Electrophysiological Characterization of a TRPC‐like Current in Cerebral Arterial Smooth Muscle
Bibliographic record
Abstract
The goal of this investigation was to isolate and characterize a TRPC‐like current in cerebral arterial smooth muscle cells (VSMCs). Briefly, VSMCs were enzymatically isolated from rat cerebral arteries and whole cell currents monitored using patch clamp electrophysiology. Our initial experiments revealed two subpopulations of VSMCs that displayed either an outwardly rectifying or a doubly rectifying current. The reversal potential of both currents shifted with the Na(+) equilibrium potential and were potently blocked by micromolar concentrations of Gd(3+). A pharmacological characterization subsequently revealed that the doubly rectifying TRPC‐like current was insensitive to Cl(‐) channels inhibitors (DIDS and niflumic acid), amiloride and flufemamate. In contrast, tamoxifen elicited a dual effect both attenuating and activating this current at submicromolar and micromolar concentrations, respectively. Similar to findings from cultured smooth muscle cells, hyposmotic challenge and vasoconstrictor agonists (UTP) activated this TRPC‐like non selective cation current. To summarize, this study is the first to characterize the electrical and pharmacological properties of a doubly‐rectifying TRPC‐like cation current in cerebral VSMCs. Ongoing investigations continue to define the molecular composition of this TRPC‐like current along with it's mechanisms of physiological regulation.
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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".