The PVH as a Site of CB1-Mediated Stimulation of Thermogenesis by MC4R Agonism in Male Rats
Bibliographic record
Abstract
The present study was designed to investigate the involvement of the cannabinoid receptor 1 (CB1) in the stimulating effects of the melanocortin-4 receptor (MC4R) agonism on whole-body and brown adipose tissue (BAT) thermogenesis. In a first series of experiments, whole-body and BAT thermogenesis were investigated in rats infused in the third ventricle of the brain with the MC4R agonist melanotan II (MTII) and the CB1 agonist δ9-tetrahydrocannabinol (δ(9)-THC) or the CB1 antagonist AM251. Whole-body thermogenesis was measured by indirect calorimetry and BAT thermogenesis assessed from interscapular BAT (iBAT) temperature. δ(9)-THC blunted the effects of MTII on energy expenditure and iBAT temperature, whereas AM251 tended to potentiate the MTII effects. δ(9)-THC also blocked the stimulating effect of MTII on (14)C-bromopalmitate and (3)H-deoxyglucose uptakes in iBAT. Additionally, δ(9)-THC attenuated the stimulating effect of MTII on the expression of peroxisome proliferator-activated receptor-γ coactivator 1-α (Pgc1α), type II iodothyronine deiodinase (Dio2), carnitine palmitoyltransferase 1B (Cpt1b), and uncoupling protein 1 (Ucp1). In a second series of experiments, we addressed the involvement of the paraventricular hypothalamic nucleus (PVH) in the CB1-mediated effects of MTII on iBAT thermogenesis, which were assessed following the infusion of MTII in the PVH and δ(9)-THC or AM251 in the fourth ventricle of the brain. We demonstrated the ability of δ(9)-THC to blunt MTII-induced iBAT temperature elevation. δ(9)-THC also blocked the PVH effect of MTII on (14)C-bromopalmitate uptake as well as on Pgc1α and Dio2 expression in iBAT. Altogether the results of this study demonstrate the involvement of the PVH in the CB1-mediated stimulating effects of the MC4R agonist MTII on whole-body and BAT thermogenesis.
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) | 0.002 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".