Gastric cancer (GC) is the fourth most common cancer globally. Recently, microRNAs (miRNAs) have been suggested to be closely associated with tumorigenesis. Aberrant expression of miR-509-3p has been reported in cancer studies. However, the expression and mechanism of its function in GC remain unclear. Here we showed that miR-509-3p was downregulated in GC specimens, which was associated with overall survival. Functional investigations demonstrated that the overexpression of miR-509-3p inhibited the migration and proliferation of the GC cells. Additionally, we identified X-linked inhibitor of apoptosis protein (XIAP) as a direct target of miR-509-3p. Knockdown of XIAP significantly attenuated the ability of proliferation, migration, and invasion of GC cells. The data therefore suggest that miR-509-3p plays an important role in the development and progression of GC, implicating possible applications in the clinic as a biomarker and a potential new target.

No abstract

Intramuscular myxoma (IM) is a benign intramuscular neoplasm composed of fibroblasts and abundant myxoid stroma. IMs most commonly affect larger skeletal muscles, while those affecting the oral and maxillofacial regions are rare, with a small number of documented cases in the available literature. The aim of the present study was to describe a highly rare case of an IM within the hyoglossus muscle of the tongue in a 74-year-old male. The patient presented with a painless mass in the submental space that had been growing slowly for more than five years. A computed tomography scan revealed a hypodense lesion located in the root of the tongue. The mass was easily excised with thin margins, including only a small amount of the adjacent muscle tissue. The pathological diagnosis of the mass was an IM. The patient made an excellent recovery following the surgery and the follow-up three years later revealed no local recurrence. IMs of the hyoglossus muscle are highly rare, however must be considered in the differential diagnosis of swellings in the root of the tongue region.

No abstract

The defect rate of initially produced block bamboo (Bambusoideae) parts is >20 percent. Sorting out these defective parts manually is a highly time-consuming and tedious process. An intelligent sorting system was developed based on machine vision using a Radial Basis Function (RBF) neural network learning algorithm in this study. First, a high-speed charge-coupled device camera was used to obtain a series of images of perfect and defective block bamboo parts. Next, the RBF neural-network learning algorithm was applied to obtain defect characteristics and to locate defective parts moving forward on a conveyor belt. An array of air jets was designed to force defective parts off the belt. Experimental results showed that the average defective part removal rate of the proposed system was 91.7 percent.