The nuclear receptors NUR77 and SF1 play additive roles with c-JUN through distinct elements on the mouse Star promoter
Bibliographic record
Abstract
The steroidogenic acute regulatory protein plays an essential role in steroid biosynthesis in steroidogenic cells. It is involved in the transport of cholesterol through the mitochondrial membrane where the first step of steroidogenesis occurs. Star gene expression in testicular Leydig cells is regulated by the pituitary LH through the cAMP signaling pathway. So far, several transcription factors have been implicated in the regulation of Star promoter activity in these cells. These include the nuclear receptors NUR77 and SF1, AP-1 family members (particularly c-JUN), GATA4, C/EBPbeta, DLX5/6, and CREB. Some of these factors were also shown to act in a cooperative manner to further enhance Star promoter activity. Here, we report that NUR77 and c-JUN have additive effects on the Star promoter. These effects were abolished only when both elements, NUR77 at -95 bp and AP-1 at -78 bp, were mutated. Consistent with this, in vitro co-immunoprecipitation revealed that NUR77 and c-JUN interact and that this interaction is mediated through part of the ligand binding domain of NUR77. Furthermore, we found that SF1 could cooperate with c-JUN on the mouse Star promoter but this cooperation involved different regulatory elements. Collectively, our data not only provide new insights into the molecular mechanisms that control mouse Star transcription in Leydig cells but also reveal a novel mechanism for the regulation of NR4A1-dependent genes in tissues where NUR77 and c-JUN factors are co-expressed.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".