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Record W2165747837 · doi:10.1002/ana.21799

Substantial early, but nonprogressive neuronal loss in multiple sclerosis (ms) spinal cord

2009· article· en· W2165747837 on OpenAlexaff
Lucas Schirmer, Monika Albert, Armin Buss, Walter Schulz‐Schaeffer, Jack P. Antel, Wolfgang Brück, Christine Stadelmann

Bibliographic record

VenueAnnals of Neurology · 2009
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsAmyotrophic lateral sclerosisSpinal cordMultiple sclerosisMedicineLesionLumbar Spinal CordPathologyLumbarCentral nervous systemNeuroscienceCentral nervous system diseaseDiseaseAnatomyBiologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Research in multiple sclerosis (MS) has recently been focusing on the extent of neuroaxonal damage and its contribution to disease outcome. In the present study, we examined spinal cord tissue from 30 clinically well-characterized MS patients. MS, amyotrophic lateral sclerosis (ALS), and control spinal cord tissue were subjected to morphometric analysis and immunohistochemistry for markers of cell damage and regeneration. Data were related to disease duration and age at death. Here, we present evidence for substantial, nonprogressive neuronal loss on the cervical and lumbar levels early in the disease course of MS. Chromatolytic neurons and immunoreactivity for c-Jun and GAP43 were observed in the ventral gray matter in and adjacent to actively demyelinating lesions, pointing toward neuronal damage and regeneration as an early response to lesion formation.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.274
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.188
GPT teacher head0.381
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 teacher head, 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

Citations54
Published2009
Admission routes1
Has abstractyes

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