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Record W4390236992 · doi:10.18502/cjn.v22i4.14526

Plasma neurofilament light chain associated with impaired regional cerebral blood flow in healthy individuals

2023· article· en· W4390236992 on OpenAlex
Fardin Nabizadeh, Richard T. Ward, Mohammad Balabandian, Samuel Berchi Kankam, Mahsa Pourhamzeh

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCurrent Journal of Neurology · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNational Institutes of HealthGenentechIXICOH. Lundbeck A/SServierEisaiNorthern California Institute for Research and EducationPfizerNovartis Pharmaceuticals CorporationUniversity of Southern CaliforniaBiogenEli Lilly and CompanyBristol-Myers SquibbBioClinicaU.S. Department of DefenseAlzheimer's Disease Neuroimaging InitiativeMeso Scale DiagnosticsNational Institute on AgingAlzheimer's Association
KeywordsCerebral blood flowInternal medicineMedicineBiomarkerNeuroimagingDiseaseApolipoprotein EOncologyCardiologyAlzheimer's diseaseCognitive impairmentPsychologyNeurosciencePsychiatryBiology

Abstract

fetched live from OpenAlex

Background: Recent findings suggest that the plasma axonal structural protein, neurofilament light (NFL) chain, may serve as a potential blood biomarker for early signs of neurodegenerative diseases, such as Alzheimer’s disease (AD). Given the need for early detection of neurodegenerative disorders, the current study investigated the associations between regional cerebral blood flow (rCBF) in brain regions associated with neurodegenerative disorders and memory function with plasma NFL in AD, mild cognitive impairment (MCI), and healthy controls (HCs). Methods: We recruited 29 AD, 76 MCI, and 39 HCs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database in the current cross-sectional study. We used Pearson’s correlation models adjusted for the effect of age, sex, and APOE genotype to investigate the association between plasma NFL and rCBF. Results: We found non-significant differences in age (F(2, 141) = 1.304; P = 0.275) and years of education (F(2, 141) = 0.013; P = 0.987). Additionally, we found significant differences between groups in terms of MMSE scores (F(2, 141) = 100.953; P < 0.001). Despite the observation of significantly reduced rCBF in AD and MCI groups versus HCs, we did not detect significant differences in plasma NFL between these groups. We found significant negative associations between plasma NFL and rCBF in various AD-related regions, these findings were only observed after analyses in all participants, and were observed in HCs alone and no significant associations were observed in the AD or MCI groups. Conclusion: These outcomes add to our current understanding surrounding the use of rCBF and plasma NFL biomarkers as tools for early detection and diagnosis of neurodegenerative diseases. A conclusion might be that the association between NFL and impaired rCBF exists before the clinical symptoms appear. Further longitudinal studies with a large sample size should be performed to examine the correlation between plasma NFL and rCBF in order to understand these complex relationships.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.621

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.326
Teacher spread0.283 · 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