PET demonstrates reduced dopamine transporter expression in PD with dyskinesias
Bibliographic record
Abstract
OBJECTIVE: Dyskinesias are common in Parkinson disease (PD). Prior investigations suggest that dopamine (DA) terminals compensate for abnormal DA transmission. We verified whether similar adaptations could be related to the development of treatment-related complications. METHODS: Thirty-six patients with PD with motor fluctuations were assessed with PET using [(11)C]-d-threo-methylphenidate (MP) and [(11)C]-(+/-) dihydrotetrabenazine (DTBZ). The expression of DA transporter relative to DA nerve terminal density was estimated by determining the MP/DTBZ ratio. Age, treatment, and disease severity were also taken into account in the evaluation of our data. RESULTS: Twenty-seven of the 36 patients had dyskinesias. Nine individuals had motor fluctuations without dyskinesia. The two patient groups were comparable in terms of age, disease duration and severity, medication, and striatal MP and DTBZ binding potentials. The MP/DTBZ ratio in the caudate was not different between groups (nondyskinesia 1.54 +/- 0.36, dyskinesia 1.39 +/- 0.28; mean +/- SD, p = 0.23). Putaminal MP/DTBZ was decreased in individuals with dyskinesia (1.18 +/- 0.24), compared to those who had motor fluctuations without dyskinesia (1.52 +/- 0.24, p = 0.019). The relationship between putaminal MP/DTBZ ratio and the presence of dyskinesias was not altered after correcting for age, treatment, and measures of disease severity. CONCLUSIONS: This investigation supports the role of presynaptic alterations in the appearance of dyskinesias. Dopamine (DA) transporter downregulation may minimize symptoms by contributing to increased synaptic DA levels in early Parkinson disease, but at the expense of leading to increased extracellular DA catabolism and oscillating levels of DA. Such oscillations might ultimately facilitate the appearance of dyskinesias.
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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 | 0.000 | 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".