<scp>PET</scp> imaging of synaptic density in Parkinsonian disorders
Bibliographic record
Abstract
Synaptic dysfunction and altered synaptic pruning are present in people with Parkinsonian disorders. Dopamine loss and alpha-synuclein accumulation, two hallmarks of Parkinson's disease (PD) pathology, contribute to synaptic dysfunction and reduced synaptic density in PD. Atypical Parkinsonian disorders are likely to have unique spatiotemporal patterns of synaptic density, differentiating them from PD. Therefore, quantification of synaptic density has the potential to support diagnoses, monitor disease progression, and treatment efficacy. Novel radiotracers for positron emission tomography which target the presynaptic vesicle protein SV2A have been developed to quantify presynaptic density. The radiotracers have successfully investigated synaptic density in preclinical models of PD and people with Parkinsonian disorders. Therefore, this review will summarize the preclinical and clinical utilization of SV2A radiotracers in people with Parkinsonian disorders. We will evaluate how SV2A abundance is associated with other imaging modalities and the considerations for interpreting SV2A in Parkinsonian pathology.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".