Understanding how exercise and standard-of-care drugs affect iPSC-derived cardiomyocytes from a male ACM patient
Bibliographic record
Abstract
Arrhythmogenic Cardiomyopathy (ACM) is a heart disease causing sudden cardiac death and heart failure. There is a large population of ACM patients in Newfoundland and Labrador (NL) with an autosomal dominant mutation in the TMEM43 gene (TMEM43-S358L). The Esseltine lab collected dermal punch biopsies from several NL ACM patients harbouring the TMEM43 mutation and genetically reprogrammed these skin cells into induced pluripotent stem cells (iPSCs). Additionally, we sought to investigate the fibrosis component of the disease using ACM patient dermal fibroblasts. However, IPSCs can differentiate into any cell type in the body, including cardiomyocytes. The two largest factors for severe disease presentation include being male and engaging in exercise. Although it is unknown how exercise exacerbates arrhythmogenicity in ACM, it is postulated to occur through adrenaline stimulation of the β-adrenergic receptor. In fact, β-blockers are standard-of-care treatment for ACM patients. Therefore, we are investigating how male ACM patient-derived iPSC-cardiomyocytes respond to the β-adrenergic receptor modulation. Unstimulated male ACM iPSC-cardiomyocytes demonstrate disturbed contraction frequencies and aberrations in calcium handling compared to unaffected male control iPSC-cardiomyocytes. β-adrenergic modulation did not affect the frequency of contraction for ACM patient iPSC-CMs. Dermal fibroblasts experiments showed fibrotic features for the ACM patient fibroblasts. Future studies will identify personalized treatment strategies for ACM patients, and how the TMEM43-S358L mutation leads to cardiac fibrosis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".