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| 1 | Derivation of Putative Porcine Embryonic Germ Cells and Analysis of Their Multi-Lineage Differentiation Potential显示文摘Embryonic germ(EG)cells are cultured pluripotent stem cells derived from the primordial germ cells(PGCs)that migrate from the dorsal mesentery of the hindgut to the developing genital ridge.In this study,the morphology of the porcine genital ridge was assessed in embryos harvested on days 22-30 of pregnancy.PGCs from embryos at these stages were cultured to obtain porcine EG cell lines,and EG-like cells were derived from PGCs from embryos harvested on days 24-28 of pregnancy.The EG-like cells expressed Oct4,Sox2,Nanog,SSEA-3,SSEA-4 and alkaline phosphatase(AP).These cells were able to form embryoid bodies(EBs)in suspension culture and differentiate into cells representative of the three germ layers as verified by a-fetoprotein(AFP),a-smooth muscle actin(a-SMA),and Nestin expression.Spontaneous differentiation from the porcine EG-like cells of delayed passage in vitro showed that they could differentiate into epithelial-like cells,mesenchymal-like cells and neuron-like cells.In vitro directed differentiation generated osteocytes,adipocytes and a variety of neural lineage cells,as demonstrated by alizarin red staining,oil red O staining,and immunofluorescence for neuronal classⅢb-tubulin(Tuj1),glial fibrillary protein(GFAP)and galactosylceramidase(GALC),respectively.These results indicate that porcine EG-like cells have the potential for multi-lineage differentiation and are useful for basic porcine stem cell research. | Yimei Cong Jing Ma Ruizhen Sun Jianyu Wang Binghua Xue Jiaqiang Wang Bingteng Xie Juan Wang Kui Hu Zhonghua Liu | 2013 | Journal of Genetics and Genomics2013，40，9： | 4 |
| 2 | AN IMPROVED SPARSITY ADAPTIVE MATCHING PURSUIT ALGORITHM FOR COMPRESSIVE SENSING BASED ON REGULARIZED BACKTRACKING显示文摘Sparsity Adaptive Matching Pursuit (SAMP) algorithm is a widely used reconstruction algorithm for compressive sensing in the case that the sparsity is unknown. In order to match the sparsity more accurately, we presented an improved SAMP algorithm based on Regularized Backtracking (SAMP-RB). By adapting a regularized backtracking step to SAMP algorithm in each iteration stage, the proposed algorithm can flexibly remove the inappropriate atoms. The experimental results show that SAMP-RB reconstruction algorithm greatly improves SAMP algorithm both in reconstruction quality and computational time. It has better reconstruction efficiency than most of the available matching pursuit algorithms. | Zhao Ruizhen Ren Xiaoxin Han Xuelian Hu Shaohai | 2012 | Journal of Electronics(China)2012，29，6： | 3 |
| 3 | Co-segmentation of 3D shapes via subspace elustering 显示文摘 | HU Ruizhen FAN Lubin LIU Ligang | 2012 | Computer Graphics Forum2012，31，5： | 1 |
| 4 | Image-guided color mapping for categorical data visualization显示文摘Appropriate color mapping for categorical data visualization can significantly facilitate the discovery of underlying data patterns and effectively bring out visual aesthetics.Some systems suggest pre-defined palettes for this task.However,a predefined color mapping is not always optimal,failing to consider users’needs for customization.Given an input cate-gorical data visualization and a reference image,we present an effective method to automatically generate a coloring that resembles the reference while allowing classes to be easily distinguished.We extract a color palette with high perceptual distance between the colors by sampling dominant and discriminable colors from the image’s color space.These colors are assigned to given classes by solving an integer quadratic program to optimize point distinctness of the given chart while preserving the color spatial relations in the source image.We show results on various coloring tasks,with a diverse set of new coloring appearances for the input data.We also compare our approach to state-of-the-art palettes in a controlled user study,which shows that our method achieves comparable performance in class discrimination,while being more similar to the source image.User feedback after using our system verifies its efficiency in automatically generating desirable colorings that meet the user’s expectations when choosing a reference. | Qian Zheng Min Lu Sicong Wu Ruizhen Hu Joel Lanir Hui Huang | 2022 | Computational Visual Media2022，8，4： | 1 |
| 5 | Mechanical Properties and Corrosion Behavior of Multi-Microalloying Mg Alloys Prepared by Adding AlCoCrFeNi Alloy显示文摘In this work,a series of multi-microalloying Mg alloys with a high degradation rate and high strength was prepared by adding AlCoCrFeNi HEA particles to the Mg melt followed by hot extrusion.The microstructure evolution and mechanical properties of the alloys were studied,meanwhile,the corrosion properties were evaluated by immersion weight loss and electrochemical tests.Results indicated that HEA particles in the Mg melt were decomposed and formed the Ni-rich phase,which was distributed uniformly in the Mg matrix.Compared with the pure Mg matrix,the Mg-3 HEA alloy exhibited excellent mechanical properties of the ultimate tensile strength~237 MPa and tensile yield strength~181 MPa,an increased rate of~49.1 and~96.7%,respectively,without sacrificing the elongation.And the ultimate compressive strength(UCS)and compressive yield strength increased by~31.5 and~43%to 392±3 and 103±2 MPa,respectively.Based on theoretical analysis,the high YS of the alloys was mainly attributed to fine-grain strengthening and second phase strengthening.Besides,based on the study of corrosion behavior,it was found that with the increase in HEA particle content,the degradation rate of the composites increased because of the promotion of micro-galvanic corrosion,and the Mg-3 HEA alloy showed a maximum degradation rate of~25.2 mg cmh. | Xiong Zhou Qichi Le Chenglu Hu Ruizhen Guo Tong Wang Chunming Liu Dandan Li Xiaoqiang Li | 2022 | Acta Metallurgica Sinica(English Letters)2022，35，8： | 0 |
| 6 | Microbiota-mediated shaping of mouse spleen structure and immune function characterized by scRNA-seq and Stereo-seq显示文摘Gut microbes exhibit complex interactions with their hosts and shape an organism's immune system throughout its lifespan.As the largest secondary lymphoid organ,the spleen has a wide range of immunological functions.To explore the role of microbiota in regulating and shaping the spleen,we employ scRNA-seq and Stereo-seq technologies based on germ-free(GF)mice to detect differences in tissue size,anatomical structure,cell types,functions,and spatial molecular characteristics.We identify 18 cell types,9 subtypes of T cells,and 7 subtypes of B cells.Gene differential expression analysis reveals that the absence of microorganisms results in alterations in erythropoiesis within the red pulp region and congenital immune deficiency in the white pulp region.Stereo-seq results demonstrate a clear hierarchy of immune cells in the spleen,including marginal zone(MZ)macrophages,MZ B cells,follicular B cells and T cells,distributed in a well-defined pattern from outside to inside.However,this hierarchical structure is disturbed in GF mice.Ccr7 and Cxcl13 chemokines are specifically expressed in the spatial locations of T cells and B cells,respectively.We speculate that the microbiota may mediate the structural composition or partitioning of spleen immune cells by modulating the expression levels of chemokines. | Yin Zhang Juan Shen Wei Cheng Bhaskar Roy Ruizhen Zhao Tailiang Chai Yifei Sheng Zhao Zhang Xueting Chen Weiming Liang Weining Hu Qijun Liao Shanshan Pan Wen Zhuang Yangrui Zhang Rouxi Chen Junpu Mei Hong Wei Xiaodong Fang | 2023 | Journal of Genetics and Genomics2023，50，9： | 0 |
| 7 | Point cloud completion via structured feature maps using a feedback network显示文摘In this paper,we tackle the challenging problem of point cloud completion from the perspective of feature learning.Our key observation is that to recover the underlying structures as well as surface details,given partial input,a fundamental component is a good feature representation that can capture both global structure and local geometric details.We accordingly first propose FSNet,a feature structuring module that can adaptively aggregate point-wise features into a 2D structured feature map by learning multiple latent patterns from local regions.We then integrate FSNet into a coarse-to-fine pipeline for point cloud completion.Specifically,a 2D convolutional neural network is adopted to decode feature maps from FSNet into a coarse and complete point cloud.Next,a point cloud upsampling network is used to generate a dense point cloud from the partial input and the coarse intermediate output.To efficiently exploit local structures and enhance point distribution uniformity,we propose IFNet,a point upsampling module with a self-correction mechanism that can progressively refine details of the generated dense point cloud.We have conducted qualitative and quantitative experiments on ShapeNet,MVP,and KITTI datasets,which demonstrate that our method outperforms stateof-the-art point cloud completion approaches. | Zejia Su Haibin Huang Chongyang Ma Hui Huang Ruizhen Hu | 2023 | Computational Visual Media2023，9，1： | 0 |
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