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Record W1528862705 · doi:10.1113/jphysiol.2013.259382

Network interactions within the canine intrinsic cardiac nervous system: implications for reflex control of regional cardiac function

2013· article· en· W1528862705 on OpenAlexaff
Éric Beaumont, Siamak Salavatian, E. Marie Southerland, Alain Vinet, Vincent Jacquemet, J. Andrew Armour, Jeffrey L. Ardell

Bibliographic record

VenueThe Journal of Physiology · 2013
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsUniversité de MontréalHôpital du Sacré-Cœur de Montréal
FundersNational Heart, Lung, and Blood InstituteUniversity of Warwick
KeywordsReflexNeuroscienceCardiac function curveFunction (biology)Nervous systemCentral nervous systemMedicineCardiologyPsychologyBiologyHeart failure

Abstract

fetched live from OpenAlex

Key points Control of regional cardiac function, as mediated by the intrinsic cardiac (IC) nervous system, is dependent upon its cardiac afferent neuronal inputs, changes in its central neuronal drive and interactions mediated within via local circuit neurons. The majority of its local circuit neurons receive indirect central (sympathetic and parasympathetic) inputs, lesser proportions transducing the cardiac milieu. Fifty per cent of IC neurons exhibit cardiac cycle‐related periodicity that is primarily related to direct cardiac mechano‐sensory afferent inputs and, secondarily, to indirect central autonomic efferent inputs. In response to mediastinal nerve stimulation, most IC neurons became excessively activated in the induction of atrial arrhythmias such that their stochastic interactivity precedes and persists throughout neuronally induced atrial fibrillation. Modulation of such stochastic IC local circuit neuronal recruitment may represent a novel target for the treatment of select cardiac disease, including atrial arrhythmias. Abstract The aims of the study were to determine how aggregates of intrinsic cardiac (IC) neurons transduce the cardiovascular milieuversusresponding to changes in central neuronal drive and to determine IC network interactions subsequent to induced neural imbalances in the genesis of atrial fibrillation (AF). Activity from multiple IC neurons in the right atrial ganglionated plexus was recorded in eight anaesthetized canines using a 16‐channel linear microelectrode array. Induced changes in IC neuronal activity were evaluated in response to: (1) focal cardiac mechanical distortion; (2) electrical activation of cervical vagi or stellate ganglia; (3) occlusion of the inferior vena cava or thoracic aorta; (4) transient ventricular ischaemia, and (5) neurally induced AF. Low level activity (ranging from 0 to 2.7 Hz) generated by 92 neurons was identified in basal states, activities that displayed functional interconnectivity. The majority (56%) of IC neurons so identified received indirect central inputs (vagus alone: 25%; stellate ganglion alone: 27%; both: 48%). Fifty per cent transduced the cardiac milieu responding to multimodal stressors applied to the great vessels or heart. Fifty per cent of IC neurons exhibited cardiac cycle periodicity, with activity occurring primarily in late diastole into isovolumetric contraction. Cardiac‐related activity in IC neurons was primarily related to direct cardiac mechano‐sensory inputs and indirect autonomic efferent inputs. In response to mediastinal nerve stimulation, most IC neurons became excessively activated; such network behaviour preceded and persisted throughout AF. It was concluded that stochastic interactions occur among IC local circuit neuronal populations in the control of regional cardiac function. Modulation of IC local circuit neuronal recruitment may represent a novel approach for the treatment of cardiac disease, including atrial arrhythmias.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.023
GPT teacher head0.272
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations127
Published2013
Admission routes1
Has abstractyes

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