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Record W2084348174 · doi:10.1016/j.jalz.2013.08.111

P4‐330: Association of brain amyloidosis and metabolism with the Trail Making Test in MCI and Alzheimer's disease

2012· article· en· W2084348174 on OpenAlexaff
Sara Mohades, Jared Rowley, Antoine Leuzy, Liyong Wu, Marina Tedeschi Dauar, Vladimir Fonov, Monica Shin, Christine Zaccaria, Serge Gauthier, Pedro Rosa‐Neto

Bibliographic record

VenueAlzheimer s & Dementia · 2012
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsDementiaMedicineNeuropsychologyAlzheimer's diseasePittsburgh compound BBoston Naming TestCognitive declineVoxelPopulationAmyloidosisInternal medicineNuclear medicinePsychologyPathologyCognitionDiseasePsychiatryRadiology

Abstract

fetched live from OpenAlex

Alzheimer's disease is a process characterized by cognitive decline secondary to progressive amyloidosis and neurodegeneration. Making Test B-A latency (TMTB-AL) is a method to measure executive dysfunction in individuals with presymptomatic dementia. Aims: To investigate the association between TMTB-AL and regional patterns of amyloidosis ([18 F]AV45 retention) and synaptic dysfunction ([18 F]FDG uptake) in individuals with early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI) and Alzheimer's dementia (AD). We analyzed a subsample of participants from ADNIGO and ADNI2, with clinical, neuropsychological, [18F]AV45, [18F]FDG data collected in the same study visit. Diagnosis of cognitively normal (CN), EMCI, LMCI and AD was adjusted to study visit according to ADNI2 guidelines. PET scans were registered to the MRI. PET uptake ratios (UR) were calculated by dividing [18F]AV45 and [18F]FDG scans by the median counts of cerebellar GM and pons, respectively. PET images were registered to the MNI space using the previously defined non-linear transformations. Voxel-based (age-corrected) regression between PET images and TMTB-A delayed recall were calculated with PET-UR resampled and blurred with a 6mm Gaussian filter. Demographic and PET data is summarized in Table 1. Positive correlation was found between global [18 F]AV45 and TMPB-A across all groups (p< 0.0001, r= 0.243). Global [18 F]FDG-UR and TMPB-A was negatively correlated in all subjects (p < 0.0001, r= 0.268). Across the entire population, voxel-based analysis showed cortical [18 F]AV45 were associated with TMPB-A, while correlations with [18 F]FDG-UR were found in dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), inferior parietal cortex (IPC), and posterior cingulated cortex (PCC). Association between TMPB-AL and [18 F]AV45 was observed in the left DLPFC and precuneus, in EMCI and LMCI, respectively. Areas associated with [18 F]FDG-UR and TMPB-A in EMCI and LMCI were found in IPC and DLPFC, while PCC was also present in AD. In EMCI and LMCI, decline in TMPB-AL is linked to the synaptic degeneration of IPC-DLPFC circuits underlying executive function whereas in demented individuals the PCC synaptic degeneration also significantly contribute to executive deficits. Decline in TMPB-AL is not associated to a specific regional pattern of amyloid deposition. In figure it is shown Aβ (1–42) where Aβ (13–23) is illustrated in silver.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.020
GPT teacher head0.292
Teacher spread0.272 · 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
Published2012
Admission routes1
Has abstractyes

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