Receptor Signaling Directs Global Recruitment of Pre-existing Transcription Factors to Inducible Elements.
Bibliographic record
Abstract
Gene expression programs are largely regulated by the tissue-specific expression of lineage-defining transcription factors or by the inducible expression of transcription factors in response to specific stimuli. Here I will review our own work over the last 20 years to show how specific activation signals also lead to the wide-spread re-distribution of pre-existing constitutive transcription factors to sites undergoing chromatin reorganization. I will summarize studies showing that activation of kinase signaling pathways creates open chromatin regions that recruit pre-existing factors which were previously unable to bind to closed chromatin. As models I will draw upon genes activated or primed by receptor signaling in memory T cells, and genes activated by cytokine receptor mutations in acute myeloid leukemia. I also summarize a hit-and-run model of stable epigenetic reprograming in memory T cells, mediated by transient Activator Protein 1 (AP-1) binding, which enables the accelerated activation of inducible enhancers.
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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 | 0.002 | 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) | 0.004 | 0.005 |
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".