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RhoGDI2 induced malignant phenotypes of pancreatic cancer cells via regulating Snail expression
Yi Bin,Hu You,Zhu Dongming,Yao Jun,Zhou Jian,Zhang Yi,He Zhilong,Zhang Lifeng,Zhang Zixiang,Yang Jian,Tang Yuchen,Huang Yujie,Li Dechun,Liu Qiuhua 한국유전학회 2022 Genes & Genomics Vol.44 No.5
Background: Rho GDP dissociation inhibitor 2 (RhoGDI2) has been shown to contribute to the aggressive phenotypes of human cancers, such as tumor metastasis and chemoresistance. Objective: This study aimed to assess the effects of RhoGDI2 on tumor progression and chemoresistance in pancreatic cancer cells. Methods: The expression of RhoGDI2 in pancreatic cancer cells was detected by Western blot analysis. Gain-of-function and loss-of-function approaches were done to examine the malignant phenotypes of the RhoGDI2-expressing or RhoGDI2-depleting cells. The correlation between RhoGDI2 and Snail was also analyzed. Results: Differential expression of RhoGDI2 protein in pancreatic cancer cell lines was identified. Gain-of-function and loss-of-function experiments showed that RhoGDI2 induced the malignant phenotypes of pancreatic cancer cells, including proliferation, migration, invasion, and gemcitabine (GEM) chemoresistance. The upregulation of RhoGDI2 stimulated the expression of Snail, resulting in the altered expression of epithelial marker E-cadherin and mesenchymal marker Vimentin, which were characteristics of the tumorigenic activity of epithelial-mesenchymal transition. The expression of RhoGDI2 and Snail was upregulated in clinical tumor samples, and higher expression of RhoGDI2 or Snail was significantly associated with poor patient survival in pancreatic ductal adenocarcinoma (PDAC). Conclusion: The findings indicated that RhoGDI2 promoted GEM resistance and tumor progression in pancreatic cancer and that RhoGDI2 might be a potential therapeutic target in patients with PDAC.
Huang, Yi-Dong,Shan, Wei,Zeng, Li,Wu, Yang Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.8
Objective: The purpose of this study was to identify genes related to bladder cancer with samples from normal and disease cases by microarray chip. Methods: After downloading the gene expression profile GSE3167 from Gene Expression Omnibus database which includes 50 bladder samples, comprising 9 normal and 41 disease samples, differentially expressed genes were identified with packages in R language. The selected differentially expressed genes were further analyzed using bioinformatics methods. Firstly, molecular functions, biological processes and cell component analysis were researched by software Gestalt. Then, software String was used to search interaction relationships among differentially expressed genes, and hub genes of the network were selected. Finally, by using plugins of software Cytoscape, Mcode and Bingo, module analysis of hub-genes was performed. Results: A total of 221 genes were identified as differentially expressed by comparing normal and disease bladder samples, and a network as well as the hub gene C1QBP was obtained from the network. The C1QBP module had the closest relationship to production of molecular mediators involved in inflammatory responses. Conclusion: We obtained differentially expressed genes of bladder cancer by microarray, and both PRDX2 and YWHAZ in the module with hub gene C1QBP were most significantly related to production of molecular mediators involved in inflammatory responses. From knowledge of inflammatory responses and cancer, our results showed that, the hub gene and its module could induce inflammation in bladder cancer. These related genes are candidate bio-markers for bladder cancer diagnosis and might be helpful in designing novel therapies.
FA/Mel@ZnO nanoparticles as drug self-delivery systems for RPE protection against oxidative stress
Yi, Caixia,Yu, Zhihai,Sun, Xin,Zheng, Xi,Yang, Shuangya,Liu, Hengchuan,Song, Yi,Huang, Xiao Techno-Press 2022 Advances in nano research Vol.13 No.1
Drug self-delivery systems can easily realize combination drug therapy and avoid carrier-induced toxicity and immunogenicity because they do not need non-therapeutic carrier materials. So, designing appropriate drug self-delivery systems for specific diseases can settle most of the problems existing in traditional drug delivery systems. Retinal pigment epithelium is very important for the homeostasis of retina. However, it is vulnerable to oxidative damage and difficult to repair. Worse still, the antioxidants can hardly reach the retina by non-invasive administration routes due to the ocular barriers. Herein, the targeted group (folic acid) and antioxidant (melatonin) have been grafted on the surface of ZnO quantum dots to fabricate a new kind of drug self-delivery systems as a protectant via eyedrops. In this study, the negative nanoparticles with size ranging in 4~6 nm were successfully synthesized. They could easily and precisely deliver drugs to retinal pigment epithelium via eyedrops. And they realized acid degradation to controlled release of melatonin and zinc in retinal pigment epithelium cells. Consequently, the structure of retinal pigment epithelium cells were stabilized according to the expression of ZO-1 and β-catenin. Moreover, the antioxidant capacity of retinal pigment epithelium were enhanced both in health mice and photic injury mice. Therefore, such new drug self-delivery systems have great potential both in prevention and treatment of oxidative damage induced retinal diseases.
A Versatile Fruit and Vegetable Image Recognition Method based on Deep Convolutional Neural Networks
( Yi-hsuan Huang ),( Ta-te Lin ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1
Due to the increasing labor costs and shortage of labor in the agricultural industry, automation in agriculture has become ever more important. This paper proposes a versatile and automatic fruit and vegetable recognition method through the use of computer vision and deep neural networks. The proposed method allows for detection, recognition, and localization of selected fruits and vegetables via images or video streams. Therefore, the method can be used in various applications in agriculture such as robotic harvest, greenhouse management, or crop phenotyping. To detect fruits or vegetables in images, traditional image processing algorithms have some limitations due to occlusions and background variations. Different fruits or vegetables may require different algorithms. However, deep convolutional neural networks have brought about a breakthrough in dealing with this problem. The significance of deep neural networks in imaging processing is that features are no longer extracted by image processing algorithms. Instead, the network will learn by itself from the input data and extract the important features, called deep features. Therefore, we apply deep convolutional neural networks with You Only Look Once (YOLO), a real-time object detection algorithm, to build a versatile image recognition model for selected fruits and vegetables. Using YOLO, the models are trained with five kinds of fruits and vegetables: apple, tomato, cucumber, orange and strawberry. There are two kinds of models developed: ‘one vs. all’ and ‘one vs. one’ models. These models are compared to obtain the ensemble model. In addition, the effects of different phenotype between training data sets and testing data sets are also evaluated. Finally, the optimized model is applied in the recognition system and multiple kinds of fruits are recognized. We also tested the method with images and video streams acquired from greenhouses to evaluate the performance of the method.
A cohesive model for concrete mesostructure considering friction effect between cracks
Yi-qun Huang,Shao-wei Hu 사단법인 한국계산역학회 2019 Computers and Concrete, An International Journal Vol.24 No.1
Compressive ability is one of the most important mechanical properties of concrete material .The compressive failure process of concrete is pretty complex with internal tension, shear damage and friction between cracks. To simulate the complex fracture process of concrete at meso level, methodology for meso-structural analysis of concrete specimens is developed; the zero thickness cohesive elements are pre-inserted to simulate the crack initiation and propagation; the constitutive applied in cohesive element is established to describe the mechanism of crack separation, closure and friction behavior between the fracture surfaces. Aseries of simulations were carried out based on the model proposed in this paper. The results reproduced the main fracture and mechanical feature of concrete under compression condition. The effect of key material parameters, structure size, and aggregate content on the concrete fracture pattern and loading carrying capacities was investigated. It is found that the inner friction coefficient has a significant influence on the compression character of concrete, the compression strength raises linearly with the increase of the inner friction coefficient, and the fracture pattern is sensitive to the mesostructure of concrete.
Huang, Wei-Yi,Chen, Dong-Hui,Ning, Li,Wang, Li-Wei Asian Pacific Journal of Cancer Prevention 2012 Asian Pacific journal of cancer prevention Vol.13 No.5
The gene encoding the Nin one binding (NOB1) protein which plays an essential role in protein degradation has been investigated for possible tumor promoting functions. The present study was focused on NOB1 as a possible therapeutic target for breast cancer treatment. Lentivirus mediated NOB1 siRNA transfection was used to silence the NOB1 gene in two established breast cancer cell lines, MCF-7 and MDA-MB-231, successful transfection being confirmed by fluorescence imaging. NOB1 deletion caused significant decline in cell proliferation was observed in both cell lines as investigated by MTT assay. Furthermore the number and size of the colonies formed were also significantly reduced in the absence of NOB1. Moreover NOB1 gene knockdown arrested the cell cycle and inhibited cell cycle related protein expression. Collectively these results indicate that NOB1 plays an essential role in breast cancer cell proliferation and its gene expression could be a therapeutic target.