Drug screening platform using human induced pluripotent stem cell-derived atrial cardiomyocytes and optical mapping
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Current drug development efforts for the treatment of atrial fibrillation are hampered by the fact that many preclinical models have been unsuccessful in reproducing human cardiac physiology and its response to medications. In this study, we demonstrated an approach using human induced pluripotent stem cell-derived atrial and ventricular cardiomyocytes (hiPSC-aCMs and hiPSC-vCMs, respectively) coupled with a sophisticated optical mapping system for drug screening of atrial-selective compounds in vitro. We optimized differentiation of hiPSC-aCMs by modulating the WNT and retinoid signaling pathways. Characterization of the transcriptome and proteome revealed that retinoic acid pushes the differentiation process into the atrial lineage and generated hiPSC-aCMs. Functional characterization using optical mapping showed that hiPSC-aCMs have shorter action potential durations and faster Ca2+ handling dynamics compared with hiPSC-vCMs. Furthermore, pharmacological investigation of hiPSC-aCMs captured atrial-selective effects by displaying greater sensitivity to atrial-selective compounds 4-aminopyridine, AVE0118, UCL1684, and vernakalant when compared with hiPSC-vCMs. These results established that a model system incorporating hiPSC-aCMs combined with optical mapping is well-suited for preclinical drug screening of novel and targeted atrial selective compounds.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it