Interplay among distinct Ca<sup>2+</sup> conductances drives Ca<sup>2+</sup> sparks/spontaneous transient outward currents in rat cerebral arteries
Bibliographic record
Abstract
Key points Distinct Ca2+ channels work in a coordinated manner to grade Ca2+ spark/spontaneous transient outward currents (STOCs) in rat cerebral arteries. The relative contribution of each Ca2+ channel to Ca2+ spark/STOC production depends upon their biophysical properties and the resting membrane potential of smooth muscle. Na+/Ca2+ exchanger, but not TRP channels, can also facilitate STOC production. Abstract Ca2+ sparks are generated in a voltage‐dependent manner to initiate spontaneous transient outward currents (STOCs), events that moderate arterial constriction. In this study, we defined the mechanisms by which membrane depolarization increases Ca2+ sparks and subsequent STOC production. Using perforated patch clamp electrophysiology and rat cerebral arterial myocytes, we monitored STOCs in the presence and absence of agents that modulate Ca2+ entry. Beginning with CaV3.2 channel inhibition, Ni2+ was shown to decrease STOC frequency in cells held at hyperpolarized (−40 mV) but not depolarized (−20 mV) voltages. In contrast, nifedipine, a CaV1.2 inhibitor, markedly suppressed STOC frequency at −20 mV but not −40 mV. These findings aligned with the voltage‐dependent profiles of L‐ and T‐type Ca2+ channels. Furthermore, computational and experimental observations illustrated that Ca2+ spark production is intimately tied to the activity of both conductances. Intriguingly, this study observed residual STOC production at depolarized voltages that was independent of CaV1.2 and CaV3.2. This residual component was insensitive to TRPV4 channel modulation and was abolished by Na+/Ca2+ exchanger blockade. In summary, our work highlights that the voltage‐dependent triggering of Ca2+ sparks/STOCs is not tied to a single conductance but rather reflects an interplay among multiple Ca2+ permeable pores with distinct electrophysiological properties. This integrated orchestration enables smooth muscle to grade Ca2+ spark/STOC production and thus precisely tune negative electrical feedback.
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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".