ORIGINAL ARTICLE: The approach to the mechanism of calcitonin gene-related peptide-inducing inhibition of food intake
Bibliographic record
Abstract
The aim of this study was to investigate the anorectic mechanism of calcitonin gene-related peptide (CGRP) in rats. Intraperitoneal injection of CGRP (50 μg/kg) resulted in decline (p < 0.05) in the food intake of rats at 0.5, 1, 2 and 4 h in comparison with saline control. Compared with saline-treated group, the levels of hypothalamic 3',5'-cyclic adenosine monophosphate (cAMP) and plasma glucagon were increased (p < 0.05) in CGRP-treated group, but insulin level was decreased (p < 0.05). No significant changes (p > 0.05) in the plasma leptin were observed between two treatment groups. Calcitonin gene-related peptide injection down regulated (p < 0.05) both neuropeptide Y (NPY) and melanin-concentrating hormone (MCH) genes at mRNA levels, but up regulated (p < 0.05) the expression of cholecystokinin (CCK) gene. The correlations analysis showed that food intake was negatively correlated (p < 0.05) with CCK mRNA, cAMP and glucagon levels. Moreover, there existed negative correlations (p < 0.05) between MCH mRNA and glucagon levels, and positive correlations (p < 0.05) between insulin and leptin levels. The results showed that cAMP acting as the second messenger may play a vital role in the anorectic effects of CGRP. Calcitonin gene-related peptide could stimulate anorexigenic neuropeptides (i.e. CCK) and/or inhibit orexigenic neuropeptides (i.e. NPY and MCH) expression, and ultimately suppressed food intake that was functionally coupled to cAMP/PKA pathway activation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".