Gonadotropin‐dependent regulation of the prostaglandin E2 receptor in equine preovulatory follicles during the ovulatory process in mares
Bibliographic record
Abstract
The objectives of the study were to clone the primary structure of the prostaglandin E2 receptor subtype 2 (PTGER2) cDNA and to characterize its regulation in equine follicles during gonadotropin-induced ovulation. Results from DNA isolation indicated that the equine PTGER2 cDNA encodes a predicted 353-amino acid protein, which is highly similar (76-85%) to known mammalian homologues. The regulation of PTGER2 was studied by semi-quantitative RT-PCR/Southern blot using preparations of theca interna and mural granulosa cells isolated from equine follicles 0-39 hr post-treatment with human chorionic gonadotropin (hCG). Results indicated that a significant increase of PTGER2 mRNA occurred at 24 and 39 hr post-hCG in granulosa cells, and 30 and 33 hr post-hCG in theca cells (P < 0.05). Immunohistochemical staining and immunoblotting performed on equine follicular samples showed a corresponding increase of PTGER2 protein in both cell types after treatment with hCG. Levels of PTGER2 mRNA were also high in uterus, thymus and spleen, but moderate to low in other tested tissues. In the ovary, the expression of PTGER4 mRNA was observed and predominantly occurred in granulosa cells, with highest abundance of transcripts observed at 12 and 39 hr post-hCG. Thus, this study reports for the first time in mares that the ovulatory process is accompanied by the gonadotropin-dependent up-regulation of PTGER2 and PTGER4, which may in turn regulate PGE2-mediated preovulatory effects.
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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".