Role of caveolin-1 in p42/p44 MAP kinase activation and proliferation of human airway smooth muscle
Bibliographic record
Abstract
Chronic airways diseases, including asthma, are associated with an increased airway smooth muscle (ASM) mass, which may contribute to chronic airway hyperresponsiveness. Increased muscle mass is due, in part, to increased ASM proliferation, although the precise molecular mechanisms for this response are not completely clear. Caveolae, which are abundant in smooth muscle cells, are membrane microdomains where receptors and signaling effectors can be sequestered. We hypothesized that caveolae and caveolin-1 play an important regulatory role in ASM proliferation. Therefore, we investigated their role in p42/p44 MAPK signaling and proliferation using human ASM cell lines. Disruption of caveolae using methyl-beta-cyclodextrin and small interfering (si)RNA-knockdown of caveolin-1 caused spontaneous p42/p44 MAPK activation; additionally, caveolin-1 siRNA induced ASM proliferation in mitogen deficient conditions, suggesting a key role for caveolae and caveolin-1 in maintaining quiescence. Moreover, caveolin-1 accumulates twofold in myocytes induced to a contractile phenotype compared with proliferating ASM cells. Caveolin-1 siRNA failed to increase PDGF-induced p42/p44 MAPK activation and cell proliferation, however, indicating that PDGF stimulation actively reversed the antimitogenic control by caveolin-1. Notably, the PDGF induced loss of antimitogenic control by caveolin-1 coincided with a marked increase in caveolin-1 phosphorylation. Furthermore, the strong association of PDGF receptor-beta with caveolin-1 that exists in quiescent cells was rapidly and markedly reduced with agonist addition. This suggests a dynamic relationship in which mitogen stimulation actively reverses caveolin-1 suppression of p42/p44 MAPK signal transduction. As such, caveolae and caveolin-1 coordinate PDGF receptor signaling, leading to myocyte proliferation, and inhibit constitutive activity of p42/p44 MAPK to sustain cell quiescence.
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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 | 0.000 |
| 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".