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| 1 | RECQL4 regulates DNA damage response and redox homeostasis in esophageal cancer显示文摘Objective:RECQL4(a member of the RECQ helicase family)upregulation has been reported to be associated with tumor progression in several malignancies.However,whether RECQL4 sustains esophageal squamous cell carcinoma(ESCC)has not been elucidated.In this study,we determined the functional role for RECQL4 in ESCC progression.Methods:RECQL4 expression in clinical samples of ESCC was examined by immunohistochemistry.Cell proliferation,cellular senescence,the epithelial-mesenchymal transition(EMT),DNA damage,and reactive oxygen species in ESCC cell lines with RECQL4 depletion or overexpression were analyzed.The levels of proteins involved in the DNA damage response(DDR),cell cycle progression,survival,and the EMT were determined by Western blot analyses.Results:RECQL4 was highly expressed in tumor tissues when compared to adjacent non-tumor tissues in ESCC(P<0.001)and positively correlated with poor differentiation(P=0.011),enhanced invasion(P=0.033),and metastasis(P=0.048).RECQL4 was positively associated with proliferation and migration in ESCC cells.Depletion of RECQL4 also inhibited growth of tumor xenografts in vivo.RECQL4 depletion induced G0/G1 phase arrest and cellular senescence.Importantly,the levels of DNA damage and reactive oxygen species were increased when RECQL4 was depleted.DDR,as measured by the activation of ATM,ATR,CHK1,and CHK2,was impaired.RECQL4 was also shown to promote the activation of AKT,ERK,and NF-k B in ESCC cells.Conclusions:The results indicated that RECQL4 was highly expressed in ESCC and played critical roles in the regulation of DDR,redox homeostasis,and cell survival. | Guosheng Lyu Peng Su Xiaohe Hao Shiming Chen Shuai Ren Zixiao Zhao Yaoqin Gong Qiao Liu Changshun Shao | 2021 | Cancer Biology & Medicine2021，18，1： | 2 |
| 2 | Thermogravimetric analysis of co-combustion of biomass and biochar显示文摘 | Qiguo Yi Fangjie Qi Gong Cheng Yongguang Zhang Bo Xiao Zhiquan Hu Shiming Liu Haiyan Cai Shan Xu | 2013 | Journal of Thermal Analysis and Calorimetry2013，，3： | 1 |
| 3 | Current Situations and Development Ideas of Buckwheat Tea Industry in Liangshan Prefecture显示文摘This paper firstly introduces current situations of buckwheat tea industry in Liangshan Prefecture,current situations of intellectual property right of buckwheat tea in whole China,and total flavonoid content in buckwheat tea. On the basis of these current situations,it analyzes drawbacks of buckwheat tea sold in the market. Finally,it presents development ideas of buckwheat tea industry in Liangshan Prefecture. | Fayong GONG Shiming XIAO Jing LI | 2013 | Asian Agricultural Research2013，5，6： | 1 |
| 4 | Synthesis of nocel soluble polyimides containing triphenylamine groups for liquid crystal vertical alignment layers 显示文摘 | Gong Shiming Liu Ming Xia Sanlin | 2014 | J Polym Res2014，21，： | 1 |
| 5 | End-to-end encrypted network traffic classification method based on deep learning显示文摘Network traffic classification,which matches network traffic for a specific class of different granularities,plays a vital role in the domain of network administration and cyber security.With the rapid development of network communication techniques,more and more network applications adopt encryption techniques during communication,which brings significant challenges to traditional network traffic classification methods.On the one hand,traditional methods mainly depend on matching features on the application layer of the ISO/OSI reference model,which leads to the failure of classifying encrypted traffic.On the other hand,machine learning-based methods require human-made features from network traffic data by human experts,which renders it difficult for them to deal with complex network protocols.In this paper,the convolution attention network(CAT)is proposed to overcom those difficulties.As an end-to-end model,CAT takes raw data as input and returns classification results automatically,with engineering by human experts.In CAT,firstly,the importance of different bytes with an attention mechanism of network traffic is achieved.Then,convolution neural network(CNN)is used to learn features automatically and feed the output into a softmax function to get classification results.It enables CAT to learn enough information from network traffic data and ensure the classified accuracy.Extensive experiments on the public encrypted network traffic dataset ISCX2016 demonstrate the effectiveness of the proposed model. | Tian Shiming Gong Feixiang Mo Shuang Li Meng Wu Wenrui Xiao Ding | 2020 | The Journal of China Universities of Posts and Telecommunications2020，27，3： | 1 |
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