Network interactions within the intrinsic cardiac nervous system: Implications for reflex control of regional cardiac function
Bibliographic record
Abstract
Objective To determine how aggregates of intrinsic cardiac (IC) neurons transduce the cardiovascular milieu vs respond to changes in central drive. Also to determine how IC network interactions, subsequent to induced neural imbalances, subserve the genesis of atrial fibrillation (AF). Methods Activity from multiple IC neurons within the right atrial ganglionated plexus was recorded from anesthetized canines. Induced changes in IC neuronal activity were evaluated in response to: (1) cardiac touch; (2) electrical activation of the cervical vagus or stellate ganglia; (3) occlusion of the inferior vena cava or thoracic aorta; (4) focal left ventricular ischemia and (5) neurally induced atrial arrhythmias (AF). Results The majority of IC neurons were local circuit in nature and in basal states displayed low level functional interconnectivity. The majority of IC neurons received indirect central inputs (vagus and stellate) and a lesser proportion transduced the cardiac milieu including responding to multimodal stressors applied to the great vessels and heart. In response to mediastinal nerve stimulation most IC neurons became excessive excited and their functional interconnectivity enhanced; such network behavior preceding and continuing throughout AF. Conclusion Stochastic interactions among IC neuronal populations underlie control of regional cardiac function. (Supported by HL71830)
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".