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1159 - Characterization Of Golden Retriever Muscular Dystrophy Biomechanics With Motion Capture During A 6-month Longitudinal Study

2019· preprint· en· W4391532426 sur OpenAlexaboutno aff
Lise Ochej

Notice bibliographique

Revuenon disponible
Typepreprint
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueMuscle Physiology and Disorders
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLabrador RetrieverBiomechanicsMuscular dystrophyPhysical medicine and rehabilitationMedicineAnatomySurgeryInternal medicine

Résumé

récupéré en direct d'OpenAlex

INTRODUCTION: Muscular Dystrophies (MD) are incurable diseases that progressively weaken voluntary muscles [1]. The most severe type of MD is Duchenne Muscular Dystrophy (DMD) which affects 1 in 4000-6000 boys [2]. Patients are wheelchair bound in their teens and typically die from respiratory failure or cardiomyopathy with an average life expectancy of 26 years [3]. Golden Retriever Muscular Dystrophy (GRMD) is considered a good animal model for DMD due to its genetic homology and is used to study DMD and evaluate treatments [2]. The purpose of this study is to develop a non-invasive motion capture method based on gait analysis parameters to characterize GRMD biomechanics and ultimately assess treatments proposed to improve muscular control.METHODS: Twelve dogs were divided into a control group of 5 healthy dogs, a treatment group of 5 affected dogs treated with an adeno-associated virus gene therapy and a sham control of 2 untreated affected dogs. They were studied at 2, 4 and 6 months of age. Each dog was equipped with 18 reflective markers placed on anatomical landmarks on their hind limbs. Dogs were walked at a self selected speed within a volume covered by 8 near infrared motion capture cameras recording at 100Hz. Data was collected for several consecutive steps in the middle of the capture volume. Steps from the beginning and the end of the walk were excluded to avoid acceleration impact and to make sure collected data was representative of the dogu2019s gait. After gathering data according to walking speed, joint range of motion (ROM), stride length and duration, paw elevation, and movement correlation were calculated for each dog and compared at different time points. Studentu2019s T-tests were performed to assess the statistical significance of results between the three groups.. The analysis was blinded to minimize bias. The study was conducted according to institutional animal care guidelines and was approved by the Animal Use Protocol AUP 081065.RESULTS: GRMD dogs (treated and untreated) showed lower and decreasing ROM for the hock angle compared to healthy dogs. They had a similar ROM but with more extended limbs for the stifle angle and the pelvic tilt. Paw elevation and stride length ratios for all GRMD dogs decreased with age while it was stable for their counterparts. Step duration was on average 44u00b121% longer for healthy dogs and 19u00b114% longer for affected and treated dogs compared to affected and non-treated dogs. Other parameters did not show significant differences between the groups.DISCUSSION: This motion capture method has been able to identify significant differences between affected and non-affected subjects based on their ROM, paw elevation and stride length. The slight improvement trend seen on step duration for treated dogs could be attributed to gene therapy efficacy but further studies with more subjects have to be conducted to confirm this assessment.SIGNIFICANCE/CLINICAL RELEVANCE: Golden Retrievers are considered to be the most relevant model for Duchenne Muscular Dystrophy, and studying the first 6 months of life of GRMD dogs is critical as it is considered to correspond to the first 10 years of life of DMD children. The current biomechanical characterization of the disease evolution in the dog model suggests the possibility of a similar protocol adapted for humans. Our laboratory is currently going through IRB approval to start a DMD biomechanics research study at the Orthopedic Biomechanics Research Laboratory (Houston) in collaboration with Houston Methodist Research Institute.REFERENCES: [1] Dubowitz, V. (1977). Muscular Dystrophy (pp. 5-8). Karger Publishers.[2] Kornegay, J.N. (2017). Skeletal muscle, 7(1), 9.[3] Eagle, M. et al., (2002). Neuromuscular disorders, 12(10), 926-929.ACKNOWLEDGEMENTS: Texas A&M College of Veterinary Medicine provided the dogs and funding for this research project.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,009
Tête enseignante GPT0,225
Écart entre enseignants0,216 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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