Positron emission tomography imaging of tau pathology in progressive supranuclear palsy
Bibliographic record
Abstract
Progressive supranuclear palsy is a rare form of atypical Parkinsonism that differs neuropathologically from other parkinsonian disorders. While many parkinsonian disorders such as Parkinson’s disease, Lewy body dementia, and multiple system atrophy are classified as synucleinopathies, progressive supranuclear palsy is coined a tauopathy due to the aggregation of pathological tau in the brain. [ 18 F]AV-1451 (also known as [ 18 F]-T807) is a positron emission tomography radiotracer that binds to paired helical filaments of tau in Alzheimer’s disease. We investigated whether [ 18 F]AV-1451 could be used as biomarker for the diagnosis and disease progression monitoring in progressive supranuclear palsy. Six progressive supranuclear palsy, six Parkinson’s disease, and 10 age-matched healthy controls were recruited. An anatomical MRI and a 90-min PET scan, using [ 18 F]AV-1451, were acquired from all participants. The standardized uptake value ratio from 60 to 90 min post-injection was calculated in each region of interest, using the cerebellar cortex as a reference region. No significant differences in standardized uptake value ratios were detected in our progressive supranuclear palsy group compared to the two control groups. [ 18 F]AV-1451 may bind selectivity to the paired helical filaments in Alzheimer’s disease, which differ from the straight conformation of tau filaments in progressive supranuclear palsy.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".