Stimulatory Effects of Insulin-Like Growth Factor 1 on Expression of Gonadotropin Subunit Genes and Release of Follicle-Stimulating Hormone and Luteinizing Hormone in Masu Salmon Pituitary Cells Early in Gametogenesis
Bibliographic record
Abstract
Insulin-like growth factor-I (IGF-I) has been shown to be involved in pubertal activation of gonadotropin (GTH) secretion. The aim of this study was to determine if IGF-I directly stimulates synthesis and release of GTH at an early stage of gametogenesis. The effects of IGF-I on expression of genes encoding glycoprotein alpha (GPalpha), follicle-stimulating hormone (FSH) beta, and luteinizing hormone (LH) beta subunits and release of FSH and LH were examined using primary pituitary cells of masu salmon at three reproductive stages: early gametogenesis, maturing stage, and spawning. IGF-I alone or IGF-I + salmon GnRH (sGnRH) were added to the primary pituitary cell cultures. Amounts of GPalpha, FSHbeta, and LHbeta mRNAs were determined by real-time PCR. Plasma and medium levels of FSH and LH were determined by RIA. In males, IGF-I increased the amounts of all three subunit mRNAs early in gametogenesis in a dose-dependent manner, but not in the later stages. In females, IGF-I stimulated release of FSH and LH early in gametogenesis, whereas no stimulatory effects on the subunit mRNA levels were observed at any stage. IGF-I + sGnRH stimulated release of FSH and LH at all stages in both sexes, but had different effects on the subunit mRNA levels depending on subunit and stage. The present results suggest that IGF-I itself directly stimulates synthesis and release of GTH early in gametogenesis in masu salmon, possibly acting as a metabolic signal that triggers the onset of puberty.
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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".