University of Jena

About: University of Jena is a education organization based out in Jena, Thüringen, Germany. It is known for research contribution in the topics: Laser & Population. The organization has 22198 authors who have published 45159 publications receiving 1401514 citations. The organization is also known as: Friedrich-Schiller-Universität Jena & Friedrich Schiller University Jena.

The importance of the gastrointestinal system in the pathogenesis of heart failure

Abstract: Chronic heart failure (CHF) is a multi-organ disease with increasing evidence for the involvement of the gastrointestinal (GI) system in this syndrome. In recent research, the gut has received very little attention from cardiologists as its role in the pathogenesis of cardiovascular disease is poorly understood. Intestinal ischaemia may play an important role in bacterial translocation by increasing bowel permeability. Decreased cardiac function can reduce bowel perfusion and so clearly impairs the function of the intestinal barrier. There is an increasing evidence to suggest that a ‘leaky’ bowel wall may lead to translocation of bacteria and/or endotoxin, which may be an important stimulus for inflammatory cytokine activation in CHF. Impaired functioning of the GI system may also contribute to malnutrition and cachexia in CHF. It is hoped that by improving our understanding of the role of the gut in cardiac disease will lead to the development of novel therapeutic strategies in the future.

The great escape: how cationic polyplexes overcome the endosomal barrier.

Abstract: The targeted and efficiency-oriented delivery of (therapeutic) nucleic acids raises hope for successful gene therapy, ie, for the local and individual treatment of acquired and inherited genetic disorders Despite promising achievements in the field of polymer-mediated gene delivery, the efficiency of the non-viral vectors remains orders of magnitude lower than viral-mediated ones Several obstacles on the molecular and cellular level along the gene delivery process were identified, starting from the design and formulation of the nano-sized carriers up to the targeted release to their site of action In particular, the efficient escape from endo-lysosomal compartments was demonstrated to be a major barrier and its exact mechanism still remains unclear Different hypotheses and theories of the endosomal escape were postulated The most popular one is the so-called "proton sponge" hypothesis, claiming an escape by rupture of the endosome through osmotic swelling It was the first effort to explain the excellent transfection efficiency of poly(ethylene imine) Moreover, it was thought that a unique mechanism based on the ability to capture protons and to buffer the endosomal pH is the basis of endosomal escape Recent theories deal with the direct interaction of the cationic polyplex or free polymer with the exoplasmic lipid leaflet causing membrane destabilization, permeability or polymer-supported nanoscale hole formation Both escape strategies are more related to viral-mediated escape compared to the "proton sponge" effect This review addresses the different endosomal release theories and highlights their key mechanism

Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra

Abstract: Metabolomics using nontargeted tandem mass spectrometry can detect thousands of molecules in a biological sample. However, structural molecule annotation is limited to structures present in libraries or databases, restricting analysis and interpretation of experimental data. Here we describe CANOPUS (class assignment and ontology prediction using mass spectrometry), a computational tool for systematic compound class annotation. CANOPUS uses a deep neural network to predict 2,497 compound classes from fragmentation spectra, including all biologically relevant classes. CANOPUS explicitly targets compounds for which neither spectral nor structural reference data are available and predicts classes lacking tandem mass spectrometry training data. In evaluation using reference data, CANOPUS reached very high prediction performance (average accuracy of 99.7% in cross-validation) and outperformed four baseline methods. We demonstrate the broad utility of CANOPUS by investigating the effect of microbial colonization in the mouse digestive system, through analysis of the chemodiversity of different Euphorbia plants and regarding the discovery of a marine natural product, revealing biological insights at the compound class level. Unknown metabolites are classified from mass spectrometry data.