Effect of Follicle-Stimulating Hormone on Steroid Secretion and Messenger Ribonucleic Acids Encoding Cytochromes P450 Aromatase and Cholesterol Side-Chain Cleavage in Bovine Granulosa Cells In Vitro1
Bibliographic record
Abstract
We determined 1) whether the previously observed induction of estradiol secretion in bovine granulosa cells cultured in serum-free conditions is associated with an increase in cytochrome P450 aromatase (P450(arom)) mRNA abundance and 2) whether P450(arom) mRNA levels are responsive to FSH in vitro. Granulosa cells from small (2-4-mm) follicles were cultured in serum-free medium. Estradiol secretion increased with time in culture and was correlated with increased P450(arom) mRNA abundance. Progesterone secretion also increased with time in culture, but P450 cholesterol side-chain cleavage (P450(scc)) mRNA abundance did not. FSH stimulated estradiol secretion and P450(arom) mRNA abundance; the effect was quadratic for both estradiol and P450(arom) mRNA. Estradiol secretion and P450(arom) mRNA levels were correlated. FSH stimulated progesterone secretion and P450(scc) mRNA abundance, although the minimum effective dose of FSH was lower for estradiol (0.1 ng/ml) than for progesterone (10 ng/ml) production. Insulin alone stimulated estradiol secretion and P450(arom) mRNA levels but not progesterone or P450(scc) mRNA abundance. We conclude that this cell culture system maintained both estradiol secretion and P450(arom) mRNA abundance responsiveness to FSH and insulin, whereas P450(scc) mRNA abundance and progesterone secretion were responsive to FSH but not insulin.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".