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Record W4390194318 · doi:10.1002/alz.075974

Interaction between Oligomeric Amyloid‐β and Cardiovascular Risk Factors is Associated with Executive and Dorsal Attention Network Dysfunction in Pre‐dementia

2023· article· en· W4390194318 on OpenAlexaboutno aff
Dilip Kumar, See Ann Soo, Gurveen Kaur Sandhu, Fatin Zahra Zailan, Yi Jin Leow, Ashwati Vipin, Chen Ling Koh, Faith Phemie Hui En Lee, Smriti Ghildiyal, Nagaendran Kandiah

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaMedicineExecutive dysfunctionInternal medicineCognitionMontreal Cognitive AssessmentCognitive declineDefault mode networkCohortNeuropsychologyPsychologyOncologyPsychiatryDisease

Abstract

fetched live from OpenAlex

Abstract Background Oligomeric amyloid‐β(OAβ) accumulation within brain tissue has been shown to be associated with major AD neuropathological features including tau pathology, synaptic loss, inflammation and oxidative damage; as well as cognitive impairment in dementia cohorts (Celine.E.N et.al.,2018). However, association of OAβ with functional connectivity (FC) and cardiovascular risk factors is not clearly known in the pre‐dementia stage. We aimed to examine association of FC with OAβ and other dementia risk factors in a pre‐dementia cohort to understand the underlying mechanisms related to OAβ. Methods We included 98 age and sex matched participants and classified them into OAβ+(28) and OAβ‐(70) subgroups using a OAβ cut‐off ratio of ≥ 0.9 (MDS‐ OAβ Test Kit, PeopleBio Inc, South Korea). Participants completed resting‐state functional MRI, clinical and lifestyle history questionnaires, blood, and neuropsychological assessments for global cognition on Montreal cognitive assessment and Visual Cognitive Assessment at Dementia Research Centre (Singapore). The Cardiovascular Risk Factors, Aging and Dementia (CAIDE) risk score was computed, and independent sample or chi‐squared analysis were performed to evaluate group‐level participant characteristics. Region‐of‐interest based FC analysis for 19 seeds from executive control (ECN), default‐mode, salience and dorsal‐attention networks (DAN) was performed to examine the network‐based FC differences in OAβ+ and OAβ‐ groups in association with CAIDE using ANCOVA model. Results Mean age of OAβ+ and OAβ‐ were 62.04±8.84, and 62.05±8.07 (Table‐1). No significant FC differences were observed between OAβ+ vs OAβ‐ subjects. There were no significant FC differences related to CAIDE score in OAβ+ and OAβ‐ groups. Nonetheless, the OAβ*CAIDE interaction showed significant FC changes. The OAβ+*CAIDE interaction analyses showed reduced FC within ECN and DAN (Figure‐1a). Whereas OAβ‐*CAIDE interaction showed reduced FC only within ECN (Figure‐1b). Furthermore, OAβ interaction with apolipoprotein‐ε4 (OAβ*APOE4) was found to further influence FC trends in ECN and DAN (Figure‐1c,1d). Conclusion While no FC differences were observed between OAβ+ vs OAβ‐ subjects, the interaction between CAIDE and APOE4 moderated FC changes within the ECN and DAN. These observations in a pre‐dementia cohort suggest that the presence of cerebrovascular risk factors may result in differential FC dysfunction in ECN and DAN depending on APOE4 status.

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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.252
Teacher spread0.219 · 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
Published2023
Admission routes1
Has abstractyes

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