Activation of Big Mitogen-Activated Protein Kinase-1 Regulates Smooth Muscle Cell Replication
Bibliographic record
Abstract
This study examined the activation of big mitogen-activated protein (MAP) kinase-1 (BMK1) in rat carotid smooth muscle cells (SMCs). Platelet-derived growth factor, fibroblast growth factor-2, sorbitol, and serum all increased the activation of BMK1 in rat carotid SMCs, whereas angiotensin II, phorbol esters, and tumor necrosis factor-alpha had only slight effects. With the exception of tumor necrosis factor-alpha, all these factors phosphorylated extracellular signal-regulated kinase (ERK)1/2. The MAPK kinase inhibitor (MEKI), U0126 (1 micromol/L), blocked ERK1/2 phosphorylation and at higher doses (5 micromol/L) blocked BMK1 phosphorylation. This inhibitor also blocked SMC DNA synthesis in a dose-dependent manner. When SMCs were transfected with an adenoviral construct expressing dominant mutant BMK1 and stimulated with fibroblast growth factor-2, a significantly smaller increase in cyclin D1 and cyclin A expression and in retinoblastoma factor phosphorylation was detected compared with the increase in cells transfected with an adenoviral construct expressing green fluorescent protein (GFP). SMC DNA synthesis was significantly blocked in the cells transfected with the dominant mutant BMK1. These data support the suggestion that BMK1 is important and necessary for mitogen-induced SMC proliferation.
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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 | 0.001 |
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".