A STAR for the ages: a 30-year historical perspective of the role of transcription factors in the regulation of steroidogenic acute regulatory gene expression
Bibliographic record
Abstract
The steroidogenic acute regulatory (STAR) protein is an essential cholesterol transporter that shuttles cholesterol from the outer to the inner mitochondrial membrane in the major steroidogenic endocrine organs. It is a key player in the acute regulation of steroid hormone biosynthesis in response to tropic hormone stimulation. Its discovery 30 years ago sparked immediate interest in understanding how STAR action is controlled. Since increased STAR gene expression is a classic feature of the acute regulation of steroidogenesis, a special emphasis was placed on defining the transcriptional regulatory mechanisms that underlie its rapid induction in response to tropic hormone stimulation. These mechanisms include the effects of enhancers, the regulation of chromatin accessibility, the impact of epigenetic factors, and the role of transcription factors. Over the past three decades, understanding the transcription factors that regulate STAR gene expression has been the subject of more than 170 independent scientific publications, making it one of, and if not the best, studied genes in the steroidogenic pathway. This intense research effort has led to the identification of dozens of transcription factors and their related binding sites in STAR 5' flanking (promoter) sequences across multiple species. STAR gene transcription appears to be complex in that a large number of transcription factors have been proposed to interact with either isolated or overlapping regulatory sequences that are tightly clustered over a relatively short promoter region upstream of the STAR transcription start site. Many of these transcription factors appear to work in unique combinatorial codes and are impacted by diverse hormonal and intracellular signaling pathways. This review provides a retrospective overview of the transcription factors proposed to regulate both basal and acute (hormonal) STAR gene expression, and how insights in this area have evolved over the past 30 years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".