Ghrelin Receptor Signaling Is Not Required for Glucocorticoid-Induced Obesity in Male Mice
Bibliographic record
Abstract
Chronically elevated levels of glucocorticoids increase food intake, weight gain, and adiposity. Similarly, ghrelin, a gut-secreted hormone, is also associated with weight gain, adiposity, and increased feeding. Here we sought to determine if corticosterone-induced metabolic and behavioral changes require functional ghrelin receptors (GHSR). To do this, we treated male C57BL mice with chronic corticosterone (CORT) mixed in their drinking water for 28 days. Half of these mice received the GHSR antagonist JMV2959 via osmotic minipumps while treated with CORT. In a second experiment, we gave the same CORT protocol to mice with a targeted mutation to the GHSR or their wild-type littermates. As expected, CORT treatment increased food intake, weight gain, and adiposity, but contrary to expectations, mice treated with a GHSR receptor antagonist or GHSR knockout (KO) mice did not show attenuated food intake, weight gain, or adiposity in response to CORT. Similarly, the effects of CORT on the liver were the same or more pronounced in GHSR antagonist-treated and GHSR KO mice. Treatment with JMV2959 did attenuate the effects of chronic CORT on glycemic regulation as determined by the glucose tolerance test. Finally, disruption of GHSR signaling resulted in behavioral responses associated with social withdrawal, potentially due to neuroprotective effects of GHSR activation. In all, we propose that blocking GHSR signaling helps to moderate glucose concentrations when CORT levels are high, but blocking GHSR signaling does not prevent increased food intake, weight gain, or increased adiposity produced by chronic CORT.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".