Human Stem Cell-Derived Cardiac Model of Chronic Drug Exposure
Bibliographic record
Abstract
Animal models have been instrumental in providing insight into the molecular basis of disease. While such information has been successfully applied to the study of human disease, this translation would be significantly strengthened by the availability of models based on human cells. This would be particularly important for cardiovascular disease, as the physiology of human cardiomyocytes (CMs) differs significantly from rodents. Here, we have generated a three-dimensional human engineered cardiac tissue, termed biowire, from human embryonic stem cell-derived CMs to investigate the effects of chronic (7 day) treatment with isoproterenol, endothelin-1, or angiotensin II. We show that biowires chronically treated with either isoproterenol, endothelin-1, or angiotensin II have disrupted myofibril alignment and significantly reduced force of contraction. Isoproterenol-treated biowires have upregulated brain natriuretic peptide and atrial natriuretic peptide gene expression. Endothelin-1 and angiotensin II-treated biowires demonstrated a significantly increased cell size. Endothelin-1-treated biowires exhibited increased cardiac troponin secretion into the culture media. This demonstrates that human biowires treated for 7 days with isoproterenol, angiotensin II, or endothelin-1 exhibit some changes compatible with hypertrophic cardiomyopathy.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".