In vivo Evidence for Brain Region-Specific Molecular Interactions Between Cannabinoid and Orexin Receptors
Bibliographic record
Abstract
The endocannabinoid and orexin neuromodulatory systems serve key roles in many of the same biological functions such as sleep, appetite, pain processing, and emotional behaviors related to reward. The type 1 cannabinoid receptor (CB1R) and both subtypes of the orexin receptor, orexin receptor type 1 (OX1R) and orexin receptor type 2 (OX2R) are not only expressed in the same brain regions modulating these functions, but physically interact as heterodimers in recombinant and neuronal cell cultures. In the current study, male and female C57BL/6 mice were co-treated with the cannabinoid receptor agonist CP55,940 and either the OX2R antagonist TCS-OX2-29 or the dual orexin receptor antagonist (DORA) TCS-1102. Mice were then evaluated for catalepsy, body temperature, thermal anti-nociception, and locomotion, after which their brains were collected for receptor colocalization analysis. Combined treatment with the DORA TCS-1102 and CP55,940 potentiated catalepsy more than CP55,940 alone, but this effect was not observed for changes in body temperature, nociception, locomotion, or via selective OX2R antagonism. Co-treatment with CP55,940 and TCS-1102 also led to increased CB1R-OX1R colocalization in the ventral striatum. This was not seen following co-treatment with TCS-OX2-29, nor in CB1R-OX2R colocalization. The magnitude of effects following co-treatment with CP55,940 and either the DORA or OX2R-selective antagonist was greater in males than females. These data show that CB1R-OX1R colocalization in the ventral striatum underlies cataleptic additivity between CP55,940 and the DORA TCS-1102. Moreover, cannabinoid-orexin receptor interactions are sex-specific with regards to brain region and functionality. Physical or molecular interactions between these two systems may provide valuable insight into drug-drug interactions between cannabinoid and orexin drugs for the treatment of insomnia, pain, and other disorders.
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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 | 0.001 |
| 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".