Evidence map›Paper›PMID 40462750›Full record

ArticleDisease models & mechanisms2025

Long-term, age-associated activity quantification in the DE50-MD dog model of Duchenne muscular dystrophy.

Kamila Karimjee, Rachel C M River, Emil Olsen, Yu-Mei Chang, Dominic J Wells, Monica A Daley, Richard J Piercy

Abstract read
In one paragraph

Article in Disease models & mechanisms, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Kamila KarimjeeComparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, Royal Veterinary College, London NW1 0TU, UK.ORCID 0009-0005-6697-8321
Rachel C M RiverComparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, Royal Veterinary College, London NW1 0TU, UK.
Emil OlsenComparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, Royal Veterinary College, London NW1 0TU, UK.ORCID 0000-0001-5809-3324
Yu-Mei ChangDepartment of Comparative Biomedical Sciences, Royal Veterinary College, London NW1 0TU, UK.
Dominic J WellsComparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, Royal Veterinary College, London NW1 0TU, UK.
Monica A DaleyCenter for Integrative Movement Sciences, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA.ORCID 0000-0001-8584-2052
Richard J PiercyComparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, Royal Veterinary College, London NW1 0TU, UK.ORCID 0000-0002-4344-6438

Funding

Royal Veterinary CollegeWellcome TrustWellcome Trust 101550/Z/13/Z
6 · The paper itself

Abstract

Animal models with a clinically relevant phenotype remain important for robust evaluation of novel therapeutics for the fatal X-linked genetic disorder Duchenne muscular dystrophy (DMD). Demonstration of functional improvement is crucial for both patients and regulatory authorities. Here, we investigate non-invasive methods to quantify activity changes in DE50-MD dogs. Using collar-based Axivity-AX3 tri-axial accelerometers, we measured activity in affected DE50-MD male dogs (3-8 per age point) and littermate wild-type (WT) male controls (3-13 per age point) at monthly intervals from 3 to 18 months of age. Acceleration vector magnitudes were used to derive a series of activity measures over 24 h. Mixed model analyses were used to examine differences between affected and WT groups at different ages. Activity indicators for DE50-MD dogs were significantly higher for percent time spent at rest (P<0.001) and significantly lower for all other activity indicators (all P<0.05), when compared to age-matched WT dogs. Relatively few animals would be required to detect treatment effects with adequate power using these unbiassed, selected and composite activity measures. Our approach reveals opportunities for cross-model standardisation of activity monitoring.

Indexed as

AgingMotor ActivityMuscular Dystrophy, DuchenneAnimalsDisease Models, AnimalDogsMaleTime FactorsAccelerometerActivityAnimal modelCanineDE50-MDDMDDogDuchenne muscular dystrophySensorWearable

Identifiers

PMID40462750
PMCPMC12309892

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.