Early growth response protein‐1 (Egr‐1) expression by hydrogen peroxide (H <sub>2</sub> O <sub>2</sub> ) is mediated via c‐Src and PKB‐dependent CREB signaling events in vascular smooth muscle cells (VSMC)
Bibliographic record
Abstract
Increased generation of reactive oxygen species (ROS) is believed to play a key role in the pathophysiology of cardiovascular diseases. Excessive growth and proliferation of vascular smooth muscle cells (VSMC) have been suggested to be major contributors to vascular dysfunction. A potential involvement of early growth response protein‐1 (Egr‐1), a zinc‐finger transcription factor, in the development of vascular injury has been suggested. Recent studies have shown that H 2 O 2 , one of the most stable ROS, increases Egr‐1 expression in VSMC, however, signaling events leading to H 2 O 2 ‐induced Egr‐1 expression are not fully understood. Here, we report that H 2 O 2 increased Egr‐1 expression in a time and dose‐dependent fashion in A10 VSMC and pharmacological blockade of insulin‐like growth factor‐1 receptor (IGF‐1R) and c‐Src, by AG1024 and PP2 respectively, abolished H 2 O 2 ‐induced Egr‐1 expression while AG1478, an inhibitor of the epidermal growth factor receptor (EGFR), and PP3, the inactive analog of PP2, had no effect. H 2 O 2 also stimulated the phosphorylation of PKB, and siRNA‐induced silencing of c‐Src resulted in a significant reduction in PKB phosphorylation as well Egr‐1 expression. In addition, phosphorylation of cyclic AMP response element binding protein (CREB) was also enhanced by H 2 O 2, however, inhibition of PI3K/PKB by wortmannin and SC‐66 attenuated this phosphorylation, as well as suppressed protein and mRNA levels of Egr‐1 induced by H 2 O. In summary, our data suggests that H 2 O 2 provokes Egr‐1 expression through the activation of upstream tyrosine kinases IGF‐1R and c‐Src as well as PKB and CREB‐dependent signaling events in VSMC. Support or Funding Information (Supported by CIHR) This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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) | 0.001 | 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) | 0.002 | 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".