Erratum to: `Manifestation of an adaptive neuro-fuzzy model on landslide susceptibility mapping: Klang valley, Malaysia` [Expert Systems with Applications 38 (2011) 8208`8219]

This note is to point out and correct an error in Sezer et al. (2011). İn the paper (Sezer et al. 2011), the authors mention “ANFIS model has not been used for landslide susceptibility mapping previously”. This statement must be corrected as “The ANFIS model has been applied in landslide susceptibility mapping previously by Pradhan, Sezer, Gokceoglu, and Buchroithner (2010) in a different study area namely Cameron Highlands, Malaysia.

Covalent modification of enzymes for textile processes

Wide range of application of enzymes allowed their use in many textile processes such as biopolishing, desizing and bleaching. Cellulase enzymes have been used for the biopolishing of cellulosic fibers and fabrics. In this work the focus was on two seperate applications of modified enzymes in textile processing, one is to retain strength of viscos during pilling process and the second is to combine desizing and the bleaching processes of the fabric. Cellulases are used to prevent pilling on the surface of the viscose fabric but they couse a loss in the tensile strength of the viscose fabric. Commercial celluloses were crosslinked using different parameters in an attempt to ameliorate the loss of tensile strength and to improve enzyme properties. Native and modified enzymes were characterized and their activities against CMC and their effects on the properties of viscose (such as pilling, bursting strength) fabric were determined. Effects of mechanical agitation and surfactants were examined. Crosslinking of cellulase was found to prevent the loss of strength due to the fact that larger enzyme complexes formed by crosslinking were minly resticted to the fabric surface. Enzymes are replacing the use of harsh chemicals in many of the textile processes such as desizind and bleaching and immobilizations of these enzymes on solid supports allow their recycling. Enzymatically produced peroxide is used for bleaching of the cotton fabrics. Commercial Glucosse oxidase (GOx) enzyme was immobilized on different supports such as alumina, silica, Sepharose 4B and crosslinked enzyme aggragates of GOx were prepared. Their efficiencies against glucose substrate for the production of peroxide were analyzed. Moreover, the starch size of the cotton fabric is hydrolized into glucose by the action of amyloglucosidase and this liquor was also used to produce peroxide. The activities of immobilized enzymes and CLEAs against desizing liquor and the whiteness values of the cotton fabrics after bleaching were examined. The whiteness values reached with immobilized enzyme are not appropriate for white textile but is sufficient for further dyeing processe. Combination of desizing and bleaching in a single bath and recycling of the immobilized enzyme is an environmently friendly alternative

Protein engineering and covalent modification of trichoderma reesei cellulases in pichia pastoris for textile biofinishing

Cellulase enzymes have been extensively used for the biopolishing of cellulosic fabrics but they are inefficient to prevent pilling in viscose fabrics. Moreover, their application causes a loss in the fabric strength due to the aggressive action of the enzymes. One solution to this problem is the design and production of enzymes with increased molecular weights so that aggressive action of the cellulases would be limited to the fabric surface. In the framework of this study, cellulases and cellulase formulations that can ameliorate the problem of pilling and prevent loss of tensile strength in viscose fabrics were designed and produced . For this purpose, both protein engineering and chemical modification methods were used seperately and in combination to obtain cellulases with desired properties. Trichoderma reesei Endoglucanase I (EGI), Endoglucanase III (EGIII), Cellobiohydrolase I (CBHI) enzymes were successfully cloned and expressed in Pichia pastoris under the control of AOX1 promoter to mg/L quantities. A loop mutant of EGI, (EGI_L5) was prepared by introduction of a ten aminoacid long loop by molecular modelling and site directed mutagenesis for the creation of hotspots for directed crosslinking of the enzyme. The mutant enzyme was crosslinked using crosslinked enzyme aggregate (CLEA) technology. The effect of codon optimization on EGI production was analyzed. A mutant of EGI was prepared by inserting a second catalytic domain to EGI and thereby forming a bicatalytic mutant of EGI (EGI_BC) with increased molecular weight. All of the recombinant enzymes were produced in a laboratory scale fermenter and characterized. A commercial cellulase preparation was crosslinked using CLEA technology and fractionated according to the particle size. The effects of native, engineered and chemically modified cellulases on viscose fabrics were evaluated. It was found that commercial cellulase preparation crosslinked using CLEA technology, recombinant EGI and EGI_L5 produced in P. pastoris improved the pilling values of viscose fabrics by 20 % without much loss in the strength of the fabrics

Genome of Pythium myriotylum Uncovers an Extensive Arsenal of Virulence-Related Genes among the Broad-Host-Range Necrotrophic Pythium Plant Pathogens

The Pythium (Peronosporales, Oomycota) genus includes devastating plant pathogens that cause widespread diseases and severe crop losses. Here, we have uncovered a far greater arsenal of virulence factor-related genes in the necrotrophic Pythium myriotylum than in other Pythium plant pathogens. The genome of a plant-virulent P. myriotylum strain (~70 Mb and 19,878 genes) isolated from a diseased rhizome of ginger (Zingiber officinale) encodes the largest repertoire of putative effectors, proteases, and plant cell wall-degrading enzymes (PCWDEs) among the studied species. P. myriotylum has twice as many predicted secreted proteins than any other Pythium plant pathogen. Arrays of tandem duplications appear to be a key factor of the enrichment of the virulence factor-related genes in P. myriotylum. The transcriptomic analysis performed on two P. myriotylum isolates infecting ginger leaves showed that proteases were a major part of the upregulated genes along with PCWDEs, Nep1-like proteins (NLPs), and elicitin-like proteins. A subset of P. myriotylum NLPs were analyzed and found to have necrosis-inducing ability from agroinfiltration of tobacco (Nicotiana benthamiana) leaves. One of the heterologously produced infection-upregulated putative cutinases found in a tandem array showed esterase activity with preferences for longer-chain-length substrates and neutral to alkaline pH levels. Our results allow the development of science-based targets for the management of P. myriotylum-caused disease, as insights from the genome and transcriptome show that gene expansion of virulence factor-related genes play a bigger role in the plant parasitism of Pythium spp. than previously thought. IMPORTANCE Pythium species are oomycetes, an evolutionarily distinct group of filamentous fungus-like stramenopiles. The Pythium genus includes several pathogens of important crop species, e.g., the spice ginger. Analysis of our genome from the plant pathogen Pythium myriotylum uncovered a far larger arsenal of virulence factor-related genes than found in other Pythium plant pathogens, and these genes contribute to the infection of the plant host. The increase in the number of virulence factor-related genes appears to have occurred through the mechanism of tandem gene duplication events. Genes from particular virulence factor-related categories that were increased in number and switched on during infection of ginger leaves had their activities tested. These genes have toxic activities toward plant cells or activities to hydrolyze polymeric components of the plant. The research suggests targets to better manage diseases caused by P. myriotylum and prompts renewed attention to the genomics of Pythium plant pathogens

Fungal Genomes and Insights into the Evolution of the Kingdom

The kingdom Fungi comprises species that inhabit nearly all ecosystems. Fungi exist as both free-living and symbiotic unicellular and multicellular organisms with diverse morphologies. The genomes of fungi encode genes that enable them to thrive in diverse environments, invade plant and animal cells, and participate in nutrient cycling in terrestrial and aquatic ecosystems. The continuously expanding databases of fungal genome sequences have been generated by individual and large-scale efforts such as Génolevures, Broad Institute's Fungal Genome Initiative, and the 1000 Fungal Genomes Project (http://1000.fungalgenomes.org). These efforts have produced a catalog of fungal genes and genomic organization. The genomic datasets can be utilized to better understand how fungi have adapted to their lifestyles and ecological niches. Large datasets of fungal genomic and transcriptomic data have enabled the use of novel methodologies and improved the study of fungal evolution from a molecular sequence perspective. Combined with microscopes, petri dishes, and woodland forays, genome sequencing supports bioinformatics and comparative genomics approaches as important tools in the study of the biology and evolution of fungi

Investigating Video Viewing Behaviors of Students with Different Learning Approaches Using Video Analytics

Scopu

Using Learning Analytics To Develop Early-Warning System For At-Risk Students!

In the current study interaction data of students in an online learning setting was used to research whether the academic performance of students at the end of term could be predicted in the earlier weeks. The study was carried out with 76 second-year university students registered in a Computer Hardware course. The study aimed to answer two principle questions: which algorithms and features best predict the end of term academic performance of students by comparing different classification algorithms and pre-processing techniques and whether or not academic performance can be predicted in the earlier weeks using these features and the selected algorithm. The results of the study indicated that the kNN algorithm accurately predicted unsuccessful students at the end of term with a rate of 89%. When findings were examined regarding the analysis of data obtained in weeks 3, 6, 9, 12, and 14 to predict whether the end-of-term academic performance of students could be predicted in the earlier weeks, it was observed that students who were unsuccessful at the end of term could be predicted with a rate of 74% in as short as 3 weeks' time. The findings obtained from this study are important for the determination of features for early warning systems that can be developed for online learning systems and as indicators of student success. At the same time, it will aid researchers in the selection of algorithms and pre-processing techniques in the analysis of educational data.WoSScopu

Computational approaches for de novo design and redesign of metal-binding sites on proteins

Metal ions play pivotal roles in protein structure, function and stability. The functional and structural diversity of proteins in nature expanded with the incorporation of metal ions or clusters in proteins. Approximately one-third of these proteins in the databases contain metal ions. Many biological and chemical processes in nature involve metal ion-binding proteins, aka metalloproteins. Many cellular reactions that underpin life require metalloproteins. Most of the remarkable, complex chemical transformations are catalysed by metalloenzymes. Realization of the importance of metal-binding sites in a variety of cellular events led to the advancement of various computational methods for their prediction and characterization. Furthermore, as structural and functional knowledgebase about metalloproteins is expanding with advances in computational and experimental fields, the focus of the research is now shifting towards de novo design and redesign of metalloproteins to extend nature's own diversity beyond its limits. In this review, we will focus on the computational toolbox for prediction of metal ion-binding sites, de novo metalloprotein design and redesign. We will also give examples of tailor-made artificial metalloproteins designed with the computational toolbox