Search results for: protein structure prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11410

Search results for: protein structure prediction

11140 Functional Cell Surface Display Using Ice Nucleation Protein from Erwina ananas on Escherischia coli

Authors: Mei Yuin Joanne Wee, Rosli Md. Illias

Abstract:

Cell surface display is the expression of a protein with an anchoring motif on the surface of the cell. This approach offers advantages when used in bioconversion in terms of easier purification steps and more efficient enzymatic reaction. A surface display system using ice nucleation protein (InaA) from Erwina ananas as an anchoring motif has been constructed to display xylanase (xyl) on the surface of Escherischia coli. The InaA was truncated so that it is made up of the N- and C-terminal domain (INPANC-xyl) and it has successfully directed xylanase to the surface of the cell. A study was also done on xylanase fused to two other ice nucleation proteins, InaK (INPKNC-xyl) and InaZ (INPZNC-xyl) from Pseudomonas syringae KCTC 1832 and Pseudomonas syringae S203 respectively. Surface localization of the fusion protein was verified using SDS-PAGE and Western blot on the cell fractions and all anchoring motifs were successfully displayed on the outer membrane of E. coli. Upon comparison, whole-cell activity of INPANC-xyl was more than six and five times higher than INPKNC-xyl and INPZNC-xyl respectively. Furthermore, the expression of INPANC-xyl on the surface of E. coli did not inhibit the growth of the cell. This is the first report of surface display system using ice nucleation protein, InaA from E. ananas. From this study, this anchoring motif offers an attractive alternative to the current surface display systems.

Keywords: cell surface display, Escherischia coli, ice nucleation protein, xylanase

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11139 Grey Wolf Optimization Technique for Predictive Analysis of Products in E-Commerce: An Adaptive Approach

Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

Abstract:

E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

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11138 Extraction of Rice Bran Protein Using Enzymes and Polysaccharide Precipitation

Authors: Sudarat Jiamyangyuen, Tipawan Thongsook, Riantong Singanusong, Chanida Saengtubtim

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Rice is a staple food as well as exported commodity of Thailand. Rice bran, a 10.5% constituent of rice grain, is a by-product of rice milling process. Rice bran is normally used as a raw material for rice bran oil production or sold as feed with a low price. Therefore, this study aimed to increase value of defatted rice bran as obtained after extracting of rice bran oil. Conventionally, the protein in defatted rice bran was extracted using alkaline extraction and acid precipitation, which results in reduction of nutritious components in rice bran. Rice bran protein concentrate is suitable for those who are allergenic of protein from other sources eg. milk, wheat. In addition to its hypoallergenic property, rice bran protein also contains good quantity of lysine. Thus it may act as a suitable ingredient for infant food formulations while adding variety to the restricted diets of children with food allergies. The objectives of this study were to compare properties of rice bran protein concentrate (RBPC) extracted from defatted rice bran using enzymes together with precipitation step using polysaccharides (alginate and carrageenan) to those of a control sample extracted using a conventional method. The results showed that extraction of protein from rice bran using enzymes exhibited the higher protein recovery compared to that extraction with alkaline. The extraction conditions using alcalase 2% (v/w) at 50 C, pH 9.5 gave the highest protein (2.44%) and yield (32.09%) in extracted solution compared to other enzymes. Rice bran protein concentrate powder prepared by a precipitation step using alginate (protein in solution: alginate 1:0.006) exhibited the highest protein (27.55%) and yield (6.62%). Precipitation using alginate was better than that of acid. RBPC extracted with alkaline (ALK) or enzyme alcalase (ALC), then precipitated with alginate (AL) (samples RBP-ALK-AL and RBP-ALC-AL) yielded the precipitation rate of 75% and 91.30%, respectively. Therefore, protein precipitation using alginate was then selected. Amino acid profile of control sample, and sample precipitated with alginate, as compared to casein and soy protein isolated, showed that control sample showed the highest content among all sample. Functional property study of RBP showed that the highest nitrogen solubility occurred in pH 8-10. There was no statically significant between emulsion capacity and emulsion stability of control and sample precipitated by alginate. However, control sample showed a higher of foaming and lower foam stability compared to those of sample precipitated with alginate. The finding was successful in terms of minimizing chemicals used in extraction and precipitation steps in preparation of rice bran protein concentrate. This research involves in a production of value-added product in which the double amount of protein (28%) compared to original amount (14%) contained in rice bran could be beneficial in terms of adding to food products eg. healthy drink with high protein and fiber. In addition, the basic knowledge of functional property of rice bran protein concentrate was obtained, which can be used to appropriately select the application of this value-added product from rice bran.

Keywords: alginate, carrageenan, rice bran, rice bran protein

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11137 Application of Computational Chemistry for Searching Anticancer Derivatives of 2-Phenazinamines as Bcr-Abl Tyrosine Kinase Inhibitors

Authors: Gajanan M. Sonwane

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The computational studies on 2-phenazinamines with their protein targets have been carried out to design compounds with potential anticancer activity. This strategy of designing compounds possessing selectivity over specific tyrosine kinase has been achieved through G-QSAR and molecular docking studies. The objective of this research has been to design newer 2-phenazinamine derivatives as Bcr-Abl tyrosine kinase inhibitors by G-QSAR, molecular docking studies followed by wet-lab studies along with evaluation of their anticancer potential. Computational chemistry was done by using VLife MDS 4.3 and Autodock 4.2 followed by wet-lab experiments for synthesizing 2-phenazinamine derivatives. The chemical structures of ligands in 2D were drawn by employing Chemdraw 2D Ultra 8.0 and were converted into 3D. These were optimized by using a semi-empirical method called MOPAC. The protein structure was retrieved from RCSC protein data bank as a PDB file. The binding interactions of protein and ligands were done by using PYMOL. The molecular properties of the designed compounds were predicted in silico by using Osiris property explorer. The parent compound 2-phenazinamine was synthesized by reduction of 2, 4-dinitro-N-phenyl-benzenamine in the presence of tin chloride followed by cyclization in the presence of nitrobenzene and magnesium sulfate. The derivatization at the amino function of 2-phenazinamine was performed by treating parent compound with various aldehydes in the presence of dicyclohexylcarbodiimide (DCC) and urea to afford 2-(2-chlorophenyl)-3-(phenazine-2-yl) thiazolidine-4-one. Synthesized 39 novel derivatives of 2-phenazinamine and performed antioxidant activity, anti antiproliferative on the bulb of onion and anticancer activity on cell line showing significant competition with marked blockbuster drug imatinib.

Keywords: computer-aided drug design, tyrosin kinases, anticancer, docking

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11136 Hybrid Approach for Software Defect Prediction Using Machine Learning with Optimization Technique

Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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11135 Development of Prediction Tool for Sound Absorption and Sound Insulation for Sound Proof Properties

Authors: Yoshio Kurosawa, Takao Yamaguchi

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High frequency automotive interior noise above 500 Hz considerably affects automotive passenger comfort. To reduce this noise, sound insulation material is often laminated on body panels or interior trim panels. For a more effective noise reduction, the sound reduction properties of this laminated structure need to be estimated. We have developed a new calculate tool that can roughly calculate the sound absorption and insulation properties of laminate structure and handy for designers. In this report, the outline of this tool and an analysis example applied to floor mat are introduced.

Keywords: automobile, acoustics, porous material, transfer matrix method

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11134 Machine Learning Techniques to Develop Traffic Accident Frequency Prediction Models

Authors: Rodrigo Aguiar, Adelino Ferreira

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Road traffic accidents are the leading cause of unnatural death and injuries worldwide, representing a significant problem of road safety. In this context, the use of artificial intelligence with advanced machine learning techniques has gained prominence as a promising approach to predict traffic accidents. This article investigates the application of machine learning algorithms to develop traffic accident frequency prediction models. Models are evaluated based on performance metrics, making it possible to do a comparative analysis with traditional prediction approaches. The results suggest that machine learning can provide a powerful tool for accident prediction, which will contribute to making more informed decisions regarding road safety.

Keywords: machine learning, artificial intelligence, frequency of accidents, road safety

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11133 Admission C-Reactive Protein Serum Levels and In-Hospital Mortality in the Elderly Admitted to the Acute Geriatrics Department

Authors: Anjelika Kremer, Irina Nachimov, Dan Justo

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Background: C-reactive protein (CRP) serum levels are commonly measured in hospitalized patients. Elevated admission CRP serum levels and in-hospital mortality has been seldom studied in the general population of elderly patients admitted to the acute Geriatrics department. Methods: A retrospective cross-sectional study was conducted at a tertiary medical center. Included were all elderly patients (age 65 years or more) admitted to a single acute Geriatrics department from the emergency room between April 2014 and January 2015. CRP serum levels were measured routinely in all patients upon the first 24 hours of admission. A logistic regression analysis was used to study if admission CRP serum levels were associated with in-hospital mortality independent of age, gender, functional status, and co-morbidities. Results: Overall, 498 elderly patients were included in the analysis: 306 (61.4%) female patients and 192 (38.6%) male patients. The mean age was 84.8±7.0 years (median: 85 years; IQR: 80-90 years). The mean admission CRP serum levels was 43.2±67.1 mg/l (median: 13.1 mg/l; IQR: 2.8-51.7 mg/l). Overall, 33 (6.6%) elderly patients died during the hospitalization. A logistic regression analysis showed that in-hospital mortality was independently associated with history of stroke (p < 0.0001), heart failure (p < 0.0001), and admission CRP serum levels (p < 0.0001) – and to a lesser extent with age (p = 0.042), collagen vascular disease (p=0.011), and recent venous thromboembolism (p=0.037). Receiver operating characteristic (ROC) curve showed that admission CRP serum levels predict in-hospital mortality fairly with an area under the curve (AUC) of 0.694 (p < 0.0001). Cut-off value with maximal sensitivity and specificity was 19.7 mg/L. Conclusions: Admission CRP serum levels may be used to predict in-hospital mortality in the general population of elderly patients admitted to the acute Geriatrics department.

Keywords: c-reactive protein, elderly, mortality, prediction

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11132 Nanoparticle-Based Histidine-Rich Protein-2 Assay for the Detection of the Malaria Parasite Plasmodium Falciparum

Authors: Yagahira E. Castro-Sesquen, Chloe Kim, Robert H. Gilman, David J. Sullivan, Peter C. Searson

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Diagnosis of severe malaria is particularly important in highly endemic regions since most patients are positive for parasitemia and treatment differs from non-severe malaria. Diagnosis can be challenging due to the prevalence of diseases with similar symptoms. Accurate diagnosis is increasingly important to avoid overprescribing antimalarial drugs, minimize drug resistance, and minimize costs. A nanoparticle-based assay for detection and quantification of Plasmodium falciparum histidine-rich protein 2 (HRP2) in urine and serum is reported. The assay uses magnetic beads conjugated with anti-HRP2 antibody for protein capture and concentration, and antibody-conjugated quantum dots for optical detection. Western Blot analysis demonstrated that magnetic beads allows the concentration of HRP2 protein in urine by 20-fold. The concentration effect was achieved because large volume of urine can be incubated with beads, and magnetic separation can be easily performed in minutes to isolate beads containing HRP2 protein. Magnetic beads and Quantum Dots 525 conjugated to anti-HRP2 antibodies allows the detection of low concentration of HRP2 protein (0.5 ng mL-1), and quantification in the range of 33 to 2,000 ng mL-1 corresponding to the range associated with non-severe to severe malaria. This assay can be easily adapted to a non-invasive point-of-care test for classification of severe malaria.

Keywords: HRP2 protein, malaria, magnetic beads, Quantum dots

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11131 Social Structure, Involuntary Relations and Urban Poverty

Authors: Mahmood Niroobakhsh

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This article deals with special structuralism approaches to explain a certain kind of social problem. Widespread presence of poverty is a reminder of deep-rooted unresolved problems of social relations. The expected role from an individual for the social system recognizes poverty derived from an interrelated social structure. By the time, enabled to act on his role in the course of social interaction, reintegration of the poor in society may take place. Poverty and housing type are reflections of the underlying social structure, primarily structure’s elements, systemic interrelations, and the overall strength or weakness of that structure. Poverty varies based on social structure in that the stronger structures are less likely to produce poverty.

Keywords: absolute poverty, relative poverty, social structure, urban poverty

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11130 Encapsulation and Protection of Bioactive Nutrients Based on Ligand-Binding Property of Milk Proteins

Authors: Hao Cheng, Yingzhou Ni, Amr M. Bakry, Li Liang

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Functional foods containing bioactive nutrients offer benefits beyond basic nutrition and hence the possibility of delaying and preventing chronic diseases. However, many bioactive nutrients degrade rapidly under food processing and storage conditions. Encapsulation can be used to overcome these limitations. Food proteins have been widely used as carrier materials for the preparation of nano/micro-particles because of their ability to form gels and emulsions and to interact with polysaccharides. The mechanisms of interaction between bioactive nutrients and proteins must be understood in order to develop protein-based lipid-free delivery systems. Beta-lactoglobulin, a small globular protein in milk whey, exhibits an affinity to a wide range of compounds. Alfa-tocopherol, resveratrol and folic acid were respectively bound to the central cavity, the outer surface near Trp19–Arg124 and the hydrophobic pocket in the groove between the alfa-helix and the beta-barrel of the protein. Beta-lactoglobulin could thus bind the three bioactive nutrients simultaneously to form protein-multi-ligand complexes. Beta-casein, an intrinsically unstructured but major milk protein, could also interact with resveratrol and folic acid to form complexes. These results suggest the potential to develop milk-protein-based complex carrier systems for encapsulation of multiple bioactive nutrients for functional food application and also pharmaceutical and medical uses.

Keywords: milk protein, bioactive nutrient, interaction, protection

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11129 Plasma-Induced Modification of Biomolecules: A Tool for Analysis of Protein Structures

Authors: Yuting Wu, Faraz Choudhury, Daniel Benjamin, James Whalin, Joshua Blatz, Leon Shohet, Michael Sussman, Mark Richards

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Plasma-Induced Modification of Biomolecules (PLIMB) has been developed as a technology, which, together with mass spectrometry, measures three-dimensional structural characteristics of proteins. This technique uses hydroxyl radicals generated by atmospheric-pressure plasma discharge to react with the solvent-accessible side chains of protein in an aqueous solution. In this work, we investigate the three-dimensional structure of hemoglobin and myoglobin using PLIMB. Additional modifications to these proteins, such as oxidation, fragmentations, and conformational changes caused by PLIMB are also explored. These results show that PLIMB, coupled with mass spectrometry, is an effective way to determine solvent access to hemoproteins. Furthermore, we show that many factors, including pH and the electrical parameters used to generate the plasma, have a significant influence on solvent accessibility.

Keywords: plasma, hemoglobin, myoglobin, solvent access

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11128 Expression of Human Papillomavirus Type 18 L1 Virus-Like Particles in Methylotropic Yeast, Pichia Pastoris

Authors: Hossein Rassi, Marjan Moradi Fard, Samaneh Niko

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Human papillomavirus type 16 and 18 are closely associated with the development of human cervical carcinoma, which is one of the most common causes of cancer death in women worldwide. At present, HPV type 18 accounts for about 34 % of all HPV infections in Iran and the most promising vaccine against HPV infection is based on the L1 major capsid protein. The L1 protein of HPV18 has the capacity to self-assemble into capsomers or virus-like particles (VLPs) that are non-infectious, highly immunogenic and allowing their use in vaccine production. The methylotrophic yeast Pichia pastoris is an efficient and inexpensive expression system used to produce high levels of heterologous proteins. In this study we expressed HPV18 L1 VLPs in P. pastoris. The gene encoding the major capsid protein L1 of the high-risk HPV type 18 was isolated from Iranian patient by PCR and inserted into pTG19-T vector to obtain the recombinant expression vector pTG19-HPV18-L1. Then, the pTG19-HPV18-L1 was transformed into E. coli strain DH5α and the recombinant protein HPV18 L1 was expressed under IPTG induction in soluble form. The HPV18 L1 gene was excised from recombinant plasmid with XhoI and EcoRI enzymes and ligated into the yeast expression vector pPICZα linearized with the same enzymes, and transformed into P. pastoris. Induction and expression of HPV18 L1 protein was demonstrated by BMGY/BMMY and RT PCR. The parameters for induced cultivation for strain in P. pastoris KM71 with HPV16L1 were investigated in shaking flask cultures. After induced cultivation BMMY (pH 7.0) medium supplemented with methanol to a final concentration of 1.0% every 24 h at 37 degrees C for 96 h, the recombinant produced 78.6 mg/L of L1 protein. This work offers the possibility for the production of prophylactic vaccine for cervical carcinoma by P. pastoris for HPV-18 L1 gene. The VLP-based HPV vaccines can prevent persistent HPV18 infections and cervical cancer in Iran. The HPV-18 L1 gene was expressed successfully in E.coli, which provides necessary basis for preparing HPV-18 L1 vaccine in human. Also, HPV type 6 L1 proteins expressed in Pichia pastoris will facilitate the HPV vaccine development and structure-function study.

Keywords: Pichia pastoris, L1 virus-like particles, human papillomavirus type 18, biotechnology

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11127 Protein Quality of Game Meat Hunted in Latvia

Authors: Vita Strazdina, Aleksandrs Jemeljanovs, Vita Sterna

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Not all proteins have the same nutritional value, since protein quality strongly depends on its amino acid composition and digestibility. The meat of game animals could be a high protein source because of its well-balanced essential amino acids composition. Investigations about biochemical composition of game meat such as wild boar (Sus scrofa scrofa), roe deer (Capreolus capreolus) and beaver (Castor fiber) are not very much. Therefore, the aim of the investigation was evaluate protein composition of game meat hunted in Latvia. The biochemical analysis, evaluation of connective tissue and essential amino acids in meat samples were done, the amino acids score were calculate. Results of analysis showed that protein content 20.88-22.05% of all types of meat samples is not different statistically. The content of connective tissue from 1.3% in roe deer till 1.5% in beaver meat allowed classified game animal as high quality meat. The sum of essential amino acids in game meat samples were determined 7.05–8.26g100g-1. Roe deer meat has highest protein content and lowest content of connective tissues among game meat hunted in Latvia. Concluded that amino acid score for limiting amino acids phenylalanine and tyrosine is high and shows high biological value of game meat.

Keywords: dietic product, game meat, amino acids, scores

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11126 Impact of Dietary L-Threonine Supplementation on Performance and Health of Broiler Chickens, a Review

Authors: Mandana Hoseini

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During last decades, intensive selection for higher growth rate in broiler chickens has accelerated daily body weight gain, which this has changed/increased the trends and amounts of nutrient requirements in the diet. As a result, considerable studies have been focused on the better determination of protein/amino acids requirements in modern broiler diets. One approach to minimize dietary crude protein inclusion levels is substitution of some of the dietary crude protein with synthetic amino acids. In addition, using synthetic forms of limiting essential amino acids in the diet could help better coincidence of dietary protein with ideal protein concept, which this in turn, minimizes nitrogen dissipation and environmental pollution. Threonine is usually considered as the third limiting amino acid in broiler diets. Recent studies have been demonstrated that dietary supplemental threonine would optimize growth performance, immune system, intestinal morphology, as well as oxidative defense in broiler chickens. In this review, threonine metabolism and its effects in relation with different aspects of broiler performance have been discussed.

Keywords: immune system, intestine, performance, requirement, threonine

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11125 Bioinformatic Prediction of Hub Genes by Analysis of Signaling Pathways, Transcriptional Regulatory Networks and DNA Methylation Pattern in Colon Cancer

Authors: Ankan Roy, Niharika, Samir Kumar Patra

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Anomalous nexus of complex topological assemblies and spatiotemporal epigenetic choreography at chromosomal territory may forms the most sophisticated regulatory layer of gene expression in cancer. Colon cancer is one of the leading malignant neoplasms of the lower gastrointestinal tract worldwide. There is still a paucity of information about the complex molecular mechanisms of colonic cancerogenesis. Bioinformatics prediction and analysis helps to identify essential genes and significant pathways for monitoring and conquering this deadly disease. The present study investigates and explores potential hub genes as biomarkers and effective therapeutic targets for colon cancer treatment. Colon cancer patient sample containing gene expression profile datasets, such as GSE44076, GSE20916, and GSE37364 were downloaded from Gene Expression Omnibus (GEO) database and thoroughly screened using the GEO2R tool and Funrich software to find out common 2 differentially expressed genes (DEGs). Other approaches, including Gene Ontology (GO) and KEGG pathway analysis, Protein-Protein Interaction (PPI) network construction and hub gene investigation, Overall Survival (OS) analysis, gene correlation analysis, methylation pattern analysis, and hub gene-Transcription factors regulatory network construction, were performed and validated using various bioinformatics tool. Initially, we identified 166 DEGs, including 68 up-regulated and 98 down-regulated genes. Up-regulated genes are mainly associated with the Cytokine-cytokine receptor interaction, IL17 signaling pathway, ECM-receptor interaction, Focal adhesion and PI3K-Akt pathway. Downregulated genes are enriched in metabolic pathways, retinol metabolism, Steroid hormone biosynthesis, and bile secretion. From the protein-protein interaction network, thirty hub genes with high connectivity are selected using the MCODE and cytoHubba plugin. Survival analysis, expression validation, correlation analysis, and methylation pattern analysis were further verified using TCGA data. Finally, we predicted COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as potential master regulators in colonic cancerogenesis. Moreover, our experimental data highlights that disruption of lipid raft and RAS/MAPK signaling cascade affects this gene hub at mRNA level. We identified COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as determinant hub genes in colon cancer progression. They can be considered as biomarkers for diagnosis and promising therapeutic targets in colon cancer treatment. Additionally, our experimental data advertise that signaling pathway act as connecting link between membrane hub and gene hub.

Keywords: hub genes, colon cancer, DNA methylation, epigenetic engineering, bioinformatic predictions

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11124 Interaction between Kazal-Type Serine Proteinase Inhibitor SPIPm2 and Cyclophilin A from the Black Tiger Shrimp Penaeus monodon

Authors: Sirikwan Ponprateep, Anchalee Tassanakajon, Vichien Rimphanitchayakit

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A Kazal-type serine proteinase inhibitor, SPIPm2, was abundantly expressed in the hemocytes and secreted into shrimp plasma has anti-viral property against white spot syndrome virus (WSSV). To discover the molecular mechanism of antiviral activity, the binding assay showed that SPIPm2 bind to the components of viral particle and shrimp hemocyte. From our previous report, viral target protein of SPIPm2 was identified, namely WSV477 using yeast two-hybrid screening. WSV477 is an early gene product of WSSV and involved in viral propagation. In this study, the co-immunoprecipitation technique and Tandem Mass Spectrometry (LC-MS/MS) was used to identify the target protein of SPIPm2 from shrimp hemocyte. The target protein of SPIPm2 was cyclophilin A. In vertebrate, cyclophilin A or peptidylprolyl isomerase A was reported to be the immune suppressor interacted with cyclosporin A involved in immune defense response. The recombinant cyclophilin A from Penaeus monodon (rPmCypA) was produced in E.coli system and purified using Ni-NTA column to confirm the protein-protein interaction. In vitro pull-down assay showed the interaction between rSPIPm2 and rPmCypA. To study the biological function of these proteins, the expression analysis of immune gene in shrimp defense pathways will be investigated after rPmCypA administration.

Keywords: cyclophilin A, protein-protein interaction, Kazal-type serine proteinase inhibitor, Penaeus monodon

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11123 The Effect of the Earthworm (Lumbricus rubellus) as the Source of Protein Feed and Pathogen Antibacterial for Broiler

Authors: Waode Nurmayani, Nikmatul Riswanda

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Broilers are chickens which are kept with the most efficient time and hoped get a good body weight. All things are done, for example with the improvement of feed and use antibiotics. Feed cost is the most cost to be spent. Nearly 80% of the cost is spent just for buy feed. Earthworm (Lumbricus rubellus) is a good choice to reduce the cost of feed protein source. The Earthworm has a high crude protein content of about 48.5%-61.9%, rich with proline amino acid about 15% of the 62 amino acids. Not only about protein, this earthworm also has a role in disease prevention. Prevention of disease in livestock usual with use feed supplement. Earthworm (Lumbricus rubellus) is one of the natural materials used as feed. In addition, several types of earthworms that have been known to contain active substances about antibacterial pathogens namely Lumbricus rubellus. The earthworm could be used as an antibiotic because it contain the antibody of Lumbricine active substance. So that, this animal feed from Lumbricus rubellus could improve the performance of broilers. Bioactive of anti-bacterial is called Lumbricine able to inhibit the growth of pathogenic bacteria in the intestinal wall so that the population of pathogenic bacteria is reduced. The method of write in this scientific writing is divided into 3 techniques, namely data completion, data analysis, and thinking pan from various literature about earthworm (Lumbricus rubellus) as broiler feed. It is expected that innovation of feed material of earthworm (Lumbricus rubellus) could reduce the cost of protein feed and the use of chemical antibiotics.

Keywords: earthworm, broiler, protein, antibiotic

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11122 Apparent Ileal and Excreta Digestibility of Protein Poultry By-Product Meal in 21 to 28 Days of Age Broiler Chicken

Authors: N. Mahmoudnia, M. Khormali

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This experiment was conducted to determine the apparent protein digestibility of poultry byproduct meal (PBPM) from two industrial poultry slaughter-houses on Ross 308 male broiler chickens in independent comparisons. The experiment consisted of seven dietary treatments and three replicates per treatment with three broiler chickens per replicate in a completely randomized design. Dietary treatments consisted of a control corn- soybean diet, and levels 3, 6, and 9% PBPM produced by slaughter-house 1 and levels 3, 6, and 9% PBPM produced by slaughter house 2. Chromic oxide was added to the experimental diets as an indigestible marker. The apparent protein digestibility of each diet were determined with two methods of sample collection of ileum and excreta in 21-28 d of age. The results this experiment showed that use of PBPM had no significant effect on the performance of broiler chicks during period of experiments. The apparent protein digestibility of PBPM groups was significantly higher than control group by excreta sampling procedure (P<0.05). Using of PBPM 2 significantly (P<0.05) decreased the apparent protein digestibility values based on ileum sampling procedure vs control (85.21 vs. 90.14).Based results of this experiment,it is possible to use of PBPM 1 in broiler chicken.

Keywords: poultry by-product meal, apparent protein digestibility, independed comparison, broiler chicken

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11121 Evaluation of Coagulation Efficiency of Protein Extracts from Lupinus Albus L., Moringa Stenopetala Cufod., Trigonella Foenum-Graecum L. And Vicia Faba L. For Water Purification

Authors: Neway Adele, Adey Feleke

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Access to clean drinking water is a basic human right. However, an estimated 1.2 billion people across the world consume unclean water daily. Interest has been growing in natural coagulants as the health and environmental concerns of conventional chemical coagulants are rising. Natural coagulants have the potential to serve as alternative water treatment agents. In this study, Lupinus albus, Moringa stenopetala, Trigonella foenum-graecum and Vicia faba protein extracts were evaluated as natural coagulants for water treatment. The protein extracts were purified from crude extracts using a protein purifier, and protein concentrations were determined by the spectrophotometric method. Small-volume coagulation efficiency tests were conducted on raw water taken from the Legedadi water treatment plant. These were done using a completely randomized design (CRD) experiment with settling times of 0 min (initial time), 90 min, 180 min and 270 min and protein extract doses of 5 mg/L, 10 mg/L, 15 mg/L and 20 mg/L. Raw water as negative control and polyelectrolyte as positive control were also included. The optical density (OD) values were measured for all the samples. At 270 min and 20 mg/L, the coagulation efficiency percentages for Lupinus albus, Moringa stenopetala, Trigonella foenum-graecum and Vicia faba protein extracts were 71%, 89%, 12% and 67% in the water sample collected in April 2019 respectively. Similarly, Lupinus albus, Moringa stenopetala and Vicia faba achieved 17%, 92% and 12% at 270 min settling times and 5 mg/L, 20 mg/L and 10 mg/L concentration in the water sample collected from August 2019, respectively. Negative control (raw water) and polyelectrolyte (positive control) were also 6 − 10% and 89 − 94% at 270 min settling time in April and August 2019, respectively. Among the four protein extracts, Moringa stenopetala showed the highest coagulation efficiency, similar to polyelectrolyte. This study concluded that Moringa stenopetala protein extract could be used as a natural coagulant for water purification in both sampling times.

Keywords: coagulation efficiency, extraction, natural coagulant, protein extract

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11120 New Kinetic Approach to the Enzymatic Hydrolysis of Proteins: A Case of Thermolysin-Catalyzed Albumin

Authors: Anna Trusek-Holownia, Andrzej Noworyta

Abstract:

Using an enzyme of known specificity the hydrolysis of protein was carried out in a controlled manner. The aim was to obtain oligopeptides being the so-called active peptides or their direct precursors. An original way of expression of the protein hydrolysis kinetics was introduced. Peptide bonds contained in the protein were recognized as a diverse-quality substrate for hydrolysis by the applied protease. This assumption was positively verified taking as an example the hydrolysis of albumin by thermolysin. Peptide linkages for this system should be divided into at least four groups. One of them is a group of bonds non-hydrolyzable by this enzyme. These that are broken are hydrolyzed at a rate that differs even by tens of thousands of times. Designated kinetic constants were k'F = 10991.4 L/g.h, k'M = 14.83L/g.h, k'S about 10-1 L/g.h for fast, medium and slow bonds, respectively. Moreover, a procedure for unfolding of the protein, conducive to the improved susceptibility to enzymatic hydrolysis (approximately three-fold increase in the rate) was proposed.

Keywords: peptide bond hydrolysis, kinetics, enzyme specificity, biologically active peptides

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11119 Performance Analysis of Bluetooth Low Energy Mesh Routing Algorithm in Case of Disaster Prediction

Authors: Asmir Gogic, Aljo Mujcic, Sandra Ibric, Nermin Suljanovic

Abstract:

Ubiquity of natural disasters during last few decades have risen serious questions towards the prediction of such events and human safety. Every disaster regardless its proportion has a precursor which is manifested as a disruption of some environmental parameter such as temperature, humidity, pressure, vibrations and etc. In order to anticipate and monitor those changes, in this paper we propose an overall system for disaster prediction and monitoring, based on wireless sensor network (WSN). Furthermore, we introduce a modified and simplified WSN routing protocol built on the top of the trickle routing algorithm. Routing algorithm was deployed using the bluetooth low energy protocol in order to achieve low power consumption. Performance of the WSN network was analyzed using a real life system implementation. Estimates of the WSN parameters such as battery life time, network size and packet delay are determined. Based on the performance of the WSN network, proposed system can be utilized for disaster monitoring and prediction due to its low power profile and mesh routing feature.

Keywords: bluetooth low energy, disaster prediction, mesh routing protocols, wireless sensor networks

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11118 Numerical Approach of RC Structural MembersExposed to Fire and After-Cooling Analysis

Authors: Ju-young Hwang, Hyo-Gyoung Kwak, Hong Jae Yim

Abstract:

This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical non-linearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, Prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC structures, heat transfer analysis, nonlinear analysis, after-cooling concrete model

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11117 Intelligent Earthquake Prediction System Based On Neural Network

Authors: Emad Amar, Tawfik Khattab, Fatma Zada

Abstract:

Predicting earthquakes is an important issue in the study of geography. Accurate prediction of earthquakes can help people to take effective measures to minimize the loss of personal and economic damage, such as large casualties, destruction of buildings and broken of traffic, occurred within a few seconds. United States Geological Survey (USGS) science organization provides reliable scientific information of Earthquake Existed throughout history & Preliminary database from the National Center Earthquake Information (NEIC) show some useful factors to predict an earthquake in a seismic area like Aleutian Arc in the U.S. state of Alaska. The main advantage of this prediction method that it does not require any assumption, it makes prediction according to the future evolution of object's time series. The article compares between simulation data result from trained BP and RBF neural network versus actual output result from the system calculations. Therefore, this article focuses on analysis of data relating to real earthquakes. Evaluation results show better accuracy and higher speed by using radial basis functions (RBF) neural network.

Keywords: BP neural network, prediction, RBF neural network, earthquake

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11116 Hybrid Wavelet-Adaptive Neuro-Fuzzy Inference System Model for a Greenhouse Energy Demand Prediction

Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

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Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

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11115 N-Glycosylation in the Green Microalgae Chlamydomonas reinhardtii

Authors: Pierre-Louis Lucas, Corinne Loutelier-Bourhis, Narimane Mati-Baouche, Philippe Chan Tchi-Song, Patrice Lerouge, Elodie Mathieu-Rivet, Muriel Bardor

Abstract:

N-glycosylation is a post-translational modification taking place in the Endoplasmic Reticulum and the Golgi apparatus where defined glycan features are added on protein in a very specific sequence Asn-X-Thr/Ser/Cys were X can be any amino acid except proline. Because it is well-established that those N-glycans play a critical role in protein biological activity, protein half-life and that a different N-glycan structure may induce an immune response, they are very important in Biopharmaceuticals which are mainly glycoproteins bearing N-glycans. From now, most of the biopharmaceuticals are produced by mammalian cells like Chinese Hamster Ovary cells (CHO) for their N-glycosylation similar to the human, but due to the high production costs, several other species are investigated as the possible alternative system. In this purpose, the green microalgae Chlamydomonas reinhardtii was investigated as the potential production system for Biopharmaceuticals. This choice was influenced by the facts that C. reinhardtii is a well-study microalgae which is growing fast with a lot of molecular biology tools available. This organism is also producing N-glycan on its endogenous proteins. However, the analysis of the N-glycan structure of this microalgae has revealed some differences as compared to the human. Rather than in Human where the glycans are processed by key enzymes called N-acetylglucosaminyltransferase I and II (GnTI and GnTII) adding GlcNAc residue to form a GlcNAc₂Man₃GlcNAc₂ core N-glycan, C. reinhardtii lacks those two enzymes and possess a GnTI independent glycosylation pathway. Moreover, some enzymes like xylosyltransferases and methyltransferases not present in human are supposed to act on the glycans of C. reinhardtii. Furthermore, the recent structural study by mass spectrometry shows that the N-glycosylation precursor supposed to be conserved in almost all eukaryotic cells results in a linear Man₅GlcNAc₂ rather than a branched one in C. reinhardtii. In this work, we will discuss the new released MS information upon C. reinhardtii N-glycan structure and their impact on our attempt to modify the glycan in a Human manner. Two strategies will be discussed. The first one consisted in the study of Xylosyltransferase insertional mutants from the CLIP library in order to remove xyloses from the N-glycans. The second will go further in the humanization by transforming the microalgae with the exogenous gene from Toxoplasma gondii having an activity similar to GnTI and GnTII with the aim to synthesize GlcNAc₂Man₃GlcNAc₂ in C. reinhardtii.

Keywords: Chlamydomonas reinhardtii, N-glycosylation, glycosyltransferase, mass spectrometry, humanization

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11114 Determination of Biomolecular Interactions Using Microscale Thermophoresis

Authors: Lynn Lehmann, Dinorah Leyva, Ana Lazic, Stefan Duhr, Philipp Baaske

Abstract:

Characterization of biomolecular interactions, such as protein-protein, protein-nucleic acid or protein-small molecule, provides critical insights into cellular processes and is essential for the development of drug diagnostics and therapeutics. Here we present a novel, label-free, and tether-free technology to analyze picomolar to millimolar affinities of biomolecular interactions by Microscale Thermophoresis (MST). The entropy of the hydration shell surrounding molecules determines thermophoretic movement. MST exploits this principle by measuring interactions using optically generated temperature gradients. MST detects changes in the size, charge and hydration shell of molecules and measures biomolecule interactions under close-to-native conditions: immobilization-free and in bioliquids of choice, including cell lysates and blood serum. Thus, MST measures interactions under close-to-native conditions, and without laborious sample purification. We demonstrate how MST determines the picomolar affinities of antibody::antigen interactions, and protein::protein interactions measured from directly from cell lysates. MST assays are highly adaptable to fit to the diverse requirements of different and complex biomolecules. NanoTemper´s unique technology is ideal for studies requiring flexibility and sensitivity at the experimental scale, making MST suitable for basic research investigations and pharmaceutical applications.

Keywords: biochemistry, biophysics, molecular interactions, quantitative techniques

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11113 Effect of Different Processing Methods on the Quality Attributes of Pigeon Pea Used in Bread Production

Authors: B. F. Olanipekun, O. J. Oyelade, C. O. Osemobor

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Pigeon pea is a very good source of protein and micronutrient, but it is being underutilized in Nigeria because of several constraints. This research considered the effect of different processing methods on the quality attributes of pigeon pea used in bread production towards enhancing its utility. Pigeon pea was obtained at a local market and processed into the flour using three processing methods: soaking, sprouting and roasting and were used to bake bread in different proportions. Chemical composition and sensory attributes of the breads were thereafter determined. The highest values of protein and ash contents were obtained from 20 % substitution of sprouted pigeon pea in wheat flour and may be attributable to complex biochemical changes occurring during hydration, to invariably lead to protein constituent being broken down. Hydrolytic activities of the enzymes from the sprouted sample resulted in improvement in the constituent of total protein probably due to reduction in the carbohydrate content. Sensory qualities analyses showed that bread produced with soaked and roasted pigeon pea flours at 5 and 10% inclusion, respectively were mostly accepted than other blends, and products with sprouted pigeon pea flour were least accepted. The findings of this research suggest that supplementing wheat flour with sprouted pigeon peas have more nutritional potentials. However, with sensory analysis indices, the soaked and roasted pigeon peas up to 10% are majorly accepted, and also can improve the nutritional status. Overall, this will be very beneficial to population dependent on plant protein in order to combat malnutrition problems.

Keywords: pigeon pea, processing, protein, malnutrition

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11112 Effect of Many Levels of Undegradable Protein on Performance, Blood Parameters, Colostrum Composition and Lamb Birth Weight in Pregnant Ewes

Authors: Maria Magdy Danial Riad

Abstract:

The objective of this study was to investigate the effect of different protein sources with different degradability ratios during late gestation of ewes on colostrum composition, and its IgG concentration, body weight change of dams, and birth weight of their lambs. Objectives: 35 multiparous native crossbred ewes (BW= 59±2.5kg) were randomly allocated to five dietary treatments (7 ewes / treatment) for 2 months prior to lambing. Methods: Experimental diets were isonitrogenous (12.27% CP) and isocaloric (2.22 Mcal ME/kg DM). In diet I (the control), solvent extract soybeans (SESM 33% RUP of CP), II feed grade urea (FGU 31% RUP), III slow release urea (SRU 31% RUP). As sources of undegradable protein, extruded expeller SBM-EESM 40 (37% RUP) and extruded expeller SBM-EESM 60 (41% RUP) were used in groups IV and V, respectively. Results showed no significant effect on feed intake, crude protein (CP), or metabolizable energy (ME), and body condition score (BCS). Ewes fed the 37% RUP diet gained more (p<0.05) weight compared with ewes fed the 31% RUP diet (5.62 vs. 2.5kg). Ewes in EESM 60 had the highest levels of fat, protein, total solid, solid not fat, and immunoglobulin and the lowest in urea N content (P< 0.05) in colostrum during the first 24hrs after lambing. Conclusions: Protein source and RUP levels in ewes’ diets had no significant effect (P< 0.05) on lambs’ birth weight and ewes blood biochemical parameters. Increasing the RUP content of diet during late gestation resulted in an increase in colostrum constituents and its IgG level but had no effect on ewes’ performance and their lambs’ outcome.

Keywords: colostrum, ewes, lambs output, pregnancy, undegradable protein

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11111 Nonlinear Estimation Model for Rail Track Deterioration

Authors: M. Karimpour, L. Hitihamillage, N. Elkhoury, S. Moridpour, R. Hesami

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Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work for a long period of time. Generally, maintenance monitoring and prediction is conducted manually. With the restrictions in economy, the rail transport authorities are in pursuit of improved modern methods, which can provide precise prediction of rail maintenance time and location. The expectation from such a method is to develop models to minimize the human error that is strongly related to manual prediction. Such models will help them in understanding how the track degradation occurs overtime under the change in different conditions (e.g. rail load, rail type, rail profile). They need a well-structured technique to identify the precise time that rail tracks fail in order to minimize the maintenance cost/time and secure the vehicles. The rail track characteristics that have been collected over the years will be used in developing rail track degradation prediction models. Since these data have been collected in large volumes and the data collection is done both electronically and manually, it is possible to have some errors. Sometimes these errors make it impossible to use them in prediction model development. This is one of the major drawbacks in rail track degradation prediction. An accurate model can play a key role in the estimation of the long-term behavior of rail tracks. Accurate models increase the track safety and decrease the cost of maintenance in long term. In this research, a short review of rail track degradation prediction models has been discussed before estimating rail track degradation for the curve sections of Melbourne tram track system using Adaptive Network-based Fuzzy Inference System (ANFIS) model.

Keywords: ANFIS, MGT, prediction modeling, rail track degradation

Procedia PDF Downloads 292