Regulation of HDAC11 gene expression in early myogenic differentiation
Bibliographic record
Abstract
Histone acetylation and deacetylation affect the patterns of gene expression in cellular differentiation, playing pivotal roles in tissue development and maintenance. For example, the intrinsic histone acetyltransferase activity of transcriptional coactivator p300 is especially required for the expression of myogenic regulatory factors including Myf5 and MyoD, and consequently for skeletal myogenesis. On the other hand, histone deacetylases (HDACs) remove the acetyl group from histones, which is critical for gene repression in stem cell fate transition. Through integrative omic analyses, we found that while some HDACs were differentially expressed at the early stage of skeletal myoblast differentiation, Hdac11 gene expression was significantly enhanced by nuclear receptor signaling. In addition, p300 and MyoD control Hdac11 expression in milieu of normal and signal-enhanced myoblast differentiation. Thus, HDAC11 may be essential to differential gene expression at the onset of myoblast differentiation.
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 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".