S-Glutathionylation of Ion Channels: Insights into the Regulation of Channel Functions, Thiol Modification Crosstalk, and Mechanosensing
Bibliographic record
Abstract
SIGNIFICANCE: Ion channels control membrane potential, cellular excitability, and Ca(++) signaling, all of which play essential roles in cellular functions. The regulation of ion channels enables cells to respond to changing environments, and post-translational modification (PTM) is one major regulation mechanism. RECENT ADVANCES: Many PTMs (e.g., S-glutathionylation, S-nitrosylation, S-palmitoylation, S-sulfhydration, etc.) targeting the thiol group of cysteine residues have emerged to be essential for ion channels regulation under physiological and pathological conditions. CRITICAL ISSUES: Under oxidative stress, S-glutathionylation could be a critical PTM that regulates many molecules. In this review, we discuss S-glutathionylation-mediated structural and functional changes of ion channels. Criteria for testing S-glutathionylation, methods and reagents used in ion channel S-glutathionylation studies, and thiol modification crosstalk, are also covered. Mechanotransduction, and S-glutathionylation of the mechanosensitive KATP channel, are discussed. FUTURE DIRECTIONS: Further investigation of the ion channel S-glutathionylation, especially the physiological significance of S-glutathionylation and thiol modification crosstalk, could lead to a better understanding of the thiol modifications in general and the ramifications of such modifications on cellular functions and related diseases.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".