Cell differentiation along multiple pathways accompanied by changes in histone acetylation status
Bibliographic record
Abstract
Post-translational modification of histones is fundamental to the regulation of basic nuclear processes and subsequent cellular events, including differentiation. In this study, we analyzed acetylated forms of histones H2A, H2B, and H4 during induced differentiation in mouse (mESCs) and human (hESCs) embryonic stem cells and during induced enterocytic differentiation of colon cancer cells in vitro. Endoderm-like differentiation of mESCs induced by retinoic acid and enterocytic differentiation induced by histone deacetylase inhibitor sodium butyrate were accompanied by increased mono-, di-, and tri-acetylation of histone H2B and a pronounced increase in di- and tri-acetylation of histone H4. In enterocytes, mono-acetylation of histone H2A also increased and tetra-acetylation of histone H4 appeared only after induction of this differentiation pathway. During differentiation of hESCs, we observed increased mono-acetylation and decreased tri-acetylation of H2B. Mono-, di-, and tri-acetylation of H4 were reduced, manifested by a significant increase in nonacetylated H4 histones. Levels of acetylated histones increased during induced differentiation in mESCs and during histone deacetylase (HDAC) inhibitor-induced enterocytic differentiation, whereas differentiation of human ESCs was associated with reduced acetylation of histones H2B and H4.
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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".