Altered metabolic and neurochemical responses to chronic unpredictable stressors in ghrelin receptor‐deficient mice
Bibliographic record
Abstract
Ghrelin, a hormone produced by the stomach, is generally associated with feeding responses and the regulation of food intake. Recent evidence, however, suggests that ghrelin is also a stress hormone, given that it is released following acute and chronic stressors. The present study examined the role of ghrelin in producing normal metabolic and neurochemical responses to chronic stress. This was achieved by examining these responses in mice with targeted deletions of the ghrelin receptor gene (GHSR KO mice), and comparing them with the same responses in their wild-type (WT) littermates. As expected, WT stressed mice decreased their caloric intake, body weight gain and caloric efficiency while maintaining adiposity. GHSR KO mice, however, did not show these alterations despite having normal glucocorticoid responses to stress. In parallel with these changes, chronic unpredictable stress caused changes in norepinephrine, dopamine and serotonin in a number of brain regions. Of these, norepinephrine neurotransmission in the arcuate nucleus and prefrontal cortex was differentially altered in GHSR KO mice. Within the nucleus acumbens, dopamine utilization was increased in WT mice but not in GHSR KO mice. Finally, there were strain differences in serotonin neurotransmission that may explain interstrain body weight and adiposity differences. These results suggest that the metabolic changes necessary to deal with the energetic challenge presented by repeated exposure to stressors do not occur in GHSR KO mice, and they are discussed within the context of the potential vulnerability to stress-induced pathology.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".