T‐ and L‐type Calcium Channels Contribute to Myogenic Tone In Cerebral Arteries
Bibliographic record
Abstract
The study scrutinized which voltage‐operated Ca 2+ channels are expressed in cerebral arterial smooth muscle cells, and what role they play in myogenic tone development. A broad RT‐PCR screen of α 1 subunits revealed mRNA expression of L‐type (Cav1.2) and T‐type (Cav3.1, and Cav3.2) Ca 2+ channels in cerebral arterial smooth muscle cells. Western blot analysis conducted on whole arteries subsequently showed that all 3 α 1 subunits were present at the protein level with T‐type expression qualitatively greater than L‐type. An immunohistochemical analysis of whole arteries revealed that Cav1.2 was primarily expressed in perivascular nerves although some limited/punctuate labeling was observable in smooth muscle. In contrast, the T‐type (Cav3.1, and Cav3.2) channels were robustly expressed in cerebral arterial smooth muscle and display defined periodicity. Functional measurements performed on cerebral arteries pressurized to 80 mmHg revealed that L‐type Ca 2+ channels blockers, such as nifidipine (50–300nM) partially attenuate myogenic tone although a near complete blockade was achievable with the further addition of Mibefradil (300nm–1μM), a T‐type Ca 2+ channel blocker. Cumulatively, these findings indicate that both L‐ and T‐type Ca 2+ channels are expressed in cerebral arterial smooth muscle cells and that both Ca 2+ channels play an important role in establishing myogenic tone in small cerebral arteries. These findings have important conceptual and therapeutic implications particularly as it relates to the treatment of cerebrovascular diseases. Supported by 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 | 0.000 |
| 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".