Antiparkinson therapeutic potencies correlate with their affinities at dopamine D2<sup>High</sup> receptors
Bibliographic record
Abstract
To determine whether antiparkinson dopamine agonists preferentially act on the high-affinity or the low-affinity states of dopamine D1 and D2 receptors, the agonist potencies were obtained by competition against [(3)H]SCH23390 for D1(High) and D1(Low), and against [(3)H]domperidone for D2(High) and D2(Low). N-propylnorapomorphine and cabergoline were the most potent at D2(High), with dissociation constants of 0.18 and 0.36 nM, respectively. Other agonists had D2(High)K(i) values of 0.52 nM for quinagolide, 0.6 nM for (+)PHNO, 0.9 for bromocriptine, 1.8 nM for apomorphine, 2.4 nM for pergolide, 3 nM for quinpirole, and 6.2 nM for lergotrile. There was a clear correlation between the K(i) values at D2(High) and their therapeutic concentrations in the plasma water, as derived from the known concentrations after correction for the fraction bound to the human plasma proteins. The data suggest that D2(High) is the primary and common target for the antiparkinson action of dopamine agonists. Bromocriptine, cabergoline, lergotrile, pergolide, and pramipexole had no affinity for D1(High), consistent with the clinical observations that the D2-selective bromocriptine and pramipexole elicit low levels of dyskinesia.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".