RESUMEN
OBJECTIVE: To compare the accuracy and generalizability of an automated deep neural network and the Philip Sleepware G3™ Somnolyzer system (Somnolyzer) for sleep stage scoring using American Academy of Sleep Medicine (AASM) guidelines. METHODS: Sleep recordings from 104 participants were analyzed by a convolutional neural network (CNN), the Somnolyzer and skillful technicians. Evaluation metrics were derived for different combinations of sleep stages. A further comparison between the Somnolyzer and the CNN model using a single-channel signal as input was also performed. Sleep recordings from 263 participants with a lower prevalence of OSA served as a cross-validation dataset to validate the generalizability of the CNN model. RESULTS: The overall agreement between automated and manual scoring for sleep staging in 104 participants outperformed that of the Somnolyzer according to various metrics (accuracy: 81.81 % vs. 77.07 %; F1: 76.36 % vs. 73.80 %; Cohen's kappa: 0.7403 vs. 0.6848). The results showed that the left electrooculography (EOG) single-channel model had minor advantages over the Somnolyzer. In terms of consistency with manual sleep staging, the CNN model demonstrated superior performance in identifying more pronounced sleep transitions, particularly in the N2 stage and sleep latency metrics. Conversely, the Somnolyzer showed enhanced proficiency in the analysis of REM stages, notably in measuring REM latency. The accuracy in the cross-validation set of 263 participants was also above 80 %. CONCLUSIONS: The CNN-based automated deep neural network outperformed the Somnolyzer and is sufficiently accurate for sleep study analyses using the AASM classification criteria.
Asunto(s)
Redes Neurales de la Computación , Polisomnografía , Fases del Sueño , Humanos , Fases del Sueño/fisiología , Masculino , Femenino , Adulto , Persona de Mediana Edad , Polisomnografía/métodos , Anciano , Electrooculografía/métodos , Procesamiento de Señales Asistido por ComputadorRESUMEN
MSC-exosomes are homogeneous menbrane vesicles with diameter 40-100 nm, derived from mesenchymal stem cells at physiological or pathology conditions. MSC-exosomes contain a great quantity and a wide variety of bioactive substances, such as proteins and miRNA. MSC-exosomes transfer bioactive substances to recipient cells to affect their functions through membrane fusion or endocytosis, which like the storage pools of signal vehicles for cell-to-cell comunication in vivo. MSC-exosomes can mimic the beneficial effect of MSC treatment, such as the promotion of tissue repair or the immune regulation. The biological property and functions of MSC-exosomes are reviwed in this article.