Angiotensin II Inhibits T‐type Ca <sup>2+</sup> Channels in Cerebral Arterial Smooth Muscle Cells
Bibliographic record
Abstract
T‐type Ca 2+ channels (Ca V 3.1 and Ca V 3.2) are expressed in cerebral arterial smooth muscle cells and they play a key role in regulating arterial tone. In this study, we investigated whether and by what mechanism Angiotensin II (Ang II), a vasoactive peptide produced within the cerebral arterial wall, influences T‐type Ca 2+ channels. Using patch clamp electrophysiology and rat cerebral arterial myocytes, Ang II (100 nM) was shown to inhibit T‐type Ca 2+ currents in a time‐dependent manner (~ 40% after 15 min); it also shifted the voltage‐dependency of activation by 7 mV. Ang II induced inhibition was mediated through the AT 1 receptor, as preincubation with Losartan (1 μM) abolished the effect. Protein kinase C (PKC) blockade by GF 109203X (100 nM) did not eliminate Ang II‐mediated inhibition, demonstrating that this signaling protein was not involved. In contrast, NADPH oxidase inhibitors abolished the inhibitory effect of Ang II revealing a role for reactive oxygen species (ROS) on T‐type Ca 2+ channels. To delineate if Ang II is targeting a particular T‐type channel, Ni 2+ (50 μM) was added to selectively block Ca V 3.2. In the presence of Ni 2+ , Ang II did not induce further inhibition of the residual current, indicating that Ang II was selectively targeting Ca V 3.2. In summary, Ang II inhibits Ca V 3.2 channels in cerebral myocytes through the generation of ROS. These findings suggest that T‐type channels are a regulatory target of vasoactive stimuli, known to facilitate the “constrictive” phenotype prevalent with cerebrovascular disease. Support or Funding Information Canadian Institutes of Health Research, Alberta Innovates Health Solutions, Vanier Graduate Scholarship (CIHR)
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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 | 0.001 |
| 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".