Evolution and potential function of fibrinogen-like domains across twelve Drosophila species

<p>Abstract</p> <p>Background</p> <p>The fibrinogen-like (FBG) domain consists of approximately 200 amino acid residues, which has high sequence similarity to the C-terminal halves of fibrinogen β and γ chains. Fibrinogen-related proteins (FREPs) containing one or more FBG domains are found universally in vertebrates and invertebrates. In invertebrates, FREPs are involved in immune responses and other aspects of physiology. To understand the complexity of this gene family in <it>Drosophila</it>, we analyzed FREPs in twelve <it>Drosophila </it>species.</p> <p>Results</p> <p>Using the genome data from 12 <it>Drosophila </it>species, we identified FBG domains in each species. The results show that the gene numbers in each species vary from 14 genes up to 43 genes. Using sequence profile analysis, we found that FBG domains have high sequence similarity and are highly conserved throughout. By comparison of structure and sequence conservation, some of the FBG domains in <it>Drosophila melanogaster </it>are predicted to function in recognition of carbohydrates and their derivatives on the surface of microorganisms in innate immunity.</p> <p>Conclusion</p> <p>Sequence and structural analyses show that FREP family across 12 <it>Drosophila </it>species contains conserved FBG domains. Expansion of the FREP families in <it>Drosophila </it>is mainly accounted by a major expansion of FBG domains.</p

Elucidating Signal Transduction Modulatory Drug Target Network of Colon Cancer: A Network Biology Approach

Latest evaluation and validation of cancer drugs and their targets has demonstrated the lack and inadequate development of new and better drugs, based on available protocols. Even though the specificity of drug targets is a great challenge in the pharmaco-proteomics field of cancer biology, for eradicating such hurdles and paving the way for the drugs of future, a novel step has been envisaged here to study the relation between drug target network and the corresponding drug network using the advanced concepts of proteomics and network biology. The literature mining was done for the collection of receptors and the ligands. About 1000 natural compounds were collected and out of those 300 molecules showed anti-cancer activity against colon cancer. Ligand Vs multiple receptor docking was done using the software Quantum 3.3.0; the results were further used for the designing of a well connected Protein Ligand Interaction (PLI) network of colon cancer. The obtained network is then extrapolated to sort out the receptors expressed in the specific cancer type. The network is then statistically analyzed and represented by the graphical interpretation, in order to ascertain the hub nodes and their locally parsed neighbours. Based on the best docking scores, the graphs obtained from the docking analysis are statistically validated with the help of VisANT. In the network three hub nodes Neutrophil cytosol factor 2, UV excision repair protein RAD23 homolog A, &#x26; Receptor-type tyrosine-protein phosphatase eta were identified, which showed the highest interaction with the ligands. Butyrate and Farnesol showed highest interaction as ligands. Multiple Sequence Alignment was done of the binding site sequence of the drug targets to find out the evolutionary closeness of the binding sites. The phylogenetic tree was also constructed to further validate the observation. Further in-vitro and in-vivo studies needs to be done to analyse the receptor specificity and anti tumor activity of these compounds in Colon cancer

HySafe Standard benchmark Problem SBEP-V11: Predictions of hydrogen release and dispersion from a CGH2 bus in an underpass

One of the tasks of the HySafe Network of Excellence was the evaluation of available CFD tools and models for dispersion and combustion in selected hydrogen release scenarios identified as “standard benchmark problems” (SBEPs). This paper presents the results of the HySafe standard benchmark problem SBEP-V11. The situation considered is a high pressure hydrogen jet release from a compressed gaseous hydrogen (CGH2) bus in an underpass. The bus considered is equipped with 8 cylinders of 5 kg hydrogen each at 35 MPa storage pressure. The underpass is assumed to be of the common beam and slab type construction with I-beams spanning across the highway at 3 m centres (normal to the bus), plus cross bracing between the main beams, and light armatures parallel to the bus direction. The main goal of the present work was to evaluate the role of obstructions on the underside of the bridge deck on the dispersion patterns and assess the potential for hydrogen accumulation. Four HySafe partners participated in this benchmark, with 4 different CFD codes, ADREA-HF, CFX, FLACS and FLUENT. Four scenarios were examined in total. In the base case scenario 20 kg of hydrogen was released in the basic geometry. In Sensitivity Test 1 the release position was moved so that the hydrogen jet could hit directly the light armature on the roof of the underpass. In Sensitivity Test 2 the underside of the bridge deck was flat. In Sensitivity Test 3 the release was from one cylinder instead of four (5 kg instead of 20). The paper compares the results predicted by the four different computational approaches and attempts to identify the reasons for observed disagreements. The paper also concludes on the effects of the obstructions on the underside of the bridge deck

Investigations on noval method for the formulation of solid dispersions part- I Formulation, characterization and selection

The solid dispersions of indomethacin with hydrophilic polymers were prepared by lyophilization. The polymers used in the investigation were HPMC, PVP K30, CBR and PLF 127. The solubility and dissolution of indomethacin from prepared lyophilized solid dispersions were investigated in 0.1 N HCl, purified water and USP-NF dissolution media.  Out of fifteen lyophilized formulations from F1 to F15, five formulations F2, F5, F8, F12 and F14 showed highest solubility in purified water. Formulation F2, F8 failed to comply with the USP-NF dissolution test for indomethacin capsules. Formulation F14 showed maximum dissolution in the respective dissolution media within 60 min.  Sustained drug release was observed for 6 h with formulations F2 and F8 in USP-NF media. The formulations F2, F5, F8, F12 and F14 were characterized by modulated DSC and FT-IR spectroscopy. Some Formulations on stability testing were found physico-chemically stable at accelerated temperature conditions

Seismic Design Optimization of Steel Structures Using Particle Swarm Algorithm

Earthquakes are one of the most devastating and expensive natural disasters in the world. Economical and earthquake-resistant design remains a challenge for structural engineers. This study explores the optimal design of a seismic force resisting steel frame using a population based stochastic algorithm known as Particle Swarm Optimization (PSO). PSO is able to efficiently explore a complex solution space with many design variables and constraints. PSO is also problem independent and can be built around any approach to earthquake design. As a case study, the seismic design of a three-story moment resisting frame is optimized for the linear static, linear dynamic, and nonlinear static analysis methods. An interface was created between MATLAB and OpenSees to link optimization with a well-known and freely available earthquake engineering software. This application is extended to the performance-based design of structures, in which the optimal design meets the target performance objectives of Immediate Occupancy, Life Safety, and Collapse Prevention under Frequent, Design, and Maximum-considered seismic hazard levels

Bioinformatics solution for clinical utilization of next generation DNA sequencing

University of Minnesota Ph.D. dissertation. September 2014. Major: Biomedical Informatics and Computational Biology. Advisor: Dr.Claudia Neuhauser. 1 computer file (PDF); x, 132 pages, appendix A.DNA sequencing as an application of Next Generation Sequencing (NGS) is beginning to reshape how physicians diagnose and make treatment decisions for their patients. These NGS technologies provide a great depth of information by bringing along unprecedented throughput of data, huge scalability and speed. The terabytes of data generated has precipitated a need for efficient bioinformatics analysis and interpretation processes. My dissertation provides an end-to-end solution to analyze DNA sequencing data, interpret and deliver results efficiently and effectively. I developed a modular, robust workflow Targeted RE-sequencing Annotation Tool (TREAT) to provide a backbone for NGS DNA analysis, in collaboration with Mayo Clinic's bioinformatics core [1]. TREAT is one of the first bioinformatics solutions to incorporate alignment, variant calling, annotation and visualization of DNA sequencing data. To better evaluate the increasing foray of NGS into the clinical domain, I designed a module for comprehensive depth of coverage evaluation for genes and variants of interest. This module extending upon the TREAT pipeline helps quantify the applicability of NGS for clinical gene panels [2]. With dwindling costs and increasing availability of whole genome sequencing, turnaround time remains a major factor for clinical adaptation of NGS. I developed a novel iterative bioinformatics approach to expedite whole genome analysis by focusing on clinically relevant genomic regions, reporting results in less than 10% of the original processing time [3]. Further research employing additional clinical annotation has given us insight into a comprehensive genotype phenotype correlation evaluation of clinically reportable variants. Here I report on the characteristics of clinically relevant variants typically expected per individual from whole exome DNA sequencing data. These data highlight challenges that need to be addressed including both phenotype issues of disease penetrance and uncertainty about what is clinically reportable, and sequencing issues like incomplete sequencing coverage, thresholds for data filtering and lack of high quality databases to determine functional annotation

Experimental and neural network approach to effective electrical conductivity of carbon nanotubes dispersed chiral nematic liquid crystals

Single walled carbon nanotubes (SWCNT’s) doped cholesteric liquid crystal composite has been prepared and characterized for their electrical responses. Also theoretically, an artificial neural network (ANN) approach has been trained for predicting the effective electrical conductivity of these composites. The ANN models are based on a feedforward backpropagation (FFBP) network with such training functions as the adaptive learning rate (GDX), gradient descent with adaptive learning rate (GDA), gradient descent (GD), conjugates gradient with Powell-Beale restarts (CGB), one-step secant (OSS), and Levenberg–Marquardt (LM), and training algorithms run at the uniform threshold transfer functions-Tangent sigmoid (TANSIG) and pure linear (PURELIN) for 1000 epochs. Our modeling confirms that the expected effective electrical conductivity by different training functions of ANN is in higher agreement with the experimental results of SWCNT doped CLC composites

Re-imagining eating spaces of an inner-urban university as pathways to sustainable outcomes

Current understandings and imaginations of eating spaces and related practices limit sustainability outcomes in food provisioning and consumption at urban universities. This is because most understandings and strategies are singular and/or siloed in their approaches and do not address the complex spatial and temporal aspects of eating practices. In addition, most strategies for change are confined to changing individual behaviours and attitudes. This thesis addresses these issues through the research question, how can eating spaces be (re)imagined at urban universities as pathways for sustainable outcomes? Social Practice Theories (SPT) and in particular Schatzki&amp;rsquo;s (2002)site ontology provide a conceptual framework in this thesis to examine and re-imagine eating spaces and students&amp;rsquo; practices as relational. Further, that space is a production of these relations encompassing objective and existential timespaces. Drawing on these concepts, I reimagine university eating spaces as a variety of lived spaces where eating occurs. This approach broadens the notion of sustainability outcomes to explore these spaces and practices as sites for intervention. Moreover, the approach taken also reveals different modes of knowledge production for and at universities, positioning them as pathways for sustainable outcomes. I employed interpretive ethnography as a methodology to identify practices and material arrangements, with RMIT University&amp;rsquo;s city campus in Melbourne, Australia, as its case study. Using multiple spatially and temporally dispersed methods, I conducted: observations and attended events on campus over a period of two years; semi-structured interviews with a wide range of University and student representatives; focus groups with eighteen students in which students created food maps. I also established a private Facebook page for students to post &amp;lsquo;food selfies&amp;rsquo; that captured their food practices on- and off-campus. I studied the eating spaces on campus by focusing on four types of &amp;lsquo;lived spaces&amp;rsquo;, each providing a distinctive account of and perspective on a lived space that may facilitate different food provisioning and sustainable outcomes. These were: 1) ethnographic spaces that enabled knowledge production that can themselves be sites for intervention 2 in patterns of eating associated with the campus; 2) third spaces of mobile fooddistribution that re-imagined eating spaces as hybrid, convivial and spatio-temporally flexible; 3) spaces of capability that enabled practices with sustainable outcomes on campus by connecting on-campus practices and material arrangements to students&amp;rsquo; domestic practices; and 4) convenient eating-timespaces that added to conviviality, commensality and sociality in eating, which have been shown to have sustainable outcomes. In conclusion, I argue that eating spaces are best understood through the study of the multi-relationality of practices, material arrangements and their dynamics that produce lived spaces. This research approach provides insight into the kind of spaces produced and what kinds of sustainability outcomes are achieved or possible. It further establishes that lived spaces are important and innovative pathways toward sustainable outcomes. In this way, this study is a sociological inquiry into the geographies of practice that provides insights into inquiries of consumption and contributes to the inclusion of the spatial within sociological studies

Systematic analysis of Quercetin and its derivatives with Special Reference to anti-inflammatory property-Based on Network Pharmacology

The clinical success of phyto-chemicals and computationally assisted drug discovery-derived agents has stimulated the development of novel compounds for human illnesses. In the field of anticancer drug discovery, rational investigation has sped up the process. Quercetin and its derivatives have a long history of anti-inflammatory efficacy in pomegranate and other natural products, according to scientific evidence. Small structural alterations, for example, can drastically affect cell death behaviour and trigger inflammation, making it difficult to unravel the structure-activity relationship. As a result, our objective is to use a rational drug discovery approach to develop a mechanistic approach for quercetin and its derivatives, which will be compared to market anti-inflammatory medications utilising in-silico tools. Using the software Cytoscape, we created pharmacology networks of inflammatory proteins based on data acquired from several databases. The networks show how bioactives interact with molecular targets and how they relate to illnesses, particularly inflammation. Quercetin's network pharmacology study has shown novel connections between bioactive targets and possible inflammatory aetiology applications. The future prospect is to understand these chemicals in vitro and in vivo