Differential Regulation of Hypoxia-Inducible Factor-1 through Receptor Tyrosine Kinase Transactivation in Vascular Smooth Muscle Cells
Bibliographic record
Abstract
Hypoxia-inducible factor-1 (HIF-1) is a decisive element for the transcriptional regulation of many genes expressed in hypoxic conditions. In vascular smooth muscle cells, the vasoactive hormone angiotensin II (Ang II) is a very potent inducer and activator of HIF-1. As opposed to hypoxia, which induces HIF-1alpha by protein stabilization, Ang II induced HIF-1alpha through transcriptional and translational mechanisms. Interestingly, a number of intracellular signaling events triggered by Ang II are mediated by the transactivation of receptor tyrosine kinases. The major receptor tyrosine kinases shown to be transactivated by Ang II in vascular smooth muscle cells are the epidermal growth factor receptor and the IGF-I receptor. In this study, we demonstrate that the transactivation of both these receptor tyrosine kinases is involved in HIF-1 complex activation by Ang II. More interestingly, this modulation of HIF-1 is at different degrees and through different pathways. Our results show that transactivation of IGF-I receptor is essential for HIF-1alpha protein translation through phosphatidylinositol 3-kinase/p70S6 kinase pathway activation, and epidermal growth factor receptor transactivation is implicated in HIF-1 complex activation through the stimulation of the p42/p44 MAPK pathway. Our results therefore show that Ang II-induced receptor tyrosine kinase transactivation is essential in both the induction and activation of HIF-1. These findings identify novel and intricate signaling mechanisms involved in HIF-1 complex activation.
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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 | 0.000 | 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) | 0.000 | 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".