Dopamine transporter relation to levodopa‐derived synaptic dopamine in a rat model of Parkinson’s: an <i>in vivo</i> imaging study
Bibliographic record
Abstract
Studies showed that the dopamine (DA) transporter (DAT) modulates changes in levodopa-derived synaptic dopamine levels (Delta(DA)) in Parkinson's disease (PD). Here we evaluate the relationship between DAT and Delta(DA) in the 6-hydroxydopamine model of Parkinson's disease to investigate these mechanisms as a function of dopaminergic denervation and in relation to other denervation-induced regulatory changes. 27 rats with a unilateral 6-hydroxydopamine lesion (denervation approximately 20-97%) were imaged with (11)C-dihydrotetrabenazine (VMAT2 marker), (11)C-methylphenidate (DAT marker) and (11)C-raclopride (D2-type receptor marker). For denervation <75%Delta(DA) was significantly correlated with a combination of relatively preserved terminal density and lower DAT. For denervation <90%, Delta(DA) was significantly negatively correlated with DAT with a weaker dependence on VMAT2. For the entire data set, no dependence on pre-synaptic markers was observed; Delta(DA) was significantly positively correlated with (11)C-raclopride binding-derived estimates of DA loss. These findings parallel observations in humans, and show that (i) regulatory changes attempt to normalize synaptic DA levels (ii) a lesion-induced functional dependence of Delta(DA) on DAT occurs up to approximately 90% denervation (iii) for denervation < 75% relative lower DAT levels may relate to effective compensation; for higher denervation, lower DAT levels likely contribute to oscillations in synaptic DA associated with dyskinesias.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".