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ABSTRACT: Background
Duchenne muscular dystrophy (DMD) is an X-linked lethal muscle disease. Dystrophic dogs are excellent models to test novel therapies for DMD. However, the use of the dog model has been hindered by the lack of an effective method to evaluate whole-body mobility. We recently showed that night activity is a good indicator of dog mobility. However, our published method relies on frame-by-frame manual processing of a 12-hour video for each dog. This labor-intensive and time-consuming approach makes it unrealistic to use this assay as a routine outcome measurement.Objective
To solve this problem, we developed an automatic video-capturing/imaging processing system. The new system reduces the data analysis time over 1,000 fold and also provides a more detailed activity profile of the dog.Methods
Using the new system, we analyzed more than 120 twelve-hour recordings from 12 normal and 22 affected dogs.Results
We observed similar activity profiles during repeated recording of the same dog. Throughout the night, normal dogs were in motion 10.4 ± 0.9% of the time while affected dogs were in motion 4.6 ± 0.2% of the time (p < 0.0001). Further, normal dogs made significantly more movements (p < 0.0001) while affected dogs rested significantly longer (p < 0.0001) during the period of recording (from 6 pm to 6 am next day). Importantly, statistical significance persisted irrespective of the coat color, gender and mutation type.Conclusions
Our results suggest that night activity reduction is a robust, quantitative physiological biomarker for dystrophic dogs. The new system may be applicable to study mobility in other species.
SUBMITTER: Hakim CH
PROVIDER: S-EPMC5089072 | biostudies-literature |
REPOSITORIES: biostudies-literature