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Record W4406217741 · doi:10.1002/alz.092848

Exercise reduces white matter pathology in vascular cognitive impairment

2024· article· en· W4406217741 on OpenAlexaff
Nárlon Cássio Boa Sorte Silva, Elizabeth Dao, Ryan S. Falck, Walid Ahmed Alkeridy, Roger Tam, Kevin Lam, Cindy K. Barha, Rachel A. Crockett, Lisanne F. ten Brinke, Thalia S. Field, Teresa Liu‐Ambrose

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsLibin Cardiovascular Institute of AlbertaOntario Brain InstituteVancouver Coastal HealthVancouver Coastal Health Research InstituteInternational Collaboration On Repair DiscoveriesUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsWhite matterCognitive impairmentMedicineCognitionPathologyWhite (mutation)HyperintensityPhysical medicine and rehabilitationPsychologyNeuroscienceMagnetic resonance imagingRadiologyBiology

Abstract

fetched live from OpenAlex

Abstract Background Subcortical ischemic vascular cognitive impairment (SIVCI) is highly prevalent in older individuals. White matter hyperintensities (WMH) are a defining feature of SIVCI. There are sex differences in SIVCI, with females having higher volume and faster WMH progression than males. Resistance exercise training (RT) can slow WMH progression in cognitively unimpaired individuals; however, evidence in SIVCI is scarce. It is also unknown if biological sex influences WMH response to exercise. We investigated whether RT mitigated WMH in older individuals living with SIVCI and assessed whether biological sex moderated intervention effects. Methods This was a 12‐month single‐blind, randomized controlled trial. Participants were randomized to RT (n = 45, females = 32) or a balance and tone (BAT) control group (n = 46, females = 29). Study eligibility included: 1) age 55 years and older; 2) magnetic resonance imaging (MRI) evidence of cerebral small vessel disease; 3) mild cognitive impairment; and 4) absence of dementia. We measured WMH using a seed‐based pipeline incorporating T2‐ and PD‐weighted MRI scans. We extracted volumes for whole‐brain and lobe‐specific regions‐of‐interest. Differences between groups from baseline to 12 months were assessed via analysis of covariance adjusting for baseline WMH volume, estimated intracranial volume, and sex. We assessed sex‐specific effects via group‐by‐sex interaction terms. Results Seventy‐four participants (aged 74.3 [SD = 5.6], 65% females) completed follow‐up assessment and were included in the analysis. At 12 months, no main effect of intervention was observed for whole‐brain WMH volume (estimated mean difference [asinh‐transformed cm3]: ‐0.045, 95% CI: ‐0.124 to 0.034, p = 0.264). Biological sex significantly moderated intervention effects on whole‐brain WMH volume (p = 0.019), whereby RT reduced WMH volume (vs BAT controls) in females (‐0.113, 95% CI: ‐0.208 to ‐0.018, p = 0.021) but not males (0.081, 95% CI: ‐0.048 to 0.211, p = 0.216). Lobe‐specific analysis revealed that RT reduced WMH volume (vs BAT controls) in the parietal (‐0.074, 95% CI: ‐0.148 to ‐0.0004, p = 0.049) and temporal (‐0.069, 95%CI: ‐0.138 to ‐0.00003, p = 0.049) lobes. Group‐by‐sex interaction effects approached significance for parietal WMH volume (p = 0.052), suggesting an overall sex‐dependent effect of training. Conclusion RT may be an effective strategy to mitigate WMH progression in older individuals with SIVCI and females likely reap greater benefits than males.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.274
Teacher spread0.247 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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