Myogenic Vasoconstriction Requires Canonical G <sub>q/11</sub> Signaling of the Angiotensin II Type 1 Receptor
Bibliographic record
Abstract
Background Blood pressure and tissue perfusion are controlled in part by the level of intrinsic (myogenic) arterial tone. However, many of the molecular determinants of this response are unknown. We previously found that mice with targeted disruption of the gene encoding the angiotensin II type 1a receptor (AT1AR) ( Agtr1a ), the major murine angiotensin II type 1 receptor (AT1R) isoform, showed reduced myogenic tone; however, uncontrolled genetic events (in this case, gene ablation) can lead to phenotypes that are difficult or impossible to interpret. Methods and Results We tested the mechanosensitive function of AT1R using tamoxifen‐inducible smooth muscle‐specific AT1aR knockout (smooth muscle‐ Agtr1a −/− ) mice and studied downstream signaling cascades mediated by G q/11 and/or β‐arrestins. FR900359, Sar1Ile4Ile8‐angiotensin II (SII), TRV120027 and TRV120055 were used as selective G q/11 inhibitor and biased agonists to activate noncanonical β‐arrestin and canonical G q/11 signaling of the AT1R, respectively. Myogenic and Ang II‐induced constrictions were diminished in the perfused renal vasculature, mesenteric and cerebral arteries of smooth muscle‐ Agtr1a −/− mice. Similar effects were observed in arteries of global mutant Agtr1a −/− but not Agtr1b −/− mice. FR900359 decreased myogenic tone and angiotensin II‐induced constrictions whereas selective biased targeting of AT1R‐β‐arrestin signaling pathways had no effects. Conclusions This study demonstrates that myogenic arterial constriction requires G q/11 ‐dependent signaling pathways of mechanoactivated AT1R but not G protein‐independent, noncanonical pathways in smooth muscle cells.
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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".