Abstract 19764: Cardiac Disease Modeling of Familial Left Ventricular Noncompaction Cardiomyopathy Using Induced Pluripotent Stem Cells
Bibliographic record
Abstract
Left ventricular noncompaction cardiomyopathy (LVNC) is thought to arise from developmental arrest of the normal compaction of ventricular heart muscle, sometime between weeks 4-8 of gestation. In normal heart development, a network of muscle bands (trabeculations) compact fully, resulting in a dense muscle and a smooth inner surface. Failure of trabecular compaction results in a muscle wall consisting of a spongy myocardium with a meshwork of trabeculations that can lead to thin dilated heart muscle and impaired muscle function. Although several disease-causing genes have been implicated in LVNC, the genetic cause remains unknown in more than 50% of patients. We hypothesize that LVNC arises from developmental arrest of the embryonic ventricular myocardial compaction process and that LVNC patients will have expression profiles reflective of this. We have identified a family with LVNC affecting 4 individuals. Through whole exome sequencing we identified a mutation in a cardiac developmental gene that was associated with the LVNC phenotype and was fully penetrant in this family. Using dermal fibroblasts from members of this family, we generated induced pluripotent stem (iPS) cells from affected and unaffected family members to identify transcriptome and functional consequences in cardiomyocytes harboring the genetic mutation. We will present our results from this genetic and cellular approach to LVNC, which allows study of the physiologic consequences of genetic mutations in relevant human cells.
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) | 0.004 | 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".