Material condition assessment with eddy current sensors

Eddy current sensors and sensor arrays are used for process quality and material condition assessment of conducting materials. In an embodiment, changes in spatially registered high resolution images taken before and after cold work processing reflect the quality of the process, such as intensity and coverage. These images also permit the suppression or removal of local outlier variations. Anisotropy in a material property, such as magnetic permeability or electrical conductivity, can be intentionally introduced and used to assess material condition resulting from an operation, such as a cold work or heat treatment. The anisotropy is determined by sensors that provide directional property measurements. The sensor directionality arises from constructs that use a linear conducting drive segment to impose the magnetic field in a test material. Maintaining the orientation of this drive segment, and associated sense elements, relative to a material edge provides enhanced sensitivity for crack detection at edges

Continuous multiparametric monitoring of cell metabolism in response to transient overexpression of the sirtuin deacetylase SIRT3

The analysis and visualisation of research data in an environment which is most similar to living conditions belong to the most challenging claims of present scientific research endeavours. To date, the effect of protein function on cell metabolism is most commonly assessed from a series of end point analyses, which finally allows an approximate estimation on how a specific effect takes its course. In the study presented herein, we demonstrate how the combination of transient transfection and a biosensor chip system gives the opportunity to analyse the effect of a specific protein on cell metabolism in living cells through real-time monitoring of metabolically relevant parameters, such as oxygen consumption, acidification rate and cell adhesion. In addition, this method allows online monitoring of the time course of metabolic changes due to changes in expression levels of metabolic regulative proteins from the time of transfection to maximum overexpression. The methodology presented herein was assessed for the transient overexpression of the sirtuin deacetylase SIRT3, a mitochondrial key element in the regulation of energy metabolism, metabolic disease, cancer and ageing

Metastable Corundum-Type In2O3: Phase Stability, Reduction Properties, and Catalytic Characterization

The phase stability, reduction, and catalytic properties of corundum-type rhombohedral In2O3 have been comparatively studied with respect to its thermodynamically more stable cubic In2O3 counterpart. Phase stability and transformation were observed to be strongly dependent on the gas environment and the reduction potential of the gas phase. As such, reduction in hydrogen caused both the efficient transformation into the cubic polymorph as well as the formation of metallic In especially at high reduction temperatures between 573 and 673 K. In contrast, reduction in CO suppresses the transformation into cubic In2O3 but leads to a larger quantity of In metal at comparable reduction temperatures. This difference is also directly reflected in temperature-dependent conductivity measurements. Catalytic characterization of rh-In2O3 reveals activity in both routes of the water-gas shift equilibrium, which gives rise to a diminished CO2-selectivity of 60% in methanol steam reforming. This is in strong contrast to its cubic counterpart where CO2 selectivities of close to 100% due to the suppressed inverse water-gas shift reaction, have been obtained. Most importantly, rh-In2O3 in fact is structurally stable during catalytic characterization and no unwanted phase transformations are triggered. Thus, the results directly reveal the application-relevant physicochemical properties of rh-In2O3 that might encourage subsequent studies on other less-common In2O3 polymorphs.(VLID)2581066Accepted versio

Macro- and microscopic properties of strontium doped indium oxide

Solid state synthesis and physical mechanisms of electrical conductivity variation in polycrystalline, strontium doped indium oxide In2O3:(SrO)x were investigated for materials with different doping levels at different temperatures (T=20-300 C) and ambient atmosphere content including humidity and low pressure. Gas sensing ability of these compounds as well as the sample resistance appeared to increase by 4 and 8 orders of the magnitude, respectively, with the doping level increase from zero up to x=10%. The conductance variation due to doping is explained by two mechanisms: acceptor-like electrical activity of Sr as a point defect and appearance of an additional phase of SrIn2O4. An unusual property of high level (x=10%) doped samples is a possibility of extraordinarily large and fast oxygen exchange with ambient atmosphere at not very high temperatures (100-200 C). This peculiarity is explained by friable structure of crystallite surface. Friable structure provides relatively fast transition of samples from high to low resistive state at the expense of high conductance of the near surface layer of the grains. Microscopic study of the electro-diffusion process at the surface of oxygen deficient samples allowed estimation of the diffusion coefficient of oxygen vacancies in the friable surface layer at room temperature as 3x10^(-13) cm^2/s, which is by one order of the magnitude smaller than that known for amorphous indium oxide films.Comment: 19 pages, 7 figures, 39 reference

Elevated APOBEC3B Correlates with Poor Outcomes for Estrogen-Receptor-Positive Breast Cancers

Recent observations connected DNA cytosine deaminase APOBEC3B to the genetic evolution of breast cancer. We addressed whether APOBEC3B is associated with breast cancer clinical outcomes. APOBEC3B messenger RNA (mRNA) levels were related in 1,491 primary breast cancers to disease-free (DFS), metastasis-free (MFS), and overall survival (OS). For independent validation, APOBEC3B mRNA expression was associated with patient outcome data in five additional cohorts (over 3,500 breast cancer cases). In univariate Cox regression analysis, increasing APOBEC3B expression as a continuous variable was associated with worse DFS, MFS, and OS (hazard ratio [HR] = 1.20, 1.21, and 1.24, respectively; all P < .001). Also, in untreated ER-positive (ER+), but not in ER−, lymph-node-negative patients, high APOBEC3B levels were associated with a poor DFS (continuous variable: HR = 1.29, P = .001; dichotomized at the median level, HR = 1.66, P = .0002). This implies that APOBEC3B is a marker of pure prognosis in ER + disease. These findings were confirmed in the analyses of five independent patient sets. In these analyses, APOBEC3B expression dichotomized at the median level was associated with adverse outcomes (METABRIC discovery and validation, 788 and 706 ER + cases, disease-specific survival (DSS), HR = 1.77 and HR = 1.77, respectively, both P < .001; Affymetrix dataset, 754 ER + cases, DFS, HR = 1.57, P = 2.46E-04; NKI295, 181 ER + cases, DFS, HR = 1.72, P = .054; and BIG 1-98, 1,219 ER + cases, breast-cancer-free interval (BCFI), HR = 1.42, P = 0.0079). APOBEC3B is a marker of pure prognosis and poor outcomes for ER + breast cancer, which strongly suggests that genetic aberrations induced by APOBEC3B contribute to breast cancer progression. Electronic supplementary material The online version of this article (doi: 10.1007/s12672-014-0196-8) contains supplementary material, which is available to authorized users

Defining functional distances over Gene Ontology

<p>Abstract</p> <p>Background</p> <p>A fundamental problem when trying to define the functional relationships between proteins is the difficulty in quantifying functional similarities, even when well-structured ontologies exist regarding the activity of proteins (i.e. 'gene ontology' -GO-). However, functional metrics can overcome the problems in the comparing and evaluating functional assignments and predictions. As a reference of proximity, previous approaches to compare GO terms considered linkage in terms of ontology weighted by a probability distribution that balances the non-uniform 'richness' of different parts of the Direct Acyclic Graph. Here, we have followed a different approach to quantify functional similarities between GO terms.</p> <p>Results</p> <p>We propose a new method to derive 'functional distances' between GO terms that is based on the simultaneous occurrence of terms in the same set of Interpro entries, instead of relying on the structure of the GO. The coincidence of GO terms reveals natural biological links between the GO functions and defines a distance model <it>D</it>_{<it>f </it>}which fulfils the properties of a Metric Space. The distances obtained in this way can be represented as a hierarchical 'Functional Tree'.</p> <p>Conclusion</p> <p>The method proposed provides a new definition of distance that enables the similarity between GO terms to be quantified. Additionally, the 'Functional Tree' defines groups with biological meaning enhancing its utility for protein function comparison and prediction. Finally, this approach could be for function-based protein searches in databases, and for analysing the gene clusters produced by DNA array experiments.</p

Domain-Domain Interactions Underlying Herpesvirus-Human Protein-Protein Interaction Networks

Protein-domains play an important role in mediating protein-protein interactions. Furthermore, the same domain-pairs mediate different interactions in different contexts and in various organisms, and therefore domain-pairs are considered as the building blocks of interactome networks. Here we extend these principles to the host-virus interface and find the domain-pairs that potentially mediate human-herpesvirus interactions. Notably, we find that the same domain-pairs used by other organisms for mediating their interactions underlie statistically significant fractions of human-virus protein inter-interaction networks. Our analysis shows that viral domains tend to interact with human domains that are hubs in the human domain-domain interaction network. This may enable the virus to easily interfere with a variety of mechanisms and processes involving various and different human proteins carrying the relevant hub domain. Comparative genomics analysis provides hints at a molecular mechanism by which the virus acquired some of its interacting domains from its human host

Biological Process Linkage Networks

BACKGROUND. The traditional approach to studying complex biological networks is based on the identification of interactions between internal components of signaling or metabolic pathways. By comparison, little is known about interactions between higher order biological systems, such as biological pathways and processes. We propose a methodology for gleaning patterns of interactions between biological processes by analyzing protein-protein interactions, transcriptional co-expression and genetic interactions. At the heart of the methodology are the concept of Linked Processes and the resultant network of biological processes, the Process Linkage Network (PLN). RESULTS. We construct, catalogue, and analyze different types of PLNs derived from different data sources and different species. When applied to the Gene Ontology, many of the resulting links connect processes that are distant from each other in the hierarchy, even though the connection makes eminent sense biologically. Some others, however, carry an element of surprise and may reflect mechanisms that are unique to the organism under investigation. In this aspect our method complements the link structure between processes inherent in the Gene Ontology, which by its very nature is species-independent. As a practical application of the linkage of processes we demonstrate that it can be effectively used in protein function prediction, having the power to increase both the coverage and the accuracy of predictions, when carefully integrated into prediction methods. CONCLUSIONS. Our approach constitutes a promising new direction towards understanding the higher levels of organization of the cell as a system which should help current efforts to re-engineer ontologies and improve our ability to predict which proteins are involved in specific biological processes.Lynn and William Frankel Center for Computer Science; the Paul Ivanier center for robotics research and production; National Science Foundation (ITR-048715); National Human Genome Research Institute (1R33HG002850-01A1, R01 HG003367-01A1); National Institute of Health (U54 LM008748