In Vivo Dopamine Transporter Imaging in a Unilateral 6-Hydroxydopamine Rat Model of Parkinson Disease Using <sup>11</sup>C-Methylphenidate PET
Bibliographic record
Abstract
UNLABELLED: Dopamine transporter (DAT) function is altered by many neurodegenerative diseases. For instance, in Parkinson disease DAT density has been shown to decrease in early disease and to play a role in the occurrence of motor complications. DAT is thus an important imaging target with potential therapeutic relevance in humans and animal models of disease. The PET DAT marker (11)C-methylphenidate is commonly used to quantify DAT function. Here we investigate the characteristics of the (11)C-methylphenidate-derived quantification of DAT in rodents using the 6-hydroxydopamine Parkinson disease rat model. METHODS: Seven unilaterally 6-hydroxydopamine-lesioned rats (dopaminergic denervation [DD] range, 36%-94%) were injected with 3.7 MBq/100 g of body weight and tracer masses ranging from 93.8 to 0.0041 μg/100 g of body weight. We evaluated the maximum available transporter density and the in vivo (apparent) ligand-transporter dissociation constant (B(max) and K app d, respectively) with an in vivo Scatchard method using several modeling approaches and estimated the transporter occupancy as a function of the amount of tracer injected and tracer specific activity (SA). RESULTS: Strong evidence of different nonspecific binding in the striatal region, compared with the reference region, leading to bias in the estimate of DD severity was found. One percent transporter occupancy was reached with 0.14 μg of tracer/100 g of body weight, corresponding to an SA of 5.7 kBq/pmol for the given radioactivity dose, and 10% occupancy was reached at 1.5 μg of tracer/100 g of body weight, corresponding to an SA of 0.57 kBq/pmol. The 6-hydroxydopamine lesion affected B(max) (control, 402 ± 94 pmol/mL; lesioned, 117 ± 120 pmol/mL; P = 0.003) but not K app d (control, 331 ± 63 pmol/mL; lesioned, 362 ± 119 pmol/mL; P = 0.63). CONCLUSION: Although DAT imaging can be performed at a relatively high mass of (11)C-methylphenidate (low SA), the additional nonspecific binding found in the striatum can introduce a DD severity-dependent bias in the estimate of tissue-derived binding potential and care must be taken in comparing (11)C-methylphenidate-derived assessment of DD with that obtained using other dopaminergic tracers.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".