Early Growth Response-1 Regulates Angiopoietin-1-Induced Endothelial Cell Proliferation, Migration, and Differentiation
Bibliographic record
Abstract
OBJECTIVE: Angiopoietin-1 (Ang-1) is an important regulator of angiogenesis in endothelial cells. It promotes migration, proliferation, and differentiation of cells, although the regulating factors involved in these processes remain unclear. In this study, we evaluated the contribution of the transcription factor early growth response-1 (Egr-1) to Ang-1-induced angiogenesis in human umbilical vein endothelial cells (HUVECs). METHODS AND RESULTS: Expression of Egr-1 was evaluated with real-time PCR and immunoblotting, whereas Egr-1 DNA binding activity was monitored with electrophoretic mobility shift assays. Cell migration was measured with wound healing and Boyden chamber assays, whereas cell proliferation and differentiation of cells into capillary-like tube structures were monitored with cell counting, BrdU incorporation and Matrigels. To selectively inhibit Egr-1 expression, we used both siRNA oligonucleotides and specific DNAzymes. Egr-1 mRNA expression rose approximately 9-fold within 2 hours of Ang-1 exposure and declined thereafter. Upregulation of Egr-1 expression was accompanied by an increase in nuclear mobilization and augmented DNA binding. These processes were mediated through the Erk1/2, PI-3 kinase/AKT, and mTOR pathways. Knockdown of Egr-1 expression completely abrogated Ang-1-induced endothelial migration and significantly reduced proliferation and capillary-like tube formation of HUVECs that overexpress Ang-1. CONCLUSIONS: Ang-1 triggers significant and transient induction of Egr-1, and Egr-1 contributes to Ang-1-induced endothelial cell migration and 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 | 0.001 |
| 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".