[18F]SynVest-1 PET imaging in people with Parkinson’s disease
Bibliographic record
Abstract
Abstract The [18F]SynVest-1 radiotracer targets the synaptic vesicle glycoprotein 2A (SV2A) and is a proxy of presynaptic density. Parkinson’s disease is associated with synaptic dysfunction. Here we investigated synaptic density via the [18F]SynVest-1 radiotracer in people with PD compared with healthy controls, with reference to how it compares to the previous SV2A radiotracer, [11C]UCB-J. Ten Parkinson’s patients and 12 healthy subjects underwent a [18F]SynVest-1 PET scan. We compared non-displaceable binding potential via voxel-wise and volume of interest analysis to investigate group differences. Volume-of-interest-analyses reported lower non-displaceable binding potential in key a priori regions associated with Parkinson’s disease, namely the substantia nigra and caudate nucleus (P < 0.05). Follow-up exploratory volume-of-interest-analyses reported widespread reduction in non-displaceable binding potential within all brain lobes, cerebellum, hippocampus, thalamus and insula; however, these findings did not survive correction for multiple comparisons (P < 0.004). In addition, voxel-wise analyses with family-wise error correction, highlighted significantly lower non-displaceable binding potential in the PD cohort within the putamen and cerebellum. We did not observe any relationships between clinical metrics and non-displaceable binding potential. The results are in line with differences observed using the [11C]UCB-J radiotracer. The [18F]SynVest-1 radiotracer confirmed lower synaptic density in the Parkinson’s disease cohort and adds to the growing evidence of synaptic dysfunction in Parkinson’s disease 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 | 0.000 | 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) | 0.000 | 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".