Potential Applications for Growth Hormone Secretagogues Treatment ofAmyotrophic Lateral Sclerosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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 it