Somatostatin Is Essential for the Sexual Dimorphism of GH Secretion, Corticosteroid-Binding Globulin Production, and Corticosterone Levels in Mice
Bibliographic record
Abstract
Distinct male and female patterns of pituitary GH secretion produce sexually differentiated hepatic gene expression profiles, thereby influencing steroid and xenobiotic metabolism. We used a fully automated system to obtain serial nocturnal blood samples every 15 minutes from cannulated wild-type (WT) and somatostatin knockout (Sst-KO) mice to determine the role of SST, the principal inhibitor of GH release, in the generation of sexually dimorphic GH pulsatility. WT males had lower mean and median GH values, less random GH secretory bursts, and longer trough periods between GH pulses than WT females. Each of these parameters was feminized in male Sst-KO mice, whereas female Sst-KO mice had higher GH levels than all other groups, but GH pulsatility was unaffected. We next performed hepatic mRNA profiling with high-density microarrays. Male Sst-KO mice exhibited a globally feminized pattern of GH-dependent mRNA levels, but female Sst-KO mice were largely unaffected. Among the differentially expressed female-predominant genes was Serpina6, which encodes corticosteroid-binding globulin (CBG). Increased CBG was associated with elevated diurnal peak plasma corticosterone in unstressed WT females and both sexes of Sst-KO mice compared with WT males. Sst-KO mice also had exaggerated ACTH and corticosterone responses to acute restraint stress. However, consistent with their lack of phenotypic signs of excess glucocorticoids, cerebrospinal fluid concentrations of free corticosterone in Sst-KO mice were not elevated. In summary, SST is necessary for the prolonged interpulse troughs that define masculinized pituitary GH secretion. SST also contributes to sexual dimorphism of the hypothalamic-pituitary-adrenal axis via GH-dependent regulation of hepatic CBG production.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".