Administration of Acylated Ghrelin Reduces Insulin Sensitivity, Whereas the Combination of Acylated Plus Unacylated Ghrelin Strongly Improves Insulin Sensitivity
Bibliographic record
Abstract
We investigated the metabolic actions of ghrelin in humans by examining the effects of acute administration of acylated ghrelin, unacylated ghrelin, and the combination in eight adult-onset GH-deficient patients. We followed glucose, insulin, and free fatty acid concentrations before and after lunch and with or without the presence of GH in the circulation. We found that acylated ghrelin, which is rapidly cleared from the circulation, induced a rapid rise in glucose and insulin levels. Unacylated ghrelin, however, prevented the acylated ghrelin-induced rise in insulin and glucose when it was coadministered with acylated ghrelin. Surprisingly, the injection of acylated ghrelin induced an acute increase in unacylated ghrelin and therefore total ghrelin levels. Finally, acylated ghrelin decreased insulin sensitivity up to the end of a period of 6 h after administration. This decrease in insulin sensitivity was prevented by coinjection of unacylated ghrelin. This combined administration of acylated and unacylated ghrelin even significantly improved insulin sensitivity, compared with placebo, for at least 6 h, which warrants studies to investigate the long-term efficacy of this combination in the treatment of disorders with disturbed insulin sensitivity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".