Re-entrant waves demonstrated in human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs: using light to create reentrant pathways in a cardiac substrate
Bibliographic record
Abstract
Abnormal heart rhythms are a leading cause of mortality worldwide.Tachycardias, which are abnormally fast heart rhythms, can be caused by a circulating wave of excitation referred to as reentry.Patients who previously experienced a myocardial infarction are at a particularly high risk of developing re-entrant rhythms, as scarring can create the requisite pathway.Anatomical cardiac re-entry occurs when an impulse propagates in a circuit around an inexcitable obstacle instead of terminating at the base of the ventricles at the end of the cardiac cycle.In this thesis, I carried out experimental studies using novel techniques in tissue patterning to investigate plausible mechanisms of re-entry formation.The model system consists of a monolayer of human induced pluripotent stem cells differentiated into cardiomyocytes (hiPSCs) and sensitized to light by expression of Channelrhodopsin-2 (ChR2), a light activated channel.By incorporating CHR2, precise short pulses (<100 ms) of patterned light could be applied to stimulate the monolayers.By applying long pulses (>500 ms) of patterned light to the monolayer, conduction block could be provoked in the illuminated region.The light exposure parameters and patterns can be readily changed anytime during the experiment.These results demonstrate that an all optical dynamical approach is feasible to both stimulate and induce regions of block in the monolayer.This investigation provides a novel strategy for studying the mechanisms of arrhythmia generation in a model system that may lead to insights for treatment options.
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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) | 0.000 | 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 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".