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Record W2020848875 · doi:10.1002/jnr.20449

Mice with the deleted neurofilament of low-molecular-weight (Nefl) gene: 1. Effects on regional brain metabolism

2005· article· en· W2020848875 on OpenAlexafffund
Martine Dubois, Robert Lalonde, Jean‐Pierre Julien, C. Strazielle

Bibliographic record

VenueJournal of Neuroscience Research · 2005
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsMcGill UniversityMontreal General HospitalHôpital Saint-Luc
FundersNational Institutes of Natural SciencesNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthNational Institute for Health and Care Research
KeywordsBrainstemAmyotrophic lateral sclerosisCerebellumNeurofilamentBiologyCytochrome c oxidaseMotor neuronNeuroscienceDeep cerebellar nucleiInternal medicineCell biologySpinal cordCerebellar cortexMitochondrionMedicine

Abstract

fetched live from OpenAlex

Neuronal intermediate filaments consist of the NFL subunit linked with NFM and NFH, and their alterations have been proposed as a pathogenesic cause in motor neuron diseases. Depletion of the Nefl gene in mice mimicks the reduced NFL mRNA levels seen in amyotrophic lateral sclerosis and causes perikaryal accumulation of neurofilament proteins and axonal hypotrophy in motoneurons. NFL -/- mice were evaluated for regional brain metabolism by means of quantitative histochemical estimation of cytochrome oxidase (COx) activity. The NFL null mice displayed enzymatic activity alterations in numerous hindbrain regions, mainly the cerebellum, connected regions of the brainstem (red nucleus, vestibular nuclei, and reticular formation), and cranial nerve nuclei. All of the affected regions presented elevated COx activity, except for the Purkinje cells of the cerebellum and the magnocellular red nucleus, where enzymatic activity was lower. NFL-disrupted mice displayed functional alterations in brainstem sensorimotor regions affected in amyotrophic lateral sclerosis.

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)0.003
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.051
GPT teacher head0.365
Teacher spread0.314 · 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

Citations14
Published2005
Admission routes2
Has abstractyes

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