The role of Ca <sup>2+</sup> influx pathways in voltage‐dependent STOC production (853.10)
Bibliographic record
Abstract
Ca 2+ sparks are generated in a voltage dependent manner to initiate spontaneous transient outward currents (STOC) that antagonize arterial constriction. In the present study, we defined the mechanisms by which membrane depolarization increases Ca 2+ sparks and subsequent STOC production. Using perforated patch clamp electrophysiology and rat cerebral arterial myocytes, we monitored STOC in the presence and absence of agents that modulate Ca 2+ entry pathways. Beginning with the Ca V 3.2 inhibitor Ni 2+ , STOC frequency decreased in cells held at hyperpolarized voltage (‐40 mV). In contrast, Ca V 1.2 inhibition with nifedipine suppressed STOC frequency at depolarized potential (‐20 mV). These findings are consistent with the voltage‐dependent profiles of L‐ and T‐type Ca 2+ channels; and were replicated in a computational model of Ca 2+ spark production. Upon concomitant Ca V 1.2 and Ca V 3.2 blockade, we further observed residual voltage‐independent STOC production. This residual component was insensitive to stimulation or inhibition of TRPV4 channels. Further ongoing work aims to investigate the involvement of other Ca 2+ entry routes. In summary, distinct Ca 2+ channel isoforms govern the voltage‐dependency of STOC production and they do so at defined membrane potentials. These findings have important mechanistic implications to the basis of negative feedback, arterial tone regulation and blood flow control.
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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 | 0.001 | 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".