Gonadotropin-dependent regulation of bovine pituitary adenylate cyclase-activating polypeptide in ovarian follicles prior to ovulation
Bibliographic record
Abstract
To study the regulation of bovine pituitary adenylate cyclase-activating polypeptide (PACAP) in preovulatory follicles prior to ovulation, PACAP cDNA was isolated by RT-PCR. Its open reading frame (ORF) is composed of 531 bp, and encodes for a 176-amino acid protein that bears 76-90% identity with other PACAP homologs. Using bovine preovulatory follicles obtained between 0 and 24 h after human chorionic gonadotropin (hCG) and semiquantitative RT-PCR/Southern blot, we demonstrate that levels of PACAP mRNA were low at 0 h, markedly increased at 6 and 12 h (P<0.05), and declined 18 and 24 h after hCG. Levels of PACAP mRNA were high in the bovine pituitary, testis, intestine and uterus, but moderate to low in other tissues. Analyses performed on isolated preparations of granulosa and theca cells showed a significant increase of PACAP transcripts in both cell types after hCG, whereas primary granulosa cell cultures revealed high levels of PACAP as well as its receptors PAC-1 and VPAC-2 mRNA after forskolin treatment. Overexpression of the catalytic subunit of protein kinase A (PKA) in granulosa cells stimulated, but treatment with H89 or PKA inhibitor protein inhibited PACAP mRNA expression, whereas PACAP overexpression stimulated an increase in abundance of transcripts for PGHS-2, PGES, EP2 receptor, progesterone receptor, and ADAMTS-1, but not for P450-side chain cleavage and P450 aromatase. Thus, this study demonstrates the gonadotropin-dependent regulation of PACAP mRNA in bovine preovulatory follicles, the importance of PKA activation in the expression of PACAP in granulosa cells, and stimulating effect of PACAP on gene expression during the ovulatory process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".