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Record W2076319069 · doi:10.1002/mus.21160

Progressive motor unit loss in the G93A mouse model of amyotrophic lateral sclerosis is unaffected by gender

2009· article· en· W2076319069 on OpenAlexaff
Janka Hegedus, Charles T. Putman, Tessa Gordon

Bibliographic record

VenueMuscle & Nerve · 2009
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMotor unitAmyotrophic lateral sclerosisIsometric exerciseMedicineInternal medicineEndocrinologyAnatomyNeurosciencePsychologyDisease

Abstract

fetched live from OpenAlex

We examined whether there are gender differences in the progressive loss of functional motor units in SOD1(G93A) transgenic mice. Isometric muscle and motor unit twitch contractions were recorded in fast- and slow-twitch muscles in response to stimulation of the sciatic nerve. Using a modified motor unit number estimation technique (ITS-MUNE), we found that motor unit numbers declined rapidly from 40 to 90 days of age during the asymptomatic phase of ALS in fast- but not slow-twitch hindlimb muscles of both male and female mice. There was a corresponding decline in twitch and tetanic contractile forces of the fast-twitch muscles. Gender did not affect the progressive loss of motor units and associated decline in force production. We conclude that gender does not alter progressive, muscle-specific motor unit loss in ALS, even though gender does influence disease onset.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.064
GPT teacher head0.303
Teacher spread0.238 · 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

Citations43
Published2009
Admission routes1
Has abstractyes

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