Interrelationship of CB1R and OBR pathways in regulation of metabolic, neuroendocrine, and behavioral responses to food restriction and voluntary wheel running
Bibliographic record
Abstract
We hypothesized the cannabinoid-1 receptor and leptin receptor (ObR) operate synergistically to modulate metabolic, neuroendocrine, and behavioral responses of animals exposed to a survival challenge (food restriction and wheel running). Obese-prone (OP) JCR:LA-cp rats, lacking functional ObR, and lean-prone (LP) JCR:LA-cp rats (intact ObR) were assigned to OP-C and LP-C (control) or CBR1-antagonized (SR141716, 10 mg/kg body wt in food) OP-A and LP-A groups. After 32 days, all rats were exposed to 1.5-h daily meals without the drug and 22.5-h voluntary wheel running, a survival challenge that normally culminates in activity-based anorexia (ABA). Rats were removed from the ABA protocol when body weight reached 75% of entry weight (starvation criterion) or after 14 days (survival criterion). LP-A rats starved faster (6.44 ± 0.24 days) than LP-C animals (8.00 ± 0.29 days); all OP rats survived the ABA challenge. LP-A rats lost weight faster than animals in all other groups (P < 0.001). Consistent with the starvation results, LP-A rats increased the rate of wheel running more rapidly than LP-C rats (P = 0.001), with no difference in hypothalamic and primary neural reward serotonin levels. In contrast, OP-A rats showed suppression of wheel running compared with the OP-C group (days 6-14 of ABA challenge, P < 0.001) and decreased hypothalamic and neural reward serotonin levels (P < 0.01). Thus there is an interrelationship between cannabinoid-1 receptor and ObR pathways in regulation of energy balance and physical activity. Effective clinical measures to prevent and treat a variety of disorders will require understanding of the mechanisms underlying these effects.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".