Regulation of Cation Channel Voltage and Ca<sup>2+</sup> Dependence by Multiple Modulators
Bibliographic record
Abstract
Ion channel regulation is key to controlling neuronal excitability. However, the extent that modulators and gating factors interact to regulate channels is less clear. For Aplysia, a nonselective cation channel plays an essential role in reproduction by driving an afterdischarge in the bag cell neurons to elicit egg-laying hormone secretion. We examined the regulation of cation channel voltage and Ca2+ dependence by protein kinase C (PKC) and inositol trisphosphate (IP3)-two prominent afterdischarge signals. In excised, inside-out patches, the channel remained open longer and reopened more often with depolarization from -90 to +30 mV. As previously reported, PKC could closely associate with the channel and increase activity at -60 mV. We now show that, following the effects of PKC, voltage dependence was shifted to the left (essentially enhanced), particularly at more negative voltages. Conversely, the voltage dependence of channels lacking PKC was shifted to the right (essentially suppressed). Predictably, activity was increased at all Ca2+ concentrations following the effects of PKC; nevertheless, Ca2+ dependence was actually shifted to the right. Moreover, whereas IP3 did not alter activity at -60 mV, it drastically shifted Ca2+ dependence to the right-an outcome largely reversed by PKC. With respect to the afterdischarge, these data suggest PKC initially upregulates the channel by direct gating and shifting voltage dependence to the left. Subsequently, PKC and IP3 attenuate the channel by suppressing Ca2+ dependence. This ensures hormone delivery by allowing afterdischarge initiation and maintenance but also prevents interminable bursting. Similar regulatory interactions may be used by other neurons to achieve diverse outputs.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".