VMAT2 binding is elevated in dopa‐responsive dystonia: Visualizing empty vesicles by PET
Bibliographic record
Abstract
Dopa-responsive dystonia (DRD) is a lifelong disorder in which dopamine deficiency is not associated with neuronal loss and therefore it is an ideal human model for investigating the compensatory changes that occur in response to this biochemical abnormality. Using positron emission tomography (PET), we examined the (+/-)-alpha-[(11)C]dihydrotetrabenazine ([(11)C]DTBZ) binding potential of untreated DRD patients and normal controls. Two other PET markers of presynaptic nigrostriatal function, d-threo-[(11)C]methylphenidate ([(11)C]MP) and 6-[(18)F]fluoro-L-dopa ([(18)F]-dopa), and [(11)C]raclopride were also used in the study. We found increased [(11)C]DTBZ binding potential in the striatum of DRD patients. By contrast, no significant changes were detected in either [(11)C]MP binding potential or [(18)F]-dopa uptake rate constant. In addition, we found evidence for increased dopamine turnover in one DRD patient by examining changes in [(11)C]raclopride binding potential in relation to levodopa treatment. We propose that the increase in [(11)C]DTBZ binding likely reflects the dramatic decrease in the intravesicular concentration of dopamine that occurs in DRD; upregulation of vesicular monoamine transporter type 2 (VMAT2) expression may also contribute. Our findings suggest that the striatal expression of VMAT2 (as estimated by [(11)C]DTBZ binding) is not coregulated with dopamine synthesis. This is in keeping with a role for VMAT2 in other cellular processes (i.e., sequestration and release from the cell of potential toxic products), in addition to its importance for the quantal release of monoamines.
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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 | 0.001 | 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".