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Record W4390200708 · doi:10.1002/alz.077885

Brain glutathione may be associated with white matter hyperintensities in patients with cardiovascular disease

2023· article· en· W4390200708 on OpenAlexaffabout
Jinghan Jenny Chen, Nathan Herrmann, Kate Survilla, Sandra E. Black, Joel Ramirez, Ana C. Andreazza, Paul Oh, Damien Gallagher, Simon J. Graham, Krista L. Lanctôt

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsUniversity of TorontoUniversity Health NetworkHealth Sciences CentreSunnybrook HospitalToronto Rehabilitation InstituteSunnybrook Health Science Centre
Fundersnot available
KeywordsHyperintensityMontreal Cognitive AssessmentInternal medicineMedicineCardiologyDementiaWhite matterMagnetic resonance imagingAtrophyOxidative stressGlutathioneVascular dementiaStroke (engine)PsychologyDiseaseRadiology

Abstract

fetched live from OpenAlex

Abstract Background White matter hyperintensity (WMH) is a marker of age‐related cerebrovascular damage and is correlated with cognitive impairment; ischemia and inflammatory mechanisms have been proposed to be involved in its pathogenesis. These processes are associated with oxidative stress (OS), which may impair cellular function and affect antioxidant balance; however, the role of central antioxidant responses is still unclear. Method Patients (age 55‐85) with ≥2 vascular risk factors or a previous vascular event were assessed at baseline for an exercise rehabilitation program. All participants completed the Montreal Cognitive Assessment (MoCA). Baseline WHM severity was determined using the standardized Canadian Dementia Imaging Protocol and semiautomatic protocols. Brain glutathione (GSH) at baseline was obtained in the anterior cingulate (AC) and occipital region (OC) using 1H magnetic resonance spectroscopy (MEscher–GArwood Point Resolved Spectroscopy). Spectroscopic analysis was completed using the Gannet toolkit (vers. 3.1) in Matlab (vers. 2020b). Result Of 30 participants (mean age: 66.2 ± 7.42 SD; 80% male) currently enrolled, brain volumetric measurements were completed for 25 participants. Lower MoCA score was associated with greater total WMH volume, controlling for age (b[SE] = ‐0.017 [0.005], t(22) = ‐3.24, p = 0.004); this relationship remained significant when controlling for years of education separately (b[SE] = ‐0.016 [0.006], t(22) = ‐2.86, p = 0.01). Correcting for cerebrospinal fluid volume, lower AC‐GSH level was associated with higher deep WMH volume in the medial middle frontal (MMF) region of interest (b[SE] = ‐0.056 [0.023], t(23) = ‐2.38, p = 0.026), but not with MMF paraventricular WMH volume. After controlling for age, the model was no longer significant (F (2, 22) = 2.87, p = 0.078). No significant associations were found between OC‐GSH and occipital lobe WMH. Conclusion As expected, total white matter hyperintensity volume was associated with poorer global cognition. In the medial middle frontal (MMF) region of interest, higher deep WMH was associated with lower GSH levels, suggesting altered brain antioxidant levels may be associated with the presence or formation of WMH. Recruitment is ongoing, and additional participants are needed to reinforce findings and to control for confounders in the analysis.

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)0.002
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 integrity0.0010.001
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 head0.028
GPT teacher head0.224
Teacher spread0.196 · 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 routes2
Has abstractyes

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