Involvement of Protein Kinase C and Arachidonic Acid Pathways in the Gonadotropin-Releasing Hormone Regulation of Oocyte Meiosis and Follicular Steroidogenesis in the Goldfish Ovary1
Bibliographic record
Abstract
The involvement of protein kinase C (PKC) and arachidonic acid (AA) pathways were investigated in the GnRH regulation of oocyte meiosis and follicular testosterone production in the goldfish ovary. The results clearly demonstrate differences in the postreceptor mechanisms involving the stimulatory and inhibitory actions of GnRH peptides on basal and gonadotropin (GtH)-induced reinitiation of oocyte meiosis and steroidogenesis. In isolated goldfish follicles in vitro, the observed stimulatory effects of both salmon GnRH (sGnRH) and chicken GnRH-II (cGnRH-II) on germinal vesicle breakdown were completely blocked by addition of PKC inhibitors, suggesting the involvement of PKC, presumably through activation of phospholipase C/diacylglycerol pathways in the GnRH-induced reinitiation of oocyte meiosis. Administration of an AA metabolism inhibitor, however, only blocked the stimulatory effect of sGnRH without affecting cGnRH-II-induced meiosis. As observed previously, in the presence of GtH, sGnRH was found to inhibit GtH-induced resumption of meiosis and testosterone production, whereas cGnRH-II was without effect. The inhibitory effect of sGnRH on GtH-induced meiosis and steroidogenesis was completely reversed by addition an AA metabolism inhibitor, whereas PKC inhibitors had no effect. These findings provide functional evidence in support of the novel hypothesis that goldfish ovarian follicles contain GnRH-receptor subtypes with different ligand selectivity mediating stimulatory and inhibitory actions of sGnRH and cGnRH in the goldfish ovary.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".