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Record W3007160812 · doi:10.1097/rlu.0000000000002949

Tau Imaging in the 4-Repeat-Tauopathies Progressive Supranuclear Palsy and Corticobasal Syndrome

2020· article· en· W3007160812 on OpenAlexaff
Nils Schröter, Ganna Blazhenets, Lars Frings, Christoph Barkhausen, Wolfgang H. Jost, Cornelius Weiller, Michel Rijntjes, Philipp T. Meyer

Bibliographic record

VenueClinical Nuclear Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsBC Research (Canada)
Fundersnot available
KeywordsProgressive supranuclear palsyCorticobasal degenerationMedicineNeuroscienceFrontotemporal dementiaDementia with Lewy bodiesTau pathologyDementiaPathologyNuclear medicineAlzheimer's diseaseDiseasePsychology

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: To evaluate tau PET using C-pyridinyl-butadienyl-benzothiazole 3 (C-PBB3) in the 4-repeat (4R)-tauopathies progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS). METHODS: Retrospective analysis of C-PBB3 PET in 2, 7, and 2 patients with CBS, PSP, and Alzheimer dementia (AD), respectively. Normalized C-PBB3 uptake in clusters with significant hypometabolism on F-FDG-PET and corresponding atlas-based volumes of interest was compared between diagnostic groups. RESULTS: In accordance with visually appreciable group differences, C-PBB3 uptake was significantly higher in dorsolateral frontal and motor cortex in CBS patients and frontal and temporal cortices in AD patients as compared with PSP patients. Patients with PSP showed mildly but significantly higher uptake in midbrain compared with AD patients. CONCLUSIONS: In line with known neuropathological changes, the spatial pattern and magnitude of C-PBB3 tau binding differ between CBS, PSP, and AD, which may be of diagnostic utility. Thus, C-PBB3 offers a promising lead structure for development of ligands for tau imaging, including 4R-tauopathies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.568

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.046
GPT teacher head0.341
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2020
Admission routes1
Has abstractyes

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