Orexin/hypocretin role in reward: implications for opioid and other addictions
Bibliographic record
Abstract
UNLABELLED: Addiction is a devastating disorder that affects 15.3 million people worldwide. While prevalent, few effective treatments exist. Orexin receptors have been proposed as a potential target for anti-craving medications. Orexins, also known as hypocretins, are neuropeptides produced in neurons of the lateral and dorsomedial hypothalamus and perifornical area, which project widely throughout the brain. The absence of orexins in rodents and humans leads to narcolepsy. However, orexins also have an established role in reward seeking. This review will discuss some of the original studies describing the roles of the orexins in reward seeking as well as specific works that were presented at the 2013 International Narcotics Research Conference. Orexin signalling can promote drug-induced plasticity of glutamatergic synapses onto dopamine neurons of the ventral tegmental area (VTA), a brain region implicated in motivated behaviour. Additional evidence suggests that orexin signalling can also promote drug seeking by initiating an endocannabinoid-mediated synaptic depression of GABAergic inputs to the VTA, and thereby disinhibiting dopaminergic neurons. Orexin neurons co-express the inhibitory opioid peptide dynorphin. It has been proposed that orexin in the VTA may not mediate reward per se, but rather occludes the 'anti-reward' effects of dynorphin. Finally, orexin signalling in the prefrontal cortex and the central amygdala is implicated in reinstatement of reward seeking. This review will highlight recent work describing the role of orexin signalling in cellular processes underlying addiction-related behaviours and propose novel hypotheses for the mechanisms by which orexin signalling may impart drug seeking. LINKED ARTICLES: This article is part of a themed section on Opioids: New Pathways to Functional Selectivity. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2015.172.issue-2.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".