Sodium current deficit and arrhythmogenesis in a murine model of plakophilin-2 haploinsufficiency
Bibliographic record
Abstract
AIMS: The shRNA-mediated loss of expression of the desmosomal protein plakophilin-2 leads to sodium current (I(Na)) dysfunction. Whether pkp2 gene haploinsufficiency leads to I(Na) deficit in vivo remains undefined. Mutations in pkp2 are detected in arrhythmogenic right ventricular cardiomyopathy (ARVC). Ventricular fibrillation and sudden death often occur in the 'concealed phase' of the disease, prior to overt structural damage. The mechanisms responsible for these arrhythmias remain poorly understood. We sought to characterize the morphology, histology, and ultrastructural features of PKP2-heterozygous-null (PKP2-Hz) murine hearts and explore the relation between PKP2 abundance, I(Na) function, and cardiac electrical synchrony. METHODS AND RESULTS: Hearts of PKP2-Hz mice were characterized by multiple methods. We observed ultrastructural but not histological or gross anatomical differences in PKP2-Hz hearts compared with wild-type (WT) littermates. Yet, in myocytes, decreased amplitude and a shift in gating and kinetics of I(Na) were observed. To further unmask I(Na) deficiency, we exposed myocytes, Langendorff-perfused hearts, and anaesthetized animals to a pharmacological challenge (flecainide). In PKP2-Hz hearts, the extent of flecainide-induced I(Na) block, impaired ventricular conduction, and altered electrocardiographic parameters were larger than controls. Flecainide provoked ventricular arrhythmias and death in PKP2-Hz animals, but not in the WT. CONCLUSIONS: PKP2 haploinsufficiency leads to I(Na) deficit in murine hearts. Our data support the notion of a cross-talk between desmosome and sodium channel complex. They also suggest that I(Na) dysfunction may contribute to generation and/or maintenance of arrhythmias in PKP2-deficient hearts. Whether pharmacological challenges could help unveil arrhythmia risk in patients with mutations or variants in PKP2 remains undefined.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".