Internalization of the Kv1.4 Potassium Channel Is Suppressed by Clustering Interactions with PSD-95
Bibliographic record
Abstract
The contribution of voltage-dependent ion channels to nerve function depends upon their cell-surface distributions. Nevertheless, the mechanisms underlying channel localization are poorly understood. Two phenomena appear particularly important: the clustering of channels by membrane-associated guanylate kinases (MAGUKs), such as PSD-95, and the regional stabilization of cell-surface proteins by differential suppression of endocytosis. Could these phenomena be related? To test this possibility we examined the effect of PSD-95 on the internalization rate of Kv1.4 K(+) channels in transfected HEK293 cells using cell-surface biotinylation assays. When expressed alone Kv1.4 was internalized with a half-life of 87 min, but, in the presence of PSD-95, Kv1.4 internalization was completely suppressed. Immunochemistry and electrophysiology showed PSD-95 had little effect on total or cell-surface levels of Kv1.4 or on current amplitude, activation, or inactivation kinetics. Clustering was necessary and sufficient to suppress Kv1.4 internalization since C35S-PSD-95, a mutant reported to bind but not cluster Kv1.4, (confirmed by imaging cells co-expressing a functional, GFP-variant-tagged Kv1.4) restored and, surprisingly, enhanced the rate of Kv1.4 internalization (t((1)/(2)) = 16 min). These data argue PSD-95-mediated clustering suppresses Kv1.4 internalization and suggest a fundamentally new role for PSD-95, and perhaps other MAGUKs, orchestrating the stabilization of channels at the cell-surface.
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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 | 0.001 | 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".