High Quality Bioreplication of Intricate nanostructures from a Fragile Gecko Skin Surface with Bactericidal Properties

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A genome-wide association study implicates the pleiotropic effect of NMUR2 on asthma and COPD

Asthma and chronic obstructive pulmonary disease (COPD) are two distinct diseases that are associated with chronic inflammation. They share common features in terms of their advanced stages and genetic factors. This study aimed to identify novel genes underlying both asthma and COPD using genome-wide association study (GWAS) to differentiate between the two diseases. We performed a GWAS of asthma and COPD in 7828 Koreans from three hospitals. In addition, we investigated genetic correlations. The UK Biobank dataset was used for the replication studies. We found that rs2961757, located near neuromedin U receptor 2 (NMUR2) on chromosome 5, was genome-wide significant ([Formula: see text] = 0.44, P-valueAsthma-COPD = 3.41 × 10-8), and significant results were replicated with the UK Biobank data ([Formula: see text] = 0.04, P-valueAsthma-COPD = 0.0431). A positive genetic correlation was observed between asthma and COPD (39.8% in the Korean dataset and 49.8% in the UK Biobank dataset). In this study, 40-45% of the genetic effects were common to asthma and COPD. Moreover, NMUR2 increases the risk of asthma development and suppresses COPD development. This indicates that NMUR2 allows for better differentiation of both diseases, which can facilitate tailored medical therapy

A Genome-Wide Knockout Screen in Human Macrophages Identified Host Factors Modulating Salmonella Infection.

A genome-scale CRISPR knockout library screen of THP-1 human macrophages was performed to identify loss-of-function mutations conferring resistance to Salmonella uptake. The screen identified 183 candidate genes, from which 14 representative genes involved in actin dynamics (ACTR3, ARPC4, CAPZB, TOR3A, CYFIP2, CTTN, and NHLRC2), glycosaminoglycan metabolism (B3GNT1), receptor signaling (PDGFB and CD27), lipid raft formation (CLTCL1), calcium transport (ATP2A2 and ITPR3), and cholesterol metabolism (HMGCR) were analyzed further. For some of these pathways, known chemical inhibitors could replicate the Salmonella resistance phenotype, indicating their potential as targets for host-directed therapy. The screen indicated a role for the relatively uncharacterized gene NHLRC2 in both Salmonella invasion and macrophage differentiation. Upon differentiation, NHLRC2 mutant macrophages were hyperinflammatory and did not exhibit characteristics typical of macrophages, including atypical morphology and inability to interact and phagocytose bacteria/particles. Immunoprecipitation confirmed an interaction of NHLRC2 with FRYL, EIF2AK2, and KLHL13.IMPORTANCESalmonella exploits macrophages to gain access to the lymphatic system and bloodstream to lead to local and potentially systemic infections. With an increasing number of antibiotic-resistant isolates identified in humans, Salmonella infections have become major threats to public health. Therefore, there is an urgent need to identify alternative approaches to anti-infective therapy, including host-directed therapies. In this study, we used a simple genome-wide screen to identify 183 candidate host factors in macrophages that can confer resistance to Salmonella infection. These factors may be potential therapeutic targets against Salmonella infections

Incorporating topological information for predicting robust cancer subnetwork markers in human protein-protein interaction network

BACKGROUND: Discovering robust markers for cancer prognosis based on gene expression data is an important yet challenging problem in translational bioinformatics. By integrating additional information in biological pathways or a protein-protein interaction (PPI) network, we can find better biomarkers that lead to more accurate and reproducible prognostic predictions. In fact, recent studies have shown that, “modular markers,” that integrate multiple genes with potential interactions can improve disease classification and also provide better understanding of the disease mechanisms. RESULTS: In this work, we propose a novel algorithm for finding robust and effective subnetwork markers that can accurately predict cancer prognosis. To simultaneously discover multiple synergistic subnetwork markers in a human PPI network, we build on our previous work that uses affinity propagation, an efficient clustering algorithm based on a message-passing scheme. Using affinity propagation, we identify potential subnetwork markers that consist of discriminative genes that display coherent expression patterns and whose protein products are closely located on the PPI network. Furthermore, we incorporate the topological information from the PPI network to evaluate the potential of a given set of proteins to be involved in a functional module. Primarily, we adopt widely made assumptions that densely connected subnetworks may likely be potential functional modules and that proteins that are not directly connected but interact with similar sets of other proteins may share similar functionalities. CONCLUSIONS: Incorporating topological attributes based on these assumptions can enhance the prediction of potential subnetwork markers. We evaluate the performance of the proposed subnetwork marker identification method by performing classification experiments using multiple independent breast cancer gene expression datasets and PPI networks. We show that our method leads to the discovery of robust subnetwork markers that can improve cancer classification. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1224-1) contains supplementary material, which is available to authorized users

Differences in Disease Severity but Similar Telomere Lengths in Genetic Subgroups of Patients with Telomerase and Shelterin Mutations

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Improved ground-state modulation characteristics in 1.3 μm InAs/GaAs quantum dot lasers by rapid thermal annealing

We investigated the ground-state (GS) modulation characteristics of 1.3 μm InAs/GaAs quantum dot (QD) lasers that consist of either as-grown or annealed QDs. The choice of annealing conditions was determined from our recently reported results. With reference to the as-grown QD lasers, one obtains approximately 18% improvement in the modulation bandwidth from the annealed QD lasers. In addition, the modulation efficiency of the annealed QD lasers improves by approximately 45% as compared to the as-grown ones. The observed improvements are due to (1) the removal of defects which act as nonradiative recombination centers in the QD structure and (2) the reduction in the Auger-related recombination processes upon annealing

Investigation on the Plasma-Induced Emission Properties of Large Area Carbon Nanotube Array Cathodes with Different Morphologies

Large area well-aligned carbon nanotube (CNT) arrays with different morphologies were synthesized by using a chemical vapor deposition. The plasma-induced emission properties of CNT array cathodes with different morphologies were investigated. The ratio of CNT height to CNT-to-CNT distance has considerable effects on their plasma-induced emission properties. As the ratio increases, emission currents of CNT array cathodes decrease due to screening effects. Under the pulse electric field of about 6 V/μm, high-intensity electron beams of 170–180 A/cm2 were emitted from the surface plasma. The production mechanism of the high-intensity electron beams emitted from the CNT arrays was plasma-induced emission. Moreover, the distribution of the electron beams was in situ characterized by the light emission from the surface plasma

The economic burden of musculoskeletal disease in Korea: A cross sectional study

<p>Abstract</p> <p>Background</p> <p>Musculoskeletal diseases are becoming increasingly important due to population aging. However, studies on the economic burden of musculoskeletal disease in Korea are scarce. Therefore, we conducted a population-based study to measure the economic burden of musculoskeletal disease in Korea using nationally representative data.</p> <p>Methods</p> <p>This study used a variety of data sources such as national health insurance statistics, the Korea Health Panel study and cause of death reports generated by the Korea National Statistical Office to estimate the economic burden of musculoskeletal disease. The total cost of musculoskeletal disease was estimated as the sum of direct medical care costs, direct non-medical care costs, and indirect costs. Direct medical care costs are composed of the costs paid by the insurer and patients, over the counter drugs costs, and other costs such as medical equipment costs. Direct non-medical costs are composed of transportation and caregiver costs. Indirect costs are the sum of the costs associated with premature death and the costs due to productivity loss. Age, sex, and disease specific costs were estimated.</p> <p>Results</p> <p>Among the musculoskeletal diseases, the highest costs are associated with other dorsopathies, followed by disc disorder and arthrosis. The direct medical and direct non-medical costs of all musculoskeletal diseases were $4.18 billion and$338 million in 2008, respectively. Among the indirect costs, those due to productivity loss were $2.28 billion and costs due to premature death were$79 million. The proportions of the total costs incurred by male and female patients were 33.8% and 66.2%, respectively, and the cost due to the female adult aged 20-64 years old was highest. The total economic cost of musculoskeletal disease was $6.89 billion, which represents 0.7% of the Korean gross domestic product.</p> <p>Conclusions</p> <p>The economic burden of musculoskeletal disease in Korea is substantial. As the Korean population continues to age, the economic burden of musculoskeletal disease will continue to increase. Policy measures aimed at controlling the cost of musculoskeletal disease are therefore required.</p

A Genome-Wide Investigation of SNPs and CNVs in Schizophrenia

We report a genome-wide assessment of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) in schizophrenia. We investigated SNPs using 871 patients and 863 controls, following up the top hits in four independent cohorts comprising 1,460 patients and 12,995 controls, all of European origin. We found no genome-wide significant associations, nor could we provide support for any previously reported candidate gene or genome-wide associations. We went on to examine CNVs using a subset of 1,013 cases and 1,084 controls of European ancestry, and a further set of 60 cases and 64 controls of African ancestry. We found that eight cases and zero controls carried deletions greater than 2 Mb, of which two, at 8p22 and 16p13.11-p12.4, are newly reported here. A further evaluation of 1,378 controls identified no deletions greater than 2 Mb, suggesting a high prior probability of disease involvement when such deletions are observed in cases. We also provide further evidence for some smaller, previously reported, schizophrenia-associated CNVs, such as those in NRXN1 and APBA2. We could not provide strong support for the hypothesis that schizophrenia patients have a significantly greater “load” of large (>100 kb), rare CNVs, nor could we find common CNVs that associate with schizophrenia. Finally, we did not provide support for the suggestion that schizophrenia-associated CNVs may preferentially disrupt genes in neurodevelopmental pathways. Collectively, these analyses provide the first integrated study of SNPs and CNVs in schizophrenia and support the emerging view that rare deleterious variants may be more important in schizophrenia predisposition than common polymorphisms. While our analyses do not suggest that implicated CNVs impinge on particular key pathways, we do support the contribution of specific genomic regions in schizophrenia, presumably due to recurrent mutation. On balance, these data suggest that very few schizophrenia patients share identical genomic causation, potentially complicating efforts to personalize treatment regimens