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Record W4417212224 · doi:10.1016/j.cophys.2025.100888

The role of epicardial fat in the progression of cardiovascular disease in women

2025· article· en· W4417212224 on OpenAlexafffund
Erele Tzidon, Inna Rabinovich-Nikitin

Bibliographic record

VenueCurrent Opinion in Physiology · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Disease and Adiposity
Canadian institutionsSt. Boniface Hospital
FundersCanadian Institutes of Health ResearchFondation de l’Hôpital Saint-Boniface
KeywordsEpicardial fatObesityDiseaseVisceral fatAtrial fibrillationHormoneSleep apneaHeart diseaseObstructive sleep apnea

Abstract

fetched live from OpenAlex

Obesity is a global health burden with significant sex-specific implications, especially in cardiovascular disease (CVD). Epicardial fat tissue (EFT), a metabolically active visceral fat depot between the myocardium and visceral pericardium, plays a critical role in cardiac health. Under normal conditions, EFT supports the heart via anti-inflammatory signaling, fatty acid metabolism, and nitric oxide–mediated vasodilation. However, in obesity and cardiometabolic syndrome, EFT becomes proinflammatory, contributing to cardiac remodeling and endothelial dysfunction. Since women experience unique hormonal and metabolic influences, risk factors such as menopause, polycystic ovarian syndrome, vitamin D deficiency, and sleep apnea are linked to increased EFT in women, independent of body mass index, and correlate with adverse cardiac remodeling and inflammation. Therapeutic strategies such as exercise, GLP-1 receptor agonists, and hormone replacement therapy show promise in reducing EFT. Understanding sex-specific EFT biology is essential for personalized CVD prevention and treatment in obesity-related disorders.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.314
Teacher spread0.300 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2025
Admission routes2
Has abstractyes

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