SCN5A mutation (T1620M) causing Brugada syndrome exhibits different phenotypes when expressed in <i>Xenopus</i> oocytes and mammalian cells
Bibliographic record
Abstract
Brugada syndrome is a hereditary cardiac disease causing abnormal ST segment elevation in the ECG, right bundle branch block, ventricular fibrillation and sudden death. In this study we characterized a new mutation in the SCN5A gene (T1620M), causing the Brugada syndrome. The mutated channels were expressed in both Xenopus leavis oocytes and in mammalian tsA201 cells with and without the beta-subunit and studied using the patch clamp technique. Opposite phenotypes were observed depending on the expression system. T1620M mutation led to a faster recovery from inactivation and a shift of steady-state inactivation to more positive voltages when expressed in Xenopus oocytes. However, using the mammalian expression system no effect on steady-state inactivation was observed, but this mutation led to a slower recovery from inactivation. Our finding supports the idea that the slower recovery from inactivation of the cardiac sodium channels seen in our mammalian expression system could decrease the density of sodium channels during the cardiac cycle explaining the in vivo arrhythmogenesis in patients with Brugada syndrome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".