Mechanical stretch increases Kv1.5 current through an interaction between the S1–S2 linker and N-terminus of the channel
Bibliographic record
Abstract
The voltage-gated potassium channel Kv1.5 plays important roles in atrial repolarization and regulation of vascular tone. In the present study, we investigated the effects of mechanical stretch on Kv1.5 channels. We induced mechanical stretch by centrifuging or culturing Kv1.5-expressing HEK 293 cells and neonatal rat ventricular myocytes in low osmolarity (LO) medium and then recorded Kv1.5 current (I Kv1.5 ) in a normal, isotonic solution. We observed that mechanical stretch increased I Kv1.5 , and this increase required the intact, long, proline-rich extracellular S1–S2 linker of the Kv1.5 channel. The low osmolarity–induced I Kv1.5 increase also required an intact intracellular N terminus, which contains the binding motif for endogenous Src tyrosine kinase that constitutively inhibits I Kv1.5 . Disrupting the Src-binding motif of Kv1.5 through N-terminal truncation or mutagenesis abolished the mechanical stretch-mediated increase in I Kv1.5 . Our results further showed that the extracellular S1–S2 linker of Kv1.5 communicates with the intracellular N terminus. Although the S1–S2 linker of WT Kv1.5 could be cleaved by extracellularly applied proteinase K (PK), an N-terminal truncation up to amino acid residue 209 altered the conformation of the S1–S2 linker and made it no longer susceptible to proteinase K–mediated cleavage. In summary, the findings of our study indicate that the S1–S2 linker of Kv1.5 represents a mechanosensor that regulates the activity of this channel. By targeting the S1–S2 linker, mechanical stretch may induce a change in the N-terminal conformation of Kv1.5 that relieves Src-mediated tonic channel inhibition and results in an increase in I Kv1.5 .
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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".