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Record W2022093757 · doi:10.2174/1568011054866946

Histone Deacetylase Inhibitors: Latest Developments, Trends and Prospects

2005· review· en· W2022093757 on OpenAlex
Oscar Moradei, Christiane R. Maroun, Isabelle Paquin, Arkadii Vaisburg

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Medicinal Chemistry - Anti-Cancer Agents · 2005
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHistone Deacetylase Inhibitors Research
Canadian institutionsPyrogenesis (Canada)
FundersNational Cancer Institute
KeywordsHistone deacetylaseHistone AcetyltransferasesAcetylationHDAC11HistoneHistone deacetylase 5Histone deacetylase 2BiochemistryVorinostatBiologyChemistryCancer researchComputational biologyGene

Abstract

fetched live from OpenAlex

Histone deacetylases (HDACs) and histone acetyltransferases (HATs) are enzymes that catalyze the deacetylation and acetylation of lysine residues located in the NH(2) terminal tails of histones and non-histone proteins. Perturbation of this balance is often observed in human cancers and inhibition of HDACs has emerged as a novel therapeutic strategy against cancer. To date, more that 30 groups, academic and industrial, are involved in research related to these target enzymes. Over the past year, dozens of research papers and patent applications describing new HDAC inhibitors belonging to different structural classes have been disclosed. The present review highlights the latest developments in design and synthesis of HDAC inhibitors -- potential anti-cancer drugs.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.923
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.055
GPT teacher head0.410
Teacher spread0.354 · 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