Protein kinase A‐mediated inhibition of T‐type Ca <sup>2+</sup> channels in the cerebral circulation
Bibliographic record
Abstract
Previous work from our laboratory documented the expression of L‐type (Ca V 1.2) and T‐type (Ca V 3.1/Ca V 3.2) Ca 2+ channels in rat cerebral arterial smooth muscle. In this study, we examine, in greater detail, the electrophysiological and regulatory properties of these voltage‐gated Ca 2+ channels. Using whole‐cell patch clamp electrophysiology and Ba 2+ as charge carrier, whole‐cell Ba 2+ current was pharmacologically subdivided into nifedipine‐sensitive and ‐insensitive components. The nifedipine‐sensitive component displayed L‐type characteristics such as slow activation/inactivation at depolarized voltages. In contrast, the nifedipine‐insensitive current displayed T‐type Ca 2+ channel properties such as fast activation/inactivation; this current could be further subdivided into Ca V 3.1 and Ca V 3.2 components based on Ni 2+ sensitivity. Modulators of Protein kinase A (PKA) were found to affect T‐type, but not the L‐type Ca 2+ channel activity in cerebral arterial smooth muscle. In greater detail, PKA activators (isoproterenol, forskolin and db‐cAMP) were observed to inhibit peak T‐type Ca 2+ current and evoke a leftward shift in the activation/inactivation kinetics. While PKA inhibitors (KT5720, PKI 14–22) did not alter the magnitude of the T‐type Ca 2+ channel current, they did prevent forskolin‐mediated inhibition. Forskolin's inhibitory effect on the T‐type Ca 2+ channel was similarly abolished by stHt31, a peptide inhibitor of A‐kinase anchoring protein. In summary, the study provides the first detailed electrophysiological delineation of L‐ and T‐type Ca 2+ channels in cerebral arterial smooth muscle. Intriguingly, it shows that T‐type Ca 2+ channels are also selectively targeted by signaling pathways that mediate arterial vasodilation.
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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".