The β‐adrenoceptor blocker propranolol ameliorates compulsive‐like gambling behaviour in a rodent slot machine task: implications for iatrogenic gambling disorder
Bibliographic record
Abstract
Abstract Previous work has shown that chronic administration of the dopamine D2/3receptor agonist ropinirole invigorates performance on a rodent slot machine task (rSMT). This behavioural change appears superficially similar to the iatrogenic gambling disorder (GD) observed in a sub‐set of patients with Parkinson's disease (PD), and has been associated with increased activation of the intra‐cellular signalling proteinsGSK3β andCREBin the striatum. Here, we wanted to determine whether this response to ropinirole could be attenuated by targeting these signalling proteins, and if the loss of dopaminergic innervation characteristic ofPDwould alter ropinirole's effects on therSMT. Male Long Evans rats were trained on therSMT. Dopaminergic terminals innervating the dorsolateral striatum were then lesioned bilaterally using the neurotoxin 6‐hydroxydopamine hydrochloride (6‐OHDA). Subsequently animals were implanted with osmotic mini‐pumps delivering ropinirole. Lastly, animals were given dietary lithium (Li+), to inhibit the activation ofGSK3β, or injections of the ß‐adrenoceptor antagonist propranolol, which potently inhibitsCREBas a secondary mechanism of action, and any changes in ropinirole‐induced increases in compulsive‐like engagement in therSMTevaluated. Chronic ropinirole increased the number of trials animals completed, reproducing our original finding. This increase in task engagement was not altered in animals with 6‐OHDAlesions, a putative model of earlyPD. In addition, the effects of ropinirole were not attenuated by administration of Li+, but were ameliorated by propranolol. These data suggest that propranolol may represent a potential pharmacotherapy for the treatment of iatrogenic gambling.
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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) | 0.000 | 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 | 0.001 | 0.002 |
| 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".