Interactions Between Androgen and Growth Factors in Granulosa Cell Subtypes of Porcine Antral Follicles1
Bibliographic record
Abstract
Androgens acting via the androgen receptor (AR) have been implicated in regulation of folliculogenesis in many animal species. These effects are possibly mediated via enhancement of FSH and/or insulin-like growth factor (IGF)-I activity in granulosa cells, which contain high levels of AR protein. We examined the in vitro effect of dihydrotestosterone (DHT) on DNA synthesis and progesterone secretion by follicular cells in response to FSH and IGF-I, alone or in combination. Cells from separate pools of 1- to 3-mm and 3- to 5-mm antral follicles were aspirated from gilt ovaries and fractioned into mural granulosa cells (MGCs) and cumulus-oocyte complexes (COCs) for subsequent cell culture. Androgen alone or with any combination of mitogen had minimal effect on proliferative and no effect on steroidogenic responses of MGCs from 3- to 5-mm antral follicles. Conversely, in MGCs from 1- to 3-mm follicles, DHT significantly enhanced IFG-I-stimulated proliferation and had variable influence on progesterone secretion. The effects of DHT on proliferative responses of COCs were also dependent on follicle size: DHT significantly augmented either IGF-I-stimulated proliferation (1- to 3-mm follicles) or FSH-stimulated proliferation (3- to 5-mm follicles). However, the steroidogenic responses of all COCs were identical, whereby DHT significantly suppressed progesterone secretion, predominantly in the presence of FSH. Addition of an AR antagonist, hydroxyflutamide, generally reversed the proliferative responses invoked by DHT but not the steroidogenic responses. We conclude that androgen-receptor-mediated activity in granulosa cells of antral follicles is dependent on follicle size, is influenced by proximity of cells to the oocyte, and possibly involves both classic and nonclassic steroid mechanisms.
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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 | 0.001 | 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 | 0.000 |
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".