Neuromodulation of the intrinsic cardiac nervous system attenuates the formation of neurally‐induced atrial arrhythmias
Bibliographic record
Abstract
The objective was to determine whether neurally‐induced atrial fibrillation (AF) differentially activates intrinsic cardiac neurons (ICN) and whether electrical or pharmacological modulation of ICN activity can reduce the arrhythmogenic potential. Trains of 5 electrical stimuli (1ms) were delivered during the atrial refractory period to mediastinal nerves (MSNS) on the right atria at the pericardial reflection to evoked AF. Recordings of neuronal activity were obtained from right atrial ganglionated plexus (RAGP) in response to MSNS prior to and following neuromodulation involving either pre‐emptive spinal cord stimulation (SCS) or ganglionic blockade (hexamethonium). MSNS evoked a ~4‐fold increase in RAGP neuronal activity, which SCS reduced by 43%. Hexamethonium blocked the MSNS evoked increase in RAGP neuronal activation. MSNS evoked atrial fibrillation/flutter in 78% of right‐sided nerve sites stimulated, which SCS reduced to 33% and hexamethonium reduced to 7%. MSNS induced bradycardia was maintained with SCS, but mitigated by hexamethonium. We conclude that MSNS activates subpopulations of intrinsic cardiac neurons resulting in the formation of atrial arrhythmias leading to atrial fibrillation. Stabilization of ICN local circuit neurons with SCS or local circuit and autonomic efferent projections with hexamethonium reduces the arrhythmogenic potential. (HL71830)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".