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Record W1588504034 · doi:10.1002/mus.24675

Age‐related T<sub>2</sub> changes in hindlimb muscles of <i>mdx</i> mice

2015· article· en· W1588504034 on OpenAlexaff
Ravneet Vohra, Sunita Mathur, Nathan Bryant, Sean C. Forbes, Krista Vandenborne, Glenn A. Walter

Bibliographic record

VenueMuscle & Nerve · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversity of Toronto
FundersNational Center for Advancing Translational SciencesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Heart, Lung, and Blood InstituteU.S. Department of DefenseNational Institutes of HealthNational Science Foundation
Keywordsmdx mouseDuchenne muscular dystrophyHindlimbMuscular dystrophyMedicineYoung adultMagnetic resonance imagingInternal medicineEndocrinologyAnatomyDystrophinRadiology

Abstract

fetched live from OpenAlex

INTRODUCTION: Magnetic resonance imaging (MRI) was used to monitor changes in the transverse relaxation time constant (T2) in lower hindlimb muscles of mdx mice at different ages. METHODS: Young (5 weeks), adult (44 weeks), and old mdx (96 weeks), and age-matched control mice were studied. Young mdx mice were imaged longitudinally, whereas adult and old mdx mice were imaged at a single time-point. RESULTS: Mean muscle T2 and percent of pixels with elevated T2 were significantly different between mdx and control mice at all ages. In young mdx mice, mean muscle T2 peaked at 7-8 weeks and declined at 9-11 weeks. In old mdx mice, mean muscle T2 was decreased compared with young and adult mice, which could be attributed to fibrosis. CONCLUSIONS: MRI captured longitudinal changes in skeletal muscle integrity of mdx mice. This information will be valuable for pre-clinical testing of potential therapeutic interventions for muscular dystrophy.

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)0.000
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 score0.049
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.015
GPT teacher head0.231
Teacher spread0.216 · 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

Citations33
Published2015
Admission routes1
Has abstractyes

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