Multipurpose modular experimental station for the DiProI beamline of Fermi@Elettra free electron laser

We present a compact modular apparatus with a flexible design that will be operated at the DiProI beamline of the Fermi@Elettra free electron laser (FEL) for performing static and time-resolved coherent diffraction imaging experiments, taking advantage of the full coherence and variable polarization of the short seeded FEL pulses. The apparatus has been assembled and the potential of the experimental setup is demonstrated by commissioning tests with coherent synchrotron radiation. This multipurpose experimental station will be open to general users after installation at the Fermi@Elettra free electron laser in 2011.     

Topography simulation of sputtering using an algorithm with second order approximation in space

For the efficient simulation of topography evolution due to, e.g., focused ion beam processes, continuum surface advancement algorithms are commonly used. In this work we present a two-dimensional surface advancement algorithm that uses circular arcs between nodes and allows kinks in the surface. The algorithm is based on the method of characteristics, which yields the motion of the points and the slope of the surface. By the interpolation with circular arcs not only the final result is better represented, but also more accurate simulation is possible after insertion of new points as the surface evolves. Kinks in the surface (shocks) are detected by the generation of loops in the surface string or by a new criterion based on the analysis of infinitesimally separated characteristics. It requires the curvature of the surface, which may readily be determined from the radii of the circular arcs. The proposed algorithm uses a second order approximation in space and therefore requires fewer data points during calculation than first order methods. It is shown to converge with third order as a function of node number. The method is demonstrated by examples of trench formation including the effect of redeposition and of facet formation from a step-like surface.     

Age and individual differences in prospective memory during a "Virtual Week": The roles of working memory, vigilance, task regularity, and cue focality.

Young (ages 18–22 years) and older (ages 61–87 years) adults (N = 106) played the Virtual Week board game, which involves simulating common prospective memory (PM) tasks of everyday life (e.g., taking medication), and performed working memory (WM) and vigilance tasks. The Virtual Week game includes regular (repeated) and irregular (nonrepeated) PM tasks with cues that are either more or less focal to other ongoing activities. Age differences in PM were reduced for repeated tasks, and performance improved over the course of the week, suggesting retrieval was more spontaneous or habitual. Correlations with WM within each age group were reduced for PM tasks that had more regular or focal cues. WM (but not vigilance) ability was a strong predictor of irregular PM tasks with less focal cues. Taken together, these results support the hypothesis that habitual and focally cued PM tasks are less demanding of attentional resources (specifically, WM), whereas tasks that are more demanding of controlled attentional processes produce larger age differences, which may be attributable to individual differences in WM. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Shifting the pH Optima of (R)-Selective Transaminases by Protein Engineering

Amine transaminases (ATAs) are powerful biocatalysts for the stereoselective synthesis of chiral amines. However, wild-type ATAs usually show pH optima at slightly alkaline values and exhibit low catalytic activity under physiological conditions. For efficient asymmetric synthesis ATAs are commonly used in combination with lactate dehydrogenase (LDH, optimal pH: 7.5) and glucose dehydrogenase (GDH, optimal pH: 7.75) to shift the equilibrium towards the synthesis of the target chiral amine and hence their pH optima should fit to each other. Based on a protein structure alignment, variants of (R)-selective transaminases were rationally designed, produced in E. coli, purified and subjected to biochemical characterization. This resulted in the discovery of the variant E49Q of the ATA from Aspergillus fumigatus, for which the pH optimum was successfully shifted from pH 8.5 to 7.5 and this variant furthermore had a two times higher specific activity than the wild-type protein at pH 7.5. A possible mechanism for this shift of the optimal pH is proposed. Asymmetric synthesis of (R)-1-phenylethylamine from acetophenone in combination with LDH and GDH confirmed that the variant E49Q shows superior performance at pH 7.5 compared to the wild-type enzyme.     

CCBE1 Is Essential for Epicardial Function during Myocardium Development

The epicardium is a single cell layer of mesothelial cells that plays a critical role during heart development contributing to different cardiac cell types of the developing heart through epithelial-to-mesenchymal transition (EMT). Moreover, the epicardium is a source of secreted growth factors that promote myocardial growth. CCBE1 is a secreted extracellular matrix protein expressed by epicardial cells that is required for the formation of the primitive coronary plexus. However, the role of CCBE1 during epicardial development was still unknown. Here, using a Ccbe1 knockout (KO) mouse model, we observed that loss of CCBE1 leads to congenital heart defects including thinner and hyper-trabeculated ventricular myocardium. In addition, Ccbe1 mutant hearts displayed reduced proliferation of cardiomyocyte and epicardial cells. Epicardial outgrowth culture assay to assess epicardial-derived cells (EPDC) migration showed reduced invasion of the collagen gel by EPDCs in Ccbe1 KO epicardial explants. Ccbe1 KO hearts also displayed fewer nonmyocyte/nonendothelial cells intramyocardially with a reduced proliferation rate. Additionally, RNA-seq data and experimental validation by qRT-PCR showed a marked deregulation of EMT-related genes in developing Ccbe1 mutant hearts. Together, these findings indicate that the myocardium defects in Ccbe1 KO mice arise from disruption of epicardial development and function.     

Impact of Melatonin on RAW264.7 Macrophages during Mechanical Strain

The concentration of melatonin is elevated during the night when patients mainly wear removable orthodontic appliances. Next to periodontal ligament fibroblasts and osteoblasts, macrophages react to mechanical strain with an increased expression of inflammatory mediators. Here, we investigated the impact of melatonin on RAW264.7 macrophages exposed to tensile or compressive strain occurring during orthodontic tooth movement in the periodontal ligament. Before exposure to mechanical strain for 4 h, macrophages were pre-incubated with different melatonin concentrations for 24 h, to determine the dependence of melatonin concentration. Afterwards, we performed experiments with and without mechanical strain, the most effective melatonin concentration (25 µM), and the melatonin receptor 2 (MT2) specific antagonist 4P-PDOT. The expression of inflammatory genes and proteins was investigated by RT-qPCR, ELISAs, and immunoblot. Both tensile and compressive strain increased the expression of the investigated inflammatory factors interleukin-1-beta, interleukin-6, tumor necrosis factor alpha, and prostaglandin endoperoxide synthase-2. This effect was inhibited by the addition of melatonin. Incubation with 4P-PDOT blocked this anti-inflammatory effect of melatonin. Melatonin had an anti-inflammatory effect on macrophages exposed to mechanical strain, independent of the type of mechanical strain. As inhibition was possible with 4P-PDOT, the MT2 receptor might be involved in the regulation of the observed effects.     

Improved Bladder Tumor RNA Isolation from Archived Tissues Using Methylene Blue for Normalization,Multiplex RNA Hybridization,Sequencing and Subtyping

Methylene blue (MB) is a dye used for histology with clinical importance and intercalates into nucleic acids. After MB staining of formalin fixed paraffin embedded (FFPE) muscle invasive bladder cancer (MIBC) and normal urothelium, specific regions could be microdissected. It is not known if MB influences RNA used for gene expression studies. Therefore, we analyzed MIBC using five different RNA isolation methods comparing patient matched FFPE and fresh frozen (FF) tissues pre-stained with or without MB. We demonstrate a positive impact of MB on RNA integrity with FF tissues using real time PCR with no interference of its chemical properties. FFPE tissues showed no improvement of RNA integrity, which we propose is due to formalin induced nucleotide crosslinks. Using direct multiplex RNA hybridization the best genes for normalization of MIBC and control tissues were identified from 34 reference genes. In addition, 5SrRNA and 5.8SrRNA were distinctive reference genes detecting <200 bp fragments important for mRNA analyses. Using these normalized RNAs from MB stained MIBC and applying multiplex RNA hybridization and mRNA sequencing, a minimal gene expression panel precisely identified luminal and basal MIBC tumor subtypes, important for diagnosis, prognosis and chemotherapy response.     

The Pro-Inflammatory Deletion Allele of the NF-κB1 Polymorphism Is Characterized by a Depletion of Subunit p50 in Sepsis

The functionally important NF-κB1 promoter polymorphism (−94ins/delATTG) significantly shapes inflammation and impacts the outcome of sepsis. However, exploratory studies elucidating the molecular link of this genotype-dependent pattern are lacking. Accordingly, we analyzed lipopolysaccharide-stimulated peripheral blood mononuclear cells from both healthy volunteers (n = 20) and septic patients (n = 10). All individuals were genotyped for the −94ins/delATTG NF-κB1 promoter polymorphism. We found a diminished nuclear activity of the NF-κB subunit p50 in ID/DD genotypes after 48 h of lipopolysaccharide stimulation compared to II genotypes (p = 0.025). This was associated with higher TNF-α (p = 0.005) and interleukin 6 concentrations (p = 0.014) and an increased production of mitochondrial radical oxygen species in ID/DD genotypes (p = 0.001). Although ID/DD genotypes showed enhanced activation of mitochondrial biogenesis, they still had a significantly diminished cellular ATP content (p = 0.046) and lower mtDNA copy numbers (p = 0.010) compared to II genotypes. Strikingly, these findings were mirrored in peripheral blood mononuclear cells taken from septic patients. Our results emphasize the crucial aspect of considering NF-κB subunits in sepsis. We showed here that the deletion allele of the NF-κB1 (−94ins/delATTG) polymorphism was associated with the lower nuclear activity of subunit p50, which, in turn, was associated with aggravated inflammation and mitochondrial dysfunction.     

Automatic classifier selection for non-experts

Choosing a suitable classifier for a given dataset is an important part of developing a pattern recognition system. Since a large variety of classification algorithms are proposed in literature, non-experts do not know which method should be used in order to obtain good classification results on their data. Meta-learning tries to address this problem by recommending promising classifiers based on meta-features computed from a given dataset. In this paper, we empirically evaluate five different categories of state-of-the-art meta-features for their suitability in predicting classification accuracies of several widely used classifiers (including Support Vector Machines, Neural Networks, Random Forests, Decision Trees, and Logistic Regression). Based on the evaluation results, we have developed the first open source meta-learning system that is capable of accurately predicting accuracies of target classifiers. The user provides a dataset as input and gets an automatically created high-performance ready-to-use pattern recognition system in a few simple steps. A user study of the system with non-experts showed that the users were able to develop more accurate pattern recognition systems in significantly less development time when using our system as compared to using a state-of-the-art data mining software.     

Diverse nearest neighbors queries using linear skylines

k-nearest neighbor (k-NN) queries are well-known and widely used in a plethora of applications. However, in the original definition of k-NN queries there is no concern regarding diversity of the answer set with respect to the user’s interests. For instance, travelers may be looking for touristic sites that are close to where they are, but that would also lead them to see different parts of the city. Likewise, if one is looking for restaurants close by, it may be more interesting to learn about restaurants of different categories or ethnicities which are nonetheless relatively close. The interesting novel aspect of this type of query is that there are two competing criteria to be optimized: closeness and diversity. We propose two approaches that leverage the notion of linear skyline queries in order to find the k diverse nearest neighbors within a radius r from a given query point, or (k, r)-DNNs for short. Our proposed approaches return a relatively small set containing all optimal solutions for any linear combination of the weights a user could give to the two competing criteria, and we consider three different notions of diversity: spatial, categorical and angular. Our experiments, varying a number of parameters and exploring synthetic and real datasets, in both Euclidean space and road networks, respectively, show that our approaches are several orders of magnitude faster than a straightforward approach.