Gait characterization in golden retriever muscular dystrophy dogs using linear discriminant analysis

Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches

Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically developing (TD) peers are visible to the eye, but quantifications of those differences outside of the gait laboratory have been elusive. In this work, we measured vertical, mediolateral, and anteroposterior acceleration using a waist-worn iPhone accelerometer during ambulation across a typical range of velocities. Fifteen TD and fifteen DMD children from 3 to 16 years of age underwent eight walking/running activities, including five 25 m walk/run speed-calibration tests at a slow walk to running speeds (SC-L1 to SC-L5), a 6-min walk test (6MWT), a 100 m fast walk/jog/run (100MRW), and a free walk (FW). For clinical anchoring purposes, participants completed a Northstar Ambulatory Assessment (NSAA). We extracted temporospatial gait clinical features (CFs) and applied multiple machine learning (ML) approaches to differentiate between DMD and TD children using extracted temporospatial gait CFs and raw data. Extracted temporospatial gait CFs showed reduced step length and a greater mediolateral component of total power (TP) consistent with shorter strides and Trendelenberg-like gait commonly observed in DMD. ML approaches using temporospatial gait CFs and raw data varied in effectiveness at differentiating between DMD and TD controls at different speeds, with an accuracy of up to 100%. We demonstrate that by using ML with accelerometer data from a consumer-grade smartphone, we can capture DMD-associated gait characteristics in toddlers to teens.

Rapid discrimination of Brucellosis in sheep using serum Fourier transform infrared spectroscopy combined with PCA-LDA algorithm

Brucellosis in sheep is an infectious disease caused by Brucella melitensis in sheep. The current conventional serological methods for screening Brucella-infected sheep have the disadvantage of time consuming and low accuracy, so a simple, rapid and highly accurate screening method is needed. The aim of this study was to evaluate the feasibility of diagnosing Brucella-infected sheep by serum samples based on the Fourier transform infrared (FTIR) spectroscopy. In this study, FTIR spectroscopy of serum from Brucella-infected sheep (n=102) and healthy sheep (n=125) revealed abnormal protein and lipid metabolism in serum from Brucella-infected sheep compared to healthy sheep. Principal component analysis-Linear discriminant analysis (PCA-LDA) method was used to differentiate the FTIR spectra of serum from Brucella-infected sheep and healthy sheep in the protein band (3700-3090 cm^-1) and lipid band (3000-2800 cm^-1), and its overall diagnostic accuracy was 100% (sensitivity 100%, specificity 100%). In conclusion, our results suggest that serum FTIR spectroscopy combined with PCA-LDA algorithm has great potential for brucellosis in sheep screening.

Four-limb wireless IMU sensor system for automatic gait detection in canines

This study aims to develop a 4-limb canine gait analysis system using wireless inertial measurement units (IMUs). 3D printed sensor holders were designed to ensure quick and consistent sensor mounting. Signal analysis algorithms were developed to automatically determine the timing of swing start and end in a stride. To evaluate the accuracy of the new system, a synchronized study was conducted in which stride parameters in four dogs were measured simultaneously using the 4-limb IMU system and a pressure-sensor based walkway gait system. The results showed that stride parameters measured in both systems were highly correlated. Bland-Altman analyses revealed a nominal mean measurement bias between the two systems in both forelimbs and hindlimbs. Overall, the disagreement between the two systems was less than 10% of the mean value in over 92% of the data points acquired from forelimbs. The same performance was observed in hindlimbs except for one parameter due to small mean values. We demonstrated that this 4-limb system could successfully visualize the overall gait types and identify rapid gait changes in dogs. This method provides an effective, low-cost tool for gait studies in veterinary applications or in translational studies using dog models of neuromuscular diseases.

The Dog Model in the Spotlight: Legacy of a Trustful Cooperation

Dogs have long been used as a biomedical model system and in particular as a preclinical proof of concept for innovative therapies before translation to humans. A recent example of the utility of this animal model is the promising myotubularin gene delivery in boys affected by X-linked centronuclear myopathy after successful systemic, long-term efficient gene therapy in Labrador retrievers. Mostly, this is due to unique features that make dogs an optimal system. The continuous emergence of spontaneous inherited disorders enables the identification of reliable complementary molecular models for human neuromuscular disorders (NMDs). Dogs’ characteristics including size, lifespan and unprecedented medical care level allow a comprehensive longitudinal description of diseases. Moreover, the highly similar pathogenic mechanisms with human patients yield to translational robustness. Finally, interindividual phenotypic heterogeneity between dogs helps identifying modifiers and anticipates precision medicine issues.

This review article summarizes the present list of molecularly characterized dog models for NMDs and provides an exhaustive list of the clinical and paraclinical assays that have been developed. This toolbox offers scientists a sensitive and reliable system to thoroughly evaluate neuromuscular function, as well as efficiency and safety of innovative therapies targeting these NMDs. This review also contextualizes the model by highlighting its unique genetic value, shaped by the long-term coevolution of humans and domesticated dogs. Because the dog is one of the most protected research animal models, there is considerable opposition to include it in preclinical projects, posing a threat to the use of this model. We thus discuss ethical issues, emphasizing that unlike many other models, the dog also benefits from its contribution to comparative biomedical research with a drastic reduction in the prevalence of morbid alleles in the breeding stock and an improvement in medical care.

Long-term microdystrophin gene therapy is effective in a canine model of Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is an incurable X-linked muscle-wasting disease caused by mutations in the dystrophin gene. Gene therapy using highly functional microdystrophin genes and recombinant adeno-associated virus (rAAV) vectors is an attractive strategy to treat DMD. Here we show that locoregional and systemic delivery of a rAAV2/8 vector expressing a canine microdystrophin (cMD1) is effective in restoring dystrophin expression and stabilizing clinical symptoms in studies performed on a total of 12 treated golden retriever muscular dystrophy (GRMD) dogs. Locoregional delivery induces high levels of microdystrophin expression in limb musculature and significant amelioration of histological and functional parameters. Systemic intravenous administration without immunosuppression results in significant and sustained levels of microdystrophin in skeletal muscles and reduces dystrophic symptoms for over 2 years. No toxicity or adverse immune consequences of vector administration are observed. These studies indicate safety and efficacy of systemic rAAV-cMD1 delivery in a large animal model of DMD, and pave the way towards clinical trials of rAAV–microdystrophin gene therapy in DMD patients.

Duchenne muscular dystrophy is a progressive degenerative disease of muscles caused by mutations in the dystrophin gene. Here the authors use AAV vectors to deliver microdystrophin to dogs with muscular dystrophy, and show restoration of dystrophin expression and reduction of symptoms up to 26 months of age.