Background:Osteosarcoma is a major bone malignancy in children and young adults, and it is highly heterogeneous. The clinical outcome of osteosarcoma is individual-dependent due to different genetic and pathological profiles. Although chemotherapy in combination with surgery has significantly improved the survival of localized disease, the prognostic improvement for metastatic patients is less marked. ECT2 (epithelial cell transforming sequence 2) is a transforming protein that can interact with Rho-like proteins of the Ras family and has been proven as an ontogenetic protein in cancer cell lines. We studied the clinical significance of ECT2 in osteosarcoma and explored its underlying oncogenic mechanisms.
Material/Methods:The protein expression pattern of ECT2 in osteosarcoma was investigated by immunohistochemical staining, and its association with clinicopathological characteristics was initially explored. The significance of ECT2 in predicting patient prognosis was verified by univariate and multivariate analyzes. Cellular experiments were conducted to explore underlying mechanisms of ECT2 in regulating osteosarcoma progression.
Results:High ECT2 expression was correlated with tumor metastasis and poor overall survival of osteosarcoma patients. ECT2 promotes cell invasion by modulating EMT process.
Conclusions:ECT2 is an independent prognostic factor for osteosarcoma and it can upregulate the metastatic capacity of osteosarcoma cells.
Core panels inspired by origami have the advantages of force allocation and energy dissipation. Used as a sandwich core, the three-dimensional panels could be created using various origami patterns. The panel is composed of the element whose structure is inspired by origami. The orthopyramid-like origami element has a tip of joined-together side triangles. Through shape deformation, it could exhibit potential mechanical performances. Owing to its deformation when collision occurs, the structure could be employed for load damping conditions. This study focuses on nine different orthopyramid-like core panels through changing the similarity parameter value and the number of edges. The experiment and numerical simulation of compression and impact tests are carried out to perform the parametric study on the influences of the similarity parameter and the number of edges. The results show that with the increase of these two parameters, the panel tends to be softer, greatly influencing the load damping ability. Moreover, the structure parameters are optimized by the Genetic Algorithm integrated with the finite element analysis model.
In order to analyse the sports psychology of athletes and to identify the psychology of athletes in their movements, a human action recognition (HAR) algorithm has been designed in this study. First, a HAR model is established based on the convolutional neural network (CNN) to classify the current action state by analysing the action information of a task in the collected videos. Secondly, the psychology of basketball players displaying fake actions during the offensive and defensive process is investigated by combining with related sports psychological theories. Then, the psychology of athletes is also analysed through the collected videos, so as to predict the next response action of the athletes. Experimental results show that the combination of grayscale and red-green-blue (RGB) images can reduce the image loss and effectively improve the recognition accuracy of the model. The optimised convolutional three-dimensional network (C3D) HAR model designed in this study has a recognition accuracy of 80% with an image loss of 5.6. Besides, the time complexity is reduced by 33%. Therefore, the proposed optimised C3D can recognise effectively human actions, and the results of this study can provide a reference for the investigation of the image recognition of human action in sports.
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