Decoding of synaptic voltage waveforms by specific classes of recombinant high‐threshold Ca<sup>2+</sup> channels
Bibliographic record
Abstract
Studies suggest that the preferential role of L-type voltage-sensitive Ca(2+) channels (VSCCs) in coupling strong synaptic stimulation to transcription is due to their selective activation of local chemical events. However, it is possible that selective activation of the L-type channel by specific voltage waveforms also makes a contribution. To address this issue we have examined the response of specific Ca(2+) channel types to simulated complex voltage waveforms resembling those encountered during synaptic plasticity (gamma and theta firing frequency). L-, P/Q- and N-type VSCCs (alpha1C, alpha1A, alpha1B/beta1B/alpha2delta, respectively) were all similarly activated by brief action potential (AP) waveforms or sustained step depolarization. When complex waveforms containing large excitatory postsynaptic potentials (EPSPs), APs and spike accommodation were applied under voltage clamp we found that the integrated L-type VSCC current was approximately three times larger than that produced by the P/Q- or N-type Ca(2+) channels (gamma frequency 1 s stimulation). For P/Q- or N-type channels the complex waveforms led to a smaller current than that expected from the response to a simple 1 s step depolarization to 0 or +20 mV. EPSPs present in the waveforms favoured the inactivation of P/Q- and N-type channels. In contrast, activation of the L-type channel was dependent on both EPSP- and AP-mediated depolarization. Expression of P/Q-type channels with reduced voltage-dependent inactivation (alpha1A/beta2A/alpha2delta) or the use of hyperpolarized intervals between AP stimuli greatly increased their response to complex voltage stimuli. We propose that in response to complex synaptic voltage waveforms P/Q- and N-type channels can undergo selective voltage-dependent inactivation leading to a Ca(2+) current mediated predominantly by L-type channels.
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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 | 0.001 |
| 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 | 0.001 |
| 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".