2889A novel serum biomarker identifying Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC)
Bibliographic record
Abstract
Introduction: Extending the paradigm of cutaneous desmosomal disease, caused by either gene mutations or anti-desmosomal antibodies, we sought to identify antibodies to cardiac desmosomal proteins among ARVC patients. Methods: A cohort of 20 subjects with definite or borderline Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) was assessed for the presence of antibodies to any of the three cadherins present in cardiac desmosomes or adherence junctions: desmocollin-2, desmoglein-2 (DSG2), or N-cadherin compared to 32 control sera. We used DSG2 protein to assess for antibodies by both Western blot (exposed to 1:100 diluted serum) and enzyme-linked immune-sorbent assay (ELISA). A validation cohort of 25 subjects with definite ARVC from the Zurich ARVC Program was assessed using the same methods to confirm our findings. We also assessed whether antibody density correlated with the burden of premature ventricular contractions on ambulatory ECG monitor, a measure of disease burden. As an additional validation, we assessed the naturally occurring ARVC model in the Boxer dog breed, comparing serum from dogs affected by ARVC to unaffected dogs without a pedigree history of ARVC, as well as unaffected dogs with ARVC in their pedigree. Finally, we used an automated robotic system to measure gap junction function in confluent human induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) cultures by single cell small molecular weight dye injection, comparing cells exposed to patient sera with cells exposed to either normal control sera or a commercial anti- DSG2 antibody as a positive control.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".