See the light: can optogenetics restore healthy heartbeats? And, if it can, is it really worth the effort?
Bibliographic record
Abstract
Cardiac optogenetics is an exciting new methodology in which light-sensitive ion channels are expressed in heart tissue to enable optical control of bioelectricity. This technology has the potential to open new avenues for safely and effectively treating rhythm disorders in the heart with gentle beams of light. Recently, we developed a comprehensive framework for modeling cardiac optogenetics. Simulations conducted in this platform will provide insights to guide in vitro investigation and steer the development of therapeutic applications - these are the first steps toward clinical translation. In this editorial, we review literature relevant to light-sensitive protein delivery and intracardiac illumination to provide a holistic feasibility assessment for optogenetics-based arrhythmia termination therapy. We then draw on examples from computational work to show that the optical control paradigm has undeniable advantages that cannot be attained with conventional electrotherapy. Hence, we argue that cardiac optogenetics is more than a flashy substitute for current approaches.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".