airway smooth muscle (ASM) mass is a hallmark of airway remodeling in severe asthma. Th17-associated cytokines, particularly IL-17A, IL-17F, and IL-22, have been postulated to play a role in the pathogenesis of asthma. To investigate the in vitro effect of Th17 cytokines on the proliferation and survival of airway smooth muscle cells (ASMCs), human ASMCs from asthmatic and nonasthmatic subjects were incubated with IL-17A, IL-17F, or IL-22. The aforementioned cytokines demonstrated an ability to promote proliferation and survival of ASMCs from asthmatic and nonasthmatic subjects, which were mediated by selective activation of their corresponding receptors on ASMCs, including IL-17RA, IL-17RC, or IL-22R1, respectively. IL-17A and IL-17F-induced proliferation of ASMCs was dependent on ERK1/2 MAPK pathway, while IL-22-induced proliferation involved both ERK1/2 MAPK and NF-κB pathways. The involvement of signaling pathways was further confirmed by the inhibition of proliferation by knockdown of ERK1/2 MAPK or NF-κB p65 expression with pathway-specific siRNA. Together, our results show that Th17-associated cytokines promote proliferation and reduce the apoptotic rate of human ASMCs, raising the possibility that Th17 cytokines may contribute to increasing airway smooth muscle mass and airway remodeling in 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) | 0.000 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".