Androstenedione increases cytochrome P450 aromatase messenger ribonucleic acid transcripts in nonluteinizing bovine granulosa cells
Bibliographic record
Abstract
The objective of this study was to determine if androgens regulate granulosa cell steroidogenesis at physiological doses found in small bovine follicles. Bovine granulosa cells were cultured under serum-free conditions that permit the induction and maintenance of FSH-dependent estradiol secretion. Increasing androstenedione concentrations from 0.1 to 1 or 10 microM significantly increased estradiol accumulation and cytochrome P450 aromatase (P450arom) mRNA abundance. No increase in progesterone accumulation or abundance of mRNA for P450 side-chain cleavage or 3beta-hydroxysteroid dehydrogenase enzymes was observed. The addition of 0.1, 1, or 10 microM progestins or estrogens had no stimulatory effect on P450arom mRNA levels. An analysis of the 5'-untranslated region of P450arom mRNA transcripts indicated that the majority was derived from Cyp19 ovary-specific promoter 2, with some contribution from promoters 1.1 and 1.5. Transcripts from these three promoters were all significantly increased by androstenedione. Testosterone increased promoter 1.1 and 1.5-derived transcripts, but only promoter 2-derived transcripts at the highest dose tested (100 microM). Dihydrotestosterone (DHT) did not affect Cyp19 expression. Collectively, these data show that androgens may exert specific stimulatory effects on P450arom mRNA concentrations in granulosa cells. Interestingly, different androgens had different effects on Cyp19 promoter usage, suggesting differential regulation of aromatase gene expression in the developing follicle.
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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) | 0.001 | 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 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".