Expression profiling and integrative analysis of the CESA/CSL superfamily in rice

<p>Abstract</p> <p>Background</p> <p>The cellulose synthase and cellulose synthase-like gene superfamily (<it>CESA</it>/<it>CSL</it>) is proposed to encode enzymes for cellulose and non-cellulosic matrix polysaccharide synthesis in plants. Although the rice (<it>Oryza sativa </it>L.) genome has been sequenced for a few years, the global expression profiling patterns and functions of the <it>OsCESA</it>/<it>CSL </it>superfamily remain largely unknown.</p> <p>Results</p> <p>A total of 45 identified members of <it>OsCESA</it>/<it>CSL </it>were classified into two clusters based on phylogeny and motif constitution. Duplication events contributed largely to the expansion of this superfamily, with Cluster I and II mainly attributed to tandem and segmental duplication, respectively. With microarray data of 33 tissue samples covering the entire life cycle of rice, fairly high <it>OsCESA </it>gene expression and rather variable <it>OsCSL </it>expression were observed. While some members from each <it>CSL </it>family (<it>A1</it>, <it>C9</it>, <it>D2</it>, <it>E1</it>, <it>F6 </it>and <it>H1</it>) were expressed in all tissues examined, many of <it>OsCSL </it>genes were expressed in specific tissues (stamen and radicles). The expression pattern of <it>OsCESA</it>/<it>CSL </it>and <it>OsBC1L </it>which extensively co-expressed with <it>OsCESA</it>/<it>CSL </it>can be divided into three major groups with ten subgroups, each showing a distinct co-expression in tissues representing typically distinct cell wall constitutions. In particular, <it>OsCESA1, -3 & -8 </it>and <it>OsCESA4, -7 & -9 </it>were strongly co-expressed in tissues typical of primary and secondary cell walls, suggesting that they form as a cellulose synthase complex; these results are similar to the findings in <it>Arabidopsis</it>. <it>OsCESA5</it>/<it>OsCESA6 </it>is likely partially redundant with <it>OsCESA3 </it>for OsCESA complex organization in the specific tissues (plumule and radicle). Moreover, the phylogenetic comparison in rice, <it>Arabidopsis </it>and other species can provide clues for the prediction of orthologous gene expression patterns.</p> <p>Conclusions</p> <p>The study characterized the <it>CESA</it>/<it>CSL </it>of rice using an integrated approach comprised of phylogeny, transcriptional profiling and co-expression analyses. These investigations revealed very useful clues on the major roles of <it>CESA</it>/<it>CSL</it>, their potentially functional complement and their associations for appropriate cell wall synthesis in higher plants.</p

Green tea polyphenol epigallocatechin-3-gallate increases atherosclerotic plaque stability in apolipoprotein E-deficient mice fed a high-fat diet

Background: Epigallocatechin-3-gallate (EGCG), which is the principal component of green tea, has been shown to prevent atherosclerosis. However, the effect of EGCG on atherosclerotic plaque stability remains unknown. Aim: This study aimed to assess whether EGCG can enhance atherosclerotic plaque stability and to investigate the underlying mechanisms. Methods: Apolipoprotein E-deficient mice fed a high-fat diet were injected intraperitoneally with EGCG (10 mg/kg) for 16 weeks. Cross sections of the brachiocephalic arteries were stained with haematoxylin and eosin for morphometric analyses or Masson’s trichrome for collagen content analyses. Immunohistochemistry was performed to evaluate the percentage of macrophages and smooth muscle cells (SMCs). Protein expression and matrix metalloproteinase (MMP) activity were assayed by Western blot and gelatin zymography, respectively. Serum inflammatory cytokine levels were quantified by enzyme-linked immunosorbent assays. Results: After 16 weeks of feeding the high-fat diet, there were clear atherosclerotic lesions in the proximal brachiocephalic artery segments according to HE staining. EGCG treatment significantly increased the thickness of the fibrous cap. In the atherosclerotic plaques of the EGCG group, the relative macrophage content was decreased, whereas the relative SMC and collagen contents were increased. The expression levels of MMP-2, MMP-9, and extracellular matrix metalloproteinase inducer (EMMPRIN) were significantly decreased by EGCG treatment. In addition, EGCG treatment decreased the circulat­ing tumour necrosis factor-α, interleukin-6, monocyte chemoattractant protein-1, and interferon-γ levels in apolipoprotein E-deficient mice. Conclusions: EGCG promotes atherosclerotic lesion stability in apolipoprotein E-deficient mice. Potentially, these effects are mediated through the inhibition of inflammatory cytokine, MMPs and EMMPRIN expression

Doodle to Object: Practical Zero-Shot Sketch-Based 3D Shape Retrieval

Zero-shot (ZS) sketch-based three-dimensional (3D) shape retrieval (SBSR) is challenging due to the abstraction of sketches, cross-domain discrepancies between two-dimensional sketches and 3D shapes, and ZS-driven semantic knowledge transference from seen to unseen categories. Extant SBSR datasets suffer from lack of data, and no current SBSR methods consider ZS scenarios. In this paper, we contribute a new Doodle2Object (D2O) dataset consisting of 8,992 3D shapes and over 7M sketches spanning 50 categories. Then, we propose a novel prototype contrastive learning (PCL) method that effectively extracts features from different domains and adapts them to unseen categories. Specifically, our PCL method combines the ideas of contrastive and cluster-based prototype learning, and several randomly selected prototypes of different classes are assigned to each sample. By comparing these prototypes, a given sample can be moved closer to the same semantic class of samples while moving away from negative ones. Extensive experiments on two common SBSR benchmarks and our D2O dataset demonstrate the efficacy of the proposed PCL method for ZS-SBSR. Resource is available at https://github.com/yigohw/doodle2object

A CNN-MPSK Demodulation Architecture with Ultra-Light Weight and Low-Complexity for Communications

Modulation is an indispensable component in modern communication systems and multiple phase shift keying (MPSK) is widely studied to improve the spectral efficiency. It is of great significance to study the MPSK modulations of symmetric phases in practice. Based on convolutional neural networks (CNNs), we propose a generic architecture for MPSK demodulation, referred to as CNN-MPSK. The architecture utilizes a single-layer CNN and a pooling trick to crop network parameters. In comparison with conventional coherent demodulation, the CNN-MPSK eliminates three modules, i.e., carrier multiplication, bandpass filter and sampling decision. Thus, we can avoid π-inverted phenomenon from the multiplication of two carrier waves with different phases, as the carrier multiplication is not employed. In addition, we can reduce errors introduced by sampling decision. Furthermore, we conduct bit-error-rate tests for binary-PSK, 4PSK, 8PSK, and 16PSK demodulation. Experimental results reveal that the performance of CNN-MPSK is almost the same to that of conventional coherent demodulation. However, the CNN-MPSK demodulation reduces computational complexity from O(n2) to O(n) as compared to the latter one. Additionally, the proposed scheme can be readily applied for demodulation of non-symmetric MPSK constellations that maybe distorted by linear and nonlinear impairments in communication systems

Enhanced architecture and implementation of spectrum shaping codes

Spectral shaping codes are modulation codes widely used in communication and data storage systems. This research enhances the algorithms employed in constructing spectral shaping codes for hardware implementation. We present a parallel scrambling calculation with a time complexity of O(1). Second, in the minimum accumulated signal power (MASP) module, the sine-cosine accumulation needs to be determined by remainder with time complexity O(n2). We offer reduced MASP computations for short bit-width data, ROM storage, and addition pipelines. It can remove the remainder operation, reducing accumulated complexity to O(1). In addition, we present a search algorithm to generate segmented lines to replace the square operations in the MASP module. By employing the search algorithm and shift operations, we can reduce the complexity of the square from O(n2) to O(1). The implementation results reveal that the original and proposed MASPs yield nearly identical spectrum nulls. The encoder-decoder of the spectral shaping codes with proposed approaches consumes just 6% of the hardware resources when carried out with a Spartan6 XC6SLX25

Data-Driven Rock Strength Parameter Identification Using Artificial Bee Colony Algorithm

Rock strength parameters are essential to understanding the rock failure mechanism and safely constructing rock excavation. It is a challenging problem for determining the rock failure criterion and its parameters due to the complexity of rock media. This study adopts an artificial bee colony (ABC) algorithm to determine the Hoek-Brown failure criterion, widely used in rock engineering practice, based on experimental data. The ABC-based approach is presented in detail and applied to a collection of experimental data collected from the literature. The ABC-based approach successfully determines the Hoek-Brown failure criterion, and the determined failure envelope is in excellent agreement with the measured curve. The maximum relative error obtained by ABC is only 2.15% and is far less than the 12.24% obtained by the traditional method. Then, the developed approach is applied to the Goupitan Hydropower Station, China, and determines the rheological parameters of soft rock based on the Burgers model. The deformation of an experiment located in the Goupitan Hydropower Station is evaluated based on obtained parameters by the developed approach. The predicted deformation matches the monitored displacement in the field. The obtained parameters of the failure criterion characterize the mechanical behavior of rock mass well. Thus, the method used provides a reliable and robust approach to determining the mechanical parameters of the failure criterion