Endothelin-1 Regulates Proliferative Responses, both alone and Synergistically with PDGF, in Rat Tracheal Smooth Muscle Cells
Bibliographic record
Abstract
The peptide, endothelin-1 (ET-1) regulates proliferative responses in numerous cell types. Recently, a dual ET receptor antagonist was shown to prevent the increase in airway smooth muscle cell (SMC) proliferation that accompanies airway smooth muscle remodeling in a rat model of experimental asthma. Thus, we used [(3)H]-thymidine incorporation assays and western immunoblotting to identify signaling pathways that regulate proliferative responses in cultured rat tracheal SMC. Our data indicate that ET-1 activation of the ET A receptor subtype induced [(3)H]-thymidine incorporation and activation of ERK 1/2 in primary rat tracheal SMC. ET-1-induced [(3)H]-thymidine incorporation and activation of ERK 1/2 were inhibited by pretreatment of SMC with pertussis toxin or down regulation of phorbol ester responsive isoforms of PKC. While ET- 1-induced ERK 1/2 activation was unaffected following inhibition of Rho kinase, ET-1-induced [(3)H]-thymidine incorporation was abrogated. ET-1 also potentiated [(3)H]-thymidine incorporation as well as cell proliferation of SMC stimulated with PDGF-BB and this response did not appear to be regulated by ERK1/ 2. These data demonstrate that ET-1 induces activation of multiple G proteins that regulate rat tracheal SMC proliferative responses, likely through signaling pathways downstream of ERK1/2 and Rho kinase.
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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".