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Record W2613352189 · doi:10.3390/genes8050138

DNA Methylation Dynamics and Cocaine in the Brain: Progress and Prospects

2017· review· en· W2613352189 on OpenAlexaff
Kathryn Vaillancourt, Carl Ernst, Deborah C. Mash, Gustavo Turecki

Bibliographic record

VenueGenes · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersNational Institute on Drug Abuse
KeywordsDNA methylationEpigeneticsMethyltransferaseMethylationBiologyEpigenomicsMechanism (biology)GeneticsDNAComputational biologyGeneGene expression

Abstract

fetched live from OpenAlex

Cytosine modifications, including DNA methylation, are stable epigenetic marks that may translate environmental change into transcriptional regulation. Research has begun to investigate DNA methylation dynamics in relation to cocaine use disorders. Specifically, DNA methylation machinery, including methyltransferases and binding proteins, are dysregulated in brain reward pathways after chronic cocaine exposure. In addition, numerous methylome-wide and candidate promoter studies have identified differential methylation, at the nucleotide level, in rodent models of cocaine abuse and drug seeking behavior. This review highlights the current progress in the field of cocaine-related methylation, and offers considerations for future research.

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)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.044
GPT teacher head0.358
Teacher spread0.314 · 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

Citations48
Published2017
Admission routes1
Has abstractyes

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