Characterization of ENU-induced mutations in red blood cell structural proteins

Murine models with modified gene function as a result of N-ethyl-N-nitrosourea (ENU) mutagenesis have been used to study phenotypes resulting from genetic change. This study investigated genetic factors associated with red blood cell (RBC) physiology and structural integrity that may impact on blood component storage and transfusion outcome. Forward and reverse genetic approaches were employed with pedigrees of ENU-treated mice using a homozygous recessive breeding strategy. In a “forward genetic” approach, pedigree selection was based upon identification of an altered phenotype followed by exome sequencing to identify a causative mutation. In a second strategy, a “reverse genetic” approach based on selection of pedigrees with mutations in genes of interest was utilised and, following breeding to homozygosity, phenotype assessed. Thirty-three pedigrees were screened by the forward genetic approach. One pedigree demonstrated reticulocytosis, microcytic anaemia and thrombocytosis. Exome sequencing revealed a novel single nucleotide variation (SNV) in Ank1 encoding the RBC structural protein ankyrin-1 and the pedigree was designated Ank1EX34. The reticulocytosis and microcytic anaemia observed in the Ank1EX34 pedigree were similar to clinical features of hereditary spherocytosis in humans. For the reverse genetic approach three pedigrees with different point mutations in Spnb1 encoding RBC protein spectrin-1β, and one pedigree with a mutation in Epb4.1, encoding band 4.1 were selected for study. When bred to homozygosity two of the spectrin-1β pedigrees (a, b) demonstrated increased RBC count, haemoglobin (Hb) and haematocrit (HCT). The third Spnb1 mutation (spectrin-1β c) and mutation in Epb4.1 (band 4.1) did not significantly affect the haematological phenotype, despite these two mutations having a PolyPhen score predicting the mutation may be damaging. Exome sequencing allows rapid identification of causative mutations and development of databases of mutations predicted to be disruptive. These tools require further refinement but provide new approaches to the study of genetically defined changes that may impact on blood component storage and transfusion outcome.

Characterization of a DC-driven microplasma between a capillary tube and water surface

A microplasma generated between a stainless-steel capillary and water surface in ambient air with flowing argon as working gas appears as a bright spot at the tube orifice and expands to form a larger footprint on the water surface, and the dimensions of the bell-shaped microplasma are all below 1 mm. The electron density of the microplasma is estimated to be ranging from 5.32 × 109 cm−3 to 2.02 × 1014 cm−3 for the different operating conditions, which is desirable for generating abundant amounts of reactive species. A computational technique is adopted to fit the experimental emission from the N2 second positive system with simulation results. It is concluded that the vibrational temperature (more than 2000 K) is more than twice the gas temperature (more than 800 K), which indicates the non-equilibrium state of the microplasma. Both temperatures showed dependence on the discharge parameters (i.e., gas flow and discharge current). Such a plasma device could be arranged in arrays for applications utilizing plasmainduced liquid chemistry.

Computational micromodel for epigenetic mechanisms

Characterization of the epigenetic profile of humans since the initial breakthrough on the human genome project has strongly established the key role of histone modifications and DNA methylation. These dynamic elements interact to determine the normal level of expression or methylation status of the constituent genes in the genome. Recently, considerable evidence has been put forward to demonstrate that environmental stress implicitly alters epigenetic patterns causing imbalance that can lead to cancer initiation. This chain of consequences has motivated attempts to computationally model the influence of histone modification and DNA methylation in gene expression and investigate their intrinsic interdependency. In this paper, we explore the relation between DNA methylation and transcription and characterize in detail the histone modifications for specific DNA methylation levels using a stochastic approach.

Synthesis, characterization, and electronic structure studies of cubic Bi1.5ZnTa1.5O7 for photocatalytic applications

Bi1.5ZnTa1.5O7 (BZT) has been synthesized using an alkoxide based sol-gel reaction route. The evolution of the phases produced from the alkoxide precursors and their properties have been characterized as function of temperature using a combination of thermogravimetric analysis (TGA) coupled with mass spectrometry (MS), infrared emission spectrometry (IES), X-ray diffraction (XRD), ultraviolet and visible (UV-Vis) spectroscopy, Raman spectroscopy, and N2 adsorption/desorption isotherms. The lowest sintering temperature (600∘C) to obtain phase pure BZT powders with high surface area (14.5m2/g) has been determined from the thermal decomposition and phase analyses.The photocatalytic activity of the BZT powders has been tested for the decolorization of organic azo-dye and found to be photoactive under UV irradiation.The electronic band structure of the BZT has been investigated using density functional theory (DFT) calculations to determine the band gap energy (3.12 eV) and to compare it with experimental band gap (3.02 eV at 800∘C) from optical absorptionmeasurements. An excellent match is obtained for an assumption of Zn cation substitutions at specifically ordered sites in the BZT structure.

Electrical Characterization of Airborne Vehicle Exhaust Plume

he induced current and voltage on the skin of an airborne vehicle due to the coupling of external electromagnetic field could be altered in the presence of ionized exhaust plume. So in the present work, a theoretical analysis is done to estimate the electrical parameters such as electrical conductivity and permittivity and their distribution in the axial and radial directions of the exhaust plume of an airborne vehicle. The electrical conductivity depends on the distribution of the major ionic species produced from the propellant combustion. In addition it also depends on temperature and pressure distribution of the exhaust plume as well as the generated shock wave. The chemically reactive rocket exhaust flow is modeled in two stages. The first part is simulated from the combustion chamber to the throat of the supersonic nozzle by using NASA Chemical Equilibrium with Application (CEA) package and the second part is simulated from the nozzle throat to the downstream of the plume by using a commercial Computational Fluid Dynamics (CFD) solver. The contour plots of the exhaust parameters are presented. Eight barrel shocks which influence the distribution of the vehicle exhaust parameters are obtained in this simulation. The computed peak value of the electrical conductivity of the plume is 0.123 S/m and the relative permittivity varies from 0.89 to 0.99. The attenuation of the microwave when it is passing through the conducting exhaust plume has also been presented.

Characterization of Alloy-Spinel-Corundum Equilibrium in the System Fe-Ni-Al-O

The three phase equilibrium between alloy, spinel solid solution and α-alumina in the Fe-Ni-Al-O system has been fully characterized at 1823K as a function of alloy composition using both experimental and computational methods. The oxygen potential was measured using a solid state cell incorporating yttria-doped thoria as the electrolyte and Cr+ Cr2O3 as the reference electrode. Oxygen concentration of the alloy was determined by an inert gas fusion technique. The composition of the spinel solid solution, formed at the interface between the alloy and an alumina crucible, was determined by EPMA. The variation of the oxygen concentration and potential and composition of the spinel solid solution with mole fraction of nickel in the alloy have been computed using activities in binary Fe-Ni system, free energies of formation of end member spinels FeO•(1+x)Al2O3 and NiO•(1+x)Al2O3 and free energies of solution of oxygen in liquid iron and nickel, available in the literature. Activities in the spinel solid solution were computed using a cation distribution model. The variation of the activity coefficient of oxygen with alloy composition in Fe-Ni-O system was calculated using both the quasichemical model of Jacob and Alcock and the Wagner's model, with the correlation of Chiang and Chang. The computed results for the oxygen potential and the composition of the spinel solid solution are in good agreement with the measurements. The measured oxygen concentration lies between the values computed using models of Wagner and Jacob and Alcock. The results of the study indicate that the deoxidation hyper-surface in multicomponent systems can be computed with useful accuracy using data for end member systems and thermodynamic models.

Dendrimer building toolkit: Model building and characterization of various dendrimer architectures

We have developed a graphical user interface based dendrimer builder toolkit (DBT) which can be used to generate the dendrimer configuration of desired generation for various dendrimer architectures. The validation of structures generated by this tool was carried out by studying the structural properties of two well known classes of dendrimers: ethylenediamine cored poly(amidoamine) (PAMAM) dendrimer, diaminobutyl cored poly(propylene imine) (PPI) dendrimer. Using full atomistic molecular dynamics (MD) simulation we have calculated the radius of gyration, shape tensor and monomer density distribution for PAMAM and PPI dendrimer at neutral and high pH. A good agreement between the available simulation and experimental (small angle X-ray and neutron scattering; SAXS, SANS) results and calculated radius of gyration was observed. With this validation we have used DBT to build another new class of nitrogen cored poly(propyl ether imine) dendrimer and study it's structural features using all atomistic MD simulation. DBT is a versatile tool and can be easily used to generate other dendrimer structures with different chemistry and topology. The use of general amber force field to describe the intra-molecular interactions allows us to integrate this tool easily with the widely used molecular dynamics software AMBER. This makes our tool a very useful utility which can help to facilitate the study of dendrimer interaction with nucleic acids, protein and lipid bilayer for various biological applications. © 2012 Wiley Periodicals, Inc.

Dendrimer building toolkit: Model building and characterization of various dendrimer architectures

We have developed a graphical user interface based dendrimer builder toolkit (DBT) which can be used to generate the dendrimer configuration of desired generation for various dendrimer architectures. The validation of structures generated by this tool was carried out by studying the structural properties of two well known classes of dendrimers: ethylenediamine cored poly(amidoamine) (PAMAM) dendrimer, diaminobutyl cored poly(propylene imine) (PPI) dendrimer. Using full atomistic molecular dynamics (MD) simulation we have calculated the radius of gyration, shape tensor and monomer density distribution for PAMAM and PPI dendrimer at neutral and high pH. A good agreement between the available simulation and experimental (small angle X-ray and neutron scattering; SAXS, SANS) results and calculated radius of gyration was observed. With this validation we have used DBT to build another new class of nitrogen cored poly(propyl ether imine) dendrimer and study it's structural features using all atomistic MD simulation. DBT is a versatile tool and can be easily used to generate other dendrimer structures with different chemistry and topology. The use of general amber force field to describe the intra-molecular interactions allows us to integrate this tool easily with the widely used molecular dynamics software AMBER. This makes our tool a very useful utility which can help to facilitate the study of dendrimer interaction with nucleic acids, protein and lipid bilayer for various biological applications. (c) 2012 Wiley Periodicals, Inc.

SInCRe-structural interactome computational resource for Mycobacterium tuberculosis

We have developed an integrated database for Mycobacterium tuberculosis H37Rv (Mtb) that collates information on protein sequences, domain assignments, functional annotation and 3D structural information along with protein-protein and protein-small molecule interactions. SInCRe (Structural Interactome Computational Resource) is developed out of CamBan (Cambridge and Bangalore) collaboration. The motivation for development of this database is to provide an integrated platform to allow easily access and interpretation of data and results obtained by all the groups in CamBan in the field of Mtb informatics. In-house algorithms and databases developed independently by various academic groups in CamBan are used to generate Mtb-specific datasets and are integrated in this database to provide a structural dimension to studies on tuberculosis. The SInCRe database readily provides information on identification of functional domains, genome-scale modelling of structures of Mtb proteins and characterization of the small-molecule binding sites within Mtb. The resource also provides structure-based function annotation, information on small-molecule binders including FDA (Food and Drug Administration)-approved drugs, protein-protein interactions (PPIs) and natural compounds that bind to pathogen proteins potentially and result in weakening or elimination of host-pathogen protein-protein interactions. Together they provide prerequisites for identification of off-target binding.

Energetics and Structural Characterization of the large-scale Functional Motion of Adenylate Kinase

Adenylate Kinase (AK) is a signal transducing protein that regulates cellular energy homeostasis balancing between different conformations. An alteration of its activity can lead to severe pathologies such as heart failure, cancer and neurodegenerative diseases. A comprehensive elucidation of the large-scale conformational motions that rule the functional mechanism of this enzyme is of great value to guide rationally the development of new medications. Here using a metadynamics-based computational protocol we elucidate the thermodynamics and structural properties underlying the AK functional transitions. The free energy estimation of the conformational motions of the enzyme allows characterizing the sequence of events that regulate its action. We reveal the atomistic details of the most relevant enzyme states, identifying residues such as Arg119 and Lys13, which play a key role during the conformational transitions and represent druggable spots to design enzyme inhibitors. Our study offers tools that open new areas of investigation on large-scale motion in proteins.

An active learning approach for rapid characterization of endothelial cells in human tumors.

Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers.

Difference equation sensor characterization algorithms for two-thermocouple probes

The characterization of thermocouple sensors for temperature measurement in variable flow environments is a challenging problem. In this paper, novel difference equation-based algorithms are presented that allow in situ characterization of temperature measurement probes consisting of two-thermocouple sensors with differing time constants. Linear and non-linear least squares formulations of the characterization problem are introduced and compared in terms of their computational complexity, robustness to noise and statistical properties. With the aid of this analysis, least squares optimization procedures that yield unbiased estimates are identified. The main contribution of the paper is the development of a linear two-parameter generalized total least squares formulation of the sensor characterization problem. Monte-Carlo simulation results are used to support the analysis.

The Characterization of Friction Stir Welding Process Effects on Stiffened Panel Buckling Performance

The introduction of advanced welding methods as an alternative joining process to riveting in the manufacture of primary aircraft structure has the potential to realize reductions in both manufacturing costs and structural weight. However, welding processes can introduce undesirable residual stresses and distortions in the final fabricated components, as well as localized loss of mechanical properties at the weld joints. The aim of this research is to determine and characterize the key process effects of advanced welding assembly methods on stiffened panel static strength performance. This in-depth understanding of the relationships between welding process effects and buckling and collapse strength is required to achieve manufacturing cost reductions without introducing structural analysis uncertainties and hence conservative over designed welded panels. This current work is focused at the sub-component level and examines the static strength of friction stir welded multi stiffener panels. The undertaken experimental and computational studies have demonstrated that local skin buckling is predominantly influenced by the magnitude of welding induced residual stresses and associated geometric distortions, whereas panel collapse behavior is sensitive to the lateral width of the physically joined skin and stiffener flange material, the strength of material in the Heat Affected Zone as well as the magnitude of the welding induced residual stresses. Copyright © 2006 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.


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Reaxys Database Information
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In silico identification and characterization of protein-ligand binding sites

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.

On the efficiency of data representation on the modeling and characterization of complex networks

Specific choices about how to represent complex networks can have a substantial impact on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically by adjacency matrices or dynamically by adjacency lists. Three theoretical models of complex networks are considered: two types of Erdos-Renyi as well as the Barabasi-Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. degree, clustering coefficient, shortest path length, and betweenness centrality). We found that different forms of representation generally have a substantial effect on the execution time, with the sparse representation frequently resulting in remarkably superior performance. (C) 2011 Elsevier B.V. All rights reserved.