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Record W2142833256 · doi:10.1007/s12016-009-8172-8

Epigenetic Therapeutics in Autoimmune Disease

2009· review· en· W2142833256 on OpenAlexafffund
Moshe Szyf

Bibliographic record

VenueClinical Reviews in Allergy & Immunology · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchMinisterio de Economía y Competitividad
KeywordsEpigeneticsDNA demethylationDNA methylationHistoneHistone deacetylaseSystemic lupus erythematosusBiologyDemethylationEpigenomicsDiseaseEpigenetic therapyDNAGeneticsBioinformaticsMedicineImmunologyGeneGene expressionInternal medicine

Abstract

fetched live from OpenAlex

Several lines of evidence suggest the involvement of disturbance in epigenetic processes in autoimmune disease. Most noteworthy is the global DNA hypomethylation seen in lupus. Epigenetic states in difference from genetic lesions are potentially reversible and hence candidates for pharmacological intervention. Potential targets for drug development are histone modification and DNA methylating and demethylating enzymes. The most advanced set of drugs in clinical development are histone deacetylase (HDAC) inhibitors. However, the prevalence of DNA hypomethylation in lupus suggests that we should shift our attention from HDAC inhibitors to DNA demethylation inhibitors. MBD2 was recently proposed to be involved in demethylation in T cells in lupus and is, therefore, a candidate target. Although this field is at its infancy, it carries great promise.

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)0.001
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.003

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 head0.114
GPT teacher head0.434
Teacher spread0.320 · 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

Citations51
Published2009
Admission routes2
Has abstractno

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