Optical interrogation of sympathetic neuronal effects on macroscopic cardiac monolayer dynamics
Bibliographic record
Abstract
ABSTRACT Alterations in autonomic function are known to occur in cardiac conditions including sudden cardiac death. Cardiac stimulation via sympathetic neurons can potentially trigger arrhythmias. Dissecting direct neural-cardiac interactions at the cellular level is technically challenging and understudied due to the lack of experimental model systems and methodologies. Here we demonstrate the utility of optical interrogation of sympathetic neurons and their effects on macroscopic cardiac monolayer dynamics to address research targets such as the effects of adrenergic stimulation via the release of neurotransmitters, the effect of neuronal numbers on cardiac wave behaviour and the applicability of optogenetics in mechanistic in vitro studies. We combine photo-uncaging or optogenetic neural stimulation with imaging of cardiac monolayers to measure electrical activity in an automated fashion, illustrating the power and high throughput capability of such interrogations. The methods described highlight the challenges and benefits of co-cultures as experimental model systems.
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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 | 0.000 | 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) | 0.001 | 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 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".