A Comparative Update on the Neuroendocrine Regulation of Growth Hormone in Vertebrates
Bibliographic record
Abstract
Growth hormone (GH), mainly produced from the pituitary somatotrophs is a key endocrine regulator of somatic growth. GH, a pleiotropic hormone, is also involved in regulating vital processes, including nutrition, reproduction, physical activity, neuroprotection, immunity, and osmotic pressure in vertebrates. The dysregulation of the pituitary GH and hepatic insulin-like growth factors (IGFs) affects many cellular processes associated with growth promotion, including protein synthesis, cell proliferation and metabolism, leading to growth disorders. The metabolic and growth effects of GH have interesting applications in different fields, including the livestock industry and aquaculture. The latest discoveries on new regulators of pituitary GH synthesis and secretion deserve our attention. These novel regulators include the stimulators adropin, klotho, and the fibroblast growth factors, as well as the inhibitors, nucleobindin-encoded peptides (nesfatin-1 and nesfatin-1-like peptide) and irisin. This review aims for a comparative analysis of our current understanding of the endocrine regulation of GH from the pituitary of vertebrates. In addition, we will consider useful pharmacological molecules (i.e. stimulators and inhibitors of the GH signaling pathways) that are important in studying GH and somatotroph biology. The main goal of this review is to provide an overview and update on GH regulators in 2020. While an extensive review of each of the GH regulators and an in-depth analysis of specifics are beyond its scope, we have compiled information on the main endogenous and pharmacological regulators to facilitate an easy access. Overall, this review aims to serve as a resource on GH endocrinology for a beginner to intermediate level knowledge seeker on this topic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".