RESUMEN
There are many reports that workouts relieve daily stress and are effective in improving mental and physical health. In recent years, there has been a demand for quick and easy methods to analyze and evaluate living organisms using biological information measured from wearable sensors. In this study, we attempted workout detection for one healthy female (40 years old) based on multiple types of biological information, such as the number of steps taken, activity level, and pulse, obtained from a wristband-type wearable sensor using machine learning. Data were recorded intermittently for approximately 64 days and 57 workouts were recorded. Workouts adopted for exercise were yoga and the workout duration was 1 h. We extracted 3416 min of biometric information for each of three categories: workout, awake activities (activities other than workouts), and sleep. Classification was performed using random forest (RF), SVM, and KNN. The detection accuracy of RF and SVM was high, and the recall, precision, and F-score values when using RF were 0.962, 0.963, and 0.963, respectively. The values for SVM were 0.961, 0.962, and 0.962, respectively. In addition, as a result of calculating the importance of the feature values used for detection, sleep state (39.8%), skin temperature (33.3%), and pulse rate (13.2%) accounted for approximately 86.3% of the total. By applying RF or SVM to the biological information obtained from the wearable wristband sensor, workouts could be detected every minute with high accuracy.
RESUMEN
Melanoma differentiation-associated gene 5 (MDA5), a member of the retinoic acid-inducible gene I (RIG-I)-like receptors (RLRs), has pivotal roles in innate immune responses against many positive-stranded RNA viruses, including picornavirus and coronavirus. Upon engagement with dsRNA derived from viral infection, MDA5 initiates coordinated signal transduction leading to type I IFN induction to restrict viral replication. In this study, we describe a targeted cleavage events of MDA5 by the 3C protease from Theilovirus. Upon ectopic expression of theilovirus 3C protease from Saffold virus or Theiler's murine encephalomyelitis virus but not encephalomyocarditis virus, fragments of cleaved MDA5 were observed in a dose-dependent manner. When enzymatically inactive Theilovirus 3C protease was expressed, MDA5 cleavage was completely abrogated. Mass spectrometric analysis identified two cleavage sites at the C terminus of MDA5, cleaving off one of the RNA-binding domains. The same cleavage pattern was observed during Theilovirus infection. The cleavage of MDA5 by Theilovirus protease impaired ATP hydrolysis, RNA binding, and filament assembly on RNA, resulting in dysfunction of MDA5 as an innate immune RNA sensor for IFN induction. Furthermore, the cleavage-resistant MDA5 mutant against the 3C protease showed an enhanced IFN response during Saffold virus infection, indicating that Theilovirus has a strategy to circumvent the antiviral immune response by cleaving MDA5 using 3C protease. In summary, these data suggest MDA5 cleavage by 3C protease as a novel immune evasive strategy of Theilovirus.