Rasagiline, a monoamine oxidase B inhibitor, reduces in vivo [18F]THK5351 uptake in progressive supranuclear palsy
Bibliographic record
Abstract
[18F]THK5351 is a tau positron emission tomography tracer that has shown promise in quantifying tau distribution in tauopathies such as Alzheimer's disease (AD) and progressive supranuclear palsy (PSP). However, the interpretation of [18F]THK5351 uptake has been shown to be confounded by high monoamine oxidase B (MAO-B) availability across the brain in AD. To test the hypothesis that the MAO-B inhibitor, rasagiline reduces [18F]THK5351 uptake in PSP. Six individuals (4: PSP; 2: cognitively unimpaired, CU) underwent [18F]THK5351 and [18F]AZD4694 to quantify baseline tau and amyloid deposition, respectively. Following a 10-day course of 1 mg rasagiline, all participants received a post-challenge [18F]THK5351 scan. The baseline and post-rasagiline challenge standardized uptake value (SUV) were generated normalized for patient weight and injected radioactivity. The post-rasagiline regional SUV was reduced on average by 69–89% in PSP, and 53–81% in CU. The distributions of post-rasagiline [18F]THK5351 SUV among PSP individuals were not consistent with the typical pattern of tau aggregates in PSP. Similar to AD, the interpretation of [18F]THK5351 uptake in PSP is likely confounded by off-target binding to MAO-B binding sites. [18F]THK5351 is not sufficient in quantifying tau aggregates in PSP using the proposed rasagiline dosing regimen.
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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) | 0.001 | 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 | 0.001 |
| 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".