Ovarian Stanniocalcin Is Structurally Unique in Mammals and Its Production and Release Are Regulated through the Luteinizing Hormone Receptor
Bibliographic record
Abstract
Stanniocalcin (STC) is a recently discovered mammalian hormone that is widely distributed in many tissues. In rodents the STC gene is most highly expressed in ovary, specifically in androgen-producing thecal and interstitial cells. In addition, ovarian levels of expression rise 15-fold over pregnancy. The objective of this study was to develop a primary culture system for ovarian thecal-interstitial cells (TICs) to identify factors governing STC production and release. We used highly purified primary cultures of rat and bovine TICs, the purity of which was routinely assessed with antigenic and enzymatic markers. The functionality of cells was assured by their responsiveness to LH in the form of progesterone release. We found that forskolin significantly increased STC gene expression and secretion by both rat and bovine TICs, an effect that was only replicated by human (h) chorionic gonadotropin (CG). Coincubation of TICs with hCG and phosphodiesterase inhibitors further increased STC secretion, whereas coincubation of TICs with hCG and protein kinase A inhibitors attenuated hCG-stimulated release. Intriguingly, ovarian STC proved to be substantially larger than the 50-kDa homodimer produced in most other tissues. These results indicate that ovarian STC is physically distinct, a feature that could explain its presence in serum during pregnancy and lactation.
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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".