The proinflammatory actions of angiotensin II are mediated through the phosphorylation of p65/Rel A on Ser 536
Bibliographic record
Abstract
Objectif The proinflammatory actions of Angiotensin II (Ang II), through the activation of NF‐κB transcription factor, are though to be involved in the development of atherosclerosis. However the signaling pathways leading to the activation of NF‐κB by Ang II needs further investigations. Methods Vascular smooth muscle cells (VSMC) in culture were left untreated or preexposed to pharmacological inhibitors or siRNA duplexes both targeting the IκB kinase (IKK) complex as well as the MEK‐ERK‐RSK cascade. Cells were then stimulated with Ang II. Different biochemical assays were performed to determine the signaling pathways involved in activation of NF‐κB. These assays included: Electromobility shift assays (EMSA), in vitro kinase assays, Western blot and RT‐PCR analysis, and chromatine immunoprecipitation (ChIP) assays. Results The phosphotransferase activity of the IKK complex, the DNA binding activity of NF‐κB and the inductions of the NF‐κB‐related gene IL‐6 were all increased in Ang II‐treated VSMC. Intriguinly no serine 32 phosphorylation nor degradation of IκBα were observed. Instead, we observed that Ang II treatment led to the phosphorylation of p65 on Ser‐536 in an RSK‐independent manner. In addition, we observed a significative recruitment of p65 Ser‐536 to the IL‐6 promoter in Ang II‐treated cells. Conclusion Our data demonstrate that part of the proinflammatory activities of AngII are likely dependent on phosphorylation of p65 on Ser‐536. Since RSK is not involved in this process, we suggest that the IKK complex is responsible of the detected phosphop65 signal in Ang II‐treated VSMC. This study is supported by the IRSC.
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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) | 0.004 | 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".