Paracrine regulation of growth hormone gene expression by gonadotrophin release in grass carp pituitary cells: functional implications, molecular mechanisms and signal transduction
Bibliographic record
Abstract
Growth hormone (GH) is known to stimulate luteinizing hormone (LH) release via paracrine interactions between somatotrophs and gonadotrophs. However, it is unclear if LH can exert a reciprocal effect to modulate somatotroph functions. Here we examined the paracrine effects of LH on GH gene expression using grass carp pituitary cells as a cell model. LH receptors were identified in grass carp somatotrophs and their activation by human chorionic gonadotropin (hCG) increased 'steady-state' GH mRNA levels. Removal of endogenous LH by immunoneutralization using LH antiserum inhibited GH release and GH mRNA expression. GH secretagogues, including gonadotrophin releasing hormone (GnRH), pituitary adenylate cyclase-activating polypeptide (PACAP) and apomorphine, were effective in elevating GH mRNA levels but these stimulatory actions were blocked by LH antiserum. In pituitary cells pretreated with actinomycin D, the half-life of GH mRNA was not affected by hCG but was enhanced by LH immunoneutralization. Treatment with LH antiserum also suppressed basal levels of mature GH mRNA and primary transcripts. hCG increased cAMP synthesis in carp pituitary cells and hCG-induced GH mRNA expression was mimicked by forskolin but suppressed by inhibiting adenylate cyclase and protein kinase A. Similarly, the stimulatory actions of hCG and forskolin on GH mRNA expression were blocked by inhibiting Janus kinase 2 (JAK2) and MAP kinase (MAPK), including P42/44(MAPK) and P38 (MAPK). These results suggest that LH is essential for the maintenance of GH release, GH gene expression, and somatotroph responsiveness to GH-releasing factors. The paracrine actions of LH on GH mRNA expression are mediated by a concurrent increase in GH gene transcription and GH mRNA turnover, probably through JAK2/MAPK coupled to the cAMP-dependent pathway.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".