Use-Dependent Activation of Neuronal Kv1.2 Channel Complexes
Bibliographic record
Abstract
In excitable cells, ion channels are frequently challenged by repetitive stimuli, and their responses shape cellular behavior by regulating the duration and termination of bursts of action potentials. We have investigated the behavior of Shaker family voltage-gated potassium (Kv) channels subjected to repetitive stimuli, with a particular focus on Kv1.2. Genetic deletion of this subunit results in complete mortality within 2 weeks of birth in mice, highlighting a critical physiological role for Kv1.2. Kv1.2 channels exhibit a unique property described previously as "prepulse potentiation," in which activation by a depolarizing step facilitates activation in a subsequent pulse. In this study, we demonstrate that this property enables Kv1.2 channels to exhibit use-dependent activation during trains of very brief depolarizations. Also, Kv subunits usually assemble into heteromeric channels in the central nervous system, generating diversity of function and sensitivity to signaling mechanisms. We demonstrate that other Kv1 channel types do not exhibit use-dependent activation, but this property is conferred in heteromeric channel complexes containing even a single Kv1.2 subunit. This regulatory mechanism is observed in mammalian cell lines as well as primary cultures of hippocampal neurons. Our findings illustrate that use-dependent activation is a unique property of Kv1.2 that persists in heteromeric channel complexes and may influence function of hippocampal neurons.
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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".