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Record W4283391921 · doi:10.1017/cjn.2022.143

P.042 A novel SOD1 mutation associated with rapidly evolving lower motor neuron syndrome and MR ventral nerve root enhancement

2022· article· en· W4283391921 on OpenAlexaffvenue
T Perera, C Bencsik, G Pfeffer, T Mobach

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2022
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsCalgary Laboratory Services
Fundersnot available
KeywordsAmyotrophic lateral sclerosisSOD1Nerve rootMutationMedicinePhenotypePoint mutationPathologyGeneBiologyAnatomyGeneticsDisease

Abstract

fetched live from OpenAlex

Background: Mutations in the Cu/Zn superoxide dismutase 1 (SOD 1) gene are estimated to cause 20% of familial ALS and 1-2% of sporadic cases. Accurate gene variant classification of novel mutations in amyotrophic lateral sclerosis (ALS) has deepened our understanding of clinical phenotypes, provided pathologic insights, and is crucial to incorporating emerging therapies. Methods: We describe a case of a 75-year-old female who presented with a rapidly progressive lower motor neuron syndrome leading to flaccid quadriparesis and complete loss of independence over a five month period. Results: Genetic testing demonstrated a heterozygous variant of uncertain significance in the SOD1 gene with a g > c point mutation at position 382 that has been described in one other patient in available literature. MR of the lumbar spine demonstrated abnormal smooth nerve root enhancement. Conclusions: This novel mutation in the SOD1 gene may be associated with a rapidly progressive phenotype of sporadic ALS. Ventral nerve root enhancement should not exclude a diagnosis of ALS especially in the absence of nodularity or nerve enlargement.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
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 head0.032
GPT teacher head0.267
Teacher spread0.235 · 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 designCase report
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

Citations0
Published2022
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques→Same topicAmyotrophic Lateral Sclerosis Research→French-language works237,207→