Single-Cell Mechanical Analysis of Human Pluripotent Stem Cell-Derived Cardiomyocytes for Drug Testing and Pathophysiological Studies
Bibliographic record
Abstract
Current platforms for studying the mechanical properties of human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) as single cells do not measure forces directly, require numerous assumptions, and cannot study cell mechanics at different loading conditions. We present a method for directly measuring the active and passive forces generated by single-cell hPSC-CMs at different stretch levels. Utilizing this technique, single hPSC-CMs exhibited positive length-tension relationship and appropriate inotropic, klinotropic, and lusitropic changes in response to pharmacological treatments (isoproterenol and verapamil). The unique potential of the approach for drug testing and disease modeling was exemplified by doxorubicin and omecamtiv mecarbil drug studies revealing their known actions to suppress (doxorubicin) or augment (omecamtiv mecarbil at low dose) cardiomyocyte contractility, respectively. Finally, mechanistic insights were gained regarding the cellular effects of these drugs as doxorubicin treatment led to cellular mechanical alternans and high doses of omecamtiv mecarbil suppressed contractility and worsened the cellular diastolic properties.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".