Dopamine turnover increases in asymptomatic <i>LRRK2</i> mutations carriers
Bibliographic record
Abstract
Increase in dopamine (DA) turnover was found to occur early in symptomatic Parkinson's disease (PD) and to be functionally related to the dopamine transporter (DAT). The objectives of this study were to examine changes in DA turnover in the asymptomatic PD phase; to compare them with changes in other dopaminergic markers, and to investigate a possible relationship between DAT and DA turnover. Eight subjects from families at increased risk of PD due to LRRK2 mutation were investigated. Positron emission tomography imaging was performed with: ¹⁸F-fluorodopa to determine the effective DA distribution volume (EDV), the inverse of DA turnover, and the DA uptake rate K(occ), a marker of DA synthesis and storage; ¹¹C-methylphenidate (MP, a DAT marker) and ¹¹C-dihydrotetrabenazine (DTBZ, a VMAT2 marker) to estimate the binding potentials BP(ND_MP) and BP(ND_DTBZ). On average, EDV showed the largest reduction from age-matched control values (42%) followed by BP(ND_MP) (23%) and BP(ND_DTBZ) (17%), whereas K(occ) remained in the normal range for all subjects. No correlation was found between EDV and any other marker. DA turnover was found to be elevated in asymptomatic mutation carriers at increased risk of PD. Such change was determined to be larger than and statistically independent from changes observed with the other markers. These results support a compensatory role of increased DA turnover in presymptomatic disease and indicate that at this stage, in contrast to the symptomatic PD phase, increased turnover is not related to DAT.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".