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Record W2527902187 · doi:10.1161/atvbaha.115.305043

Epigenetics in the Vascular Endothelium

2015· review· en· W2527902187 on OpenAlexafffund
Matthew S. Yan, Philip A. Marsden

Bibliographic record

VenueArteriosclerosis Thrombosis and Vascular Biology · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsSt. Michael's Hospital
FundersNational Heart, Lung, and Blood InstituteCanadian Institutes of Health Research
KeywordsEpigeneticsBiologyChromatinMendelian inheritanceEpigenesisPhenotypeDiseaseHistoneGeneticsDNA methylationGeneComputational biologyBioinformaticsGene expressionMedicinePathology

Abstract

fetched live from OpenAlex

Cardiovascular diseases are commonly thought to be complex, non-Mendelian diseases that are influenced by genetic and environmental factors. A growing body of evidence suggests that epigenetic pathways play a key role in vascular biology and might be involved in defining and transducing cardiovascular disease inheritability. In this review, we argue the importance of epigenetics in vascular biology, especially from the perspective of endothelial cell phenotype. We highlight and discuss the role of epigenetic modifications across the transcriptional unit of protein-coding genes, especially the role of intragenic chromatin modifications, which are underappreciated and not well characterized in the current era of genome-wide studies. Importantly, we describe the practical application of epigenetics in cardiovascular disease therapeutics.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.096
GPT teacher head0.361
Teacher spread0.265 · 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

Citations58
Published2015
Admission routes2
Has abstractyes

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