Clinical impact of antibiotic-resistant Gram-positive pathogens

AbstractThe European Union’s attention to the problem of antibacterial resistance will soon reach a 10-year mark, but the rates of resistance in Gram-positive and Gram-negative bacteria are still increasing. This review focuses on the clinical impact of resistant Gram-positive bacteria on patients. Multiple drug resistance in pneumococcal infections will lead to more treatment failures and higher mortality, which so far have been seen with penicillins and pathogens with high-level resistance. Several studies have demonstrated higher mortality, prolonged length of hospital stay and higher costs associated with methicillin-resistant Staphylococcus aureus infections, in comparison with methicillin-susceptible Staphylococcus aureus infections. Similarly, vancomycin-resistant enterococci bloodstream infections have a negative impact with respect to mortality, length of hospital stay and costs, in comparison with infections due to vancomycin-susceptible enterococci. Several distinctive prophylactic and therapeutic approaches have to be undertaken to successfully prevent the clinical consequences of antibiotic resistance in Gram-positive bacteria. This review addresses the impact of antibiotic-resistant Gram-positive pathogens on clinical outcomes

Global and gene-specific DNA methylation effects of exposing different asbestos fibres on human bronchial epithelial cells

Inhalation exposure to asbestos is associated with lung and pleural diseases in humans and remains a major public health issue worldwide. Human bronchial epithelial cells (16HBE) were exposed to UICC amosite, crocidolite and chrysotile. Cytotoxicity, genotoxicity, global DNA methylation on cytosine residues (using LC-MS/MS) were investigated at different doses (2.5-100 µg/ml). Gene-specific DNA methylation alterations at the whole genome were investigated using a microarray that interrogates more than 450 thousand CpG sites. Subsequently, gene functional analyses (KEGG pathway, Gene Ontology and functional classification) were performed on genes with differentially methylated gene promoters. At non-cytotoxic doses, global DNA methylation was altered after 24 h exposure to amosite and crocidolite (> 2.5 µg/ml). Exposure to amosite and crocidolite (amphibole type asbestos) induced both hypomethylation and hypermethylation at single CpG site and gene promoter levels whereas exposure to chrysotile (serpentine type asbestos) induced hypomethylation at the gene promoter level. Gene functional classification analyses revealed that all types of asbestos fibres induce alterations on GO-clusters i.e on regulation of Rho-protein signal transduction, nucleus, (e.g. homeobox genes), ATP-binding function and extracellular region (e.g. WNT-group of genes). These differentially methylated genes might contribute to asbestos-related diseases in bronchial cells.status: publishe

Computational prediction of the molecular configuration of three-dimensional network polymers

The three-dimensional arrangement of natural and synthetic network materials determines their application range. Control over the real-time incorporation of each building block and functional group is desired to regulate the macroscopic properties of the material from the molecular level onwards. Here we report an approach combining kinetic Monte Carlo and molecular dynamics simulations that chemically and physically predicts the interactions between building blocks in time and in space for the entire formation process of three-dimensional networks. This framework takes into account variations in inter- and intramolecular chemical reactivity, diffusivity, segmental compositions, branch/network point locations and defects. From the kinetic and three-dimensional structural information gathered, we construct structure–property relationships based on molecular descriptors such as pore size or dangling chain distribution and differentiate ideal from non-ideal structural elements. We validate such relationships by synthesizing organosilica, epoxy–amine and Diels–Alder networks with tailored properties and functions, further demonstrating the broad applicability of the platform.</p