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Record W2910508414 · doi:10.1016/j.jalz.2018.07.222

Vascular dysfunction—The disregarded partner of Alzheimer's disease

2019· article· en· W2910508414 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAlzheimer s & Dementia · 2019
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsOntario Brain InstituteMcGill UniversityUniversity of CalgaryUniversity of British ColumbiaToronto Dementia Research AllianceMontreal Neurological Institute and HospitalWestern UniversityUniversity of TorontoHotchkiss Brain InstituteHealth Sciences CentreHeart and Stroke FoundationSunnybrook Health Science Centre
FundersNational Institute of Biomedical Imaging and BioengineeringNovo Nordisk FondenUniversity of TorontoNational Institutes of HealthSunnybrook Research InstituteLundbeckfondenNational Institute of Neurological Disorders and StrokeNational Institute for Health and Care ResearchNational Center for Advancing Translational SciencesUniversity of Southern CaliforniaMedical Research CouncilNational Institute on AgingAlzheimer's AssociationNational Heart, Lung, and Blood InstituteCure Alzheimer's FundHeart and Stroke Foundation of Canada
KeywordsPathophysiologyDiseaseDementiaMedicineBiomarkerVascular dementiaNeuroscienceCerebral blood flowVascular diseasePathologyBioinformaticsPsychologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Increasing evidence recognizes Alzheimer's disease (AD) as a multifactorial and heterogeneous disease with multiple contributors to its pathophysiology, including vascular dysfunction. The recently updated AD Research Framework put forth by the National Institute on Aging-Alzheimer's Association describes a biomarker-based pathologic definition of AD focused on amyloid, tau, and neuronal injury. In response to this article, here we first discussed evidence that vascular dysfunction is an important early event in AD pathophysiology. Next, we examined various imaging sequences that could be easily implemented to evaluate different types of vascular dysfunction associated with, and/or contributing to, AD pathophysiology, including changes in blood-brain barrier integrity and cerebral blood flow. Vascular imaging biomarkers of small vessel disease of the brain, which is responsible for >50% of dementia worldwide, including AD, are already established, well characterized, and easy to recognize. We suggest that these vascular biomarkers should be incorporated into the AD Research Framework to gain a better understanding of AD pathophysiology and aid in treatment efforts.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.022
GPT teacher head0.291
Teacher spread0.269 · 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