Differential Involvement of Protein Kinase C and Protein Kinase A in Ghrelin-Induced Growth Hormone and Gonadotrophin Release from Goldfish (Carassius auratus) Pituitary Cells
Bibliographic record
Abstract
Ghrelin (GRLN) and its receptor have been identified and characterised in goldfish brain and the pituitary, and recent evidence shows that goldfish (g)GRLN(19) induces both growth hormone (GH) and maturational gonadotrophin (LH) release through an extracellular Ca(2+) -dependent mechanism in goldfish. To further understand the role of GRLN in hormone release, the present study examined the involvement of protein kinase C (PKC) and protein kinase A (PKA) in gGRLN(19) -induced GH and LH release and corresponding Ca(2+) signals in primary cultures of goldfish pituitary cells. Treatments with PKC inhibitors, Bis-II and Gö 6976, significantly reduced gGRLN(19) -induced GH and LH release and their corresponding intracellular Ca(2+) signals in identified somatotrophs and gonadotrophs, respectively. gGRLN(19) was unable to further stimulate hormone release or Ca(2+) signals when cells were pretreated with the PKC agonist, DiC8. PKA inhibitors, H-89 and KT 5720, inhibited gGRLN(19) -induced LH release and Ca(2+) signals in gonadotrophs but not GH release or Ca(2+) signals in somatotrophs. Interestingly, pretreatment of pituitary cells with the adenylate cyclase activator forskolin potentiated gGRLN(19) -induced GH, but not LH, release, although it had no effect on intracellular Ca(2+) signals in either cell type. Taken together, the results suggest that PKC is an important intracellular component in gGRLN(19) -induced GH and LH release, whereas PKA is involved in gGRLN(19) -elicited LH release. Furthermore, the PKA pathway potentiates gGRLN(19) -induced GH release via a Ca(2+) -independent mechanism. Overall, the present study provides insight into the neuroendocrine regulation of GH and LH release by elucidating the mechanistic aspects of GRLN, a hormone involved in many critical physiological processes, including pituitary functions.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".