Returning to the stem state: Epigenetics of recapitulating pre‐differentiation chromatin structure
Bibliographic record
Abstract
Embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) can self-renew indefinitely and contribute to all tissue types of the adult organism. Stem cell-based therapeutic approaches hold enormous promise for the cure of regenerative diseases. Over the last few years, several studies have attempted to decipher the important role of transcription factor networks and epigenetic regulatory signals in the maintenance of ESC pluripotency, but the exact underlying mechanisms have yet to be identified. Among the epigenetic factors, chromatin dynamics and structure have been found to contribute greatly to maintenance of pluripotency and regulation of differentiation in ESCs. These modifications include: covalent histone acetylation and methylation, histone bivalents and chromatin remodeling, and DNA methylation. Studies in ESCs have shown that genes associated with early development are arranged within a bivalent chromatin structure. This is thought to be a "poised yet repressed" situation, which can be activated upon differentiation. The breakthrough of iPSCs has opened a new era in stem cell biology. During reprogramming, the chromatin state of differentiated cells is reset to an embryonic form via a largely unknown mechanism. In this review, the fundamental impact of chromatin dynamic in ESCs as well as its critical role in the generation of iPSCs is discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".