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Record W2461886997 · doi:10.1016/j.jalz.2015.06.376

P1‐177: Extensive white matter burden represents a new radiological phenotype in a distinct population of ad patients

2015· article· en· W2461886997 on OpenAlexaff
Paolo Vitali, Serge Gauthier, Tom Beaudry, Jean‐Paul Soucy, Simona M. Brambati, Pedro Rosa‐Neto

Bibliographic record

VenueAlzheimer s & Dementia · 2015
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsInstitut Universitaire de Gériatrie de MontréalDouglas Mental Health University InstituteMcGill UniversityMcGill Genome CentreUniversité de Montréal
Fundersnot available
KeywordsGrey matterWhite matterAlzheimer's Disease Neuroimaging InitiativeNeurodegenerationNeuroimagingMedicineInternal medicinePathologyPopulationDiseasePsychologyAlzheimer's diseaseOncologyNuclear medicineNeuroscienceMagnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

Previous neuropathological observations and neuroimaging studies in pathologically-proven non-AD dementias showed that tauopathies have characteristic tau inclusions throughout white matter (WM) brain regions, with relative sparing of grey matter (GM). However, the association between surrogate CSF markers of tau-induced neurodegeneration and WM structural changes in patients with Alzheimer's disease (AD) remains overlooked. In this study, we compared clinically-defined AD patients with and without CSF evidence of tau neurodegeneration, in order to radiologically characterize tau-dependent neurodegenerative processes in AD. Data were obtained from the ADNI (Alzheimer's Disease Neuroimaging Initiative) database (adni.loni.usc.edu) on all individuals with a baseline diagnosis of AD or normal control (CN), baseline T1-weighted brain MRI and CSF biomarkers. For the AD group, only patients with CSF amyloid-β1-42levels below the 192 pg/mL threshold (suggestive of significant cerebral amyloidopathy) were retained for further analyses. Selected AD patients were dichotomized using previously published CSF total tau (T-Tau) cutoff values: T-Tau positive (n=145, males=72) and T-Tau negative (n=63, males=48) patients, characterized by CSF T-Tau values above or below the 93 pg/mL threshold, respectively. Voxel-based morphometry (VBM) was applied to compare whole-brain patterns of GM and WM volume in T-Tau positive and negative patients. Statistical analyses were performed by using SPM12 software. Age, gender, education, MMSE score, MRI field strength and intracranial volume were included as nuisance variables in the analysis. T-Tau positive and negative patients were comparable in terms of age, dementia clinical severity, ApoE4 phenotype, and neuropsychological impairment. Only T-tau positive AD exhibited significant (FWE corrected) and extensive WM volume loss in bilateral medial temporal regions compared to CN, in particular in the parahyppocampal WM. When compared to T-tau negative AD, T-tau positive patients showed no GM volume reduction. Instead, they presented extensive WM atrophy in bilateral fornix, corona radiata and centrum semiovale (p<0.001 uncorrected).

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)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.043
GPT teacher head0.320
Teacher spread0.276 · 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
Published2015
Admission routes1
Has abstractyes

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