Role of IκB Kinase-β in the Growth-Promoting Effects of Angiotensin II In Vitro and In Vivo
Bibliographic record
Abstract
OBJECTIVE: Angiotensin II (Ang II) is implicated in processes underlying the development of arterial wall remodeling events, including cellular hypertrophy and inflammation. We previously documented the activation of IκB kinase-β (IKKβ) in Ang II-treated cells, a kinase involved in inflammatory reactions. In light of a study suggesting a role of IKKβ in angiogenesis through its effect on the tuberous sclerosis (TSC)1/2-mammalian target of rapamycin complex 1 pathway in cancer cells, we hypothesized that targeting IKKβ could reduce arterial remodeling events by affecting both the inflammatory and the growth-promoting response of Ang II. APPROACH AND RESULTS: Treatment of aortic vascular smooth muscle cells with Ang II induced the rapid and sustained phosphorylation of TSC1 on Ser511, which paralleled the activation of effectors of the mammalian target of rapamycin complex 1 pathway. Furthermore, we show that Ser511 of TSC1 acted as a phosphoacceptor site for Ang II-activated IKKβ. Consistent with this, the use of different short hairpin RNA constructs targeting IKKβ reduced Ang II-induced TSC1, S6 kinase, and eukaryotic translation initiation factor 4E-binding protein 1 phosphorylation and the rate of protein synthesis. Overexpression of TSC1 lacking Ser511 in vascular smooth muscle cells also exerted detrimental effects on the hypertrophic effect of Ang II. Furthermore, the selective IKKβ inhibitor N-(6-chloro-7-methoxy-9H-β-carbolin-8-yl)-2 methylnicotinamide reduced the inflammatory response and dose-dependently diminished Ang II-induced TSC1 phosphorylation and effectors of the mammalian target of rapamycin complex 1 pathway, leading to inhibition of protein synthesis in vitro and in rat arteries in vivo. CONCLUSIONS: Our findings provide new insights into the molecular understanding of the pathological role of Ang II and assist in identifying the beneficial effects of IKKβ inhibition for the treatment of cardiovascular diseases.
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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) | 0.003 | 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".