Influence of <scp>l</scp> -dopa and pramipexole on striatal dopamine transporter in early PD
Bibliographic record
Abstract
BACKGROUND: Animal data indicate that chronic exposure to dopaminergic drugs can alter levels of the dopamine transporter (DAT), which is critically involved in regulation of synaptic dopamine levels. DAT changes could influence the response to therapy in PD. METHODS: A randomized, assessor-blinded, placebo-controlled clinical trial was performed in subjects with early PD to determine whether L-dopa or pramipexole might regulate striatal DAT binding as measured by PET with [(11)C]RTI-32. Thirty clinically asymmetrical patients were randomly assigned to receive 6 weeks of L-dopa (300/75 mg/d), pramipexole (1.5 mg/d), or placebo; PET studies were performed before and after treatment. RESULTS: Mean interval change in DAT binding was significantly reduced by 16% to 22% in all striatal regions (caudate, anterior and posterior putamen) of the L-dopa-treated patients, whereas significant changes in the pramipexole-treated patients were limited to the contralateral caudate (-15%), ipsilateral anterior putamen (-14%), and posterior putamen (-20%). In the placebo group there were significant changes in contralateral caudate (-11%) and ipsilateral anterior putamen (-12%). L-dopa and pramipexole produced similar clinical benefit. CONCLUSIONS: Short-term therapy with L-dopa and, to a lesser extent, pramipexole can modestly down-regulate striatal DAT in patients with early PD. Decreased striatal DAT could increase dopaminergic neurotransmission with potential benefit, but might also play a role in the development of dopamine-related response fluctuations in patients with advanced disease. Our data also suggest caution in interpretation of longitudinal imaging studies employing DAT to assess disease progression and the efficacy of neuroprotective agents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".