Abstract 13957: Vagal Nerve Stimulation Mitigates Atrial Fibrillation by Attenuating the Intrinsic Cardiac Local Circuit Neuronal Activity
Bibliographic record
Abstract
Background: Burst electrical stimuli delivered to intra-pericardial mediastinal nerves (MNS) during the atrial refractory period reproducibly evoke atrial fibrillation (AF), an effect dependent upon heterogeneous activation of intrinsic cardiac (IC) neurons. The objective of this study was to determine whether pre-emptive vagus nerve stimulation (VNS) alters MNS-induced neuronal imbalance within the IC neurons thereby impacting susceptibility to AF. Methods: Activities of right atrial ganglionated plexus neurons were identified in anesthetized canines (n=11) using a linear microelectrode array. IC neuron activity was characterized in response to: 1) touch and great vessel occlusion versus (2) stellate ganglion or vagal stimulation. Right MNS was evaluated in relation to evoked IC activity and the potential to induce atrial tachyarrhythmias. Responses were assessed prior to and after pre-emptive left (LCV) or right (RCV) cervical VNS (15 Hz, 500 μs; 1.2x chronotropic threshold; 3 min). Results: In control, 100% MNS sites induced AF. Pre-emptive RCV VNS prevented MNS-induced AF induction from 37% of sites; it shortened AF duration in 56% of sites. Pre-emptive LCV VNS potentiated AF in 46% of right-sided MNS sites, prevented AF in 27% of sites, shortened AF in 7% of sites; it was without effect in 20% of sites. Pre-emptive VNS induced a memory effect of ~40 minutes before the MNS-induced AF returned. VNS effects on IC neuronal responses were related primarily to neurons that responded to both touch/vessel occlusion and efferent activation, as such being defined as local circuit neurons (LCNs). A RCV VNS related decrease in IC LCNs activity (0.61±1.83 to 0.16±0.57 Hz) was correlated with reduction in AF inducibility (p<0.05). Chi-square analysis indicated that an increase in LCN neuronal synchrony during MNS-induced AF was mitigated post VNS (p<0.01). Conclusions: VNS decreases the activity of the IC LCNs while maintaining their stochastic behavior, thereby mitigating AF excitability secondary to local neural imbalances. These anti-arrhythmic effects of VNS exhibit memory. Ipsilateral VNS projections more effectively stabilize discrete IC neuronal networks, likely owing to preferential nerve distributions.
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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) | 0.004 | 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".