Dopamine D2<sup>High</sup>receptors moderately elevated by bifeprunox and aripiprazole
Bibliographic record
Abstract
Because long-term antipsychotics elicit behavioral dopamine supersensitivity, the present study examined whether 7-9 days administration of partial dopamine D2 agonists with antipsychotic activity, bifeprunox and aripiprazole, could induce biochemical changes that suggest dopamine supersensitivity. In rats, behavioral dopamine supersensitivity is associated with increased dopamine D2(High) receptors in homogenized striata. In control rat striata, bifeprunox and aripiprazole had similar K(i) values at D2 receptors. In human cloned D2Long receptors, however, aripiprazole had a K(i) of 9.6 nM and recognized 41% of the D2 receptors to be in the D2(High) state, while the values for bifeprunox were 1.3 nM and 69%, indicating that bifeprunox had higher potency and efficacy at D2. Nine days of subcutaneously injected bifeprunox (0.25 mg/kg/day) and 7 days of aripiprazole (1.5 mg/kg) increased D2(High) receptors by 102-129% and 108-188%, respectively, although the total population of D2 receptors revealed no significant changes. The increase in D2(high) receptors induced by dopamine D2 partial agonists appear to be of smaller magnitude than those seen previously with D2 antagonist antipsychotics. Future research needs to test directly whether long-term treatment with dopamine partial agonists leads to any behavioral dopamine supersensitivity.
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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) | 0.001 | 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".