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Neuron-Specific Expression of Mutant Superoxide Dismutase 1 in Transgenic Mice Does Not Lead to Motor Impairment

2001· article· en· W2124976615 on OpenAlexafffund
Albéna Pramatarova, Janet Laganière, Julie Roussel, Katéri Brisebois, Guy A. Rouleau

Bibliographic record

VenueJournal of Neuroscience · 2001
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsMcGill UniversityMontreal General Hospital
FundersMedical Research Council CanadaMcGill UniversityMedical Research CouncilMuscular Dystrophy Association
KeywordsSOD1Amyotrophic lateral sclerosisTransgeneMutantMotor neuronGenetically modified mouseSuperoxide dismutaseBiologyNeurofilamentMutationPhenotypeMolecular biologyGeneCell biologyNeuroscienceSpinal cordGeneticsImmunologyPathologyDiseaseEndocrinologyMedicineOxidative stressImmunohistochemistry

Abstract

fetched live from OpenAlex

Mutations were identified in the Cu/Zn superoxide dismutase gene (SOD1) in approximately 15% of patients with familial amyotrophic lateral sclerosis. Transgenic animals expressing mutant SOD1 in all tissues develop an ALS-like phenotype. To determine whether neuron-specific expression of mutant SOD1 is sufficient to produce such a phenotype, we generated transgenic animals carrying the G37R mutation that is associated with the familial form of ALS (FALS), which is driven by the neurofilament light chain promoter. The transgenic animals express high levels of the human SOD1 protein in neuronal tissues, especially in the large motor neurons of the spinal cord, but they show no apparent motor deficit at up to 1.5 years of age. Our animal model suggests that neuron-specific expression of ALS-associated mutant human SOD1 may not be sufficient for the development of the disease in mice.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.047
GPT teacher head0.313
Teacher spread0.267 · 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 designBench or experimental
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

Citations476
Published2001
Admission routes2
Has abstractyes

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