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Xu, Jian-Yu,Lu, Shan,Xu, Xiang-Ying,Hu, Song-Liu,Li, Bin,Qi, Rui-Xue,Chen, Lin,Chang, Joe Y. Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.8
Nucleolin (C23) is an important anti-apoptotic protein that is ubiquitously expressed in exponentially growing eukaryotic cells. In order to understand the impact of C23 in radiation therapy, we attempted to investigate the relationship of C23 expression with the radiosensitivity of human non-small cell lung cancer (NSCLC) cells. We investigated the role of C23 in activating the catalytic subunit of DNA-dependent protein kinase (DNA-PKcs), which is a critical protein for DNA double-strand breaks (DSBs) repair. As a result, we found that the expression of C23 was negatively correlated with the radiosensitivity of NSCLC cell lines. In vitro clonogenic survival assays revealed that C23 knockdown increased the radiosensitivity of a human lung adenocarcinoma cell line, potentially through the promotion of radiation-induced apoptosis and adjusting the cell cycle to a more radiosensitive stage. Immunofluorescence data revealed an increasing quantity of ${gamma}$-H2AX foci and decreasing radiation-induced DNA damage repair following knockdown of C23. To further clarify the mechanism of C23 in DNA DSBs repair, we detected the expression of DNA-PKcs and C23 proteins in NSCLC cell lines. C23 might participate in DNA DSBs repair for the reason that the expression of DNA-PKcs decreased at 30, 60, 120 and 360 minutes after irradiation in C23 knockdown cells. Especially, the activity of DNA-PKcs phosphorylation sites at the S2056 and T2609 was significantly suppressed. Therefore we concluded that C23 knockdown can inhibit DNA-PKcs phosphorylation activity at the S2056 and T2609 sites, thus reducing the radiation damage repair and increasing the radiosensitivity of NSCLC cells. Taken together, the inhibition of C23 expression was shown to increase the radiosensitivity of NSCLC cells, as implied by the relevance to the notably decreased DNA-PKcs phosphorylation activity at the S2056 and T2609 clusters. Further research on targeted C23 treatment may promote effectiveness of radiotherapy and provide new targets for NSCLC patients.
Xu, Lu-Wei,Qian, Ming,Jia, Rui-Peng,Xu, Zheng,Wu, Jian-Ping,Li, Wen-Cheng,Huang, Wen-Bin,Chen, Xing-Guo Asian Pacific Journal of Cancer Prevention 2012 Asian Pacific journal of cancer prevention Vol.13 No.4
The aim of this study was to investigate the expression and significance of microsomal prostaglandin synthase-1 (mPGES-1) and Beclin-1 in the development of prostate cancer (PCa). Immunohistochemistry was performed on paraffin-embedded sections with rabbit polyclonal against mPGES-1 and Beclin-1 in 40 PCa, 40 benign prostatic hyperplasia (BPH) and 10 normal prostate specimens for this purpose. Quantitative real-time polymerase chain reaction (qRT-PCR) was applied for mRNA expression of mPGES-1 and Beclin-1, while MTT assays were used to ascertain the best working concentration of the mPGES-1 inhibitor (CAY10526). The effect of CAY10526 treatment on expression of Beclin-1 in DU-145 cells was studied using Western blot analysis. Localization of Beclin-1 and mPGES-1 was in endochylema. Significant differences in expression was noted among PCa, BPH and normal issues (P<0.05). Beclin-1 expression inversely correlated with mPGES-1 expression in PCa tissue (P<0.05). CAY10526 could significantly block mPGES-1 expression and the proliferation of DU-145 cells (P<0.05), while increasing Beclin-1 levels (P<0.05). Overexpression of mPGES-1 could decrease the autophagic PCa cell death. Inhibiting the expression of mPGES-1 may lead to DU-145 cell death and up-regulation of Beclin-1. The results suggest that inhibition of mPGES-1 may have therapeutic potential for PCa in the future.
Trade, FDI, and International Technology Diffusion
Xu, Bin,Wang, Jianmao 세종대학교 국제경제연구소 2000 Journal of Economic Integration Vol.15 No.4
This paper examines international trade and foreign direct investment as channels for technology diffusion among industrialized countries. We find strong empirical support for capital goods trade as a channel for international technology diffusion and some evidence that multinational enterprises (outward FDI) transmit foreign technology back to the home country. We find no evidence that inward FDI is a significant channel for international technology diffusion among industrialized countries. Our results also show that technology diffuses in disembodied forms, with countries that are farther from the world technology frontier benefiting more.
Xu, Xiang,Li, Lv-mu,Li, Bin,Guo, Wen-jie,Ding, Xiao-ling,Xu, Fa-zhi Asian Australasian Association of Animal Productio 2017 Animal Bioscience Vol.30 No.10
Objective: This study investigated the effect of fermented biogas residue (FBR) of wheat on the performance, serum biochemical parameters, and meat quality in pigs. Methods: We selected 128 pigs (the mean initial body weight was $40.24{\pm}3.08kg$) and randomly allocated them to 4 groups (1 control group and 3 treatment groups) with 4 replicates per group and 8 pigs per pen in a randomized complete block design based on initial body weight and sex. The control group received a corn-soybean meal-based diet, the treatment group fed diets containing 5%, 10%, and 15% FBR, respectively (abbreviated as FBR5, FBR10, and FBR15, respectively). Every group received equivalent-energy and nitrogen diets. The test lasted 60 days and was divided into early and late stages. Blood and carcass samples were obtained on 60 d. Meat quality was collected from two pigs per pen. Results: During the late stage, the average daily feed intake and average daily gain of the treatment groups was greater than that of the control group (p<0.05). During the entire experiment, the average daily gain of the treatment groups was higher than that of the control group (p<0.05). Fermented biomass residue did not significantly affect serum biochemical parameters or meat quality, but did affect amino acid profiles in pork. The contents of Asp, Arg, Tyr, Phe, Leu, Thr, Ser, Lys, Pro, Ala, essential amino acids, non-essential amino acids, and total amino acids in pork of FBR5 and FBR10 were greater than those of the control group (p<0.05). Conclusion: These combined results suggest that feeding FBR could increase the average daily gain and average daily feed intake in pigs and the content of several flavor-promoting amino acids.
Language-Independent Word Acquisition Method Using a State-Transition Model
Xu, Bin,Yamagishi, Naohide,Suzuki, Makoto,Goto, Masayuki Korean Institute of Industrial Engineers 2016 Industrial Engineeering & Management Systems Vol.15 No.3
The use of new words, numerous spoken languages, and abbreviations on the Internet is extensive. As such, automatically acquiring words for the purpose of analyzing Internet content is very difficult. In a previous study, we proposed a method for Japanese word segmentation using character N-grams. The previously proposed method is based on a simple state-transition model that is established under the assumption that the input document is described based on four states (denoted as A, B, C, and D) specified beforehand: state A represents words (nouns, verbs, etc.); state B represents statement separators (punctuation marks, conjunctions, etc.); state C represents postpositions (namely, words that follow nouns); and state D represents prepositions (namely, words that precede nouns). According to this state-transition model, based on the states applied to each pseudo-word, we search the document from beginning to end for an accessible pattern. In other words, the process of this transition detects some words during the search. In the present paper, we perform experiments based on the proposed word acquisition algorithm using Japanese and Chinese newspaper articles. These articles were obtained from Japan's Kyoto University and the Chinese People's Daily. The proposed method does not depend on the language structure. If text documents are expressed in Unicode the proposed method can, using the same algorithm, obtain words in Japanese and Chinese, which do not contain spaces between words. Hence, we demonstrate that the proposed method is language independent.
Bin Xu,Jingwen Xue,Jun Huang,Haojun Jin,Peng Shen,Qingjiang Sun 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2019 NANO Vol.15 No.01
The doped quantum dots (QDs) that feature dual emission in one nanocrystal and long fluorescence lifetime have gained great interest in biosensing and bioimaging applications. In this work, we report the synthesis and functionalization of copper ion-doped indium phosphate (Cu:InP) QDs that exhibit simultaneous green InP emission and red Cu2+ emission. The oil-soluble QDs were synthesized by adsorbing Cu2+ onto InP core, followed by growing zinc selenide (ZnSe) shell via the successive ion layer adsorption reaction. During the synthesis, fluorescence ratiometry (and resultant multiple fluorescence colors) can be generated by changing either the dopant amount or the shell-growth time, but they act in a different manner: increasing the Cu2+ amount results in quenched InP emission and oppositely improved Cu2+ emission; the increase of shell-growth time leads to continuously improved Cu2+ emission relative to constant InP emission. Further, functionalization of the oil-soluble Cu:InP QDs with dihydrolipoic acid-polyethylene glycol (DHLA-PEG) via ligand exchange produces the water-soluble and biocompatible dual-emission QDs. The PEGylated Cu:InP QDs present desirable charge neutrality and excellent thermal stability and photostability, thereby holding high potential in a diversity of biomedical applications.
Data-driven prognostics method for turbofan engine degradation using hybrid deep neural network
Bin Xue,Zhong-bin Xu,Xing Huang,Peng-cheng Nie 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.12
Powerful sequence modeling capability for massive multi-sensor data enables deep-learning-based methods to obtain accurate remaining useful life (RUL) estimations. Hybrid neural networks, with learned representations based on various networks, have enhanced the prognostics accuracies than single networks. However, assembly strategies that are limited to either parallel or serial, and insufficient utilization of single networks restrict the development of hybrid networks for more complex problems. This paper proposes a datadriven method using hybrid multi-scale convolutional neural network (MSCNN) and bidirectional long short-term memory (BLSTM) network (namely HMCB network) for RUL estimation. The framework of the network includes two parallel paths. One is composed of MSCNN and BLSTM in serial and the other is a BLSTM path. The HMCB network integrates the merits of multi-scale spatial feature extraction of MSCNN and sequence learning capacity of BLSTM. Validated by C-MAPSS dataset, the HMCB network demonstrates noticeably higher prognostic accuracy than other state-of-the-art methods.