A Direct Demonstration of Closed-State Inactivation of K+ Channels at Low pH
Bibliographic record
Abstract
Lowering external pH reduces peak current and enhances current decay in Kv and Shaker-IR channels. Using voltage-clamp fluorimetry we directly determined the fate of Shaker-IR channels at low pH by measuring fluorescence emission from tetramethylrhodamine-5-maleimide attached to substituted cysteine residues in the voltage sensor domain (M356C to R362C) or S5-P linker (S424C). One aspect of the distal S3-S4 linker alpha-helix (A359C and R362C) reported a pH-induced acceleration of the slow phase of fluorescence quenching that represents P/C-type inactivation, but neither site reported a change in the total charge movement at low pH. Shaker S424C fluorescence demonstrated slow unquenching that also reflects channel inactivation and this too was accelerated at low pH. In addition, however, acidic pH caused a reversible loss of the fluorescence signal (pKa = 5.1) that paralleled the reduction of peak current amplitude (pKa = 5.2). Protons decreased single channel open probability, suggesting that the loss of fluorescence at low pH reflects a decreased channel availability that is responsible for the reduced macroscopic conductance. Inhibition of inactivation in Shaker S424C (by raising external K(+) or the mutation T449V) prevented fluorescence loss at low pH, and the fluorescence report from closed Shaker ILT S424C channels implied that protons stabilized a W434F-like inactivated state. Furthermore, acidic pH changed the fluorescence amplitude (pKa = 5.9) in channels held continuously at -80 mV. This suggests that low pH stabilizes closed-inactivated states. Thus, fluorescence experiments suggest the major mechanism of pH-induced peak current reduction is inactivation of channels from closed states from which they can activate, but not open; this occurs in addition to acceleration of P/C-type inactivation from the open state.
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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 | 0.001 |
| 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".