Dopamine D2<sup>High</sup>receptors stimulated by phencyclidines, lysergic acid diethylamide, salvinorin A, and modafinil
Bibliographic record
Abstract
Although it is commonly stated that phencyclidine is an antagonist at ionotropic glutamate receptors, there has been little measure of its potency on other receptors in brain tissue. Although we previously reported that phencyclidine stimulated cloned-dopamine D2Long and D2Short receptors, others reported that phencyclidine did not stimulate D2 receptors in homogenates of rat brain striatum. This study, therefore, examined whether phencyclidine and other hallucinogens and psychostimulants could stimulate the incorporation of [(35)S]GTP-gamma-S into D2 receptors in homogenates of rat brain striatum, using the same conditions as previously used to study the cloned D2 receptors. Using 10 microM dopamine to define 100% stimulation, phencyclidine elicited a maximum incorporation of 46% in rat striata, with a half-maximum concentration of 70 nM for phencyclidine, when compared with 80 nM for dopamine, 89 nM for salvinorin A (48 nM for D2Long), 105 nM for lysergic acid diethylamide (LSD), 120 nM for R-modafinil, 710 nM for dizocilpine, 1030 nM for ketamine, and >10,000 nM for S-modafinil. These compounds also inhibited the binding of the D2-selective ligand [(3)H]domperidone. The incorporation was inhibited by the presence of 200 microM guanylylimidodiphosphate and also by D2 blockade, using 10 microM S-sulpiride, but not by D1 blockade with 10 microM SCH23390. Hypertonic buffer containing 150 mM NaCl inhibited the stimulation by phencyclidine, which may explain negative results by others. It is concluded that phencyclidine and other psychostimulants and hallucinogens can stimulate dopamine D2 receptors at concentrations related to their behavioral actions.
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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) | 0.002 | 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".