Innervation and Neuronal Control of the Mammalian Sinoatrial Node a Comprehensive Atlas
Bibliographic record
Abstract
Rationale: Cardiac function is under exquisite intrinsic cardiac neural control. Neuroablative techniques to modulate control of cardiac function are currently being studied in patients, albeit with variable and sometimes deleterious results. Objective: Recognizing the major gaps in our understanding of cardiac neural control, we sought to evaluate neural regulation of impulse initiation in the sinoatrial node (SAN) as an initial discovery step. Methods and Results: We report an in-depth, multiscale structural and functional characterization of the innervation of the SAN by the right atrial ganglionated plexus (RAGP) in porcine and human hearts. Combining intersectional strategies, including tissue clearing, immunohistochemical, and ultrastructural techniques, we have delineated a comprehensive neuroanatomic atlas of the RAGP-SAN complex. The RAGP shows significant phenotypic diversity of neurons while maintaining predominant cholinergic innervation. Cellular and tissue-level electrophysiological mapping and ablation studies demonstrate interconnected ganglia with synaptic convergence within the RAGP to modulate SAN automaticity, atrioventricular conduction, and left ventricular contractility. Using this approach, we comprehensively demonstrate that intrinsic cardiac neurons influence the pacemaking site in the heart. Conclusions: This report provides an experimental demonstration of a discrete neuronal population controlling a specific geographic region of the heart (SAN) that can serve as a framework for further exploration of other parts of the intrinsic cardiac nervous system (ICNS) in mammalian hearts and for developing targeted therapies.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".