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Rotator cuff tear is a muscle-tendinous injury representative of various musculoskeletal disorders. In general, rotator cuff tear occurs in the tendon, but it causes unloading of the muscle resulting in muscle degeneration including fatty infiltration. These muscle degenerations lead to muscle weakness, pain, and loss of shoulder function and are well known as important factors for poor functional outcome after rotator cuff repair. Given that rotator cuff tear in various animal species results in similar pathological changes seen in humans, the animal model can be considered a good approach to understand the many aspects of the molecular changes in injured muscle. To comprehensively analyze changes in gene expression with time following a rotator cuff tear, we established a rotator cuff tear in mouse supraspinatus tendon of shoulder. At weeks 1 and 4 after the tear, the injured muscles were harvested for RNA isolation, and microarray analysis was performed. Expression patterns of genes belonging to 10 muscle physiology-related categories, including aging, apoptosis, atrophy, and fatty acid transport, were analyzed and further validated using real-time PCR. A total of 39,429 genes were analyzed, and significant changes in expression were observed for 12,178 genes at 1 week and 2,370 genes at 4 weeks after the tear. From the list of top 10 significantly up- and downregulated genes at the 2 time periods and the network evaluation of relevant genes according to the 10 categories, several important genes in each category were observed. In this study, we found that various genes are significantly altered after rotator cuff tear, and these genes may play key roles in controlling muscle degeneration after a rotator cuff tear.

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In the recent years, cyber attacks by malicious codes called malware has become a social problem. With the explosive appearance and increase of new malware, innumerable disasters caused by metaphoric malware using the existing malicious codes have been reported. To secure more effective detection of malicious codes, in other words, to make a more accurate judgment as to whether suspicious files are malicious or not, this study introduces the malware analysis system, which is based on a profiling technique using the Finite Automata. This new analysis system enables realtime automatic detection of malware with its optimized partial execution

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