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Record W4406222830 · doi:10.1002/alz.093648

Comparison of cerebrospinal fluid and plasma oxidative stress biomarkers

2024· article· en· W4406222830 on OpenAlexaff
Adrián Noriega de la Colina, Sokratis Charisis, Eva Ntanasi, Eirini Mamalaki, Zoi Skaperda, Demetrios Kouretas, Nikolaos Scarmeas

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsCerebrospinal fluidOxidative stressPlasmaMedicinePathologyInternal medicinePhysics

Abstract

fetched live from OpenAlex

Abstract Background Numerous studies have highlighted the role of oxidative stress in Alzheimer's disease (AD) development. Yet, the alignment of systemic and central oxidative stress biomarkers is unclear across diverse populations in the AD continuum. This study aims to assess protein damage levels in plasma and cerebrospinal fluid (CSF) within the AD continuum. Methods One hundred forty participants without clinical dementia (47 with Mild Cognitive Impairment [MCI] and 93 cognitively unimpaired) from a memory clinic cohort underwent examination for central (CSF) and systemic (plasma) markers of oxidative stress. We measured Total Antioxidant Capacity (TAC), reduced glutathione (GSH), thiobarbituric acid reactive substances (TBARS), and reducing power (RP) using standard laboratory techniques and absorbance spectrophotometry (Hitachi U‐1500). Pearson’s correlations were employed to determine the congruence between the same biomarkers of oxidative stress in CSF and plasma. Factor analysis was performed to ascertain how many antioxidant dimensions they represent. Results Table 1 outlines participants' baseline characteristics. Pearson’s correlation analysis for the entire sample revealed no congruence between CSF and plasma in TAC (r=+.087) and GSH (r=.‐.161), while CSF and plasma RP (r=.+385*) and TBARS (r=‐.216*) were correlated (Figure 1). Upon analyzing group‐level data, the cognitively unimpaired group showed congruence between CSF and plasma for GSH (r.=‐.279*) and TBARS (r=‐.287*) but not for TAC (r=+.191) and RP (r=+.202). In the MCI group, only RP (r.=+.640*) demonstrated congruence between CSF and plasma. Factor analysis with CSF biomarkers identified two components in the whole sample (Figure 2). Dimension 1= GSH, and Dimension 2=TAC, TBARS, and RP. Factor analysis with plasma identified as well two components: Dimension 1=RP and GSH, Dimension 2=TBARS and TAC. The factor analysis for the MCI group revealed the presence of a single component for CSF biomarkers, while there were two components for plasma: Dimension 1=RP and TBARS, Dimension 2=TAC and GSH. Conclusion Oxidative stress biomarker patterns differ across the AD continuum. RP demonstrates the most reliability, while TAC is the least. GSH and TBARS plasma and CSF measurements are negatively associated in the cognitively unimpaired, but not in the MCI population. Understanding oxidative biomarker evolution can enhance our comprehension of their role in AD and age‐related disorders.

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)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.322
Teacher spread0.282 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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