PM361. The hallucinogen D-lysergic diethylamide (LSD) decreases dopamine firing activity through 5-HT1A, D2 and TAAR1 receptors
Bibliographic record
Abstract
Abstract D-lysergic diethylamide (LSD) is a hallucinogenic drug that interacts with the serotonin (5-HT) system binding to 5-HT1 and 5-HT2 receptors. Little is known about its potential interactions with the dopamine (DA) neurons of the ventral tegmental area (VTA). Using in-vivo electrophysiology in male adult rats, we evaluated the effects of cumulative doses of LSD on VTA DA neuronal activity, we compared these effects to those produced on 5-HT neurons in the dorsal raphe nucleus (DRN), and we attempted to identify the mechanism of action mediating the effects of LSD on VTA DA neurons. We confirmed that low doses of LSD (5–20 µg/kg, i.v.) induce a significant decrease of DRN 5-HT firing activity, but at these doses, it did not alter VTA DA neuronal activity. On the contrary, higher doses of LSD (30–120 µg/kg, i.v.) dose-dependently decreased VTA DA firing activity. The depletion of 5-HT synthesis with p-chlorophenylalanine did not modulate the effects of LSD on DA firing activity. The inhibitory effects of LSD on VTA DA firing activity were prevented by the D2 receptor antagonist haloperidol (50 µg/kg, i.v.) and by the 5-HT1A receptor antagonist WAY-100,635 (500 µg/kg, i.v.). Notably, pretreatment with the novel synthetized trace amine-associate receptor 1 (TAAR1) antagonist EPPTB (5 mg/kg, i.v.) blocked the inhibitory effect of LSD on VTA DA neurons. These results suggest that LSD at high doses strongly affects DA mesolimbic neuronal activity in a 5-HT independent manner and with a pleiotropic mechanism of action involving 5-HT1A, D2 and TAAR1 receptors.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".