Genetic Ablation of Ca <sub>V</sub> 3.2 Channels Enhances the Arterial Myogenic Response by Modulating the RyR-BK <sub>Ca</sub> Axis
Bibliographic record
Abstract
OBJECTIVE: In resistance arteries, there is an emerging view that smooth muscle CaV3.2 channels restrain arterial constriction through a feedback response involving the large-conductance Ca(2+)-activated K(+) channel (BKCa). Here, we used wild-type and CaV3.2 knockout (CaV3.2(-/-)) mice to definitively test whether CaV3.2 moderates myogenic tone in mesenteric arteries via the CaV3.2-ryanodine receptor-BKCa axis and whether this regulatory mechanism influences blood pressure regulation. APPROACH AND RESULTS: Using pressurized vessel myography, CaV3.2(-/-) mesenteric arteries displayed enhanced myogenic constriction to pressure but similar K(+)-induced vasoconstriction compared with wild-type C57BL/6 arteries. Electrophysiological and myography experiments subsequently confirmed the inability of micromolar Ni(2+), a CaV3.2 blocker, to either constrict arteries or suppress T-type currents in CaV3.2(-/-) smooth muscle cells. The frequency of BKCa-induced spontaneous transient outward K(+) currents dropped in wild-type but not in knockout arterial smooth muscle cells upon the pharmacological suppression of CaV3.2 channel. Line scan analysis performed on en face arteries loaded with Fluo-4 revealed the presence of Ca(2+) sparks in all arteries, with the subsequent application of Ni(2+) only affecting wild-type arteries. Although CaV3.2 channel moderated myogenic constriction of resistance arteries, the blood pressure measurements of CaV3.2(-/-) and wild-type animals were similar. CONCLUSIONS: Overall, our findings establish a negative feedback mechanism of the myogenic response in which CaV3.2 channel modulates downstream ryanodine receptor-BKCa to hyperpolarize and relax arteries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".