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Record W1539264785

Abstract 15690: Statins as Potential Farnesoid X Receptor Modulators in Atrial Cardiomyocytes: A Gender, Age and miR328 Controlled Response

2014· article· en· W1539264785 on OpenAlexaff
V. Salpeas, James N. Tsoporis, Shehla Izhar, Eleftheris Sakadakis, Angelos G. Rigopoulos, Thomas G. Parker, Ioannis Rizos

Bibliographic record

VenueCirculation · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiac Ischemia and Reperfusion
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsMedicineFarnesoid X receptorAtrial fibrillationInternal medicineCardiologyEndocrinologymicroRNAArteryDownregulation and upregulationAdverse effectNuclear receptorTranscription factorGene
DOInot available

Abstract

fetched live from OpenAlex

Farnesoid X receptor (FXR) plays an important role in lipid and glucose metabolism and statins are known negative regulators of FXR expression. The role of FXR in atrial fibrillation (AF) has not been defined. MicroRNA-328 (miR-328) a small non-coding RNA contributes to adverse electrical remodeling in AF a common complication after coronary artery bypass grafting (CABG). The present study aimed to examine the levels of FXR mRNA and miR328 in 30 consecutive patients undergoing CABG. The patients group was made up of 10 women and 20 men with a mean +/-SEM. age of 68.5+/-2.1 and 64.3+/-2.3 years respectively, 14 of them on statin therapy. We analyzed right atrial biopsies taken pre aortic occlusion and post reperfusion. Post reperfusion, mean (S.E.) FXR mRNA levels increased 3.41+/-1.07 fold (p

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

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)0.0050.001

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 head0.012
GPT teacher head0.261
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 designBench or experimental
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

Citations1
Published2014
Admission routes1
Has abstractyes

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