No Dopamine Agonist Modulation of Brain [<sup>18</sup>F]FEOBV Binding in Parkinson’s Disease
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The [ 18 F]fluoroethoxybenzovesamicol ([ 18 F]FEOBV) positron emission tomography (PET) ligand targets the vesicular acetylcholine transporter. Recent [ 18 F]FEOBV PET rodent studies suggest that regional brain [ 18 F]FEOBV binding may be modulated by dopamine D2-like receptor agents. We examined associations of regional brain [ 18 F]FEOBV PET binding in Parkinson’s disease (PD) subjects without versus with dopamine D2-like receptor agonist drug treatment. PD subjects ( n = 108; 84 males, 24 females; mean age 68.0 ± 7.6 [SD] years), mean disease duration of 6.0 ± 4.0 years, and mean Movement Disorder Society-revised Unified PD Rating Scale III 35.5 ± 14.2 completed [ 18 F]FEOBV brain PET imaging. Thirty-eight subjects were taking dopamine D2-like agonists. Vesicular monoamine transporter type 2 [ 11 C]dihydrotetrabenazine (DTBZ) PET was available in a subset of 54 patients. Subjects on dopamine D2-like agonists were younger, had a longer duration of disease, and were taking a higher levodopa equivalent dose (LED) compared to subjects not taking dopamine agonists. A group comparison between subjects with versus without dopamine D2-like agonist use did not yield significant differences in cortical, striatal, thalamic, or cerebellar gray matter [ 18 F]FEOBV binding. Confounder analysis using age, duration of disease, LED, and striatal [ 11 C]DTBZ binding also failed to show significant regional [ 18 F]FEOBV binding differences between these two groups. Chronic D2-like dopamine agonist use in PD subjects is not associated with significant alterations of regional brain [ 18 F]FEOBV binding.
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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) | 0.001 | 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".