Ventral striatum regulates behavioral response to ethanol and MDMA combination
Bibliographic record
Abstract
Our previous studies consistently showed that MDMA-induced locomotor hyperactivity is dramatically increased by coadministration of ethanol (EtOH) in rats, indicating possible potentiation of MDMA abuse liability. Thus, we aimed to identify the brain region(s) and neuropharmacological substrates involved in the pharmacodynamics of this potentiation. We first showed that potentiation of locomotor activity by the combination of ip administration of EtOH (1.5 g/kg) and MDMA (6.6 mg/kg) is delay sensitive and maximal when both drugs are injected simultaneously. Then, we used the 2-deoxyglucose quantitative autoradiography technique to assess the impact of EtOH, MDMA, or their combination on local cerebral metabolic rates for glucose (CMRglcs). We showed a specific metabolic activation in the ventral striatum (VS) under MDMA + EtOH versus MDMA or EtOH alone. We next tested if reversible (tetrodotoxin, TTX) or permanent (6-hydrodoxyopamine, 6-OHDA) lesion of the VS could affect locomotor response to MDMA and MDMA + EtOH. Finally, we blocked dopamine D1 or glutamate NMDA receptors in the VS and measured the effects of MDMA and MDMA + EtOH on locomotor activity. We showed that bilateral reversible inactivation (TTX) or permanent lesion (6-OHDA) of the VS prevented the potentiation by EtOH of MDMA-induced locomotor hyperactivity. Likewise, blockade of D1 or NMDA receptors in the VS also reduced the potentiation of MDMA locomotor activity by EtOH. These data indicate that dopamine D1 and glutamate NMDA receptor-driven mechanisms in the VS play a key role in the pharmacodynamics of EtOH-induced potentiation of the locomotor effects of MDMA.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".