Early Growth Response Protein‐1 Expression by Insulin‐Like Growth Factor‐1 Requires ROS‐Dependent Activation of ERK1/2 and PKB Pathways in Vascular Smooth Muscle Cells
Bibliographic record
Abstract
Early growth response protein-1 (Egr-1) is a transcription factor that plays an important role in the regulation of several genes implicated in the pathogenesis of cardiovascular disease (CVD) such as atherosclerosis. Insulin-like growth factor-1 (IGF-1), a potent mitogen, is believed to contribute to the development of CVD through the hyperactivation of mitogenic and growth promoting pathways, including the MAPK and PKB pathways, as well as regulation of multiple transcription factors. Reactive oxygen species (ROS) have been shown to mediate the effects of IGF-1 and are believed to contribute to the pathogenesis of vascular abnormalities. We have previously shown that IGF-1 induces the expression of Egr-1 in vascular smooth muscle cells (VSMC); however, the signaling pathways involved in this process remain unexplored. Therefore, we have investigated the involvement of MAPK, PKB, and ROS in IGF-1-induced Egr-1 expression in VSMC. Treatment of VSMC with IGF-1 enhanced Egr-1 protein levels in a time and dose-dependent fashion and PD98059 and SP600125, two selective inhibitors of ERK1/2 and JNK, respectively, significantly decreased IGF-1-induced increase in Egr-1 expression in these cells. In addition, blockade of PI3-K/PKB pathways by Wortmannin/SC-66 respectively, also attenuated IGF-1-induced Egr-1 protein as well as mRNA expression. Diphenyleneiodonium (DPI), an NAD(P)H oxidase inhibitor, blocked the Egr-1 expression in response to IGF-1. In summary, these data demonstrate that ROS-dependent activation of ERK1/2/JNK, PI3-K/PKB signaling events play a critical role in IGF-1 induced expression of Egr-1 in VSMC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".