Interrelationship between the Novel Peptide Ghrelin and Somatostatin/Growth Hormone-Releasing Hormone in Regulation of Pulsatile Growth Hormone Secretion
Bibliographic record
Abstract
GH is an anabolic hormone that is essential for normal linear growth and has important metabolic effects throughout life. The ultradian rhythm of GH secretion is generated by the intricate patterned release of two hypothalamic hormones, somatostatin (SRIF) and GHRH, acting both at the level of the pituitary gland and within the central nervous system. The recent discovery of ghrelin, a novel GH-releasing peptide identified as the endogenous ligand for the GH secretagogue receptor and shown to induce a positive energy balance, suggests the existence of an additional neuroendocrine pathway for GH control. To further understand how ghrelin interacts with the classical GHRH/SRIF neuronal system in GH regulation, we used a combined physiological and histochemical approach. Our physiological studies of the effects of ghrelin on spontaneous pulsatile GH secretion in conscious, free-moving male rats demonstrate that 1) ghrelin, administered either systemically or centrally, exerts potent, time-dependent GH-releasing activity under physiological conditions; 2) ghrelin is a functional antagonist of SRIF, but its GH-releasing activity at the pituitary level is not dependent on inhibiting endogenous SRIF release; 3) SRIF antagonizes the action of ghrelin at the level of the pituitary gland; and 4) the GH response to ghrelin in vivo requires an intact endogenous GHRH system. Our dual chromogenic and autoradiographic in situ hybridization experiments provide anatomical evidence that ghrelin may directly modulate GHRH mRNA- and neuropeptide Y mRNA-containing neurons in the hypothalamic arcuate nucleus, but that SRIF mRNA-expressing cells are not major direct targets for ghrelin. Together, these findings support the idea that ghrelin may be a critical hormonal signal of nutritional status to the GH neuroendocrine axis serving to integrate energy balance and the growth process.
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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".