Effect of Fasting on Cocaine-Amphetamine-Regulated Transcript, Neuropeptide Y, and Leptin Receptor Expression in the Non-Human Primate Hypothalamus
Bibliographic record
Abstract
Leptin is a cytokine produced by white adipose tissue that circulates in direct proportion to adiposity and is an important signal of energy balance. Leptin inhibits food intake in rodents by inhibiting the orexigenic neuropetides neuropeptide Y (NPY) and agouti regulated peptide (AgRP) and stimulating the anorexigenic neuropeptides alpha-melanocyte-stimulating hormone (alpha-MSH) and cocaine-amphetamine-regulated transcript (CART). In order to extend our understanding of neuroendocrine regulation of appetite in the primate, we determined the effect of a metabolic challenge on CART, NPY, and leptin receptor (Ob-R) messenger ribonucleic acid (mRNA) in the nonhuman primate (NHP) hypothalamus. Ten adult female rhesus monkeys were either maintained on a regular diet or fasted for two days before euthanasia. CART, NPY, and Ob-R mRNA were measured by in situ hybridization histochemistry (ISHH). A 2-day fast decreased CART expression in the ARC, increased NPY gene expression in the supraoptic nucleus (SON) and paraventricular nucleus (PVN), and increased Ob-R expression in the ventromedial nucleus (VMN). This is the first report that fasting inhibits CART expression and stimulates Ob-R expression in monkeys. Increased NPY expression in the SON and PVN, but not the ARC of fasted monkeys also is novel. With some exceptions, our observations are confirmatory of findings in rodent studies. Similarities in the neuroendocrine responses to a metabolic challenge in monkeys and rodents support extending existing hypotheses of neuroendocrine control of energy homeostasis to primates.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".