Heteromultimeric Kv1 Channels Contribute to Myogenic Control of Arterial Diameter
Bibliographic record
Abstract
Inhibition of vascular smooth muscle (VSM) delayed rectifier K+ channels (K(DR)) by 4-aminopyridine (4-AP; 200 micromol/L) or correolide (1 micromol/L), a selective inhibitor of Kv1 channels, enhanced myogenic contraction of rat mesenteric arteries (RMAs) in response to increases in intraluminal pressure. The molecular identity of K(DR) of RMA myocytes was characterized using RT-PCR, real-time PCR, and immunocytochemistry. Transcripts encoding the pore-forming Kvalpha subunits, Kv1.2, Kv1.4, Kv1.5, and Kv1.6, were identified and confirmed at the protein level with subunit-specific antibodies. Kvbeta transcript (beta1.1, beta1.2, beta1.3, and beta2.1) expression was also identified. Kv1.5 message was approximately 2-fold more abundant than that for Kv1.2 and Kv1.6. Transcripts encoding these three Kv1alpha subunits were approximately 2-fold more abundant in 1st/2nd order conduit compared with 4th order resistance RMAs, and Kvbeta1 was 8-fold higher than Kvbeta2 message. RMA K(DR) activated positive to -50 mV, exhibited incomplete inactivation, and were inhibited by 4-AP and correolide. However, neither alpha-dendrotoxin or kappa-dendrotoxin affected RMA K(DR), implicating the presence of Kv1.5 in all channels and the absence of Kv1.1, respectively. Currents mediated by channels because of coexpression of Kv1.2, Kv1.5, Kv1.6, and Kvbeta1.2 in human embryonic kidney 293 cells had biophysical and pharmacological properties similar to those of RMA K(DR). It is concluded that K(DR) channels composed of heteromultimers of Kv1 subunits play a critical role in myogenic control of arterial diameter.
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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".