Insights into single hiPSC-derived cardiomyocyte phenotypes and maturation using ConTraX, an efficient pipeline for tracking contractile dynamics
Bibliographic record
Abstract
Abstract Cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs) are powerful in-vitro models to study the mechanisms underlying cardiomyopathies and cardiotoxicity. To understand how cellular mechanisms affect the heart, it is crucial to quantify the contractile function in single hiPSC-CMs over time, however, such measurements remain demanding and low-throughput, and are too seldom considered. We developed an open-access, versatile, streamlined, and highly automated pipeline to address these challenges and enable quantitative tracking of the contractile dynamics of single hiPSC- CMs over time: ConTraX . Three interlocking software modules enable: (i) parameter-based localization and selection of single hiPSC-CMs; (ii) automated video acquisition of >200 cells/hour; and (iii) streamlined measurements of the contractile parameters via traction force microscopy. Using ConTraX , we analyzed >2,753 hiPSC-CMs over time under orthogonal experimental conditions in terms of culture media and substrate stiffnesses. Using undirected high-dimensional clustering, we dissected the complex diversity of contractile phenotypes in hiPSC-CM populations and revealed converging maturation patterns. Our modular ConTraX pipeline empowers biologists with a potent quantitative analytic tool applicable to the development of cardiac therapies.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".