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Record W2374560515

Histone Acetylation and Cancer

2003· article· en· W2374560515 on OpenAlexaff
Chun Liu

Bibliographic record

VenuePROGRESS IN BIOCHEMISTRY AND BIOPHYSICS · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHistone Deacetylase Inhibitors Research
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsHistone methyltransferaseHistone H2AHistone methylationHistoneHistone codeHistone AcetyltransferasesSAP30AcetylationHistone H1BiologyChromatinHDAC4Histone-modifying enzymesChromatin remodelingGeneticsChemistryCell biologyGeneDNA methylationNucleosomeGene expression
DOInot available

Abstract

fetched live from OpenAlex

Alterations in chromatin structure by histone post- translational modifications appear to play a central role in the regulation of gene transcription. Histone modifications consist of methylation, acetylation, phosphorylation and ubiquityination. Among them histone acetylation is of critical importance. The level of histone acetylation depends on the activity of two families of enzymes, histone acetyltransferases (HATs) and histone deacetylases (HDACs). HATs, which is frequently part of multisubunit coactivator complexes, lead to the relaxation of chromatin structure and transcriptional activation, while HDACs tend to associate with multisubunit corepressor complexes, resulting in chromatin condensation and transcriptional repression of specific target genes. Chromosomal translocations are often associated with acute leukemias, and a significant number of translocations involve genes encoding HATs and HDACs. On the other hand, some histone acetylation- modifying enzymes have been located within chromosomal regions that are particularly prone to chromosomal breaks. The recent achievements in studies aimed at elucidating the biological roles of histone acetylation modifying enzymes and their potential impacts on the molecular changes involved in the development of cancers are reviewed.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.010
GPT teacher head0.310
Teacher spread0.300 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2003
Admission routes1
Has abstractyes

Explore more

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