Effects of Recombinant Activins on Steroidogenesis in Human Granulosa-Lutein Cells
Bibliographic record
Abstract
CONTEXT: Exerting a broad range of biological effects in various tissues, activins are homo- or heterodimers of activin/inhibin β-subunits (βA, βB, βC, and βE in humans). Although activins A (βAβA), B (βBβB), AB (βAβB), and AC (βAβC) have been demonstrated in the female reproductive system, little is known about their individual functions in the ovary. OBJECTIVE: To investigate the biological roles and activities of activins in regulating steroidogenesis in human granulosa cells. DESIGN: Human granulosa-lutein cells obtained from 32 patients undergoing in vitro fertilization were used to investigate the effects of activin A, B, AB, and AC on the expression of steroidogenic enzymes and steroid production. SETTING: An academic research center. MAIN OUTCOME MEASURES: mRNA and protein levels were examined by reverse transcription quantitative real-time PCR and Western blot analysis, respectively. The production of estradiol and progesterone was measured by enzyme immunoassay. RESULTS: P450 aromatase, FSH receptor, and estradiol levels were increased, whereas steroidogenic acute regulatory protein (StAR), LH receptor, and progesterone levels were decreased after treatment with activin A, B, and AB, but not activin AC. FSH or LH induced the production of aromatase/estradiol and StAR/progesterone; however, pretreatment with activin A, B, or AB enhanced the effects of gonadotropins on aromatase/estradiol, but suppressed their effects on StAR/progesterone. Treatment with activin A, B, or AB induced the phosphorylation of SMA- and MAD-related proteins (SMAD2 and 3), whereas activin AC had no such effects. Furthermore, co-culture of activin AC (1-100 ng/mL) with activin A (25 ng/mL) did not alter the effects of activin A on P450 aromatase or StAR mRNA levels. CONCLUSION: Activin A, B, and AB have similar effects on steroidogenesis in human granulosa cells. In contrast, activin AC is not biologically active and does not act as a competitive antagonist.
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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".