Dopamine transporter PET in normal aging: Dopamine transporter decline and its possible role in preservation of motor function
Bibliographic record
Abstract
OBJECTIVES: To determine the impact of age-related decline in dopamine transporter (DAT) expression on motor function in the elderly. METHODS: About 33 normal individuals of a wide age range were scanned with PET employing d-threo-[(11)C]-methylphenidate (MP, a marker of DAT) and [(11)C]-dihydrotetrabenazine (DTBZ, that binds to the vesicular monoamine transporter Type 2). Motor function was assessed using the Purdue Pegboard Test (PPB). We analyzed the relationship between [(11)C]-MP and motor performance. RESULTS: Age ranged from 27- to 77-year old (mean +/- SD, 54.75 +/- 14.14). There was no age-related decline in binding potentials (BP) for [(11)C]-DTBZ. In contrast, [(11)C]-MP BP was inversely related to age in all striatal regions analyzed (caudate: reduction of 11.2% per decade, P < 0.0001, r = -0.86; putamen: reduction of 10.5% per decade, P < 0.0001, r = -0.80). A differential effect of [(11)C]-MP on PPB could be observed according to age group. There was a positive relation between the PPB and [(11)C]-MP in young individuals (coefficient = 13.56), whereas in individuals greater than 57 years this relationship was negative (coefficient = -19.53, P = 0.031). CONCLUSIONS: Our findings confirm prior observations of age-related DAT decline and suggest that this phenomenon is independent of changes in VMAT2. After the fifth decade of life, this reduction in DAT binding is associated with a motor performance comparable to mid-adult life. These findings imply that biochemical processes associated with healthy aging may offset the naturaldecline in motor function observed in the elderly.
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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 | 0.001 |
| 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) | 0.001 | 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".