MétaCan
Menu
Back to cohort
Record W2217744501 · doi:10.1177/1759720x15598307

Towards an understanding of the role of DNA methylation in rheumatoid arthritis: therapeutic and diagnostic implications

2015· review· en· W2217744501 on OpenAlexfundno aff
Adam P. Cribbs, Marc Feldmann, Udo Oppermann

Bibliographic record

VenueTherapeutic Advances in Musculoskeletal Disease · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsnot available
FundersVersus ArthritisMinistero dello Sviluppo EconomicoRosetrees TrustBayer HealthCareOntario Ministry of Economic Development and InnovationNational Institute for Health and Care ResearchGenome CanadaWellcome TrustGlaxoSmithKlinePfizerEli Lilly and Company
KeywordsRheumatoid arthritisMedicineDNA methylationImmunologyArthritisBioinformaticsCancer researchGeneticsGeneBiologyGene expression

Abstract

fetched live from OpenAlex

The term 'epigenetics' loosely describes DNA-templated processes leading to heritable changes in gene activity and expression, which are independent of the underlying DNA sequence. Epigenetic mechanisms comprise of post-translational modifications of chromatin, methylation of DNA, nucleosome positioning as well as expression of noncoding RNAs. Major advances in understanding the role of DNA methylation in regulating chromatin functions have been made over the past decade, and point to a role of this epigenetic mechanism in human disease. Rheumatoid arthritis (RA) is an autoimmune disorder where altered DNA methylation patterns have been identified in a number of different disease-relevant cell types. However, the contribution of DNA methylation changes to RA disease pathogenesis is at present poorly understood and in need of further investigation. Here we review the current knowledge regarding the role of DNA methylation in rheumatoid arthritis and indicate its potential therapeutic implications.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.032
GPT teacher head0.348
Teacher spread0.316 · 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 designOther design
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

Citations45
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueTherapeutic Advances in Musculoskeletal DiseaseSame topicEpigenetics and DNA MethylationFrench-language works237,207