Dielectric and conductivity relaxation in mixtures of glycerol with LiCl

We report a thorough dielectric characterization of the alpha relaxation of glass forming glycerol with varying additions of LiCl. Nine salt concentrations from 0.1 - 20 mol% are investigated in a frequency range of 20 Hz - 3 GHz and analyzed in the dielectric loss and modulus representation. Information on the dc conductivity, the dielectric relaxation time (from the loss) and the conductivity relaxation time (from the modulus) is provided. Overall, with increasing ion concentration, a transition from reorientationally to translationally dominated behavior is observed and the translational ion dynamics and the dipolar reorientational dynamics become successively coupled. This gives rise to the prospect that by adding ions to dipolar glass formers, dielectric spectroscopy may directly couple to the translational degrees of freedom determining the glass transition, even in frequency regimes where usually strong decoupling is observed.Comment: 8 pages, 7 figure

Inferring Gene-Phenotype Associations via Global Protein Complex Network Propagation

BACKGROUND: Phenotypically similar diseases have been found to be caused by functionally related genes, suggesting a modular organization of the genetic landscape of human diseases that mirrors the modularity observed in biological interaction networks. Protein complexes, as molecular machines that integrate multiple gene products to perform biological functions, express the underlying modular organization of protein-protein interaction networks. As such, protein complexes can be useful for interrogating the networks of phenome and interactome to elucidate gene-phenotype associations of diseases. METHODOLOGY/PRINCIPAL FINDINGS: We proposed a technique called RWPCN (Random Walker on Protein Complex Network) for predicting and prioritizing disease genes. The basis of RWPCN is a protein complex network constructed using existing human protein complexes and protein interaction network. To prioritize candidate disease genes for the query disease phenotypes, we compute the associations between the protein complexes and the query phenotypes in their respective protein complex and phenotype networks. We tested RWPCN on predicting gene-phenotype associations using leave-one-out cross-validation; our method was observed to outperform existing approaches. We also applied RWPCN to predict novel disease genes for two representative diseases, namely, Breast Cancer and Diabetes. CONCLUSIONS/SIGNIFICANCE: Guilt-by-association prediction and prioritization of disease genes can be enhanced by fully exploiting the underlying modular organizations of both the disease phenome and the protein interactome. Our RWPCN uses a novel protein complex network as a basis for interrogating the human phenome-interactome network. As the protein complex network can capture the underlying modularity in the biological interaction networks better than simple protein interaction networks, RWPCN was found to be able to detect and prioritize disease genes better than traditional approaches that used only protein-phenotype associations

Differential Expression of Iron Acquisition Genes by Brucella melitensis and Brucella canis during Macrophage Infection

Brucella spp. cause chronic zoonotic disease often affecting individuals and animals in impoverished economic or public health conditions; however, these bacteria do not have obvious virulence factors. Restriction of iron availability to pathogens is an effective strategy of host defense. For brucellae, virulence depends on the ability to survive and replicate within the host cell where iron is an essential nutrient for the growth and survival of both mammalian and bacterial cells. Iron is a particularly scarce nutrient for bacteria with an intracellular lifestyle. Brucella melitensis and Brucella canis share ∼99% of their genomes but differ in intracellular lifestyles. To identify differences, gene transcription of these two pathogens was examined during infection of murine macrophages and compared to broth grown bacteria. Transcriptome analysis of B. melitensis and B. canis revealed differences of genes involved in iron transport. Gene transcription of the TonB, enterobactin, and ferric anguibactin transport systems was increased in B. canis but not B. melitensis during infection of macrophages. The data suggest differences in iron requirements that may contribute to differences observed in the lifestyles of these closely related pathogens. The initial importance of iron for B. canis but not for B. melitensis helps elucidate differing intracellular survival strategies for two closely related bacteria and provides insight for controlling these pathogens

Systematic Review of Medicine-Related Problems in Adult Patients with Atrial Fibrillation on Direct Oral Anticoagulants

New oral anticoagulant agents continue to emerge on the market and their safety requires assessment to provide evidence of their suitability for clinical use. There-fore, we searched standard databases to summarize the English language literature on medicine-related problems (MRPs) of direct oral anticoagulants DOACs (dabigtran, rivaroxban, apixban, and edoxban) in the treatment of adults with atri-al fibrillation. Electronic databases including Medline, Embase, International Pharmaceutical Abstract (IPA), Scopus, CINAHL, the Web of Science and Cochrane were searched from 2008 through 2016 for original articles. Studies pub-lished in English reporting MRPs of DOACs in adult patients with AF were in-cluded. Seventeen studies were identified using standardized protocols, and two reviewers serially abstracted data from each article. Most articles were inconclusive on major safety end points including major bleeding. Data on major safety end points were combined with efficacy. Most studies inconsistently reported adverse drug reactions and not adverse events or medication error, and no definitions were consistent across studies. Some harmful drug effects were not assessed in studies and may have been overlooked. Little evidence is provided on MRPs of DOACs in patients with AF and, therefore, further studies are needed to establish the safety of DOACs in real-life clinical practice

Radar-based road boundary estimation

The topic of automated driving is receiving increasing attention from the scientific community and automotive industry. A key task for an autonomous vehicle is the recognition of drivable area and, in an extension of this, detecting the road boundaries. State-of-the-art techniques often use camera and/or LIDAR sensors to perform this task. However, these sensors can be expensive and not suitable in low visibility situations such as during nighttime or in bad weather. Radar sensors are a viable alternative. The aims of this study are twofold: to introduce a technique of radar-based road boundary estimation (RBE) using radar sensors and to develop a suitable benchmark to compare different radar-based RBE techniques. The RBE algorithm proposed in this study, Clustering-based Urban Road Boundary Estimation (CURBE), clusters the radar detections and incorporates domain knowledge to determine which of the clusters describe road boundaries (so-called boundary clusters). Additionally, we propose a novel benchmark to compare radar RBE algorithms. The benchmark makes use of the nuScenes data set. Each radar reflection in the data set is given a ground truth label. The radar reflection is given the label of boundary point or non-boundary point based on several sources such as the measured radial velocity, object annotations, and a detailed road map. To quantify the performance of an RBE algorithm, the estimated labels outputted by the RBE algorithm are compared to the ground truth labels using the metrics precision, recall, and F1-score. CURBE is evaluated on the benchmark where it achieves an F1-score of 30.4%. We conclude that with the current version of CURBE and with the current method of measuring performance there are not enough grounds to consider this method as a reliable way of RBE. However, the approach shows promise. The method has the potential to significantly improve performance by using a clustering method that is designed for radar data or implementing a different way of selecting boundary clusters. Since the proposed benchmark uses the radar reflections in the data set as ground truth the performance measurement is less accurate in recordings with limited radar coverage, but overall it is concluded that the benchmark provides a fast and consistent way to measure and compare the performance of different RBE algorithms

Access to the CNS: Biomarker Strategies for Dopaminergic Treatments

Despite substantial research carried out over the last decades, it remains difficult to understand the wide range of pharmacological effects of dopaminergic agents. The dopaminergic system is involved in several neurological disorders, such as Parkinson's disease and schizophrenia. This complex system features multiple pathways implicated in emotion and cognition, psychomotor functions and endocrine control through activation of G protein-coupled dopamine receptors. This review focuses on the system-wide effects of dopaminergic agents on the multiple biochemical and endocrine pathways, in particular the biomarkers (i.e., indicators of a pharmacological process) that reflect these effects. Dopaminergic treatments developed over the last decades were found to be associated with numerous biochemical pathways in the brain, including the norepinephrine and the kynurenine pathway. Additionally, they have shown to affect peripheral systems, for example the hypothalamus-pituitary-adrenal (HPA) axis. Dopaminergic agents thus have a complex and broad pharmacological profile, rendering drug development challenging. Considering the complex system-wide pharmacological profile of dopaminergic agents, this review underlines the needs for systems pharmacology studies that include: i) proteomics and metabolomics analysis; ii) longitudinal data evaluation and mathematical modeling; iii) pharmacokinetics-based interpretation of drug effects; iv) simultaneous biomarker evaluation in the brain, the cerebrospinal fluid (CSF) and plasma; and v) specific attention to condition-dependent (e.g., disease) pharmacology. Such approach is considered essential to increase our understanding of central nervous system (CNS) drug effects and substantially improve CNS drug development.Pharmacolog