Effect of β<sub>2</sub>-adrenoceptor agonists and other cAMP-elevating agents on inflammatory gene expression in human ASM cells: a role for protein kinase A
Bibliographic record
Abstract
In diseases such as asthma, airway smooth muscle (ASM) cells play a synthetic role by secreting inflammatory mediators such as granulocyte-macrophage colony-stimulating factor (GM-CSF), IL-6, or IL-8 and by expressing surface adhesion molecules, including ICAM-1. In the present study, PGE(2), forskolin, and short-acting (salbutamol) and long-acting (salmeterol and formoterol) beta(2)-adrenoceptor agonists reduced the expression of ICAM-1 and the release of GM-CSF evoked by IL-1beta in ASM cells. IL-1beta-induced IL-8 release was also repressed by PGE(2) and forskolin, whereas the beta(2)-adrenoceptor agonists were ineffective. In each case, repression of these inflammatory indexes was prevented by adenoviral overexpression of PKIalpha, a highly selective PKA inhibitor. These data indicate a PKA-dependent mechanism of repression and suggest that agents that elevate intracellular cAMP, and thereby activate PKA, may have a widespread anti-inflammatory effect in ASM cells. Since ICAM-1 and GM-CSF are highly NF-kappaB-dependent genes, we used an adenoviral-delivered NF-kappaB-dependent luciferase reporter to examine the effects of forskolin and the beta(2)-adrenoceptor agonists on NF-kappaB activation. There was no effect on luciferase activity measured in the presence of forskolin or beta(2)-adrenoceptor agonists. This finding is consistent with the observation that IL-1beta-induced expression of IL-6, a known NF-kappaB-dependent gene in ASM, was also unaffected by beta(2)-adrenoceptor agonists, forskolin, PGE(2), 8-bromo-cAMP, or rolipram. Collectively, these results indicate that repression of IL-1beta-induced ICAM-1 expression and GM-CSF release by cAMP-elevating agents, including beta(2)-adrenoceptor agonists, may not occur through a generic effect on NF-kappaB.
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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) | 0.002 | 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".