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Record W4233052103 · doi:10.1016/j.jalz.2018.06.2511

P4‐107: REGIONAL PATTERNS OF TAU DEPOSITION DRIVEN BY LOCAL AMYLOID ACCUMULATION RECAPITULATE BRAAK STAGES IN AD

2018· article· en· W4233052103 on OpenAlexaff
Min Su Kang, Sulantha Mathotaarachchi, Tharick A. Pascoal, Andréa Lessa Benedet, Mira Chamoun, Mélissa Savard, Joseph Therriault, Monica Shin, Émilie Thomas, Jean‐Paul Soucy, Gassan Massarweh, Serge Gauthier, Pedro Rosa‐Neto

Bibliographic record

VenueAlzheimer s & Dementia · 2018
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill Genome CentreDouglas Mental Health University InstituteDouglas CollegeMcGill University
Fundersnot available
KeywordsStatistical parametric mappingPittsburgh compound BAmyloidosisPositron emission tomographyAmyloid (mycology)PathologyPathologicalStandardized uptake valueVoxelMedicineAlzheimer's diseaseNeurosciencePsychologyDiseaseNuclear medicineMagnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

The amyloid plaques and neurofibrillary tangles (NFTs) are the two major hallmarks of Alzheimer's disease (AD). The histopathological studies hint distinct spreading and progression of amyloidosis and NFTs across AD stage. Given the divergent spatial patterns of the hallmarks, the association between the two abnormal protein aggregates in different brain regions is elusive. Here, we reveal the association between amyloidosis and NFTs in cognitively normal (CN), mild cognitive impairment (MCI), and AD individuals with positron emission tomography (PET). The emergence of novel PET tracers of [F]AZD4694 for amyloidosis and [F]MK6240 for NFTs allows precise investigation of each pathological progression in temporal and spatial in vivo. Here, we hypothesize that association between the two hallmarks spreads from posterior to anterior regions following the disease progression. A total of 16 CN, 11 MCI, and 11 AD patients was used. Each subject underwent PET [F]AZD4694 and [F]MK6240 acquisitions. [F]AZD4694 image was processed from 40 minutes post-injection for 30 minutes. [F]MK6240 image was processed from 90 minutes post-injection for 20 minutes. All images were registered to individual MRI with lsq6. Then, they are transformed into ADNI template using lsq12 with nonlinear transformations. The SUVR parametric map was generated using cerebellar grey matter as a reference region for both images. For statistical analysis, we performed voxel-wise analysis to show the association between amyloidosis and NFTs following the model in each group using VoxelStats. [F]MK6240 SUVR ∼ [F]AZD4694 SUVR + age + gender + APOE + education. The unique association between amyloidosis and NFTs was present in entorhinal cortex and PCC in CN; precuneus, PCC, and parahippocampal gyrus in MCI; ACC, entorhinal cortex, parahippocampal gyrus, and orbitofrontal cortex in AD. All groups showed the association in lateral temporal and middle frontal gyrus.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.038
GPT teacher head0.335
Teacher spread0.296 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2018
Admission routes1
Has abstractyes

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