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Record W2043868350 · doi:10.1097/hco.0b013e328345986e

Epigenetics in cardiovascular disease

2011· review· en· W2043868350 on OpenAlexafffund
Apurva Shirodkar, Philip A. Marsden

Bibliographic record

VenueCurrent Opinion in Cardiology · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsCanada Research ChairsSt. Michael's HospitalUniversity of Toronto
FundersNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchHeart and Stroke Foundation of Canada
KeywordsEpigeneticsChromatinHistoneDNA methylationDiseaseRegulation of gene expressionMedicineChromatin remodelingEpigenesisGene expressionGeneBiologyBioinformaticsComputational biologyNeuroscienceGeneticsPathology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To provide an overview of the biological processes implicated in chromatin-based pathways that control endothelial gene expression patterns in both health and disease and highlight how these processes are relevant to cardiovascular disease. RECENT FINDINGS: Epigenetics refers to chromatin-based pathways important in the regulation of gene expression and includes three distinct, but highly interrelated, mechanisms: DNA methylation, histone density and posttranslational modifications, and RNA-based mechanisms. It is of great interest that epigenetic regulation of genes enriched in the vascular endothelium is a prominent regulatory pathway. How environmental cues within the vasculature, such as hemodynamic forces or hypoxia, influence these epigenetic mechanisms will be reviewed. SUMMARY: Although a newer area for study, exciting new evidence identifies that epigenetic processes are highly dynamic and respond to a myriad of environmental stimuli. Integrating chromatin-based pathways into our understanding of gene expression offers newer insight into disease processes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.125
GPT teacher head0.378
Teacher spread0.253 · 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.

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

Citations90
Published2011
Admission routes2
Has abstractyes

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