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Record W2399400908 · doi:10.1016/j.nicl.2016.05.014

Quantifying visual pathway axonal and myelin loss in multiple sclerosis and neuromyelitis optica

2016· article· en· W2399400908 on OpenAlexaff
Praveena Manogaran, Irene M. Vavasour, Alex P. Lange, Yinshan Zhao, Katrina McMullen, Alexander Rauscher, Robert Carruthers, David K.B. Li, Anthony Traboulsee, Shannon Kolind

Bibliographic record

VenueNeuroImage Clinical · 2016
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of British Columbia HospitalUniversity of British Columbia
Fundersnot available
KeywordsOptic neuritisMultiple sclerosisNerve fiber layerNeuromyelitis opticaOptic nerveOphthalmologyMedicineMyelinRetinalGanglion cell layerInner plexiform layerWhite matterRetinal ganglion cellInner nuclear layerPathologyCentral nervous systemMagnetic resonance imagingInternal medicineRadiologyImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: The optic nerve is frequently injured in multiple sclerosis and neuromyelitis optica, resulting in visual dysfunction, which may be reflected by measures distant from the site of injury. OBJECTIVE: To determine how retinal nerve fiber layer as a measure of axonal health, and macular volume as a measure of neuronal health are related to changes in myelin water fraction in the optic radiations of multiple sclerosis and neuromyelitis optica participants with and without optic neuritis and compared to healthy controls. METHODS: 12 healthy controls, 42 multiple sclerosis (16 with optic neuritis), and 10 neuromyelitis optica participants (8 with optic neuritis) were included in this study. Optical coherence tomography assessment involved measurements of the segmented macular layers (total macular, ganglion cell layer, inner plexiform layer, and inner nuclear layer volume) and paripapillary retinal nerve fiber layer thickness. The MRI protocol included a 32-echo T2-relaxation GRASE sequence. Average myelin water fraction values were calculated within the optic radiations as a measure of myelin density. RESULTS: Multiple sclerosis and neuromyelitis optica eyes with optic neuritis history had lower retinal nerve fiber layer thickness, total macular, ganglion cell and inner plexiform layer volumes compared to eyes without optic neuritis history and controls. Inner nuclear layer volume increased in multiple sclerosis with optic neuritis history (mean = 0.99 mm(3), SD = 0.06) compared to those without (mean = 0.97 mm(3), SD = 0.06; p = 0.003). Mean myelin water fraction in the optic radiations was significantly lower in demyelinating diseases (neuromyelitis optica: mean = 0.098, SD = 0.01, multiple sclerosis with optic neuritis history: mean = 0.096, SD = 0.01, multiple sclerosis without optic neuritis history: mean = 0.098, SD = 0.02; F3,55 = 3.35, p = 0.03) compared to controls. Positive correlations between MRI and optical coherence tomography measures were also apparent (retinal nerve fiber layer thickness and ganglion cell layer thickness: r = 0.25, p = 0.05, total macular volume and inner plexiform layer volume: r = 0.27, p = 0.04). CONCLUSIONS: The relationship between reductions in OCT measures of neuro-axonal health in the anterior visual pathway and MRI-based measures of myelin health in the posterior visual pathway suggests that these measures may be linked through bidirectional axonal degeneration.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.273
GPT teacher head0.411
Teacher spread0.138 · 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 teacher head, not a consensus.

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

Citations51
Published2016
Admission routes1
Has abstractyes

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