Safety and Tolerability of the Hexadecapeptide AOD9604 in Humans
Bibliographic record
Abstract
Background: The human growth hormone (hGH) has properties making it a potential candidate to treat obesity, however safety issues limit its long-term use. AOD9604 is a peptide fragment of the C-terminus of hGH (Tyr-hGH 177-191 ), which harbors the fat reducing activity of hGH, without its negative effects. In this paper the safety data of AOD9604 obtained in clinical trials are summarized. Methods: Six randomized, double-blind, placebo-controlled trials were performed with AOD9604. Special focus was given to undesired effects associated with hGH treatment: increases in IGF-1 levels, insulin resistance, and impaired glucose tolerance. Blood samples were analyzed for presence of anti-AOD9604 antibodies to exclude immunogenicity. Results: AOD9604 had no effect on serum IGF-1 levels, which confirms the hypothesis that AOD9604 does not act via IGF-1. Results of oral glucose tolerance test demonstrated that, in contrast with hGH, AOD9604 has no negative effect on carbohydrate metabolism. There were no anti-AOD9604 antibodies detected in any of the patients selected for antibody assay. In none of the studies did a withdrawal or serious adverse event occur related to intake of AOD9604. Conclusion: AOD9604 displayed a very good safety and tolerability profile indistinguishable from placebo. AOD9604 did not result in any of the adverse effects associated with full-length hGH treatment. J Endocrinol Metab. 2013;3(1-2):7-15 doi: https://doi.org/10.4021/jem157w
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".