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Record W3033147965 · doi:10.1093/braincomms/fcaa061

Cerebral atrophy in amyotrophic lateral sclerosis parallels the pathological distribution of TDP43

2020· article· en· W3033147965 on OpenAlexaffabout
Mahsa Dadar, Ana L. Manera, Lorne Zinman, Lawrence Korngut, Angela Genge, Simon J. Graham, Richard Frayne, D. Louis Collins, Sanjay Kalra

Bibliographic record

VenueBrain Communications · 2020
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsWomen and Children’s Health Research InstituteUniversity of AlbertaFoothills Medical CentreMontreal Neurological Institute and HospitalUniversity of TorontoSunnybrook Health Science CentreHealth Sciences CentreUniversity of CalgaryMcGill University
Fundersnot available
KeywordsAmyotrophic lateral sclerosisPrecentral gyrusAtrophyCorticospinal tractWhite matterInternal capsuleMedicineMotor cortexNeuroscienceNeuroimagingPathologyGrey matterPyramidal tractsPsychologyMagnetic resonance imagingDiseaseDiffusion MRIRadiology

Abstract

fetched live from OpenAlex

Abstract Amyotrophic lateral sclerosis is a neurodegenerative disease characterized by a preferential involvement of both upper and lower motor neurons. Evidence from neuroimaging and post-mortem studies confirms additional involvement of brain regions extending beyond the motor cortex. The aim of this study was to assess the extent of cerebral disease in amyotrophic lateral sclerosis cross-sectionally and longitudinally and to compare the findings with a recently proposed disease-staging model of amyotrophic lateral sclerosis pathology. Deformation-based morphometry was used to identify the patterns of brain atrophy associated with amyotrophic lateral sclerosis and to assess their relationship with clinical symptoms. Longitudinal T1-weighted MRI data and clinical measures were acquired at baseline, 4 months and 8 months, from 66 patients and 43 age-matched controls who participated in the Canadian Amyotrophic Lateral Sclerosis Neuroimaging Consortium study. Whole brain voxel-wise mixed-effects modelling analysis showed extensive atrophy patterns differentiating patients from the normal controls. Cerebral atrophy was present in the motor cortex and corticospinal tract, involving both grey matter and white matter, and to a lesser extent in non-motor regions. More specifically, the results showed significant bilateral atrophy in the motor cortex and corticospinal tract (including the internal capsule and brainstem) and ventricular enlargement, along with significant longitudinal atrophy in precentral gyrus, frontal and parietal white matter, accompanied by ventricular and sulcal enlargement. Atrophy in the precentral gyrus was significantly associated with greater disability as quantified with the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (P < 0.0001). The pattern of atrophy observed using deformation-based morphometry was consistent with the Brettschneider’s four-stage pathological model of the disease. Deformation-based morphometry provides a sensitive indicator of atrophy in Amyotrophic lateral sclerosis and has potential as a biomarker of disease burden, in both grey matter and white matter.

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 score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.136
GPT teacher head0.328
Teacher spread0.193 · 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

Citations50
Published2020
Admission routes2
Has abstractyes

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