Electrotonic coupling of excitable and nonexcitable cells in the heart revealed by optogenetics
Bibliographic record
Abstract
Electrophysiological studies of excitable organs usually focus on action potential (AP)-generating cells, whereas nonexcitable cells are generally considered as barriers to electrical conduction. Whether nonexcitable cells may modulate excitable cell function or even contribute to AP conduction via direct electrotonic coupling to AP-generating cells is unresolved in the heart: such coupling is present in vitro, but conclusive evidence in situ is lacking. We used genetically encoded voltage-sensitive fluorescent protein 2.3 (VSFP2.3) to monitor transmembrane potential in either myocytes or nonmyocytes of murine hearts. We confirm that VSFP2.3 allows measurement of cell type-specific electrical activity. We show that VSFP2.3, expressed solely in nonmyocytes, can report cardiomyocyte AP-like signals at the border of healed cryoinjuries. Using EM-based tomographic reconstruction, we further discovered tunneling nanotube connections between myocytes and nonmyocytes in cardiac scar border tissue. Our results provide direct electrophysiological evidence of heterocellular electrotonic coupling in native myocardium and identify tunneling nanotubes as a possible substrate for electrical cell coupling that may be in addition to previously discovered connexins at sites of myocyte-nonmyocyte contact in the heart. These findings call for reevaluation of cardiac nonmyocyte roles in electrical connectivity of the heterocellular heart.
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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".