p42/p44 MAP kinase activation is localized to caveolae-free membrane domains in airway smooth muscle
Bibliographic record
Abstract
Caveolae are abundant plasma membrane invaginations in airway smooth muscle that may function as preorganized signalosomes by sequestering and regulating proteins that control cell proliferation, including receptor tyrosine kinases (RTKs) and their signaling effectors. We previously demonstrated, however, that p42/p44 MAP kinase, a critical effector for cell proliferation, does not colocalize with RTKs in caveolae of quiescent airway myocytes. Therefore, we investigated the subcellular sites of growth factor-induced MAP kinase activation. In quiescent myocytes, though epidermal growth factor receptor (EGFR) was almost exclusively found in caveolae, p42/p44 MAP kinase, Grb2, and Raf-1 were absent from these membrane domains. EGF induced concomitant phosphorylation of caveolin-1 and p42/p44 MAP kinase; however, EGF did not promote the localization of p42/p44 MAP kinase, Grb2, or Raf-1 to caveolae. Interestingly, stimulation of muscarinic M(2) and M(3) receptors that were enriched in caveolae-deficient membranes also induced p42/p44 MAP kinase phosphorylation, but this occurred in the absence of caveolin-1 phosphorylation. This suggests that the localization of receptors to caveolae and interaction with caveolin-1 is not directly required for p42/p44 MAP kinase phosphorylation. Furthermore, we found that EGF exposure induced rapid translocation of EGFR from caveolae to caveolae-free membranes. EGFR trafficking coincided temporally with EGFR and p42/p44 MAP kinase phosphorylation. Collectively, this indicates that although caveolae sequester some receptors associated with p42/p44 MAP kinase activation, the site of its activation is associated with caveolae-free membrane domains. This reveals that directed trafficking of plasma membrane EGFR is an essential element of signal transduction leading to p42/p44 MAP kinase activation.
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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".