Cloning of equine prostaglandin dehydrogenase and its gonadotropin-dependent regulation in theca and mural granulosa cells of equine preovulatory follicles during the ovulatory process
Bibliographic record
Abstract
The mammalian ovulatory process is accompanied by a gonadotropin-dependent increase in follicular levels of prostaglandin E2 (PGE2) and PGF2alpha, which are metabolized by 15-hydroxy prostaglandin dehydrogenase (PGDH). Little is known about ovarian PGDH regulation in non-primate species. The objectives of this study were to characterize the structure of equine PGDH and its regulation in follicles during human chorionic gonadotropin (hCG)-induced ovulation. The full-length equine PGDH was obtained by RT-PCR, 5'- and 3'-rapid amplification of cDNA ends (RACE). Its open reading frame encodes a 266-amino acid protein that is 72-95% homologous to other species. Semi-quantitative RT-PCR/Southern blot were used to study PGDH regulation in follicles isolated 0-39 h post-hCG. Results showed that PGDH mRNA expression was low in follicles obtained at 0 h, increased at 12 and 24 h (P < 0.05), and decreased at 36-h post-hCG. This induction of expression was biphasic, with elevated abundance of transcripts at 12 and 33 h post-hCG (P < 0.05) in mural granulosa and theca cells. Immunohistochemistry and immunoblotting confirmed regulated expression of PGHD protein in both cell types of preovulatory follicles after hCG. High levels of PGDH mRNA were observed in corpus luteum and other non-ovarian tissues tested, except kidney, muscle, brain, and heart. Thus, this study is the first to report the gonadotropin-dependent regulation of PGDH during ovulation in a non-primate species. PGDH induction was biphasic in theca and mural granulosa cells differing from primates in which this induction was monophasic and limited to granulosa cells, suggesting species-specific differences in follicular control of PGDH expression during ovulation.
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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 | 0.001 |
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".