Inhibition of Histone Deacetylase Activity by Valproic Acid Blocks Adipogenesis
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".