Phophatidylinositol-3 Kinase/Mammalian Target of Rapamycin/p70 <i> <sup>S6K</sup> </i> Regulates Contractile Protein Accumulation in Airway Myocyte Differentiation
Bibliographic record
Abstract
Increased airway smooth muscle in airway remodeling results from myocyte proliferation and hypertrophy. Skeletal and vascular smooth muscle hypertrophy is induced by phosphatidylinositide-3 kinase (PI(3) kinase) via mammalian target of rapamycin (mTOR) and p70S6 kinase (p70S6K). We tested the hypothesis that this pathway regulates contractile protein accumulation in cultured canine airway myocytes acquiring an elongated contractile phenotype in serum-free culture. In vitro assays revealed a sustained activation of PI(3) kinase and p70S6K during serum deprivation up to 12 d, with concomitant accumulation of SM22 and smooth muscle myosin heavy chain (smMHC) proteins. Immunocytochemistry revealed that activation of PI3K/mTOR/p70S6K occurred almost exclusively in myocytes that acquire the contractile phenotype. Inhibition of PI(3) kinase or mTOR with LY294002 or rapamycin blocked p70S6K activation, prevented formation of large elongated contractile phenotype myocytes, and blocked accumulation of SM22 and smMHC. Inhibition of MEK had no effect. Steady-state mRNA abundance for SM22 and smMHC was unaffected by blocking p70S6K activation. These studies provide primary evidence that PI(3) kinase and mTOR activate p70S6K in airway myocytes leading to the accumulation of contractile apparatus proteins, differentiation, and growth of large, elongated contractile phenotype airway smooth muscle cells.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".