DREAM ablation selectively alters THC place aversion and analgesia but leaves intact the motivational and analgesic effects of morphine
Bibliographic record
Abstract
DREAM (downstream regulatory element antagonistic modulator) is a novel transcriptional repressor for the prodynorphin gene, and genetic deletion of DREAM in mice results in a phenotype of ongoing analgesia by virtue of its effect on opioid gene expression. In the present study, we evaluated the motivational effects of opioids (morphine), cannabinoids [Delta(9)-tetrahydrocannabinol (THC)] and cocaine in mice lacking the dream gene (dream(-/-)). The aversive effects of THC were potentiated in dream(-/-) mice in a kappa-opioid receptor-dependent fashion, whereas morphine reward and the aversive effects of morphine withdrawal remained intact. The rewarding and aversive effects of cocaine were likewise unperturbed in dream(-/-) mice. Moreover, the aversive properties of lithium chloride and naloxone were unaffected by the absence of DREAM, indicating that the effect of DREAM on THC-induced dysphoria is not due to a general involvement in the behavioral response to aversive stimuli. Additionally, physical dependence to morphine and the locomotor-sensitizing effects of cocaine were unaltered in these animals. Finally, whereas the absence of DREAM reduced the analgesic efficacy of THC, morphine analgesia was unaffected in dream(-/-) mice.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".