Potential Applications for Growth Hormone Secretagogues Treatment ofAmyotrophic Lateral Sclerosis
Bibliographic record
Abstract
Abstract: Amyotrophic lateral sclerosis (ALS) arises from neuronal death due to complex interactions of genetic, molecular, and environmental factors. Currently, only two drugs, riluzole and edaravone, have been approved to slow the progression of this disease. However, ghrelin and other ligands of the GHS-R1a receptor have demonstrated interesting neuroprotective activities that could be exploited in this pathology. Ghrelin, a 28-amino acid hormone, primarily synthesized and secreted by oxyntic cells in the stomach wall, binds to the pituitary GHS-R1a and stimulates GH secretion; in addition, ghrelin is endowed with multiple extra endocrine bioactivities. Native ghrelin requires esterification with octanoic acid for binding to the GHS-R1a receptor; however, this esterified form is very labile and represents less than 10% of circulating ghrelin. A large number of synthetic compounds, the growth hormone secretagogues (GHS) encompassing short peptides, peptoids, and non-peptidic moieties, are capable of mimicking several biological activities of ghrelin, including stimulation of GH release, appetite, and elevation of blood IGF-I levels. GHS have demonstrated neuroprotective and anticonvulsant effects in experimental models of pathologies both in vitro and in vivo. To illustrate, some GHS, currently under evaluation by regulatory agencies for the treatment of human cachexia, have a good safety profile and are safe for human use. Collectively, evidence suggests that ghrelin and cognate GHS may constitute potential therapies for ALS.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".