Minireview: Steroidogenic Factor 1: Its Roles in Differentiation, Development, and Disease
Bibliographic record
Abstract
The orphan nuclear receptor steroidogenic factor 1 (SF-1, also called Ad4BP, encoded by the NR5A1 gene) is an essential regulator of endocrine development and function. Initially identified as a tissue-specific transcriptional regulator of cytochrome P450 steroid hydroxylases, studies of both global and tissue-specific knockout mice have demonstrated that SF-1 is required for the development of the adrenal glands, gonads, and ventromedial hypothalamus and for the proper functioning of pituitary gonadotropes. Many genes are transcriptionally regulated by SF-1, and many proteins, in turn, interact with SF-1 and modulate its activity. Whereas mice with heterozygous mutations that disrupt SF-1 function have only subtle abnormalities, humans with heterozygous SF-1 mutations can present with XY sex reversal (i.e. testicular failure), ovarian failure, and occasionally adrenal insufficiency; dysregulation of SF-1 has been linked to diseases such as endometriosis and adrenocortical carcinoma. The current state of knowledge of this important transcription factor will be reviewed with a particular emphasis on the pioneering work on SF-1 by the late Keith Parker.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 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".