Daily Δ9-Tetrahydrocannabinol and Withdrawal Increase Dopamine D1-D2 Receptor Heteromer to Mediate Anhedonia- and Anxiogenic-like Behavior Through a Dynorphin and Kappa Opioid Receptor Mechanism
Bibliographic record
Abstract
Frequent cannabis use is associated with a higher risk of developing cannabis use disorder (CUD) and other adverse consequences. In rodents, modeling the underlying mechanisms of the reinforcing and withdrawal effects of the primary constituent of cannabis, Δ 9 -tetrahydrocannabinol (THC), has been limited. The effects of daily THC (1mg/kg, i.p., 9 days) and spontaneous withdrawal (7 days) in male rats on hedonic and aversion-like behaviors were investigated. In parallel, underlying neuroadaptive changes in dopaminergic, opioidergic and cannabinoid signaling in the nucleus accumbens (NAc) were evaluated, along with a candidate peptide designed to reverse altered signaling. Chronic THC administration induced anhedonic and anxiogenic-like behaviors, not attributable to altered locomotor activity. These effects persisted after drug cessation. In NAc, THC treatment and withdrawal catalyzed increased CB1 receptor activity without modifying receptor expression. Dopamine D1-D2 receptor heteromer expression rose steeply with THC, accompanied by increased calcium-linked signaling, activation of brain-derived neurotrophic factor pathway (BDNF/TrkB), dynorphin expression and kappa opioid receptor (KOR) signaling. Disruption of the D1-D2 heteromer by an interfering peptide during withdrawal reversed the anxiogenic-like and anhedonic-like behaviors as well as the neurochemical changes. Chronic THC increases NAc dopamine D1-D2 receptor heteromer expression and function, which results in increased dynorphin expression and KOR activation. These changes plausibly reduce dopamine release, to trigger anxiogenic- and anhedonic-like behaviors after daily THC administration that persist for at least 7 days after drug cessation. These findings conceivably provide a therapeutic strategy to alleviate negative symptoms associated with cannabis use and withdrawal.
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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) | 0.002 | 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".