Novel experimental results in human cardiac electrophysiology: measurement of the Purkinje fibre action potential from the undiseased human heart
Bibliographic record
Abstract
Data obtained from canine cardiac electrophysiology studies are often extrapolated to the human heart. However, it has been previously demonstrated that because of the lower density of its K(+) currents, the human ventricular action potential has a less extensive repolarization reserve. Since the relevance of canine data to the human heart has not yet been fully clarified, the aim of the present study was to determine for the first time the action potentials of undiseased human Purkinje fibres (PFs) and to compare them directly with those of dog PFs. All measurements were performed at 37 °C using the conventional microelectrode technique. At a stimulation rate of 1 Hz, the plateau potential of human PFs is more positive (8.0 ± 1.8 vs 8.6 ± 3.4 mV, n = 7), while the amplitude of the spike is less pronounced. The maximal rate of depolarization is significantly lower in human PKs than in canine PFs (406.7 ± 62 vs 643 ± 36 V/s, respectively, n = 7). We assume that the appreciable difference in the protein expression profiles of the 2 species may underlie these important disparities. Therefore, caution is advised when canine PF data are extrapolated to humans, and further experiments are required to investigate the characteristics of human PF repolarization and its possible role in arrhythmogenesis.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".