Behaviour of the Purkinje System During Defibrillation-Strength Shocks
Bibliographic record
Abstract
During normal sinus rhythm, orderly activation of the heart is facilitated by a specialized network of fibres lining the ventricles called the Purkinje system (PS). Characteristic features of the PS encourage coordinated depolarization of spatially disparate endocardial sites. Although the basic role of the PS is well understood, many questions regarding its behaviour, especially during the process of defibrillation, remain unanswered. Purkinje fibres react differently during large electrical shocks than the myocardium on which they run because they are oriented in different directions than the endocardial fibres, they possess distinct electrophysiology, and they are part of a system that is one-dimensional in nature. Because of the small size of Purkinje fibres and their positioning on the endocardium, in vivo observation of PS-related phenomena remains problematic. Therefore, computer modelling offers a unique opportunity to investigate the role of the PS during defibrillation. In this paper, the effects of defibrillation-strength shocks on a finite element model of the ventricles coupled to a distinct PS are ascertained. Results indicate that the presence of the PS has a profound impact on the course of activation in the ventricles. During shocks, depolarizations are elicited at bends and bifurcations in the PS. Subsequently, this activity spreads throughout the PS in all directions, creating numerous regions of myocardial depolarization and accelerating the excitation of the whole structure. These excitations are explained by the cable-like nature of Purkinje fibres, which exposes them to vastly different electrical field effects than bulk myocardium due to abrupt conductivity tensor changes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".