The mu opioid receptor and the orphan receptor GPR151 contribute to social reward in the habenula
Bibliographic record
Abstract
Abstract The mu opioid receptor (MOR) and the orphan GPR151 receptor are inhibitory G protein coupled receptors that are enriched in the habenula, a small brain region involved in aversion processing, addiction and mood disorders. While MOR expression in the brain is widespread, GPR151 expression is restricted to the habenula. In a previous report, we created conditional ChrnB4-Cre × Oprm1fl/fl (so-called B4MOR) mice, where MORs are deleted specifically in Chrnb4-positive neurons restricted to the habenula, and shown a role for these receptors in naloxone aversion. Here we characterized the implication of habenular MORs in social behaviors. B4MOR−/− mice and B4MOR+/+ mice were compared in several social behavior measures, including the chronic social stress defeat (CSDS) paradigm, the social preference (SP) test and social conditioned place preference (sCPP). In the CSDS, B4MOR−/− mice showed lower preference for the social target (unfamiliar mouse of a different strain) at baseline, providing a first indication of deficient social interactions in mice lacking habenular MORs. In the SP test, B4MOR−/− mice further showed reduced sociability for an unfamiliar conspecific mouse. In the sCPP, B4MOR−/− mice also showed impaired place preference for their previous familiar littermates after social isolation. We next created and tested Gpr151−/− mice in the SP test, and also found reduced social preference compared to Gpr151+/+ mice. Altogether our results support the underexplored notion that the habenula regulates social behaviors. Also, our data suggest that the inhibitory habenular MOR and GPR151 receptors normally promote social reward, possibly by dampening the aversive habenula activity.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".