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

Epidemiological and genomic analyses of human isolates of Streptococcus suis between 2005 and 2021 in Shenzhen, China

Streptococcus suis (S. suis) is an important food-borne zoonotic pathogen that causes swine streptococcosis, which threatens human health and brings economic loss to the swine industry. Three-quarters of human S. suis infections are caused by serotype 2. A retrospective analysis of human S. suis cases in Shenzhen, a megacity in China, with high pork consumption, between 2005 and 2021 was conducted to understand its genomic epidemiology, pathogen virulence, and drug resistance characteristics. The epidemiological investigation showed that human cases of S. suis in Shenzhen were mainly associated with people who had been in close contact with raw pork or other swine products. Whole-genome sequence analysis showed that 33 human isolates in Shenzhen were dominated by serotype 2 (75.76%), followed by serotype 14 (24.24%), and the most prevalent sequence types (STs) were ST7 (48.48%) and ST1 (39.40%). ST242 (9.09%) and ST25 (3.03%), which were rarely reported, were also found. Phylogenetic analysis showed that the Shenzhen human isolates had close genetic relatedness to isolates from Guangxi (China), Sichuan (China), and Vietnam. We found a new 82 KB pathogenicity island (PAI) in the serotype 2 isolate that may play a role in sepsis. Similarly, a serotype 14 isolate, containing 78 KB PAI, was isolated from a patient presenting with streptococcal toxic shock syndrome (STSLS) who subsequently died. Multi-drug resistance (MDR) was high in human isolates of S. suis from Shenzhen. Most human isolates were resistant to tetracycline, streptomycin, erythromycin, and clindamycin, and 13 isolates had intermediate resistance to penicillin. In conclusion, swine importation from Guangxi, Sichuan, and Vietnam should be more closely monitored, and the use of antibiotics limited to reduce the potential for antimicrobial resistance (AMR)

Energy and Acoustic Performance Effects due to VAV Duct Design and Installation Practice Variations

The energy efficiency and acoustic performance trends due to variations in the installation of ductwork after the variable air volume (VAV) unit are generally known, but the quantitative measure of those effects have not been documented through a comprehensive experiment. This study applied commonly found variations in ductwork installations in a full-scale experiment to determine the quantitative main effects of each installation variation. An orthogonal test matrix design of experiment was used so that each main effect was the mean main effect for that variation when exposed to all the other installation variations. It was found that for square diffusers, the energy required to distribute air post VAV unit could be more than doubled by variations in the installation. Sound levels were predicted to differ by nearly 16 dB for different installations at the same airflow rate. The main contribution of this research is that it provides quantitative results that can be used to make energy efficiency and sound-level reduction design and installation decisions and to predict the efficiency and sound levels of an installation

A Literature Review and Result Interpretation of the System Identification of Arch Dams Using Seismic Monitoring Data

The system identification of concrete dams using seismic monitoring data can reveal the practical dynamic properties of structures during earthquakes and provide valuable information for the analysis of structural seismic response, finite element model calibration, and the assessment of postearthquake structural damage. In this investigation, seismic monitoring data of the Pacoima arch dam were used to identify the structural modal parameters. The identified modal parameters of the Pacoima arch dam, derived in different previous studies that used forced vibration tests (FVT), numerical calculation, and seismic monitoring, were compared. Meanwhile, different modal identification results using the input-output (IO) methods and the output-only (OO) identification methods as well as the linear time-varying (LTV) modal identification method were adopted to compare the modal identification results. Taking into account the different excitation, seismic input, and modal identification methods, the reasons for the differences among these identification results were analyzed, and some existing problems in the current modal identification of concrete dams are pointed out. These analysis results provide valuable guidance regarding the selection of appropriate identification methods and the evaluation of the system identification results for practical engineering applications

Metadata Extraction System for Chinese Books

Extracting metadata from academic papers has attracted much attention from researchers in past years. But how to extract metadata automatically from books is still seldom discussed. In this paper, we address this task on Chinese books and present a system to extract metadata from the title page of a book. This system consists of three components: metadata segmentation, metadata labeling, and post-processing. Different strategies are adopted in the system to identify different metadata types, and a variety of information sources, including geometric layout, linguistic, semantic content and header-footer, are used to accommodate the wide range of metadata layouts. Experimental results on real-world data have demonstrated the effectiveness of the proposed system.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000343450700147&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Computer Science, Artificial IntelligenceEngineering, Electrical &amp; ElectronicEICPCI-S(ISTP)