Electrophysiological characterization of SCN5A mutations causing long QT (E1784K) and Brugada (R1512W and R1432G) syndromes
Bibliographic record
Abstract
UNLABELLED: Familial long QT syndrome (LQTS) and Brugada syndrome are two distinct human hereditary cardiac diseases known to cause ventricular tachyarrhythmias (torsade de pointes) and idiopathic ventricular fibrillation, respectively, which can both lead to sudden death. OBJECTIVE: In this study we have identified and electrophysiologically characterized, in patients having either LQTS or Brugada syndrome, three mutations in SCN5A (a cardiac sodium channel gene). METHOD: The mutant channels were expressed in a mammalian expression system and studied by means of the patch clamp technique. RESULTS: The R1512W mutation found in our first patient diagnosed with Brugada syndrome produced a slowing of both inactivation and recovery from inactivation. The R4132G mutation found in our second patient who also presented Brugada syndrome, resulted in no measurable sodium currents. Both Brugada syndrome patients showed ST segment elevation and right bundle-branch block, and had experienced syncopes. The E1784K mutation found in the LQTS showed a persistent inward sodium current, a hyperpolarized shift of the steady-sate inactivation and a faster recovery from inactivation. CONCLUSION: The different clinical manifestations of these three mutations most probably originate from the distinct electrophysiological abnormalities of the mutant cardiac sodium channels reported in this study.
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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 | 0.001 |
| 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".