Seeing the Light: The Use of Zebrafish for Optogenetic Studies of the Heart
Bibliographic record
Abstract
Optogenetics, involving the optical measurement and manipulation of cellular activity with genetically encoded light-sensitive proteins (“reporters” and “actuators”), is a powerful experimental technique for probing (patho-)physiological function. Originally developed as a tool for neuroscience, it has now been utilized in cardiac research for over a decade, providing novel insight into the electrophysiology of the healthy and diseased heart. Among the pioneering cardiac applications of optogenetic actuators were studies in zebrafish, which first demonstrated their use for precise spatiotemporal control of cardiac activity. Zebrafish were also adopted early as an experimental model for the use of optogenetic reporters, including genetically encoded voltage- and calcium-sensitive indicators. Beyond optogenetic studies, zebrafish are becoming an increasingly important tool for cardiac research, as they combine many of the advantages of integrative and reduced experimental models. The zebrafish has striking genetic and functional cardiac similarities to that of mammals, its genome is fully sequenced and can be modified using standard techniques, it has been used to recapitulate a variety of cardiac diseases, and it allows for high-throughput investigations. For optogenetic studies, zebrafish provide additional advantages, as the whole zebrafish heart can be visualized and interrogatedin vivoin the transparent, externally developing embryo, and the relatively small adult heart allows forin situcell-specific observation and control not possible in mammals. With the advent of increasingly sophisticated fluorescence imaging approaches and methods for spatially-resolved light stimulation in the heart, the zebrafish represents an experimental model with unrealized potential for cardiac optogenetic studies. In this review we summarize the use of zebrafish for optogenetic investigations in the heart, highlighting their specific advantages and limitations, and their potential for future cardiac research.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".