Syntaxin 1A Co‐Associates with Native Rat Brain and Cloned Large Conductance, Calcium‐Activated Potassium Channels <i>in situ</i>
Bibliographic record
Abstract
Large conductance, calcium-activated potassium channels (BKCa channels) are regulated by several distinct mechanisms, including phosphorylation/dephosphorylation events and protein-protein interactions. In this study, we have examined the interaction between BKCa channels and syntaxin 1A, a soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) that is reported to modulate the activity and/or localization of different classes of ion channels. Using a reciprocal co-immunoprecipitation strategy, we observed that native BKCa channels in rat hippocampus co-associate with syntaxin 1A, but not the closely related homologue syntaxin 3. This BKCa channel-syntaxin 1A interaction could be further demonstrated in a non-neuronal cell line (human embryonic kidney (HEK) 293 cells) following co-expression of rat syntaxin 1A and BKCa channels cloned from either mouse brain or bovine aorta. However, co-expression of these same channels with syntaxin 3 did not lead to a detectable protein-protein interaction. Immunofluorescent co-staining of HEK 293 cells expressing BKCa channels and syntaxin 1A demonstrated overlapping distribution of these two proteins in situ. Functionally, co-expression of BKCa channels with syntaxin 1A, but not syntaxin 3, was observed to enhance channel gating and kinetics at low concentrations (1-4 microM) of free cytosolic calcium, but not at higher concentrations (< or = 10 microM), as judged by macroscopic current recordings in excised membrane patches. Interactions between BKCa channels and neighbouring membrane proteins may thus play important roles in regulating the activity and/or distribution of these channels within specialized cellular compartments.
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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 | 0.001 |
| 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 | 0.001 |
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".