Immunomodulatory Properties of Lactobacillus plantarum NC8 Expressing an Anti-CD11c Single-Chain Fv Fragment

( Jing Liu ),( Guilian Yang ),( Xing Gao ),( Zan Zhang ),( Yang Liu ),( Xin Yang ),( Chunwei Shi ),( Qiong Liu ),( Yanlong Jiang ),( Chunfeng Wang ) 한국미생물 · 생명공학회 2019 Journal of microbiology and biotechnology Vol.29 No.1

The lactic acid bacteria species Lactobacillus plantarum (L. plantarum) has been used extensively for vaccine delivery. Considering to the critical role of dendritic cells in stimulating host immune response, in this study, we constructed a novel CD11c-targeting L. plantarum strain with surface-displayed variable fragments of anti-CD11c, single-chain antibody (scFv-CD11c). The newly designed L. plantarum strain, named 409-aCD11c, could adhere and invade more efficiently to bone marrow-derived DCs (BMDCs) in vitro due to the specific interaction between scFv-CD11c and CD11c located on the surface of BMDCs. After incubation with BMDCs, the 409-aCD11c strain harboring a eukaryotic vector pValac-GFP could lead to more efficient expression of GFP compared with wild-type strains shown by flow cytometry analysis, indicating the enhanced translocation of pValac-GFP from L. plantarum to BMDCs. Similar results were also observed in an in vivo study, which showed that oral administration resulted in efficient expression of GFP in both Peyer’s patches (PP) and mesenteric lymph nodes (MLNs) within 7 days after the last administration. In addition, the CD11c-targeting strain significantly promoted the differentiation and maturation of DCs, the differentiation of IL-4+ and IL-17A+ T helper (Th) cells in MLNs, as well as production of B220+ IgA+ B cells in the PP. In conclusion, this study developed a novel DC-targeting L. plantarum strain which could increase the ability to deliver eukaryotic expression plasmid to host cells, indicating a promising approach for vaccine study.

Long non-coding RNA H19X promotes tumorigenesis and metastasis of colorectal cancer through regulating the miR-503-5p/KANK1 axis

Yuan Zihan,Zhao Haizhou,Zhi Qiaoming,Wang Sentai,Liu Chao,Han Ye,Xu Zhihua,Liu Fei,Liu Xingyi,Zan Xinquan,Wang Qiang,Wan Daiwei 한국유전학회 2022 Genes & Genomics Vol.44 No.12

Background: It has been well established that the long non-coding RNAs (lncRNAs) plays a critical role in tumor progression. However, the function of these transcripts and mechanisms responsible for their deregulation in colorectal cancer (CRC) remain to be investigated. Objective: To explore the potential effect and regulation mechanism of lncRNA H19X in colorectal cancer. Methods: We predicted and validated long non-coding RNA H19X from microarray data of colorectal cancer tissues. In addition, the biological behaviors of H19X and miR-503-5p on CRC were examined in vitro and in vivo, including MTT, colony formation assay, Hoechst33342 and transwell assay. The mRNA and protein levels of KN Motif and Ankyrin Repeat Domains 1 (KANK1) were analyzed by Quantitative real-time PCR (qRT-PCR), western blotting (WB) assay. Moreover, bioinformatics tools and dual-luciferase reporter assay were applied to demonstrate the relationship between KANK1 and miR-503-5p. Results: H19X was remarkably up-regulated in CRC tissues. Its expression related to tumor size (p = 0.041), lymph node metastasis (p = 0.037), distal metastasis (p = 0.028), advanced TNM stage (p = 0.034) and poor survival in CRC. H19X acted as an oncogenic lncRNA that induced CRC cell proliferation, invasion and metastasis. Through a number of functional studies, we found that H19X silencing inhibited the malignance phenotype of cancer cells through loss of miR-503-5p. Further studies demonstrated that miR-503-5p was involved in the progression of CRC by directly regulating the downstream target KANK1. Conclusion: Collectively, the findings of the present study indicate H19X/miR-503-5p/KANK1 axis has critical role in the progression of colorectal cancer, providing an effective prognostic indicator and promising target in treatment of colorectal cancer.

Human Action Recognition Using Pyramid Histograms of Oriented Gradients and Collaborative Multi-task Learning

( Zan Gao ),( Hua Zhang ),( An-an Liu ),( Yan-bing Xue ),( Guang-ping Xu ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.2

In this paper, human action recognition using pyramid histograms of oriented gradients and collaborative multi-task learning is proposed. First, we accumulate global activities and construct motion history image (MHI) for both RGB and depth channels respectively to encode the dynamics of one action in different modalities, and then different action descriptors are extracted from depth and RGB MHI to represent global textual and structural characteristics of these actions. Specially, average value in hierarchical block, GIST and pyramid histograms of oriented gradients descriptors are employed to represent human motion. To demonstrate the superiority of the proposed method, we evaluate them by KNN, SVM with linear and RBF kernels, SRC and CRC models on DHA dataset, the well-known dataset for human action recognition. Large scale experimental results show our descriptors are robust, stable and efficient, and outperform the state-of-the-art methods. In addition, we investigate the performance of our descriptors further by combining these descriptors on DHA dataset, and observe that the performances of combined descriptors are much better than just using only sole descriptor. With multimodal features, we also propose a collaborative multi-task learning method for model learning and inference based on transfer learning theory. The main contributions lie in four aspects: 1) the proposed encoding the scheme can filter the stationary part of human body and reduce noise interference; 2) different kind of features and models are assessed, and the neighbor gradients information and pyramid layers are very helpful for representing these actions; 3) The proposed model can fuse the features from different modalities regardless of the sensor types, the ranges of the value, and the dimensions of different features; 4) The latent common knowledge among different modalities can be discovered by transfer learning to boost the performance.

Active Queue Management Algorithm for TCP Networks with Integral Backstepping and Minimax

Zan-Hua Li,Yang Liu,Yuan-Wei Jing 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.4

A novel active queue management (AQM) approach is considered for a class of TCP network systems inthis paper. A sufficient condition is given and the corresponding control is obtained based on integral back-steppingtechnique (IB) and minimax method. The presented results not only are used to deal with the disturbances producedby UDP flows, but also can shorten the convergent time of the signals. Simulation examples are carried out to verifythe effectiveness and superiority of the proposed algorithm.

Human Action Recognition Via Multi-modality Information

Zan Gao,Jian-ming Song,Hua Zhang,An-An Liu,Yan-bing Xue,Guang-ping Xu 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.2

In this paper, we propose pyramid appearance and global structure action descriptors on both RGB and depth motion history images and a model-free method for human action recognition. In proposed algorithm, we firstly construct motion history image for both RGB and depth channels, at the same time, depth information is employed to filter RGB information, after that, different action descriptors are extracted from depth and RGB MHIs to represent these actions, and then multimodality information collaborative representation and recognition model, in which multi-modality information are put into object function naturally, and information fusion and action recognition also be done together, is proposed to classify human actions. To demonstrate the superiority of the proposed method, we evaluate it on MSR Action3D and DHA datasets, the well-known dataset for human action recognition. Large scale experiment shows our descriptors are robust, stable and efficient, when comparing with the-state-of-the-art algorithms, the performances of our descriptors are better than that of them, further, the performance of combined descriptors is much better than just using sole descriptor. What is more, our proposed model outperforms the state-of-the-art methods on both MSR Action3D and DHA datasets.

Molecular Cloning, Expression and Characterization of Bovine UQCC and Its Association with Body Measurement Traits

Liu, Yongfeng,Zan, Linsen,Zhao, Shuanping,Huang, Honggang,Li, Yong,Tang, Zhonglin,Yang, Shulin,Li, Kui Korean Society for Molecular and Cellular Biology 2010 Molecules and cells Vol.30 No.5

Ubiquinol-cytochrome c reductase complex chaperone (UQCC) involved in the development and maintenance of bone and cartilage is an important candidate gene for body measurement traits selection through marker-assisted selection (MAS). The expression of UQCC is upregulated in many human and animal models of height as well as other stature indexes. We have cloned the cDNA sequence coding UQCC gene in bovine. Genomic structural analysis indicated that bovine UQCC shares a high similarity with human UQCC. Furthermore, Real-Time PCR analysis showed that the expression of bovine UQCC is remarkably different in diverse tissues, including high level expression in the spleen, heart and windpipe, and relatively low expression in other tissues. We also analyzed allele frequencies in different cattle breeds and an association study on the selected SNPs. SNP DraI A2691T in intron 1 and SNP Bsh1236I A3150G in intron 8 are significantly associated with Body Length (BL), Rump Length (RL), Chest Depth (CD) and Pin Bone Width (PBW). For the A2691T SNP marker, there are significant effects on the RL (p = 0.0001), CD (p = 0.0059) and PBW (p < 0.0001) in 679 individuals; with A3150G SNP marker, there are significant effects on the BL (p = 0.0047) and CD (p = 0.0454). Regarding association analysis of combination of the two SNPs, there are significant effects on the BL (p = 0.0215), CD (p = 0.0282) and PBW (p = 0.0329) in the total population. The results suggest that the UQCC gene is a candidate gene of body measurement traits in bovine reproduction and breeding, and provide data for establishing an animal model using cattle to study big animal body type.

An Antitumor Component from Fomitiporia ellipsoidea

( Zan Lifeng ),( Haiying Bao ),( Tolgor Bau ),( Hanbin Liu ),( Baokai Cui ) 한국미생물 · 생명공학회 2012 Journal of microbiology and biotechnology Vol.22 No.11

A natural furan derivative was isolated from the methanolic extract of the fruit bodies of Fomitiporia ellipsoidea. Its chemical structure was elucidated as methyl 3,5-dioxo- 1,3,5,7-tetrahydrobenzo[1,2-c:4,5-c`]difuran-4-carboxylate by means of extensive NMR and MS data analysis, and named as fomitiporiaester A (1). Compound 1 showed significant antitumor activity to hepatoma H22 in vivo, and the inhibition rates were 42.94%, 49.17%, and 58.15% at concentrations of 5, 10, and 20 mg/kg, respectively. Compound 1 showed weak cytotoxic activities against the human hepatoblastoma (HepG-2) and human oophoroma (Skov 3) cell lines with IC50 values of more than 100 ?M.

Molecular Cloning, Expression and Characterization of Bovine UQCC and Its Association with Body Measurement Traits

Yongfeng Liu,Linsen Zan,Shuanping Zhao,Honggang Huang,Yong Li,Zhonglin Tang,Shulin Yang,Kui Li 한국분자세포생물학회 2010 Molecules and cells Vol.30 No.5

Ubiquinol-cytochrome c reductase complex chaperone (UQCC) involved in the development and maintenance of bone and cartilage is an important candidate gene for body measurement traits selection through marker-assisted selection (MAS). The expression of UQCC is upregulated in many human and animal models of height as well as other stature indexes. We have cloned the cDNA sequence coding UQCC gene in bovine. Genomic structural analysis indicated that bovine UQCC shares a high similarity with human UQCC. Furthermore, Real-Time PCR analysis showed that the expression of bovine UQCC is remarkably different in diverse tissues, including high level expression in the spleen, heart and windpipe, and relatively low expression in other tissues. We also analyzed allele frequencies in different cattle breeds and an association study on the selected SNPs. SNP DraI A2691T in intron 1 and SNP Bsh1236I A3150G in intron 8 are significantly associated with Body Length (BL), Rump Length (RL), Chest Depth (CD) and Pin Bone Width (PBW). For the A2691T SNP marker, there are significant effects on the RL (p = 0.0001), CD (p = 0.0059) and PBW (p < 0.0001) in 679 individuals; with A3150G SNP marker, there are significant effects on the BL (p = 0.0047) and CD (p = 0.0454). Regarding association analysis of combination of the two SNPs, there are significant effects on the BL (p = 0.0215), CD (p = 0.0282) and PBW (p = 0.0329) in the total population. The results suggest that the UQCC gene is a candidate gene of body measurement traits in bovine reproduction and breeding, and provide data for establishing an animal model using cattle to study big animal body type.

Research on Partial Discharge Pattern Recognition in GIS Based on EFPI Sensor

Wang Zan,Liu Zhongquan,Qiao Lili,Qian Dingdong,Chen Zhongxian,Gao Chaofei,Wang Wei 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.1

An EFPI fber optic ultrasonic sensor can be used for the detection and pattern recognition of partial discharge ultrasonic signals in Gas Insulated Switchgear. Compared with traditional piezoelectric sensors, it has many advantages, such as high sensitivity and strong anti-interference ability. Based on this, four typical PD models of the tip, metal particles, suspension and creeping surface were set up in the GIS cavity flled with 0.4 MPa SF6 gas, and the EFPI sensor was innovatively used to detect the discharge ultrasonic signal and extract the single ultrasonic pulse signal. The waveform features form a feature parameter database, and the probabilistic neural network algorithm and the support vector machine algorithm are used for pattern recognition and comparative analysis, respectively. The ultrasonic signal detected by the EFPI sensor has prominent features. On the basis of extracting the feature parameters, the two pattern recognition algorithms can achieve an average recognition rate of more than 85%, and the recognition efect of the support vector machine is better than that of the probabilistic neural network

A Framework for Human Motion Segmentation Based on Multiple Information of Motion Data

( Xiaofei Zan ),( Weibin Liu ),( Weiwei Xing ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.9

With the development of films, games and animation industry, analysis and reuse of human motion capture data become more and more important. Human motion segmentation, which divides a long motion sequence into different types of fragments, is a key part of mocap-based techniques. However, most of the segmentation methods only take into account low-level physical information (motion characteristics) or high-level data information (statistical characteristics) of motion data. They cannot use the data information fully. In this paper, we propose an unsupervised framework using both low-level physical information and high-level data information of human motion data to solve the human segmentation problem. First, we introduce the algorithm of CFSFDP and optimize it to carry out initial segmentation and obtain a good result quickly. Second, we use the ACA method to perform optimized segmentation for improving the result of segmentation. The experiments demonstrate that our framework has an excellent performance.