Relationship between the production of prostaglandins and progesterone by luteinizing human granulosa cells
Bibliographic record
Abstract
Luteinizing granulosa cells synthesize high concentrations of progesterone, prostaglandin (PG) E(2) and PGF(2 alpha). The objective of this study was to explore the relationship between prostaglandin and progesterone output from human granulosa cells as they undergo functional luteinization in culture. Granulosa cells were partially purified from ovarian follicular aspirates and cultured at a density of 10(5) cells/ml in serum-supplemented DMEM:Ham's F(12) medium for 0, 1 or 2 days. Cells were then switched to serum-free medium for 24 h before measuring hormone concentrations in this spent medium by specific radioimmunoassays. Over the first 3 days in culture, PGF(2 alpha) and PGE(2) production declined progressively by up to 82+/-3% coincident with a 55+/-11% increase in progesterone output. In subsequent experiments, cells were treated for 24 h on the second day of culture with either 0.01 to 10 microM meclofenamic acid or with 10 microM and 100 microM aminoglutethimide. Meclofenamic acid inhibited synthesis of PGF(2 alpha) and PGE(2) by up to 70+/-9% and 64+/-7% respectively without affecting progesterone output. Likewise, 100 microM aminoglutethimide inhibited progesterone production by 62+/-6% without affecting concentrations of either PGF(2 alpha) or PGE(2). We have concluded that the progressive decline in prostaglandin production and the rise in progesterone output from luteinizing human granulosa cells occur independently of each other.
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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".