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Record W2142484115 · doi:10.1074/jbc.m312795200

Inhibition of Histone Deacetylase Activity by Valproic Acid Blocks Adipogenesis

2004· article· en· W2142484115 on OpenAlexafffund
Diane C. Lagace, Mark W. Nachtigal

Bibliographic record

VenueJournal of Biological Chemistry · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHistone Deacetylase Inhibitors Research
Canadian institutionsDalhousie University
FundersNational Cancer InstituteCanadian Institutes of Health ResearchCanadian Psychiatric Research Foundation
KeywordsAdipogenesisValproic AcidHistone deacetylaseHistone deacetylase inhibitorChemistryHistonePharmacologyBiologyBiochemistryNeuroscienceEpilepsyAdipose tissueGene

Abstract

fetched live from OpenAlex

Adipogenesis is dependent on the sequential activation of transcription factors including the CCAAT/enhancer-binding proteins (C/EBP), peroxisome proliferator-activated receptor gamma (PPARgamma), and steroid regulatory element-binding protein (SREBP). We show that the mood stabilizing drug valproic acid (VPA; 0.5-2 mm) inhibits mouse 3T3 L1 and human preadipocyte differentiation, likely through its histone deacetylase (HDAC) inhibitory properties. The HDAC inhibitor trichostatin A (TSA) also inhibited adipogenesis, whereas the VPA analog valpromide, which does not possess HDAC inhibitory effects, did not prevent adipogenesis. Acute or chronic VPA treatment inhibited differentiation yet did not affect mitotic clonal expansion. VPA (1 mm) inhibited PPARgamma induced differentiation but does not activate a PPARgamma reporter gene, suggesting that it is not a PPARgamma ligand. VPA or TSA treatment reduced mRNA and protein levels of PPARgamma and SREBP1a. TSA reduced C/EBPalpha mRNA and protein levels, whereas VPA only produced a decrease in C/EBPalpha protein expression. Overall our results highlight a role for HDAC activity in adipogenesis that can be blocked by treatment with VPA.

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 score0.003
Threshold uncertainty score0.713

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 head0.016
GPT teacher head0.296
Teacher spread0.280 · 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

Citations103
Published2004
Admission routes2
Has abstractyes

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