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Record W2143356310 · doi:10.1517/17460441.3.5.519

DNA demethylation and cancer metastasis: therapeutic implications

2008· article· en· W2143356310 on OpenAlexaff
Moshe Szyf

Bibliographic record

VenueExpert Opinion on Drug Discovery · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsMcGill University
Fundersnot available
KeywordsMetastasisCancerDNACancer researchBiologyDNA demethylationCancer metastasisComputational biologyMedicineDNA methylationGeneticsGeneGene expression

Abstract

fetched live from OpenAlex

BACKGROUND: DNA methylation is a covalent modification of DNA, which plays a critical role in regulation of gene expression. Methyl marks in critical regulatory regions of genes silence gene expression. Two contrasting changes in DNA methylation were documented in cancers: regional hypermethylation of tumor suppressor genes and global hypomethylation. OBJECTIVE: Most of the attention in the field has been directed toward the phenomenon of hypermethylation and silencing of tumor suppressor genes. Hypermethylation indeed plays an extremely important role in cancer and cancer progression. Nevertheless, hypomethylation is emerging now as a mechanism that might lead to activation of prometastatic genes in cancer. CONCLUSION: Both methylation and demethylation could be pharmacologically modulated. It is argued here that inhibition of hypomethylation might provide a new therapeutic approach to antimetastatic therapy.

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)0.000
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.037
GPT teacher head0.321
Teacher spread0.285 · 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

Citations7
Published2008
Admission routes1
Has abstractyes

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