Blockade of <i>I</i><sub>Ks</sub> by HMR 1556 increases the reverse rate‐dependence of refractoriness prolongation by dofetilide in isolated rabbit ventricles
Bibliographic record
Abstract
1. The rate-dependent contributions of the rapid and slow components of the cardiac delayed rectifier K+ current (IKr and IKs, respectively) to repolarization are not fully understood. It is unclear whether the addition of IKs block will attenuate reverse rate-dependence seen after IKr block. 2. The individual and combined electrophysiological effects of selective IKr and IKs blockers, dofetilide and HMR 1556, respectively, were evaluated using Langendorff-perfused rabbit hearts. Monophasic action potential duration at 90% repolarization (MAPD90) and ventricular effective refractory period (VERP) were determined at cycle lengths (CLs) of 200-500 ms (at 50 ms intervals). 3. Dofetilide (1-100 nM) prolonged MAPD90 in a concentration-dependent manner (P < 0.001, n = 6) with reverse rate-dependence (P < 0.0001). In contrast, HMR 1556 (10-240 nM) alone did not prolong MAPD90. However, in the presence of 7.5 nM dofetilide, HMR 1556 (100 nM) increased the extent of reverse rate-dependence by further prolonging MAPD90 at CLs of 400, 450 and 500 ms (P < 0.05, n = 9) and, to a lesser extent, at shorter CLs (e.g. by 17 +/- 4 ms at CL 500 vs 2 +/- 3 ms at CL 200 ms). 4. Effects of dofetilide and HMR 1556 on VERP were similar to those on MAPD90. The slope of the VERP vs CL relation was steeper after the combination (0.081 +/- 0.013) than after dofetilide alone (0.028 +/- 0.018, P < 0.01, n = 9). 5. Blockade of rabbit IKs increased reverse rate-dependence of IKr block.
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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) | 0.001 | 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".