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Record W2553047807 · doi:10.1139/bcb-2016-0154

Functional assessment of MeCP2 in Rett syndrome and cancers of breast, colon, and prostate

2016· review· en· W2553047807 on OpenAlexvenueno aff
Somnath Pandey, Kevin Pruitt

Bibliographic record

VenueBiochemistry and Cell Biology · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsnot available
FundersNational Cancer Institute
KeywordsMECP2Rett syndromeRNA splicingChromatinRepressorBiologyHistoneEpigeneticsCarcinogenesisCancer researchNeuroscienceRNAGeneticsTranscription factorGene

Abstract

fetched live from OpenAlex

Ever since the first report that mutations in methyl-CpG-binding protein 2 (MeCP2) causes Rett syndrome (RTT), a severe neurological disorder in females world-wide, there has been a keen interest to gain a comprehensive understanding of this protein. While the classical model associated with MeCP2 function suggests its role in gene suppression via recruitment of co-repressor complexes and histone deacetylases to methylated CpG-sites, recent discoveries have brought to light its role in transcription activation, modulation of RNA splicing, and chromatin compaction. Various post-translational modifications (PTMs) of MeCP2 further increase its functional versatility. Involvement of MeCP2 in pathologies other than RTT, such as tumorigenesis however, remains poorly explored and understood. This review provides a survey of the literature implicating MeCP2 in breast, colon and prostate cancer.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.260
Teacher spread0.250 · 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

Citations13
Published2016
Admission routes1
Has abstractyes

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