The Ewing Sarcoma Protein (EWS) Binds Directly to the Proximal Elements of the Macrophage-Specific Promoter of the CSF-1 Receptor ( <i>csf1r</i> ) Gene
Bibliographic record
Abstract
Many macrophage-specific promoters lack classical transcriptional start site elements such as TATA boxes and Sp1 sites. One example is the CSF-1 receptor (CSF-1R, CD115, c-fms), which is used as a model of the transcriptional regulation of macrophage genes. To understand the molecular basis of start site recognition in this gene, we identified cellular proteins binding specifically to the transcriptional start site (TSS) region. The mouse and human csf1r TSS were identified using cap analysis gene expression (CAGE) data. Conserved elements flanking the TSS cluster were analyzed using EMSAs to identify discrete DNA-binding factors in primary bone marrow macrophages as candidate transcriptional regulators. Two complexes were identified that bind in a highly sequence-specific manner to the mouse and human TSS proximal region and also to high-affinity sites recognized by myeloid zinc finger protein 1 (Mzf1). The murine proteins were purified by DNA affinity isolation from the RAW264.7 macrophage cell line and identified by mass spectrometry as EWS and FUS/TLS, closely related DNA and RNA-binding proteins. Chromatin immunoprecipitation experiments in bone marrow macrophages confirmed that EWS, but not FUS/TLS, was present in vivo on the CSF-1R proximal promoter in unstimulated primary macrophages. Transfection assays suggest that EWS does not act as a conventional transcriptional activator or repressor. We hypothesize that EWS contributes to start site recognition in TATA-less mammalian promoters.
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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) | 0.002 | 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".