Protein kinase A and the exchange protein directly activated by cAMP (Epac) modulate phenotype plasticity in human airway smooth muscle
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Platelet-derived growth factor (PDGF) modulates the airway smooth muscle (ASM) 'contractile' phenotype to a more 'proliferative' phenotype, resulting in increased proliferation and reduced contractility. Such phenotypic modulation may contribute to airway remodelling in asthma. We have previously shown that the cAMP effector molecules, protein kinase A (PKA) and the exchange protein directly activated by cAMP (Epac) inhibited PDGF-induced phenotypic modulation in bovine ASM. Here, we investigated these mechanisms in human ASM strips and cells. EXPERIMENTAL APPROACH: ASM strips were incubated with PDGF in the absence or presence of the activators of Epac (8-pCPT-2'-O-Me-cAMP) or of PKA (6-Bnz-cAMP) for 4 days. Strips were mounted for isometric contraction experiments or analysed for the expression of contractile markers. Cell proliferation was measured and proliferative markers were analysed under similar conditions. KEY RESULTS: Activation of Epac and PKA prevented PDGF-induced ASM strip hypocontractility, and restored the expression of smooth muscle actin, myosin and calponin, which had been markedly diminished by PDGF. Epac and PKA activation inhibited the PDGF-induced ASM cell proliferation and G(1)/S phase transition and the expression and phosphorylation of cell cycle regulators. CONCLUSIONS AND IMPLICATIONS: Epac and PKA maintain a normally contractile ASM phenotype in a mitogenic environment, suggesting that specific activators of Epac and PKA may be beneficial in the treatment of airway remodelling in asthma.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".