The transcriptional regulating protein of 132 kDa (TReP-132) differentially influences steroidogenic pathways in human adrenal NCI-H295 cells
Bibliographic record
Abstract
Steroid hormones synthesized from cholesterol in the adrenal gland are important regulators of many physiological processes. It is now well documented that the expression of many genes required for steroid biosynthesis is dependent on the coordinated expression of the nuclear receptor steroidogenic factor-1 (SF-1). However, transcriptional mechanisms underlying the species-specific, developmentally programmed and hormone-dependent modulation of the adrenal steroid pathways remain to be elucidated. Recently, we demonstrated that the transcriptional regulating protein of 132 kDa (TReP-132) acts as a coactivator of SF-1 to regulate human P450scc gene transcription in human adrenal NCI-H295 cells. The present study shows that overexpression of TReP-132 increases the level of active steroids produced in NCI-H295 cells. The conversion of pregnenolone to downstream steroids following TReP-132 expression showed increased levels of glucocorticoids, C(19) steroids and estrogens. Correlating with these data, TReP-132 increases P450c17 activities via the induction of transcript levels and promoter activity of the P450c17 gene, an effect that is enhanced in the presence of cAMP or SF-1. In addition, P450aro activity and mRNA levels are highly induced by TReP-132, whereas 3beta-hydroxysteroid dehydrogenase type II and P450c11aldo transcript levels are only slightly modulated. Taken together, these results demonstrate that TReP-132 is a trans-acting factor of genes involved in adrenal glucocorticoid, C(19) steroid and estrogen production.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.000 |
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 teacher head, 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".