Bibliographic record
Abstract
The specification of cell fate is critical for proper cell differentiation and organogenesis. In endocrine tissues, this process leads to the differentiation, often a multistep process, of hormone-producing cells. This process is driven by a combination of transcription factors (TFs) that includes general factor, tissue-restricted, and/or cell-restricted factors. The last 2 decades have seen the discovery of many TFs of restricted expression and function in endocrine tissues. These factors are typically critical for expression of hormone-coding genes as well as for differentiation and proper function of hormone-producing cells. Further, genes encoding these tissue-restricted TFs are themselves subject to mutations that cause hormone deficiencies. Although the model that emerged from these 2 decades is one in which a specific combination of TFs drives a unique cell specification and genetic program, recent findings have led to the discovery of TFs that have the unique property of being able to remodel chromatin and thus modify the epigenome. Most importantly, such factors, known as pioneer TFs, appear to play critical roles in programming the epigenome during the successive steps involved in cell specification. This review summarizes our current understanding of the mechanisms for pioneer TF remodeling of chromatin. Currently, very few TFs that have proven pioneer activity are known, but it will be critical to identify these factors and understand their mechanisms of action if we are to harness the potential of regenerative therapies in endocrinology.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.014 |
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".