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Record W2534746602 · doi:10.1016/j.jalz.2016.06.1901

P3‐239: Asymmetrically Low White Matter Integrity in Seniors with Mci and POOR GAIT

2016· article· en· W2534746602 on OpenAlexaff
Jonatan Snir, Robert Bartha, Manuel Montero‐Odasso

Bibliographic record

VenueAlzheimer s & Dementia · 2016
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsWestern UniversityRobarts Clinical TrialsParkwood Institute
Fundersnot available
KeywordsFractional anisotropyDiffusion MRIWhite matterCorpus callosumPsychologyPhysical medicine and rehabilitationMagnetic resonance imagingCorticospinal tractGaitPopulationTractographyMedicineNeuroscienceRadiology

Abstract

fetched live from OpenAlex

Magnetic resonance diffusion tensor imaging (DTI) allows brain asymmetry to be studied at microscopic scale by examining differences in fiber characteristics across hemispheres. Recent studies demonstrated white matter (WM) asymmetry in healthy older adults exists but its degree is relatively stable during aging and not much dependent on sex. It has been suggested that DTI metrics indicate WM health, maturation, and therefore organization of brain networks shared for cognitive and motor capacity (e.g., gait). As a result, WM disruption may explain the high incidence of falls and predict associated risk in this population. Aberrant asymmetries, reported in several brain disorders, may indicate a pathological progression affecting processes that rely on normal hemispheric specialization. The objective of this study is to evaluate patients diagnosed with Mild Cognitive Impairment (MCI) according to the Petersen criteria for WM asymmetry on DTI and its correlation with gait performance. Twenty four subjects with MCI were evaluated with DTI using a 3T Siemens MRI scanner in addition to comprehensive neuropsychological and neurological evaluation and single- and dual-task gait testing using an electronic walkway (GAITrite systems). Analysis was performed using FSL (Analysis Group, FMRIB, Oxford, UK) and the Tract-Based Spatial Statistics tool, TBSS for left – right differences in common diffusion measures that reflect fiber integrity (fractional anisotropy FA; mean diffusivity, MD). Regions of interest were defined by a registered WM atlas. Significantly decreased FA and increased MD values were observed along WM tracks in the forceps major, left posterior thalamic radiation, corticospinal tract and corpus callosum when compared with the contralateral side within the MCI group. In addition, areas with only significantly decreased FA values and only significantly increased MD values were also detected (e.g hippocampus). Significantly lower WM integrity along the left corticospinal tract correlated with increase dual-task stride time variability and significantly lower WM integrity in the right anterior corona radiata and superior longitudinal fasciculus correlated with increased single-task stride time variability. Significant WM integrity asymmetries were found, allowing further investigations into the correlation between disease state, severity of abnormal WM asymmetry and gait performance in MCI patients.

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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.306
Teacher spread0.272 · 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
Published2016
Admission routes1
Has abstractyes

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