Multiple human single-stranded DNA binding proteins function in genome maintenance : structural, biochemical and functional analysis

DNA exists predominantly in a duplex form that is preserved via specific base pairing. This base pairing affords a considerable degree of protection against chemical or physical damage and preserves coding potential. However, there are many situations, e.g. during DNA damage and programmed cellular processes such as DNA replication and transcription, in which the DNA duplex is separated into two singlestranded DNA (ssDNA) strands. This ssDNA is vulnerable to attack by nucleases, binding by inappropriate proteins and chemical attack. It is very important to control the generation of ssDNA and protect it when it forms, and for this reason all cellular organisms and many viruses encode a ssDNA binding protein (SSB). All known SSBs use an oligosaccharide/oligonucleotide binding (OB)-fold domain for DNA binding. SSBs have multiple roles in binding and sequestering ssDNA, detecting DNA damage, stimulating strand-exchange proteins and helicases, and mediation of protein–protein interactions. Recently two additional human SSBs have been identified that are more closely related to bacterial and archaeal SSBs. Prior to this it was believed that replication protein A, RPA, was the only human equivalent of bacterial SSB. RPA is thought to be required for most aspects of DNA metabolism including DNA replication, recombination and repair. This review will discuss in further detail the biological pathways in which human SSBs function.

Multiple stages classification of Alzheimer’s disease based on structural brain networks using generalized low rank approximations (GLRAM)

To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.

A Kalman filter based strategy for linear structural system identification based on multiple static and dynamic test data

The problem of identification of stiffness, mass and damping properties of linear structural systems, based on multiple sets of measurement data originating from static and dynamic tests is considered. A strategy, within the framework of Kalman filter based dynamic state estimation, is proposed to tackle this problem. The static tests consists of measurement of response of the structure to slowly moving loads, and to static loads whose magnitude are varied incrementally; the dynamic tests involve measurement of a few elements of the frequency response function (FRF) matrix. These measurements are taken to be contaminated by additive Gaussian noise. An artificial independent variable τ, that simultaneously parameterizes the point of application of the moving load, the magnitude of the incrementally varied static load and the driving frequency in the FRFs, is introduced. The state vector is taken to consist of system parameters to be identified. The fact that these parameters are independent of the variable τ is taken to constitute the set of ‘process’ equations. The measurement equations are derived based on the mechanics of the problem and, quantities, such as displacements and/or strains, are taken to be measured. A recursive algorithm that employs a linearization strategy based on Neumann’s expansion of structural static and dynamic stiffness matrices, and, which provides posterior estimates of the mean and covariance of the unknown system parameters, is developed. The satisfactory performance of the proposed approach is illustrated by considering the problem of the identification of the dynamic properties of an inhomogeneous beam and the axial rigidities of members of a truss structure.

Particle filters for structural system identification using multiple test and sensor data: A combined computational and experimental study

The problem of structural system identification when measurements originate from multiple tests and multiple sensors is considered. An offline solution to this problem using bootstrap particle filtering is proposed. The central idea of the proposed method is the introduction of a dummy independent variable that allows for simultaneous assimilation of multiple measurements in a sequential manner. The method can treat linear/nonlinear structural models and allows for measurements on strains and displacements under static/dynamic loads. Illustrative examples consider measurement data from numerical models and also from laboratory experiments. The results from the proposed method are compared with those from a Kalman filter-based approach and the superior performance of the proposed method is demonstrated. Copyright (C) 2009 John Wiley & Sons, Ltd.

Structural and thermodynamic properties of Fe1.12Te with multiple phase transitions

The parent compound of iron chalcogenide superconductors, Fe1+yTe, with a range of excess Fe concentrations exhibits intriguing structural and magnetic properties. Here, the interplay of magnetic and structural properties of Fe1.12Te single crystals have been probed by low-temperature synchrotron X-ray powder diffraction, magnetization, and specific heat measurements. Thermodynamic measurements reveal two distinct phase transitions, considered unique to samples possessing excess Fe content in the range of 0.11 <= y <= 0.13. On cooling, an antiferromagnetic transition, T-N approximate to 57K is observed. A closer examination of powder diffraction data suggests that the transition at TN is not purely magnetic, but accompanied by the commencement of a structural phase transition from tetragonal to orthorhombic symmetry. This is followed by a second prominent first-order structural transition at T-S with T-S < T-N, where an onset of monoclinic distortion is observed. The results point to a strong magneto-structural coupling in this material. (C) 2014 AIP Publishing LLC.

Raman spectroscopy explores molecular structural signatures of hidden materials in depth: Universal Multiple Angle Raman Spectroscopy

Non-invasive 3D imaging in materials and medical research involves methodologies such as X-ray imaging, MRI, fluorescence and optical coherence tomography, NIR absorption imaging, etc., providing global morphological/density/absorption changes of the hidden components. However, molecular information of such buried materials has been elusive. In this article we demonstrate observation of molecular structural information of materials hidden/buried in depth using Raman scattering. Typically, Raman spectroscopic observations are made at fixed collection angles, such as, 906, 1356, and 1806, except in spatially offset Raman scattering (SORS) (only back scattering based collection of photons) and transmission techniques. Such specific collection angles restrict the observations of Raman signals either from or near the surface of the materials. Universal Multiple Angle Raman Spectroscopy (UMARS) presented here employs the principle of (a) penetration depth of photons and then diffuse propagation through non-absorbing media by multiple scattering and (b) detection of signals from all the observable angles.

Structural Design under Seismic Risk Using Multiple Performance Objectives

Structural design is a decision-making process in which a wide spectrum of requirements, expectations, and concerns needs to be properly addressed. Engineering design criteria are considered together with societal and client preferences, and most of these design objectives are affected by the uncertainties surrounding a design. Therefore, realistic design frameworks must be able to handle multiple performance objectives and incorporate uncertainties from numerous sources into the process.

In this study, a multi-criteria based design framework for structural design under seismic risk is explored. The emphasis is on reliability-based performance objectives and their interaction with economic objectives. The framework has analysis, evaluation, and revision stages. In the probabilistic response analysis, seismic loading uncertainties as well as modeling uncertainties are incorporated. For evaluation, two approaches are suggested: one based on preference aggregation and the other based on socio-economics. Both implementations of the general framework are illustrated with simple but informative design examples to explore the basic features of the framework.

The first approach uses concepts similar to those found in multi-criteria decision theory, and directly combines reliability-based objectives with others. This approach is implemented in a single-stage design procedure. In the socio-economics based approach, a two-stage design procedure is recommended in which societal preferences are treated through reliability-based engineering performance measures, but emphasis is also given to economic objectives because these are especially important to the structural designer's client. A rational net asset value formulation including losses from uncertain future earthquakes is used to assess the economic performance of a design. A recently developed assembly-based vulnerability analysis is incorporated into the loss estimation.

The presented performance-based design framework allows investigation of various design issues and their impact on a structural design. It is a flexible one that readily allows incorporation of new methods and concepts in seismic hazard specification, structural analysis, and loss estimation.

Effects of constraint curvature on structural instability: tensile buckling and multiple bifurcations

Bifurcation of an elastic structure crucially depends on the curvature of the constraints against which the ends of the structure are prescribed to move, an effect which deserves more attention than it has received so far. In fact, we show theoretically and we provide definitive experimental verification that an appropriate curvature of the constraint over which the end of a structure has to slide strongly affects buckling loads and can induce: (i.) tensile buckling; (ii.) decreasing- (softening), increasing- (hardening), or constant-load (null stiffness) postcritical behaviour; (iii.) multiple bifurcations, determining for instance two bifurcation loads (one tensile and one compressive) in a single-degree-of-freedom elastic system. We show how to design a constraint profile to obtain a desired postcritical behaviour and we provide the solution for the elastica constrained to slide along a circle on one end, representing the first example of an inflexional elastica developed from a buckling in tension. These results have important practical implications in the design of compliant mechanisms and may find applications in devices operating in quasi-static or dynamic conditions.

Effect of trimethylgallium flow on the structural and optical properties of InGaN/GaN multiple quantum wells

InGaN/GaN multiple quantum wells (MQWs) are grown by metal-organic chemical vapour deposition on (0001) sapphire substrates. Triple-axis X-ray diffraction (TXRD) and photoluminescence (PL) spectra are used to assess the influence of trimethylgallium (TMGa) flow on structural defects, such as dislocations and interface roughness, and the optical properties of the MQWs. In this paper, a method, involving an ! scan of every satellite peak of TXRD, is presented to measure the mean dislocation density of InGaN/GaN MQWs. The experimental results show that under certain conditions which keep the trimethlyindium flow constant, dislocation density and interface roughness decrease with the increase of TMGa flow, which will improve the PL properties. It can be concluded that dislocations, especially edge dislocations, act as nonradiative recombination centres in InGaN/GaN MQWs. Also noticed is that changing the TMGa flow has more influence on edge dislocations than screw dislocations.

Effect of critical thickness on structural and optical properties of InxGa1-xN/GaN multiple quantum wells

InGaN/GaN multiquantum-well (MQW) structures grown by metalorganic chemical-vapor deposition on n-type GaN and capped by p-type GaN were investigated by cross-sectional transmission electron microscopy, double crystal x-ray diffraction, and temperature-dependent photoluminescence. For the sample with strained-layer thicknesses greater than the critical thicknesses, a high density of pure edge type threading dislocations generated from MQW layers and extended to the cap layer was observed. These dislocations result from a relaxation of the strained layers when their thicknesses are beyond the critical thicknesses. Because of indium outdiffusion from the well layers due to the anneal effect of Mg-doped cap layer growth and defects generated from strain relaxation, the PL emission peak was almost depressed by the broad yellow band with an intensity maximum at 2.28 eV. But for the sample with strained-layer thicknesses less than the critical thicknesses, it has no such phenomenon. The measured critical thicknesses are consistent with the calculated values using the model proposed by Fischer, Kuhne, and Richter. (C) 2004 American Institute of Physics.

Influence of cracks generation on the structural and optical properties of GaN/Al0.55Ga0.45N multiple quantum wells

Both cracked and crack-free GaN/Al0.55Ga0.45N multiple quantum wells (MQWs) grown on GaN template by metalorganic chemical vapor deposition have been studied by triple-axis X-ray diffraction, grazing-incidence X-ray reflectivity, atomic force microscope, photoluminescence spectroscopy and low-energy positron annihilation spectroscopy. The experimental results show that cracks generation not only deteriorates the surface morphology, but also leads to a period dispersion and roughens the interfaces of MQWs. The mean density of dislocations in MQWs, determined from the average full-width at half-maximum of to-scan of each satellite peak, has been significantly enhanced by the cracks generation. Furthermore, the measurement of annihilation-line Doppler broadening reveals a higher concentration of negatively charged vacancies in the cracked MQWs. The combination of these vacancies and the high density of edge dislocations are assumed to contribute to the highly enhanced yellow luminescence in the cracked sample. (c) 2005 Elsevier B.V. All rights reserved.

Structural characterization and identification of dibenzocyclooctadiene lignans in Fructus Schisandrae using electrospray ionization ion trap multiple-stage tandem mass spectrometry and electrospray ionization Fourier transform ion cyclotron resonance multiple-stage tandem mass spectrometry

The electrospray ionization ion trap multiple-stage tandem mass spectrometry (ESI-MSn) and electrospray ionization Fourier transform ion cyclotron resonance multiple-stage tandem mass spectrometry (ESI-FT-ICR-MSn) have been applied successfully to the direct investigation of a number of dibenzocyclooctadiene lignan constituents from the methanol extracts of the Fructus Schisandrae in the positive ion mode. The detailed structural characterization of the same skeleton and different peripheral substituents had been studied and the precise elemental compositions of ions at high mass resolution had been obtained. So the fragmentation mechanisms could be clarified.

Multiple cutout optimization in composite plates using evolutionary structural optimization

The optimization of cutouts in composite plates was investigated by implementing a procedure known as Evolutionary Structural Optimization. Perforations were introduced into a finite element mesh of the plate from which one or more cutouts of a predetermined size were evolved. In the examples presented, plates were rejected from around each evolving cutout based on a predefined rejection criterion. The Limiting ply within each plate element around the cutout was determined based on the Tsai-Hill failure criterion. Finite element plates with values below the product of the average Tsai-Hill number and a rejection criterion were subsequently removed. This process was iterated until a steady state was reached and the rejection criterion was then incremented by an evolutionary rate and the above steps repeated until the desired cutout area was achieved. Various plates with differing lay-up and loading parameters were investigated to demonstrate the generality and robustness of this optimization procedure.