Search results for: bioinformatics pipeline

Authors: Frida Carrillo Morales, Maria Maricela Carrasco Yépez, Saúl Rojas Hernández

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Naegleria fowleri is the causative agent of primary amebic meningoencephalitis, this disease is acute and fulminant that affects humans. It has been reported that despite the existence of therapeutic options against this disease, its mortality rate is 97%. Therefore, the need arises to have vaccines that confer protection against this disease and, in addition to developing adjuvants to enhance the immune response. In this regard, in our work group, we obtained a peptide designed from the membrane protein MP2CL5 of Naegleria fowleri called Smp145 that was shown to be immunogenic; however, it would be of great importance to enhance its immunological response, being able to co-administer it with a non-toxic adjuvant. Therefore, the objective of this work was to carry out the bioinformatic design of a peptide of the Naegleria fowleri membrane protein MP2CL5 conjugated with a non-toxic modified adjuvant from the native A1 structure of Cholera Toxin. For which different bioinformatics tools were used to obtain a model with a modification in amino acid 61 of the A1 subunit of the CT (CTA1), to which the Smp145 peptide was added and both molecules were joined with a 13-glycine linker. As for the results obtained, the modification in CTA1 bound to the peptide produces a reduction in the toxicity of the molecule in in silico experiments, likewise, the prediction in the binding of Smp145 to the receptor of B cells suggests that the molecule is directed in specifically to the BCR receptor, decreasing its native enzymatic activity. The stereochemical evaluation showed that the generated model has a high number of adequately predicted residues. In the ERRAT test, the confidence with which it is possible to reject regions that exceed the error values was evaluated, in the generated model, a high score was obtained, which determines that the model has a good structural resolution. Therefore, the design of the conjugated peptide in this work will allow us to proceed with its chemical synthesis and subsequently be able to use it in the mouse meningitis protection model caused by N. fowleri.

Keywords: immunology, vaccines, pathogens, infectious disease

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Authors: Iyd Eqqab Maree, Moouyad Ibrahim Abbood

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The purpose behind this study is to predict damping effect for steel cantilever beam by using two methods of passive viscoelastic constrained layer damping. First method is Matlab Program, this method depend on the Ross, Kerwin and Unger (RKU) model for passive viscoelastic damping. Second method is experimental lab (frequency domain method), in this method used the half-power bandwidth method and can be used to determine the system loss factors for damped steel cantilever beam. The RKU method has been applied to a cantilever beam because beam is a major part of a structure and this prediction may further leads to utilize for different kinds of structural application according to design requirements in many industries. In this method of damping a simple cantilever beam is treated by making sandwich structure to make the beam damp, and this is usually done by using viscoelastic material as a core to ensure the damping effect. The use of viscoelastic layers constrained between elastic layers is known to be effective for damping of flexural vibrations of structures over a wide range of frequencies. The energy dissipated in these arrangements is due to shear deformation in the viscoelastic layers, which occurs due to flexural vibration of the structures. The theory of dynamic stability of elastic systems deals with the study of vibrations induced by pulsating loads that are parametric with respect to certain forms of deformation. There is a very good agreement of the experimental results with the theoretical findings. The main ideas of this thesis are to find the transition region for damped steel cantilever beam (4mm and 8mm thickness) from experimental lab and theoretical prediction (Matlab R2011a). Experimentally and theoretically proved that the transition region for two specimens occurs at modal frequency between mode 1 and mode 2, which give the best damping, maximum loss factor and maximum damping ratio, thus this type of viscoelastic material core (3M468) is very appropriate to use in automotive industry and in any mechanical application has modal frequency eventuate between mode 1 and mode 2.

Keywords: 3M-468 material core, loss factor and frequency, domain method, bioinformatics, biomedicine, MATLAB

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Authors: Misty Attwood, Helgi Schioth

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Transmembrane proteins are important components in many essential cell processes such as signal transduction, cell-cell signalling, transport of solutes, structural adhesion activities, and protein trafficking. Due to their involvement in diverse critical activities, transmembrane proteins are implicated in different disease pathways and hence are the focus of intense interest in understanding functional activities, their pathogenesis in disease, and their potential as pharmaceutical targets. Further, as the structure and function of proteins are correlated, investigating a group of proteins with the same tertiary structure, i.e., the same number of transmembrane regions, may give understanding about their functional roles and potential as therapeutic targets. In this in silico bioinformatics analysis, we identify and comprehensively characterize the previously unstudied group of proteins with five transmembrane-spanning regions (5TM). We classify nearly 60 5TM proteins in which 31 are members of ten families that contain two or more family members and all members are predicted to contain the 5TM architecture. Furthermore, nine singlet proteins that contain the 5TM architecture without paralogues detected in humans were also identifying, indicating the evolution of single unique proteins with the 5TM structure. Interestingly, more than half of these proteins function in localization activities through movement or tethering of cell components and more than one-third are involved in transport activities, particularly in the mitochondria. Surprisingly, no receptor activity was identified within this family in sharp contrast with other TM families. Three major 5TM families were identified and include the Tweety family, which are pore-forming subunits of the swelling-dependent volume regulated anion channel in astrocytes; the sidoreflexin family that acts as mitochondrial amino acid transporters; and the Yip1 domain family engaged in vesicle budding and intra-Golgi transport. About 30% of the proteins have enhanced expression in the brain, liver, or testis. Importantly, 60% of these proteins are identified as cancer prognostic markers, where they are associated with clinical outcomes of various tumour types, indicating further investigation into the function and expression of these proteins is important. This study provides the first comprehensive analysis of proteins with 5TM regions and provides details of the unique characteristics and application in pharmaceutical development.

Keywords: 5TM, cancer prognostic marker, drug targets, transmembrane protein

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Authors: Anil Kumar, Diwakar Aggarwal, M. Sudhakara Reddy

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The wood of Eucalyptus, Populus and bamboos are some important species used as raw material for the manufacture of pulp. However, higher levels of lignin pose a problem during Kraft pulping and yield of pulp is also lower. In order to increase the yield of pulp per unit wood and reduce the use of chemicals during kraft pulping it is important to reduce the lignin content and/or increase cellulose content in wood. Cellulose biosynthesis in wood takes place by the coordinated action of many enzymes. The two important enzymes are KORRIGAN and SUCROSE SYNTHASE. KORRIGAN (Endo-1,4--glucanase) is implicated in the process of editing growing cellulose chains and improvement of the crystallinity of produced cellulose, whereas SUCROSE SYNTHASE is involved in providing substrate (UDP-glucose) for growing cellulose chains. The present study was aimed at the cloning, characterization and overexpression of these genes in Eucalyptus and Populus. An efficient shoot organogenesis protocol from leaf explants taken from micro shoots of the species has been developed. Agrobacterium mediated genetic transformation using Agrobacterium tumefaciens strain EHA105 and LBA4404 harboring binary vector pBI121 was achieved. Both the genes were cloned from cDNA library of Populus deltoides. These were subsequently characterized using various bioinformatics tools. The cloned genes were then inserted into pBI121 under the CaMV35S promotors replacing GUS gene. The constructs were then mobilized into above strains of Agrobacterium and used for the transformation work. Subsequently, genetic transformation of these clones with target genes following already developed protocol is in progress. Four transgenic lines of Eucalyptus tereticornis overexpressing Korrigan gene under the strong constitutive promoters CaMV35S have been developed, which are being further evaluated. Work on development of more transgenic lines overexpressing these genes in Populus and Eucalyptus is also in progress. This presentation will focus on important developments in this direction.

Keywords: Eucalyptus tereticornis, genetic transformation, Kraft pulping Populus deltoides

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Authors: Sonika Raj, Amarjeet Singh, Vijay Lakshmi Sharma

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Introduction: In 21st century, due to revolution in Information and Communication Technologies (ICTs), there has been phenomenal development in quality and quantity of knowledge in the field of medical science. So, the access to relevant information to physicians is critical to the delivery of effective healthcare services to patients. The study was conducted to assess the information needs and attitudes of the medical professionals; to determine the sources and channels of information used by them; to ascertain the current usage of ICTs and the barriers faced by them in utilization of ICTs in health information access. Methodology: This descriptive cross-sectional study was carried in 2015 on hundred medical professionals working in public and private sectors of Chandigarh. The study used both quantitative and qualitative method for data collection. A semi structured questionnaire and interview schedule was used to collect data on information seeking needs, access to ICTs and barriers to healthcare information access. Five Data analysis was done using SPSS-16 and qualitative data was analyzed using thematic approach. Results: The most preferred sources to access healthcare information were internet (85%), trainings (61%) and communication with colleagues (57%). They wanted information on new drug therapy and latest developments in respective fields. All had access to computer with but almost half assessed their computer knowledge as average and only 3% had received training regarding usage. Educational status (p=0.004), place of work (p=0.004), number of years in job (p=0.004) and sector of job (p=0.04) of doctors were found to be significantly associated with their active search for information. The major themes that emerged from in-views were need; types and sources of healthcare information; exchange of information among different levels of healthcare providers; usage of ICTs to obtain and share information; barriers to access of healthcare information and quality of health information materials and involvement in their development process Conclusion and Recommendations: The medical professionals need information in their in their due course of work. However, information needs of medical professionals were not being adequately met. There should be training of professional regarding internet skills and the course on bioinformatics should be incorporated in the curricula of medical students. The policy framework must be formulated that will encourage and promote the use of ICTs as tools for health information access and dissemination.

Keywords: health information, ICTs, medical professionals, qualitative

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Authors: Tobias Milz, L. Macpherson, Varvara Vetrova

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The law is a fundamental pillar of human societies as it shapes, controls and governs how humans conduct business, behave and interact with each other. Recent advances in computer-assisted technologies such as NLP, data science and AI are creating opportunities to support the practice, research and study of this pervasive domain. It is therefore not surprising that there has been an increase in investments into supporting technologies for the legal industry (also known as “legal tech” or “law tech”) over the last decade. A sub-discipline of particular appeal is concerned with assisted legal research. Supporting law researchers and practitioners to retrieve information from the vast amount of ever-growing legal documentation is of natural interest to the legal research community. One tool that has been in use for this purpose since the early nineteenth century is legal citation indexing. Among other use cases, they provided an effective means to discover new precedent cases. Nowadays, computer-assisted network analysis tools can allow for new and more efficient ways to reveal the “hidden” information that is conveyed through citation behavior. Unfortunately, access to openly available legal data is still lacking in New Zealand and access to such networks is only commercially available via providers such as LexisNexis. Consequently, there is a need to create, analyze and provide a legal citation network with sufficient data to support legal research tasks. This paper describes the development and analysis of a legal citation Network for New Zealand containing over 300.000 decisions from 125 different courts of all areas of law and jurisdiction. Using python, the authors assembled web crawlers, scrapers and an OCR pipeline to collect and convert court decisions from openly available sources such as NZLII into uniform and machine-readable text. This facilitated the use of regular expressions to identify references to other court decisions from within the decision text. The data was then imported into a graph-based database (Neo4j) with the courts and their respective cases represented as nodes and the extracted citations as links. Furthermore, additional links between courts of connected cases were added to indicate an indirect citation between the courts. Neo4j, as a graph-based database, allows efficient querying and use of network algorithms such as PageRank to reveal the most influential/most cited courts and court decisions over time. This paper shows that the in-degree distribution of the New Zealand legal citation network resembles a power-law distribution, which indicates a possible scale-free behavior of the network. This is in line with findings of the respective citation networks of the U.S. Supreme Court, Austria and Germany. The authors of this paper provide the database as an openly available data source to support further legal research. The decision texts can be exported from the database to be used for NLP-related legal research, while the network can be used for in-depth analysis. For example, users of the database can specify the network algorithms and metrics to only include specific courts to filter the results to the area of law of interest.

Keywords: case citation network, citation analysis, network analysis, Neo4j

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Authors: Blanca A. Pichardo, Victor H. Lopez, Melchor Salazar, Rafael Garcia, Alberto Ruiz

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Clad pipes in comparison to plain carbon steel pipes offer the oil and gas industry high corrosion resistance, reduction in economic losses due to pipeline failures and maintenance, lower labor risk, prevent pollution and environmental damage due to hydrocarbons spills caused by deteriorated pipelines. In this context, it is paramount to establish reliable welding procedures to join bimetallic plates or pipes. Thus, the aim of this work is to study the microstructure and mechanical behavior of clad plates welded by the gas metal arc welding (GMAW) process. A clad of 316L stainless steel was deposited onto API 5L X-60 plates by overlay welding with the GMAW process. Welding parameters were, 22.5 V, 271 A, heat input 1,25 kJ/mm, shielding gas 98% Ar + 2% O₂, reverse polarity, torch displacement speed 3.6 mm/s, feed rate 120 mm/s, electrode diameter 1.2 mm and application of an electromagnetic field of 3.5 mT. The overlay welds were subjected to macro-structural and microstructural characterization. After manufacturing the clad plates, a single V groove joint was machined with a 60° bevel and 1 mm root face. GMA welding of the bimetallic plates was performed in four passes with ER316L-Si filler for the root pass and an ER70s-6 electrode for the subsequent welding passes. For joining the clad plates, an electromagnetic field was applied with 2 purposes; to improve the microstructural characteristics and to assist the stability of the electric arc during welding in order to avoid magnetic arc blow. The welds were macro and microstructurally characterized and the mechanical properties were also evaluated. Vickers microhardness (100 g load for 10 s) measurements were made across the welded joints at three levels. The first profile, at the 316L stainless steel cladding, was quite even with a value of approximately 230 HV. The second microhardness profile showed high values in the weld metal, ~400 HV, this was due to the formation of a martensitic microstructure by dilution of the first welding pass with the second. The third profile crossed the third and fourth welding passes and an average value of 240 HV was measured. In the tensile tests, yield strength was between 400 to 450 MPa with a tensile strength of ~512 MPa. In the Charpy impact tests, the results were 86 and 96 J for specimens with the notch in the face and in the root of the weld bead, respectively. The results of the mechanical properties were in the range of the API 5L X-60 base material. The overlap welding process used for cladding is not suitable for large components, however, it guarantees a metallurgical bond, unlike the most commonly used processes such as thermal expansion. For welding bimetallic plates, control of the temperature gradients is key to avoid distortions. Besides, the dissimilar nature of the bimetallic plates gives rise to the formation of a martensitic microstructure during welding.

Keywords: clad pipe, dissimilar welding, gas metal arc welding, magnetic fields

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Authors: Vivian A. Panes, Raymond John S. Rebong, Miel Q. Diaz

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Moringa oleifera Lam. is known mainly for its high nutritional value and medicinal properties contributing to its popular reputation as a 'miracle plant' in the tropical climates where it usually grows. The main objective of this study is to discover the genes and gene products involved in abiotic stress-induced activity that may impact the M. oleifera Lam. mature seeds as well as their corresponding functions. In this study, RNA-sequencing and de novo transcriptome assembly were performed using two assemblers, Trinity and Oases, which produced 177,417 and 120,818 contigs respectively. These transcripts were then subjected to various bioinformatics tools such as Blast2GO, UniProt, KEGG, and COG for gene annotation and the analysis of relevant metabolic pathways. Furthermore, FPKM analysis was performed to identify gene expression levels. The sequences were filtered according to the 'response to stress' GO term since this study dealt with stress response. Clustered Orthologous Groups (COG) showed that the highest frequencies of stress response gene functions were those of cytoskeleton which make up approximately 14% and 23% of stress-related sequences under Trinity and Oases respectively, recombination, repair and replication at 11% and 14% respectively, carbohydrate transport and metabolism at 23% and 9% respectively and defense mechanisms 16% and 12% respectively. KEGG pathway analysis determined the most abundant stress-response genes in the phenylpropanoid biosynthesis at counts of 187 and 166 pathways for Oases and Trinity respectively, purine metabolism at 123 and 230 pathways, and biosynthesis of antibiotics at 105 and 102. Unique and cumulative GO term counts revealed that majority of the stress response genes belonged to the category of cellular response to stress at cumulative counts of 1,487 to 2,187 for Oases and Trinity respectively, defense response at 754 and 1,255, and response to heat at 213 and 208, response to water deprivation at 229 and 228, and oxidative stress at 508 and 488. Lastly, FPKM was used to determine the levels of expression of each stress response gene. The most upregulated gene encodes for thiamine thiazole synthase chloroplastic-like enzyme which plays a significant role in DNA damage tolerance. Data analysis implies that M. oleifera stress response genes are directed towards the effects of climate change more than other stresses indicating the potential of M. oleifera for cultivation in harsh environments because it is resistant to climate change, pathogens, and foreign invaders.

Keywords: stress response, genes, Moringa oleifera, transcriptomics

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Authors: Khethiwe Mtshali, Zamantungwa T. H. Khumalo, Stanford Kwenda, Ismail Arshad, Oriel M. M. Thekisoe

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Ecologically, the gut, mammary glands and bloodstream consist of distinct microbial communities of commensals, mutualists and pathogens, forming a complex ecosystem of niches. The by-products derived from these body sites i.e. faeces, milk and blood, respectively, have many uses in rural communities where they aid in the facilitation of day-to-day household activities and occasional rituals. Thus, although livestock rearing plays a vital role in the sustenance of the livelihoods of rural communities, it may serve as a potent reservoir of different pathogenic organisms that could have devastating health and economic implications. This study aimed to simultaneously explore the microbial profiles of corresponding faecal, milk and blood samples from lactating cows using 16S rRNA metagenomic sequencing. Bacterial communities were inferred through the Divisive Amplicon Denoising Algorithm 2 (DADA2) pipeline coupled with SILVA database v138. All downstream analyses were performed in R v3.6.1. Alpha-diversity metrics showed significant differences between faeces and blood, faeces and milk, but did not vary significantly between blood and milk (Kruskal-Wallis, P < 0.05). Beta-diversity metrics on Principal Coordinate Analysis (PCoA) and Non-Metric Dimensional Scaling (NMDS) clustered samples by type, suggesting that microbial communities of the studied niches are significantly different (PERMANOVA, P < 0.05). A number of taxa were significantly differentially abundant (DA) between groups based on the Wald test implemented in the DESeq2 package (Padj < 0.01). The majority of the DA taxa were significantly enriched in faeces than in milk and blood, except for the genus Anaplasma, which was significantly enriched in blood and was, in turn, the most abundant taxon overall. A total of 30 phyla, 74 classes, 156 orders, 243 families and 408 genera were obtained from the overall analysis. The most abundant phyla obtained between the three body sites were Firmicutes, Bacteroidota, and Proteobacteria. A total of 58 genus-level taxa were simultaneously detected between the sample groups, while bacterial signatures of at least 8 of these occurred concurrently in corresponding faeces, milk and blood samples from the same group of animals constituting a pool. The important taxa identified in this study could be categorized into four potentially pathogenic clusters: i) arthropod-borne; ii) food-borne and zoonotic; iii) mastitogenic and; iv) metritic and abortigenic. This study provides insight into the microbial composition of bovine faeces, milk, and blood and its extent of overlapping. It further highlights the potential risk of disease occurrence and transmission between the animals and the inhabitants of the sampled rural community, pertaining to their unsanitary practices associated with the use of cattle by-products.

Keywords: microbial profiling, 16S rRNA, NGS, feces, milk, blood, lactating cows, small-scale farmers

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Authors: Mohammed Abdullah Alshahrani

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The research focuses on investigating the use of partial least squares (PLS) methodology for addressing challenges associated with high-dimensional correlated data. Recent technological advancements have led to experiments producing data characterized by a large number of variables compared to observations, with substantial inter-variable correlations. Such data patterns are common in chemometrics, where near-infrared (NIR) spectrometer calibrations record chemical absorbance levels across hundreds of wavelengths, and in genomics, where thousands of genomic regions' copy number alterations (CNA) are recorded from cancer patients. PLS serves as a widely used method for analyzing high-dimensional data, functioning as a regression tool in chemometrics and a classification method in genomics. It handles data complexity by creating latent variables (components) from original variables. However, applying PLS can present challenges. The study investigates key areas to address these challenges, including unifying interpretations across three main PLS algorithms and exploring unusual negative shrinkage factors encountered during model fitting. The research presents an alternative approach to addressing the interpretation challenge of predictor weights associated with PLS. Sparse estimation of predictor weights is employed using a penalty function combining a lasso penalty for sparsity and a Cauchy distribution-based penalty to account for variable dependencies. The results demonstrate sparse and grouped weight estimates, aiding interpretation and prediction tasks in genomic data analysis. High-dimensional data scenarios, where predictors outnumber observations, are common in regression analysis applications. Ordinary least squares regression (OLS), the standard method, performs inadequately with high-dimensional and highly correlated data. Copy number alterations (CNA) in key genes have been linked to disease phenotypes, highlighting the importance of accurate classification of gene expression data in bioinformatics and biology using regularized methods like PLS for regression and classification.

Keywords: partial least square regression, genetics data, negative filter factors, high dimensional data, high correlated data

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Authors: Maria Lopez-Ibarra, Ana Velazquez-Wong, Lucelli Yañez-Gutierrez, Maria Araujo-Solis, Fabio Salamanca-Gomez, Alfonso Mendez-Tenorio, Haydeé Rosas-Vargas

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Congenital heart diseases (CHD) are the most common congenital abnormalities. These conditions can occur as both an element of distinct chromosomal malformation syndromes or as non-syndromic forms. Their etiology is not fully understood. Genetic variants such copy number variants have been associated with CHD. The aim of our study was to analyze these genomic variants in peripheral blood from Mexican children diagnosed with non-syndromic CHD. We included 16 children with atrial and ventricular septal defects and 5 healthy subjects without heart malformations as controls. To exclude the most common heart disease-associated syndrome alteration, we performed a fluorescence in situ hybridization test to identify the 22q11.2, responsible for congenital heart abnormalities associated with Di-George Syndrome. Then, a microarray based comparative genomic hybridization was used to identify global copy number variants. The identification of copy number variants resulted from the comparison and analysis between our results and data from main genetic variation databases. We identified copy number variants gain in three chromosomes regions from pediatric patients, 4q13.2 (31.25%), 9q34.3 (25%) and 20q13.33 (50%), where several genes associated with cellular, biosynthetic, and metabolic processes are located, UGT2B15, UGT2B17, SNAPC4, SDCCAG3, PMPCA, INPP6E, C9orf163, NOTCH1, C20orf166, and SLCO4A1. In addition, after a hierarchical cluster analysis based on the fluorescence intensity ratios from the comparative genomic hybridization, two congenital heart disease groups were generated corresponding to children with atrial or ventricular septal defects. Further analysis with a larger sample size is needed to corroborate these copy number variants as possible biomarkers to differentiate between heart abnormalities. Interestingly, the 20q13.33 gain was present in 50% of children with these CHD which could suggest that alterations in both coding and non-coding elements within this chromosomal region may play an important role in distinct heart conditions.

Keywords: aCGH, bioinformatics, congenital heart diseases, copy number variants, fluorescence in situ hybridization

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Authors: Ridwaan N. Milase, Leonardo J. Van Zyl, Marla Trindade

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American foulbrood (AFB) is the world’s most devastating honeybee disease that has drastically reduced the population of Apis mellifera capensis since 2009. The outbreak has jeopardized the South African bee keeping industry as well as the agricultural sector dependent on honeybees for honey production and pollination, leading to significant economic losses. AFB is caused by Paenibacillus larvae, a spore-forming, Gram positive facultative anaerobic and flagellated bacterium. The use of antibiotics within beehives has selected for resistant strains of P. larvae, while the current practice of burning spore contaminated beehives and equipment contributes to the economic losses in the honeybee-keeping industry. Therefore, phage therapy is proposed as a promising alternative to combat P. larvae strains affecting A. mellifera capensis. The genomes of two P. larvae strains isolated from infected combs in the Western Cape have been sequenced and annotated using bioinformatics tools. Genome analyses has revealed that these P. larvae strains are lysogens to more than 6 different prophages and possess different type of clustered regularly interspaced short palindromic repeat (CRISPRs) regions per strain. Active prophages from one of the two P. larvae strains were detected and identified using PCR. Electron microscopy was used to determine the family of the identified active prophages. Lytic bacteriophages that specifically target the two P. larvae strains were purified from sewage wastewater, beehive materials, and soil samples to investigate their potential development as anti-P. larvae agents. Another alternative treatment being investigated is the development of a prophage endolysin cocktail. Endolysin genes of the prophages have been targeted, cloned and expressed in Escherichia coli. The heterologously expressed endolysins have been purified and are currently being assessed for their lytic activity against P. larvae strains and other commensal microorganisms that compose the honeybee larvae microbiota. The study has shown that phage therapy and endolysins have a great potential as alternative control methods for AFB disease affecting A. mellifera capensis.

Keywords: American foulbrood, bacteriophage, honeybee, Paenibacillus larvae

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Authors: Debarpita Pande

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On 22nd May 2013 Chinese Premier Li Keqiang on his visit to Pakistan tabled a proposal for connecting Kashgar in China’s Xinjiang Uygur Autonomous Region with the south-western Pakistani seaport of Gwadar via the China Pakistan Economic Corridor (hereinafter referred to as CPEC). The project, popularly termed as 'One Belt One Road' will encompass within it a connectivity component including a 3000-kilometre road, railways and oil pipeline from Kashgar to Gwadar port along with an international airport and a deep sea port. Superficially, this may look like a 'game changer' for Pakistan and other countries of South Asia but this article by doctrinal method of research will unearth some serious flaws in it, which may change the entire economic system of this region heavily affecting the socio-economic conditions of South Asia, further complicating the complete geopolitical situation of the region disturbing the world economic stability. The paper besets with a logical analyzation of the socio-economic issues arising out of this project with an emphasis on its impact on the Pakistani and Indian economy due to Chinese dominance, serious tension in international relations, security issues, arms race, political and provincial concerns. The research paper further aims to study the impact of huge burden of loan given by China towards this project where Pakistan already suffers from persistent debts in the face of declining foreign currency reserves along with that the sovereignty of Pakistan will also be at stake as the entire economy of the country will be held hostage by China. The author compares this situation with the fallout from projects in Sri Lanka, Tajikistan, and several countries of Africa, all of which are now facing huge debt risks brought by Chinese investments. The entire economic balance will be muddled by the increment in Pakistan’s demand of raw materials resulting to the import of the same from China, which will lead to exorbitant price-hike and limited availability. CPEC will also create Chinese dominance over the international movement of goods that will take place between the Atlantic and the Pacific oceans and hence jeopardising the entire economic balance of South Asia along with Middle Eastern countries like Dubai. Moreover, the paper also analyses the impact of CPEC in the context of international unrest and arms race between Pakistan and India as well as India and China due to border disputes and Chinese surveillance. The paper also examines the global change in economic dynamics in international trade that CPEC will create in the light of U.S.-China relationship. The article thus reflects the grave consequences of CPEC on the international economy, security and bilateral relations, which surpasses the positive impacts of it. The author lastly suggests for more transparency and proper diplomatic planning in the execution of this mega project, which can be a cause of economic complexity in international trade in near future.

Keywords: China, CPEC, international trade, Pakistan

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Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

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Authors: Wayde Veldman, Ozlem T. Bishop, Igor Polikarpov

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In bacteria, mono and disaccharides are phosphorylated during uptake into the cell via the widely used phosphoenolpyruvate (PEP)-dependent phosphotransferase transport system. As an initial step in the phosphorylated disaccharide metabolism pathway, certain glycoside hydrolase family 1 (GH1) enzymes play a crucial role in releasing phosphorylated and non-phosphorylated monosaccharides. However, structural determinants for the specificity of these enzymes still need to be clarified. GH1 enzymes are known to have a wide array of functions. According to the CAZy database, there are twenty-one different enzymatic activities in the GH1 family. Here, the structure and substrate specificity of a GH1 enzyme from Bacillus licheniformis, hereafter known as BlBglH, was investigated. The sequence of the enzyme BlBglH was compared to the sequences of other characterized GH1 enzymes using sequence alignment, sequence identity calculations, phylogenetic analysis, and motif discovery. Through these various analyses, BlBglH was found to have sequence features characteristic of the 6-phospho-β-glucosidase activity enzymes. Additionally, motif and structure comparisons of the three most commonly studied GH1 enzyme-activities revealed a shared loop amongst the different structures that consist of different sequence motifs – this loop is thought to guide specific substrates (depending on activity) towards the active-site. To further affirm BlBglH enzyme activity, molecular docking and molecular dynamics simulations were performed. Docking was carried out using 6-phospho-β-glucosidase enzyme-activity positive (p-Nitrophenyl-beta-D-glucoside-6-phosphate) and negative (p-Nitrophenyl-beta-D-galactoside-6-phosphate) control ligands, followed by 400 ns molecular dynamics simulations. The positive-control ligand maintained favourable interactions within the active site until the end of the simulation. The negative-control ligand was observed exiting the enzyme at 287 ns. Binding free energy calculations showed that the positive-control complex had a substantially more favourable binding energy compared to the negative-control complex. Jointly, the findings of this study suggest that the BlBglH enzyme possesses 6-phospho-β-glucosidase enzymatic activity.

Keywords: 6-P-β-glucosidase, glycoside hydrolase 1, molecular dynamics, sequence analysis, substrate specificity

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Authors: Carlos Herrera Sierralta, Husain M. Muslim, Meshal T. Alsaiari, Daniel Fischer

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Preventing piping fatigue flow induced vibration in the Oil & Gas sector demands not only the constant development of engineering design methodologies based on available software packages, but also special piping support technologies for designing safe and reliable piping systems. The vast majority of piping vibration problems in the Oil & Gas industry are provoked by the process flow characteristics which are basically intrinsically related to the fluid properties, the type of service and its different operational scenarios. In general, the corrective actions recommended for flow induced vibration in piping systems can be grouped in two major areas: those which affect the excitation mechanisms typically associated to process variables, and those which affect the response mechanism of the pipework per se, and the pipework associated steel support structure. Where possible the first option is to try to solve the flow induced problem from the excitation mechanism perspective. However, in producing facilities the approach of changing process parameters might not always be convenient as it could lead to reduction of production rates or it may require the shutdown of the system in order to perform the required piping modification. That impediment might lead to a second option, which is to modify the response of the piping system to excitation generated by the type of process flow. In principle, the action of shifting the natural frequency of the system well above the frequency inherent to the process always favours the elimination, or considerably reduces, the level of vibration experienced by the piping system. Tightening up the clearances at the supports (ideally zero gap), and adding new static supports at the system, are typical ways of increasing the natural frequency of the piping system. However, only stiffening the piping system may not be sufficient to resolve the vibration problem, and in some cases, it might not be feasible to implement it at all, as the available piping layout could create limitations on adding supports due to thermal expansion/contraction requirements. In these cases, utilization of viscous damper supports could be recommended as these devices can allow relatively large quasi-static movement of piping while providing sufficient capabilities of dissipating the vibration. Therefore, when correctly selected and installed, viscous damper supports can provide a significant effect on the response of the piping system over a wide range of frequencies. Viscous dampers cannot be used to support sustained, static loads. This paper shows over a real case example, a methodology which allows to determine the selection of the viscous damper supports via a dynamic analysis model. By implementing this methodology, it was possible to resolve the piping vibration problem throughout redesigning adequately the existing static piping supports and by adding new viscous dampers supports. This was conducted on-stream at the oil crude pipeline in question without the necessity of reducing the production of the plant. Concluding that the application of the methodology of this paper can be applied to solve similar cases in a straightforward manner.

Keywords: dynamic analysis, flow induced vibration, piping supports, turbulent flow, slug flow, viscous damper

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Authors: Anuj Tyagi, Balwinder Singh, Naveen Kumar B. T., Niraj K. Singh

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Characterization of diverse microbial communities in specific environment plays a crucial role in the better understanding of their functional relationship with the ecosystem. It is now well established that gut microbiome of fish is not the simple replication of microbiota of surrounding local habitat, and extensive species, dietary, physiological and metabolic variations in fishes may have a significant impact on its composition. Moreover, overuse of antibiotics in human, veterinary and aquaculture medicine has led to rapid emergence and propagation of antibiotic resistance genes (ARGs) in the aquatic environment. Microbial communities harboring specific ARGs not only get a preferential edge during selective antibiotic exposure but also possess the significant risk of ARGs transfer to other non-resistance bacteria within the confined environments. This phenomenon may lead to the emergence of habitat-specific microbial resistomes and subsequent emergence of virulent antibiotic-resistant pathogens with severe fish and consumer health consequences. In this study, gut microbiota of freshwater carp (Labeo rohita) was investigated by shotgun metagenomics to understand its taxonomic composition and functional capabilities. Metagenomic DNA, extracted from the fish gut, was subjected to sequencing on Illumina NextSeq to generate paired-end (PE) 2 x 150 bp sequencing reads. After the QC of raw sequencing data by Trimmomatic, taxonomic analysis by Kraken2 taxonomic sequence classification system revealed the presence of 36 phyla, 326 families and 985 genera in the fish gut microbiome. At phylum level, Proteobacteria accounted for more than three-fourths of total bacterial populations followed by Actinobacteria (14%) and Cyanobacteria (3%). Commonly used probiotic bacteria (Bacillus, Lactobacillus, Streptococcus, and Lactococcus) were found to be very less prevalent in fish gut. After sequencing data assembly by MEGAHIT v1.1.2 assembler and PROKKA automated analysis pipeline, pathway analysis revealed the presence of 1,608 Metacyc pathways in the fish gut microbiome. Biosynthesis pathways were found to be the most dominant (51%) followed by degradation (39%), energy-metabolism (4%) and fermentation (2%). Almost one-third (33%) of biosynthesis pathways were involved in the synthesis of secondary metabolites. Metabolic pathways for the biosynthesis of 35 antibiotic types were also present, and these accounted for 5% of overall metabolic pathways in the fish gut microbiome. Fifty-one different types of antibiotic resistance genes (ARGs) belonging to 15 antimicrobial resistance (AMR) gene families and conferring resistance against 24 antibiotic types were detected in fish gut. More than 90% ARGs in fish gut microbiome were against beta-lactams (penicillins, cephalosporins, penems, and monobactams). Resistance against tetracycline, macrolides, fluoroquinolones, and phenicols ranged from 0.7% to 1.3%. Some of the ARGs for multi-drug resistance were also found to be located on sequences of plasmid origin. The presence of pathogenic bacteria and ARGs on plasmid sequences suggested the potential risk due to horizontal gene transfer in the confined gut environment.

Keywords: antibiotic resistance, fish gut, metabolic pathways, microbial diversity

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Authors: Chen Wang, Jared Evans, Yan Asmann

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With the quick evolvement of next-generation sequencing techniques, whole-exome or exome-panel data have become a cost-effective way for detection of small exonic mutations, but there has been a growing desire to accurately detect copy number variations (CNVs) as well. In order to address this research and clinical needs, we developed a sequencing coverage pattern-based method not only for copy number detections, data integrity checks, CNV calling, and visualization reports. The developed methodologies include complete automation to increase usability, genome content-coverage bias correction, CNV segmentation, data quality reports, and publication quality images. Automatic identification and removal of poor quality outlier samples were made automatically. Multiple experimental batches were routinely detected and further reduced for a clean subset of samples before analysis. Algorithm improvements were also made to improve somatic CNV detection as well as germline CNV detection in trio family. Additionally, a set of utilities was included to facilitate users for producing CNV plots in focused genes of interest. We demonstrate the somatic CNV enhancements by accurately detecting CNVs in whole exome-wide data from the cancer genome atlas cancer samples and a lymphoma case study with paired tumor and normal samples. We also showed our efficient reuses of existing exome sequencing data, for improved germline CNV calling in a family of the trio from the phase-III study of 1000 Genome to detect CNVs with various modes of inheritance. The performance of the developed method is evaluated by comparing CNV calling results with results from other orthogonal copy number platforms. Through our case studies, reuses of exome sequencing data for calling CNVs have several noticeable functionalities, including a better quality control for exome sequencing data, improved joint analysis with single nucleotide variant calls, and novel genomic discovery of under-utilized existing whole exome and custom exome panel data.

Keywords: bioinformatics, computational genetics, copy number variations, data reuse, exome sequencing, next generation sequencing

Procedia PDF Downloads 257

Authors: Paula Costa, Ana Picado, Filomena Pinto, Justina Catarino

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Environmental impact associated with large scale shale gas development is of major concern to the public, policy makers and other stakeholders. To assess this impact on the atmosphere, it is important to monitoring ambient air quality prior to and during all shale gas operation stages. Baseline observations can provide a standard of the pre-shale gas development state of the environment. The lack of baseline concentrations was identified as an important knowledge gap to assess the impact of emissions to the air due to shale gas operations. In fact baseline monitoring of air quality are missing in several regions, where there is a strong possibility of future shale gas exploration. This makes it difficult to properly identify, quantify and characterize environmental impacts that may be associated with shale gas development. The implementation of a baseline air monitoring program is imperative to be able to assess the total emissions related with shale gas operations. In fact, any monitoring programme should be designed to provide indicative information on background levels. A baseline air monitoring program should identify and characterize targeted air pollutants, most frequently described from monitoring and emission measurements, as well as those expected from hydraulic fracturing activities, and establish ambient air conditions prior to start-up of potential emission sources from shale gas operations. This program has to be planned for at least one year accounting for ambient variations. In the literature, in addition to GHG emissions of CH4, CO2 and nitrogen oxides (NOx), fugitive emissions from shale gas production can release volatile organic compounds (VOCs), aldehydes (formaldehyde, acetaldehyde) and hazardous air pollutants (HAPs). The VOCs include a.o., benzene, toluene, ethyl benzene, xylenes, hexanes, 2,2,4-trimethylpentane, styrene. The concentrations of six air pollutants (ozone, particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), sulphur oxides (SOx), and lead) whose regional ambient air levels are regulated by the Environmental Protection Agency (EPA), are often discussed. However, the main concern in the emissions to air associated to shale gas operations, seems to be the leakage of methane. Methane is identified as a compound of major concern due to its strong global warming potential. The identification of methane leakage from shale gas activities is complex due to the existence of several other CH4 sources (e.g. landfill, agricultural activity or gas pipeline/compressor station). An integrated monitoring study of methane emissions may be a suitable mean of distinguishing the contribution of different sources of methane to ambient levels. All data analysis needs to be carefully interpreted taking, also, into account the meteorological conditions of the site. This may require the implementation of a more intensive monitoring programme. So, it is essential the development of a low-cost sampling strategy, suitable for establishing pre-operations baseline data as well as an integrated monitoring program to assess the emissions from shale gas operation sites. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640715.

Keywords: air emissions, baseline, green house gases, shale gas

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Authors: Angelo Corallo, Maria Elena Latino, Marta Menegoli

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The link between man and food plays, in the social and economic system, a central role where cultural and multidisciplinary aspects intertwine: food is not only nutrition, but also communication, culture, politics, environment, science, ethics, fashion. This multi-dimensionality has many implications in the food economy. In recent years, the consumer became more conscious about his food choices, involving a consistent change in consumption models. This change concerns several aspects: awareness of food system issues, employment of socially and environmentally conscious decision-making, food choices based on different characteristics than nutritional ones i.e. origin of food, how it’s produced, and who’s producing it. In this frame the ‘consumption choices’ and the ‘interests of the citizen’ become one part of the others. The figure of the ‘Citizen Consumer’ is born, a responsible and ethically motivated individual to change his lifestyle, achieving the goal of sustainable consumption. Simultaneously the branding, that before was guarantee of the product quality, today is questioned. In order to meet these needs, Agri-Food companies are developing specific product lines that follow two main philosophies: ‘Back to basics’ and ‘Less is more’. However, the issue of ethical behavior does not seem to find an adequate on market offer. Most likely due to a lack of attention on the communication strategy used, very often based on market logic and rarely on ethical one. The label in its classic concept of ‘clean labeling’ can no longer be the only instrument through which to convey product information and its evolution towards a concept of ‘clear label’ is necessary to embrace ethical and transparent concepts in progress the process of democratization of the Food System. The implementation of a voluntary traceability path, relying on the technological models of the Internet of Things or Industry 4.0, would enable the Agri-Food Supply Chain to collect data that, if properly treated, could satisfy the information need of consumers. A change of approach is therefore proposed towards Agri-Food traceability that is no longer intended as a tool to be used to respond to the legislator, but rather as a promotional tool useful to tell the company in a transparent manner and then reach the slice of the market of food citizens. The use of mobile technology can also facilitate this information transfer. However, in order to guarantee maximum efficiency, an appropriate communication model based on the ethical communication principles should be used, which aims to overcome the pipeline communication model, to offer the listener a new way of telling the food product, based on real data collected through processes traceability. The Citizen Consumer is therefore placed at the center of the new model of communication in which he has the opportunity to choose what to know and how. The new label creates a virtual access point capable of telling the product according to different point of views, following the personal interests and offering the possibility to give several content modalities to support different situations and usability.

Keywords: agri food traceability, agri-food transparency, clear label, food system, internet of things

Procedia PDF Downloads 158

Authors: Daniela E. Marin, Cornelia Braicu, Gina C. Pistol, Roxana Cojocneanu-Petric, Ioana Berindan Neagoe, Mihail A. Gras, Ionelia Taranu

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Aristolochic acid (AA) is a carcinogenic, mutagenic, and nephrotoxic compound commonly found in the Aristolochiaceae family of plants. AA is frequently associated with urothelial carcinoma of the upper urinary tract in human and animals and is considered as being responsible for Balkan Endemic Nephropathy. The pig provides a good animal model because the porcine urological system is very similar to that of humans, both in aspects of physiology and anatomy. MicroRNA (miRNA) are small non-coding RNAs that have an impact on a wide range of biological processes by regulating gene expression at post-transcriptional level. The objective of this study was to analyze the miRNA profiling in the kidneys of AA intoxicated swine. For this purpose, ten TOPIGS-40 crossbred weaned piglets, 4-week-old, male and females with an initial average body weight of 9.83 ± 0.5 kg were studied for 28 days. They were given ad libitum access to water and feed and randomly allotted to one of the following groups: control group (C) or aristolochic acid group (AA). They were fed a maize-soybean-meal-based diet contaminated or not with 0.25mgAA/kg. To profile miRNA in the kidneys of pigs, microarrays and bioinformatics approaches were applied to analyze the miRNA in the kidney of control and AA intoxicated pigs. After normalization, our results have shown that a total of 5 known miRNAs and 4 novel miRNAs had different profiling in the kidney of intoxicated animals versus control ones. Expression of miR-32-5p, miR-497-5p, miR-423-3p, miR-218-5p, miR-128-3p were up-regulated by 0.25mgAA/kg feed, while the expression of miR-9793-5p, miR-9835-3p, miR-9840-3p, miR-4334-5p was down-regulated. The microRNA profiling in kidney of intoxicated animals was associated with modified expression of target genes as: RICTOR, LASP1, SFRP2, DKK2, BMI1, RAF1, IGF1R, MAP2K1, WEE1, HDGF, BCL2, EIF4E etc, involved in cell division cycle, apoptosis, cell differentiation and cell migration, cell signaling, cancer etc. In conclusion, this study provides new data concerning the microRNA profiling in kidney after aristolochic acid intoxications with important implications for human and animal health.

Keywords: aristolochic acid, kidney, microRNA, swine

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Authors: D. Hammad, D. P. Tonge

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Rheumatoid arthritis (RA) is a disabling and common autoimmune disease during which the body's immune system attacks healthy tissues. This results in complicated and long-lasting actions being carried out by the immune system, which typically only occurs when the immune system encounters a foreign object. In the case of RA, the disease affects millions of people and causes joint inflammation, ultimately leading to the destruction of cartilage and bone. Interestingly, the disease mechanism still remains unclear. It is likely that RA occurs as a result of a complex interplay of genetic and environmental factors including an imbalance in the microorganism population inside our body. The human microbiome or microbiota is an extensive community of microorganisms in and on the bodies of animals, which comprises bacteria, fungi, viruses, and protozoa. Recently, the development of molecular techniques to characterize entire bacterial communities has renewed interest in the involvement of the microbiome in the development and progression of RA. We believe that an imbalance in some of the specific bacterial species in the gut, mouth and other sites may lead to atopobiosis; the translocation of these organisms into the blood, and that this may lead to changes in immune system status. The aim of this study was, therefore, to characterize the microbiome of RA serum samples in comparison to healthy control subjects using 16S rRNA gene amplification and sequencing. Serum samples were obtained from healthy control volunteers and from patients with RA both prior to, and following treatment. The bacterial community present in each sample was identified utilizing V4 region 16S rRNA amplification and sequencing. Bacterial identification, to the lowest taxonomic rank, was performed using a range of bioinformatics tools. Significantly, the proportions of the Lachnospiraceae, Ruminococcaceae, and Halmonadaceae families were significantly increased in the serum of RA patients compared with healthy control serum. Furthermore, the abundance of Bacteroides and Lachnospiraceae nk4a136_group, Lachnospiraceae_UGC-001, RuminococcaceaeUCG-014, Rumnococcus-1, and Shewanella was also raised in the serum of RA patients relative to healthy control serum. These data support the notion of a blood microbiome and reveal RA-associated changes that may have significant implications for biomarker development and may present much-needed opportunities for novel therapeutic development.

Keywords: blood microbiome, gut and oral bacteria, Rheumatoid arthritis, 16S rRNA gene sequencing

Procedia PDF Downloads 132

Authors: Sheng-Yu Lee

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Aim: Opioid use disorder is often characterized by repetitive drug-seeking and drug-taking behaviors with severe public health consequences. Animal model showed that opioid-induced perturbations in the gut microbiota causally relate to neuroinflammation, deficits in reward responding, and opioid tolerance, possibly due to changes in gut microbiota. Therefore, we propose that the dysbiosis of gut microbiota can be associated with pathogenesis of opioid dependence. In this current study, we explored the differences in gut microbiota between patients and normal controls and in patients before and after initiation of methadone treatment program for 12 weeks. Methods: Patients with opioid use disorder between 20 and 65 years were recruited from the methadone maintenance outpatient clinic in 2 medical centers in the Southern Taiwan. Healthy controls without any family history of major psychiatric disorders (schizophrenia, bipolar disorder and major depressive disorder) were recruited from the community. After initial screening, 15 patients with opioid use disorder joined the study for initial evaluation (Week 0), 12 of them completed the 12-week follow-up while receiving methadone treatment and ceased heroin use (Week 12). Fecal samples were collected from the patients at baseline and the end of 12th week. A one-time fecal sample was collected from the healthy controls. The microbiota of fecal samples were investigated using 16S rRNA V3V4 amplicon sequencing, followed by bioinformatics and statistical analyses. Results: We found no significant differences in species diversity in opioid dependent patients between Week 0 and Week 12, nor compared between patients at both points and controls. For beta diversity, using principal component analysis, we found no significant differences between patients at Week 0 and Week 12, however, both patient groups showed significant differences compared to control (P=0.011). Furthermore, the linear discriminant analysis effect size (LEfSe) analysis was used to identify differentially enriched bacteria between opioid use patients and healthy controls. Compared to controls, the relative abundance of Lactobacillaceae Lactobacillus (L. Lactobacillus), Megasphaera Megasphaerahexanoica (M. Megasphaerahexanoica) and Caecibacter Caecibactermassiliensis (C Caecibactermassiliensis) were increased in patients at Week 0, while Coriobacteriales Atopobiaceae (C. Atopobiaceae), Acidaminococcus Acidaminococcusintestini (A. Acidaminococcusintestini) and Tractidigestivibacter Tractidigestivibacterscatoligenes (T. Tractidigestivibacterscatoligenes) were increased in patients at Week 12. Conclusion: In conclusion, we suggest that the gut microbiome community maybe linked to opioid use disorder, such differences may not be altered even after 12-week of cessation of opioid use.

Keywords: opioid use disorder, gut microbiota, methadone treatment, follow up study

Procedia PDF Downloads 106

Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have an important role in controlling illness associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing like disk diffusion are time-consuming and other method including E-test, genotyping are relatively expensive. Fourier transform infrared (FTIR) microscopy is rapid, safe, and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 550 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 85% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E. coli, FTIR, multivariate analysis, susceptibility

Procedia PDF Downloads 265

Authors: Javed Mohammed

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Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.

Keywords: high performance, big data, parallel computation, molecular data, computational biology

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Authors: Aidin Foroutan, David S. Wishart, Leluo L. Guan, Carolyn Fitzsimmons

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Maximizing efficiency and growth potential of beef cattle requires not only genetic selection (i.e. residual feed intake (RFI)) but also adequate nutrition throughout all stages of growth and development. Nutrient restriction during gestation has been shown to negatively affect post-natal growth and development as well as fertility of the offspring. This, when combined with RFI may affect progeny traits. This study aims to investigate the impact of selection for divergent genetic potential for RFI and maternal nutrition during early- to mid-gestation, on bull calf traits such as fertility and muscle development using multiple ‘omics’ approaches. Comparisons were made between High-diet vs. Low-diet and between High-RFI vs. Low-RFI animals. An epigenetics experiment on semen samples identified 891 biomarkers associated with growth and development. A gene expression study on Longissimus thoracis muscle, semimembranosus muscle, liver, and testis identified 4 genes associated with muscle development and immunity of which Myocyte enhancer factor 2A [MEF2A; induces myogenesis and control muscle differentiation] was the only differentially expressed gene identified in all four tissues. An initial metabolomics experiment on serum samples using nuclear magnetic resonance (NMR) identified 4 metabolite biomarkers related to energy and protein metabolism. Once all the biomarkers are identified, bioinformatics approaches will be used to create a database covering all the ‘omics’ data collected from this project. This database will be broadened by adding other information obtained from relevant literature reviews. Association analyses with these data sets will be performed to reveal key biological pathways affected by RFI and maternal nutrition. Through these association studies between the genome and metabolome, it is expected that candidate biomarker genes and metabolites for feed efficiency, fertility, and/or muscle development are identified. If these gene/metabolite biomarkers are validated in a larger animal population, they could potentially be used in breeding programs to select superior animals. It is also expected that this work will lead to the development of an online tool that could be used to predict future traits of interest in an animal given its measurable ‘omics’ traits.

Keywords: biomarker, maternal nutrition, omics, residual feed intake

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Authors: V. Vsevolozhskaia

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Since 1990, energy-efficient development concepts have constituted both a turning point in civil engineering and a challenge for an environmentally friendly future. Energy and water currently play an essential role in the sustainable economic growth of the world in general and Russia in particular: the efficiency of the water supply system is the second most important parameter for energy consumption according to the British assessment method, while the water-energy nexus has been identified as a focus for accelerating sustainable growth and developing effective, innovative solutions. The activities considered in this study were aimed at organizing and executing the renovation of the property in residential buildings located in St. Petersburg, specifically buildings with local or federal historical heritage status under the control of the St. Petersburg Committee for the State Inspection and Protection of Historic and Cultural Monuments (KGIOP) and UNESCO. Even after reconstruction, these buildings still fall into energy efficiency class D. Russian Government Resolution No. 87 on the structure and required content of project documentation contains a section entitled ‘Measures to ensure compliance with energy efficiency and equipment requirements for buildings, structures, and constructions with energy metering devices’. Mention is made of the need to install collectors and meters, which only calculate energy, neglecting the main purpose: to make buildings more energy-efficient, potentially even energy efficiency class A. The least-explored aspects of energy-efficient technology in the Russian Federation remain the water balance and the possibility of implementing rain and meltwater collection systems. These modern technologies are used exclusively for new buildings due to a lack of government directive to create project documentation during the planning of major renovations and reconstruction that would include the collection and reuse of rainwater. Energy-efficient technology for rain and meltwater collection is currently applied only to new buildings, even though research has proved that using rainwater is safe and offers a huge step forward in terms of eco-efficiency analysis and water innovation. Where conservation is mandatory, making changes to protected sites is prohibited. In most cases, the protected site is the cultural heritage building itself, including the main walls and roof. However, the installation of a second water supply system and collection of rainwater would not affect the protected building itself. Water efficiency in St. Petersburg is currently considered only from the point of view of the installation that regulates the flow of the pipeline shutoff valves. The development of technical guidelines for the use of grey- and/or rainwater to meet the needs of residential buildings during reconstruction or renovation is not yet complete. The ideas for water treatment, collection and distribution systems presented in this study should be taken into consideration during the reconstruction or renovation of residential cultural heritage buildings under the protection of KGIOP and UNESCO. The methodology applied also has the potential to be extended to other cultural heritage sites in northern countries and lands with an average annual rainfall of over 600 mm to cover average toilet-flush needs.

Keywords: cultural heritage, energy efficiency, renovation, rainwater collection, reconstruction, water management, water supply

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Authors: Nicholas Aerne, John P. Parmigiani

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There is an increasing desire for renewable and sustainable energy sources to replace fossil fuels. This desire is the result of several factors. First, is the role of fossil fuels in climate change. Scientific data clearly shows that global warming is occurring. It has also been concluded that it is highly likely human activity; specifically, the combustion of fossil fuels, is a major cause of this warming. Second, despite the current surplus of petroleum, fossil fuels are a finite resource and will eventually become scarce and alternatives, such as clean or renewable energy will be needed. Third, operations to obtain fossil fuels such as fracking, off-shore oil drilling, and strip mining are expensive and harmful to the environment. Given these environmental impacts, there is a need to replace fossil fuels with renewable energy sources as a primary energy source. Various sources of renewable energy exist. Many familiar sources obtain renewable energy from the sun and natural environments of the earth. Common examples include solar, hydropower, geothermal heat, ocean waves and tides, and wind energy. Often obtaining significant energy from these sources requires physically-large, sophisticated, and expensive equipment (e.g., wind turbines, dams, solar panels, etc.). Other sources of renewable energy are from the man-made environment. An example is municipal water distribution systems. The movement of water through the pipelines of these systems typically requires the reduction of hydraulic pressure through the use of pressure reducing valves. These valves are needed to reduce upstream supply-line pressures to levels suitable downstream users. The energy associated with this reduction of pressure is significant but is currently not harvested and is simply lost. While the integrity of municipal water supplies is of paramount importance, one can certainly envision means by which this lost energy source could be safely accessed. This paper provides a technical description and analysis of one such means by the technology company InPipe Energy to generate hydroelectricity by harvesting energy from municipal water distribution pressure reducing valve stations. Specifically, InPipe Energy proposes to install hydropower turbines in parallel with existing pressure reducing valves in municipal water distribution systems. InPipe Energy in partnership with Oregon State University has evaluated this approach and built a prototype system at the O. H. Hinsdale Wave Research Lab. The Oregon State University evaluation showed that the prototype system rapidly and safely initiates, maintains, and ceases power production as directed. The outgoing water pressure remained constant at the specified set point throughout all testing. The system replicates the functionality of the pressure reducing valve and ensures accurate control of down-stream pressure. At a typical water-distribution-system pressure drop of 60 psi the prototype, operating at an efficiency 64%, produced approximately 5 kW of electricity. Based on the results of this study, this proposed method appears to offer a viable means of producing significant amounts of clean renewable energy from existing pressure reducing valves.

Keywords: pressure reducing valve, renewable energy, sustainable energy, water supply

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Authors: Md. Fazlul Karim, Ashik Sharfaraz, Aysha Ferdoushi

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Background: Computational medicinal chemistry approaches are used for designing and identifying new drug-like molecules, predicting properties and pharmacological activities, and optimizing lead compounds in drug development. SIRT7, a nicotinamide adenine dinucleotide (NAD+)-dependent deacylase which regulates aging, is an emerging target for cancer therapy with mounting evidence that SIRT7 downregulation plays important roles in reversing cancer phenotypes and suppressing tumor growth. Activation or altered expression of SIRT7 is associated with the progression and invasion of various cancers, including liver, breast, gastric, prostate, and non-small cell lung cancer. Objectives: The goal of this work was to identify potent and selective bioactive candidate inhibitors of SIRT7 by in silico screening of small molecule compounds obtained from Nigella sativa (N. sativa). Methods: SIRT7 structure was retrieved from The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), and its active site was identified using CASTp and metaPocket. Molecular docking simulation was performed with PyRx 0.8 virtual screening software. Drug-likeness properties were tested using SwissADME and pkCSM. In silico toxicity was evaluated by Osiris Property Explorer. Bioactivity was predicted by Molinspiration software. Antitumor activity was screened for Prediction of Activity Spectra for Substances (PASS) using Way2Drug web server. Molecular dynamics (MD) simulation was carried out by Desmond v3.6 package. Results: A total of 159 bioactive compounds from the N. Sativa were screened against the SIRT7 enzyme. Five bioactive compounds: chrysin (CID:5281607), pinocembrin (CID:68071), nigellidine (CID:136828302), nigellicine (CID:11402337), and epicatechin (CID:72276) were identified as potent SIRT7 anti-cancer candidates after docking score evaluation and applying Lipinski's Rule of Five. Finally, MD simulation identified Chrysin as the top SIRT7 anti-cancer candidate molecule. Conclusion: Chrysin, which shows a potential inhibitory effect against SIRT7, can act as a possible anti-cancer drug candidate. This inhibitor warrants further evaluation to check its pharmacokinetics and pharmacodynamics properties both in vitro and in vivo.

Keywords: SIRT7, antitumor, molecular docking, molecular dynamics simulation

Procedia PDF Downloads 79

Authors: Chang Liang, Weizhi Gong, Yan Zhang

Abstract:

Purpose: Hepatocellular carcinoma (HCC) is a malignant tumor with a high mortality rate and poor prognosis worldwide. Murine double minute 2 (MDM2) regulates the tumor suppressor p53, increasing cancer risk and accelerating tumor progression. Speckle-type POX virus and zinc finger protein (SPOP), a key of subunit of Cullin-Ring E3 ligase, inhibits tumor genesis and progression by the ubiquitination of its downstream substrates. This study aimed to clarify whether SPOP and MDM2 are mutually regulated in HCC and the correlation between SPOP and MDM2 and the prognosis of HCC patients. Methods: First, the expression of SPOP and MDM2 in HCC tissues were detected by TCGA database. Then, 53 paired samples of HCC tumor and adjacent tissues were collected to evaluate the expression of SPOP and MDM2 using immunohistochemistry. Chi-square test or Fisher’s exact test were used to analyze the relationship between clinicopathological features and the expression levels of SPOP and MDM2. In addition, Kaplan‒Meier curve analysis and log-rank test were used to investigate the effects of SPOP and MDM2 on the survival of HCC patients. Last, the Multivariate Cox proportional risk regression model analyzed whether the different expression levels of SPOP and MDM2 were independent risk factors for the prognosis of HCC patients. Results: Bioinformatics analysis revealed the low expression of SPOP and high expression of MDM2 were related to worse prognosis of HCC patients. The relationship between the expression of SPOP and MDM2 and tumor stem-like features showed an opposite trend. The immunohistochemistry showed the expression of SPOP protein was significantly downregulated while MDM2 protein significantly upregulated in HCC tissue compared to that in para-cancerous tissue. Tumors with low SPOP expression were related to worse T stage and Barcelona Clinic Liver Cancer (BCLC) stage, but tumors with high MDM2 expression were related to worse T stage, M stage, and BCLC stage. Kaplan–Meier curves showed HCC patients with high SPOP expression and low MDM2 expression had better survival than those with low SPOP expression and high MDM2 expression (P < 0.05). A multivariate Cox proportional risk regression model confirmed that a high MDM2 expression level was an independent risk factor for poor prognosis in HCC patients (P <0.05). Conclusion: The expression of SPOP protein was significantly downregulated, while the expression of MDM2 significantly upregulated in HCC. The low expression of SPOP and high expression. of MDM2 were associated with malignant progression and poor prognosis of HCC patients, indicating a potential therapeutic target for HCC patients.

Keywords: hepatocellular carcinoma, murine double minute 2, speckle-type POX virus and zinc finger protein, ubiquitination

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