Binding of levomepromazine and cyamemazine to human recombinant dopamine receptor subtypes
Bibliographic record
Abstract
Background and Objectives: Clozapine (CLOZ) and levomepromazine (LMP) improve treatment-resistant schizophrenia.The superior efficacy of CLOZ compared with other antipsychotic agents has been attributed to an effect on D1-like and D4 receptors.We examined the binding of LMP, CLOZ and cyamemazine (CMZ), a neuroleptic analog of LMP, to human recombinant dopamine (rDA) receptor subtypes.Methods: Binding studies were performed on frozen membrane suspensions of human rDA receptor subtypes expressed in Sf9 cells.Results: (i) LMP has a high affinity (Ki, nM) for rD2 receptor subtypes (rD2L 8.6; rD2S 4.3; rD3 8.3; rD4.2 7.9); (ii) LMP and CLOZ have comparable affinities for the rD1 receptor (54.3 vs 34.6); (iii) CMZ has high affinities for rD2-like and rD1-like receptors (rD2L 4.6; rD2S 3.3; rD3 6.2; rD4.2 8.5; rD1 3.9; rD5 10.7); (iv) CMZ is 9 times more potent than CLOZ at the rD1 receptor and 5 times more potent than CLOZ at the rD4.2 receptor; (v) CMZ has high affinities for rD1 and rD5 receptor subtypes compared with LMP and CLOZ.Conclusions: If D1 and D4 receptors are important sites for the unique action of CLOZ, the present study points to a need for clinical trials comparing CMZ with CLOZ in schizophrenia and in particular, treatment-resistant schizophrenia, especially given the risk for agranulocytosis with CLOZ.
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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 | 0.001 |
| 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".