Vascular Induction of a Disintegrin and Metalloprotease 17 by Angiotensin II Through Hypoxia Inducible Factor 1α
Bibliographic record
Abstract
BACKGROUND: A disintegrin and metalloprotease 17 (ADAM17) is a membrane-spanning metalloprotease overexpressed in various cardiovascular diseases such as hypertension and atherosclerosis. However, little is known regarding the regulation of ADAM17 expression in the cardiovascular system. Here, we test our hypothesis that angiotensin II induces ADAM17 expression in the vasculature. METHODS: Cultured vascular smooth muscle cells were stimulated with 100 nM angiotensin II. Mice were infused with 1 μg/kg/minute angiotensin II for 2 weeks. ADAM17 expression was evaluated by a promoter-reporter construct, quantitative polymerase chain reaction, immunoblotting, and immunohistochemistry. RESULTS: In vascular smooth muscle cells, angiotensin II increased ADAM17 protein expression, mRNA, and promoter activity. We determined that the angiotensin II response involves hypoxia inducible factor 1α and a hypoxia responsive element. In angiotensin II-infused mice, marked induction of ADAM17 and hypoxia inducible factor 1α was seen in vasculatures in heart and kidney, as well as in aortae, by immunohistochemistry. CONCLUSIONS: Angiotensin II induces ADAM17 expression in the vasculatures through a hypoxia inducible factor 1α-dependent transcriptional upregulation, potentially contributing to end-organ damage in the cardiovascular system.
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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 | 0.000 |
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".