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Absence of Tumor Necrosis Factor-α Does Not Affect Motor Neuron Disease Caused by Superoxide Dismutase 1 Mutations

2006· article· en· W2008176593 on OpenAlexafffund
Genevíève Gowing, Florence Dequen, Geneviève Soucy, Jean‐Pierre Julien

Bibliographic record

VenueJournal of Neuroscience · 2006
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsCentre hospitalier de l'Université Laval
FundersRobert Packard Center for ALS Research, Johns Hopkins UniversityCanadian Institutes of Health ResearchJohns Hopkins University
KeywordsSOD1Amyotrophic lateral sclerosisTumor necrosis factor alphaMotor neuronProinflammatory cytokineSuperoxide dismutaseMicrogliaBiologyGenetically modified mouseNeurodegenerationContext (archaeology)TransgeneNeuroscienceImmunologyMedicinePathologyEndocrinologyGeneDiseaseOxidative stressGeneticsInflammationSpinal cord

Abstract

fetched live from OpenAlex

An increase in the expression of the proinflammatory cytokine tumor necrosis factor alpha (TNF-alpha) has been observed in patients with amyotrophic lateral sclerosis (ALS) and in the mice models of the disease. TNF-alpha is a potent activator of macrophages and microglia and, under certain conditions, can induce or exacerbate neuronal cell death. Here, we assessed the contribution of TNF-alpha in motor neuron disease in mice overexpressing mutant superoxide dismutase 1 (SOD1) genes linked to familial ALS. This was accomplished by the generation of mice expressing SOD1(G37R) or SOD1(G93A) mutants in the context of TNF-alpha gene knock out. Surprisingly, the absence of TNF-alpha did not affect the lifespan or the extent of motor neuron loss in SOD1 transgenic mice. These results provide compelling evidence indicating that TNF-alpha does not directly contribute to motor neuron degeneration caused by SOD1 mutations.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.301
Teacher spread0.274 · 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 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

Citations101
Published2006
Admission routes2
Has abstractyes

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