LncRNA-IMAT1 Promotes Invasion of Meningiomas by Suppressing KLF4/hsa-miR22-3p/Snai1 Pathway

Tao Zhang,Yu Ge,Daijun Wang,Qin Liu,Shuchen Sun,Lingyang Hua,Jiaojiao Deng,Shihai Luan,Haixia Cheng,Qing Xie,Ye Gong,Tao Zhang 한국분자세포생물학회 2022 Molecules and cells Vol.45 No.6

Malignant meningiomas often show invasive growth that makes complete tumor resection challenging, and they are more prone to recur after radical resection. Invasive meningioma associated transcript 1 (IMAT1) is a long noncoding RNA located on Homo sapiens chromosome 17 that was identified by our team based on absolute expression differences in invasive and non-invasive meningiomas. Our studies indicated that IMAT1 was highly expressed in invasive meningiomas compared with non-invasive meningiomas. In vitro studies showed that IMAT1 promoted meningioma cell invasion through the inactivation of the Krüppel-like factor 4 (KLF4)/hsa-miR22-3p/Snai1 pathway by acting as a sponge for hsa-miR22-3p, and IMAT1 knockdown effectively restored the tumor suppressive properties of KLF4 by preserving its tumor suppressor pathway. In vivo experiments confirmed that IMAT1 silencing could significantly inhibit the growth of subcutaneous tumors and prolong the survival period of tumor-bearing mice. Our findings demonstrated that the high expression of IMAT1 is the inherent reason for the loss of the tumor suppressive properties of KLF4 during meningioma progression. Therefore, we believe that IMAT1 may be a potential biological marker and treatment target for meningiomas.

A Hybrid Feature Gene Selection Method based on Fuzzy Neighborhood Rough Set with Information Entropy

Tao Chen,Zenglin Hong,Fang-an Deng,Man Cui 보안공학연구지원센터(IJSIP) 2014 International Journal of Signal Processing, Image Vol.7 No.6

DNA microarray technique can detect tens of thousands of genes activity in cells and has been widely used in clinical diagnosis. However, microarray data has the characteristics of high dimension and small samples, moreover many irrelevant and redundant genes also decrease performance of classification algorithm. Feature gene selection is an effective method to solve this problem. This paper proposes a hybrid feature gene selection method. Firstly, a lot of irrelevant genes from original data were eliminated by using reliefF algorithm, and the candidate feature genes subset is obtained; Secondly, Fuzzy neighborhood rough set with information entropy which deals directly with continuous data is proposed to reduce redundant genes among genes subset above. Here, differential evolution algorithm is used to optimize radius before reduction by using fuzzy neighborhood rough set, because radius of neighborhood greatly affects reduction performance. The simulation results on six microarray datasets indicate that our method can obtain higher classification accuracy by using as few genes as possible, especially feature genes selected are important for understanding microarray data and identifying the pathogenic genes. The results demonstrated that this method is effective and efficient for feature genes selection.

Task Offloading Based on Edge Collaboration in MEC-Enabled IoV Networks

Deng, Tao Yu,Chen, Yueyun,Chen, Guang,Yang, Meijie,Du, Liping 한국통신학회 2023 Journal of communications and networks Vol.25 No.2

Benefiting from its abundant computing resourcesand low computing latency, mobile edge computing (MEC) isa promising approach for enhancing the computing capacity ofthe 5G Internet of vehicles (IoV). Because of the high mobility,handover is frequent and inevitable in IoV networks. In thispaper, we investigate an edge collaborative task offloading andsplitting strategy in MEC-enabled IoV networks, in which thetask is splitted on the edge and paralleling executed by eachpart of the task on several MEC servers when handover isoccured. Applications in IoV networks have flexible requirementson latency and energy consumption. To realize the tradeoffbetween latency and energy consumption, we formulate the taskoffloading and splitting as an optimization problem with the aimof minimizing the total cost of latency and energy consumptionby jointly optimizing the task splitting ratio and uplink transmitpower of vehicle terminal (VT). Because the proposed problemis non-smooth and non-convex, we divide the original probleminto two convex subproblems, and apply an alternate convexsearch (ACS) algorithm to obtain the optimized solution withlow computational complexity. Numerical simulation results showthat the proposed method can adjust the offloading strategyproperly according to task preference, and obtain a lower totalcost compared with the baseline algorithms.

Research on DCT shifting torque control and a benchmark test

Tao Deng,Fengbin Hu,Renzhi Lu 대한기계학회 2015 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.29 No.9

In this study, the working principles of Dual clutch transmission (DCT) are analyzed, the power switching rule for dual clutches duringupshift and downshift are formulated, and the model of DCT shift dynamics is established. Subsequently, upshift/downshift control strategiesand sliding friction power are simulated and analyzed. A benchmark shift control test is conducted on real DCT vehicles, and testresults show that the effect of clutch torque control strategy coincides with actual vehicle control during the upshift process. However,this effect varies during the downshift process. Two different downshift methods are proposed on the basis of the study findings. Moreover,the influence of downshift control method on engine control is analyzed, and the DCT torque control strategy employed duringdownshift is optimized.

Smart Image Analysis and Recognition Methodology for Earthwork Operation Based on the Convolutional Neural Network Model

Deng Tao,Soomin Lee,Sunjun Kim,Jongwon Seo 대한토목학회 2022 대한토목학회 학술대회 Vol.2022 No.10

Aldehyde Dehydrogenase 2 (ALDH2) Polymorphism and the Risk of Alcoholic Liver Cirrhosis among East Asians: A Meta-Analysis

Tao Deng,Lei He,Hesheng Luo 연세대학교의과대학 2016 Yonsei medical journal Vol.57 No.4

Purpose: The aldehyde dehydrogenase 2 (ALDH2) gene has been implicated in the development of alcoholic liver cirrhosis (ALC) in East Asians. However, the results are inconsistent. In this study, a meta-analysis was performed to assess the associations betweenthe ALDH2 polymorphism and the risk of ALC. Materials and Methods: Relevant studies were retrieved by searching PubMed, Web of Science, CNKI, Wanfang and Veipu databasesup to January 10, 2015. Pooled odds ratio (OR) and 95% confidence interval (CI) were calculated using either the fixed- or random effects model. Results: A total of twelve case-control studies included 1003 cases and 2011 controls were included. Overall, the ALDH2 polymorphismwas associated with a decreased risk of ALC (*1/*2 vs. *1/*1: OR=0.78, 95% CI: 0.61–0.99). However, in stratification analysis by country, we failed to detect any association among Chinese, Korean or Japanese populations. Conclusion: The pooled evidence suggests that ALDH2 polymorphism may be an important protective factor for ALC in East Asians.

Isolation and Cloning of Porcine SLC27A2 Gene and Detection of Its Polymorphism Associated with Growth and Carcass Traits

Wang, Tao,Liu, Chang,Xiong, Yuan-Zhu,Deng, Chang-Yan,Zuo, Bo,Xie, Hong-Tao,Xu, De-Quan Asian Australasian Association of Animal Productio 2007 Animal Bioscience Vol.20 No.8

The protein encoded by SLC27A2 gene is an isozyme of long-chain fatty-acid-coenzyme A ligase family, and it converts free long-chain fatty acids into fatty acyl-CoA esters, and thereby plays a key role in lipid biosynthesis and fatty acid degradation. In the present study, SLC27A2 located on human chromosome 15 was selected as candidate gene and we isolated and cloned partial fragments of mRNA sequence and genomic fragments of porcine SLC27A2 gene. The coding region of the gene as determined by alignments shared 90% and 82% identity with human and mouse cDNAs, respectively. Detection in LargeWhite and Meishan breeds showed that a single nucleotide polymorphism (SNP) ($A{\rightarrow}G$) existed in exon 7, which caused corresponding amino acid changed for encoding. In LargeWhite pigs it encoded for Val while in Meishan pigs it encoded for Ile, so we developed the PCR-RFLP genotype method for detection of this polymorphism. Association study in 135 $F_2$ reference family indicated that significant correlation existed between the polymorphism and growth and carcass traits.

K-Hop Community Search Based On Local Distance Dynamics

( Tao Meng ),( Lijun Cai ),( Tingqin He ),( Lei Chen ),( Ziyun Deng ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.7

Community search aims at finding a meaningful community that contains the query node and also maximizes (minimizes) a goodness metric. This problem has recently drawn intense research interest. However, most metric-based algorithms tend to include irrelevant subgraphs in the identified community. Apart from the user-defined metric algorithm, how can we search the natural community that the query node belongs to? In this paper, we propose a novel community search algorithm based on the concept of the k-hop and local distance dynamics model, which can naturally capture a community that contains the query node. The basic idea is to envision the nodes that k-hop away from the query node as an adaptive local dynamical system, where each node only interacts with its local topological structure. Relying on a proposed local distance dynamics model, the distances among nodes change over time, where the nodes sharing the same community with the query node tend to gradually move together, while other nodes stay far away from each other. Such interplay eventually leads to a steady distribution of distances, and a meaningful community is naturally found. Extensive experiments show that our community search algorithm has good performance relative to several state-of-the-art algorithms.

A Novel Selective Ensemble Classification of Microarray Data Based on Teaching-Learning-Based Optimization

Tao Chen,Zenglin Hong,Fang-an Deng,Xiao Yang,Jun Wei,Man Cui 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.6

Aiming at the characteristics of high dimension and small samples in microarray data, this paper proposes a selective ensemble method to classify microarray data. Firstly, kruskal-wallis test is used to filter irrelevant genes with classification task and to obtain a set of genes, and then a reduced training set is produced from original training set according to gene subset obtained. Secondly, multiple gene subsets are generated by using neighborhood rough set model with different radius and used to construct training subsets on above reduced training set. Thirdly, every constructed training subset is used to train a classifier by using SVM algorithm, and then multiple classifiers are produced as base classifiers. Finally, a set of base classifiers are selected by using teaching-learning-based optimization and build an ensemble classifier by weighted voting. Five benchmarks tumor microarray datasets are applied to evaluate performance of our proposed method. Experimental results indicate our proposed method is very effective and efficient for classifying microarray data, and it improves not only classification accuracy, but also decrease memory costs and computation times.

COMPUTING B-SPLINE SURFACES ON TRANSPUTER NETWORKS

Deng, Chao,Shen, Mong Tao 대한전자공학회 1992 HICEC:Harbin International Conference on Electroni Vol.1 No.1

This paper presents a parallel implementation of computing uniform bicubic B-spline surfaces on Transputer networks. The parallel algorithm is described, timed and evaluated against its functional equivalent single processor code. The work is essential for building Transputer-based CAD and graphics systems.