Trichostatin A decreases the levels of MeCP2 expression and phosphorylation and increases its chromatin binding affinity
Bibliographic record
Abstract
MeCP2 binds to methylated DNA in a chromatin context and has an important role in cancer and brain development and function. Histone deacetylase (HDAC) inhibitors are currently being used to palliate many cancer and neurological disorders. Yet, the molecular mechanisms involved are not well known for the most part and, in particular, the relationship between histone acetylation and MeCP2 is not well understood. In this paper, we study the effect of the HDAC inhibitor trichostatin A (TSA) on MeCP2, a protein whose dysregulation plays an important role in these diseases. We find that treatment of cells with TSA decreases the phosphorylation state of this protein and appears to result in a higher MeCP2 chromatin binding affinity. Yet, the binding dynamics with which the protein binds to DNA appear not to be significantly affected despite the chromatin reorganization resulting from the high levels of acetylation. HDAC inhibition also results in an overall decrease in MeCP2 levels of different cell lines. Moreover, we show that miR132 increases upon TSA treatment, and is one of the players involved in the observed downregulation of MeCP2.
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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) | 0.002 | 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".