OptoDyCE-plate as an affordable high throughput imager for all optical cardiac electrophysiology
Bibliographic record
Abstract
We present a simple low-cost system for comprehensive functional characterization of cardiac function under spontaneous and paced conditions, in standard 96 and 384-well plates. This full-plate actuator/imager, OptoDyCE-plate, uses optogenetic stimulation and optical readouts of voltage and calcium from all wells in parallel. The system is validated with syncytia of human induced pluripotent stem cell derived cardiomyocytes, iPSC-CMs, grown as monolayers, or in quasi-3D isotropic and anisotropic constructs using electrospun matrices, in 96 and 394-well format. Genetic modifications, e.g. interference CRISPR (CRISPRi), and nine compounds of acute and chronic action were tested, including five histone deacetylase inhibitors (HDACis). Their effects on voltage and calcium were compared across growth conditions and pacing rates. We also demonstrated deployment of optogenetic cell spheroids for point pacing to study conduction in 96-well format, and the use of temporal multiplexing to register voltage and calcium simultaneously on a single camera in this stand-alone platform. Opto-DyCE-plate showed excellent performance even in the small samples in 384-well plates, in the various configurations. Anisotropic structured constructs may provide some benefits in drug testing, although drug responses were consistent across tested configurations. Differential voltage vs. calcium responses were seen for some drugs, especially for non-traditional modulators of cardiac function, e.g. HDACi, and pacing rate was a powerful modulator of drug response, highlighting the need for comprehensive multiparametric assessment, as offered by OptoDyCE-plate. Increasing throughput and speed and reducing cost of screening can help stratify potential compounds early in the drug development process and accelerate the development of safer drugs.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".