Pregnenolone and AEF0117 block cannabinoid-induced hyperlocomotion through GSK3β signaling at striatopallidal neurons
Bibliographic record
Abstract
Abstract Administration of Δ 9 -tetrahydrocannabinol (THC), the main psychoactive component of the plant Cannabis sativa , can induce psychotic symptomatology in humans and a large spectrum of acute psychotic-like behaviors in mice, including hyperlocomotion observed at low dose of THC (0.3 mg/kg). The cellular and molecular substrates of this effect have not been fully identified yet. Here we demonstrate that THC-induced hyperlocomotion depends on plasma membrane CB1R, which regulate the β-arrestin 1/Akt/GSK3β signaling pathway in D2R-positive neurons of the dorsal striatum forming the striatopallidal pathway of the basal ganglia. Pregnenolone (PREG) and its clinically developed analog, AEF0117, which are signaling specific inhibitors of CB1R (CB1-SSi), prevented GSK3β-dependent psychomotor stimulation induced by THC. Overall, this work highlights a novel intracellular mechanism of CB1R, thereby revealing a neuronal pathway underlying an important but still underexplored effect of THC and cannabis consumption, which could help the development of innovative therapeutic concepts against psychotic conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.004 | 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".