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Record W2017236361 · doi:10.1093/cvr/cvu082.55

P114Role of atrial remodeling in reentrant dynamics during in-vitro atrial fibrillation

2014· article· en· W2017236361 on OpenAlexaff
Andreu M. Climent, María S. Guillem, P Lee, Christian Bollensdorff, María Eugenia Fernández‐Santos, Ricardo Sanz‐Ruiz, PL. Sanchez, Felipe Atienza, Francisco Fernández‐Avilés

Bibliographic record

VenueCardiovascular Research · 2014
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsEsri (Canada)
Fundersnot available
KeywordsAtrial fibrillationCardiologyInternal medicineMedicineIn vitroFibrillationChemistry

Abstract

fetched live from OpenAlex

Introduction: The role of tissue remodeling in the reentrant activity during atrial fibrillation (AF) is not well understood. The aim of this study is to evaluate in an in-vitro model of AF the role of tissue remodeling in the mechanisms of perpetuation of this arrhythmia. Methods: HL-1 cultures were obtained for early stage (6.1 ± 1.3 days in culture, N=10) and late stage (11.7 ± 0.5 days in culture, N=8) AF. Bright field images together with optical calcium mapping (Rhod-2AM staining) were obtained for evaluating remodeling and electrophysiological characteristics of cell cultures. Results: The number of singularity points per square centimeter at baseline was significantly higher in the late stage group (i.e. 0.43±0.19 vs. 1.12±0.14 PS/cm2, p <0.01) and showed an inverse correlation with the degree of homogeneity in the corresponding bright field microscopy images (R2=0.78, p <0.01) (Fig.1). These results demonstrate that the electrical complexity in the dish increased with the culture time. Rotor dynamics (i.e. curvature and rotor movement) were significantly correlated with the amount of PSs in the cultures (R2=0.86 and R2=0.79 respectively, Fig. 1). Figure 1

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.080
GPT teacher head0.361
Teacher spread0.282 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2014
Admission routes1
Has abstractyes

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