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"Hoffmann, Martin"
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Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra
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.
Journal Article
Hans in luck : seven stories
\"Felix Hoffmann--one of Switzerland's most important children's book illustrators of the twentieth century--brings wonder and intrigue to these classic Brothers Grimm fairy tales ... Hoffman's subtle details and keen ability to portray expression in humans and animals alike make this collection a visual treaure, and one to explore again and again.\"--Book jacket front flap.
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High-confidence structural annotation of metabolites absent from spectral libraries
Untargeted metabolomics experiments rely on spectral libraries for structure annotation, but, typically, only a small fraction of spectra can be matched. Previous in silico methods search in structure databases but cannot distinguish between correct and incorrect annotations. Here we introduce the COSMIC workflow that combines in silico structure database generation and annotation with a confidence score consisting of kernel density
P
value estimation and a support vector machine with enforced directionality of features. On diverse datasets, COSMIC annotates a substantial number of hits at low false discovery rates and outperforms spectral library search. To demonstrate that COSMIC can annotate structures never reported before, we annotated 12 natural bile acids. The annotation of nine structures was confirmed by manual evaluation and two structures using synthetic standards. In human samples, we annotated and manually validated 315 molecular structures currently absent from the Human Metabolome Database. Application of COSMIC to data from 17,400 metabolomics experiments led to 1,715 high-confidence structural annotations that were absent from spectral libraries.
COSMIC outperforms spectral library search for metabolite annotation and annotates previously unseen structures.
Journal Article
Developing Industrial CPS: A Multi-Disciplinary Challenge
Industrial Cyber–Physical System (CPS) is an emerging approach towards value creation in modern industrial production. The development and implementation of industrial CPS in real-life production are rewarding yet challenging. This paper aims to present a concept to develop, commercialize, operate, and maintain industrial CPS which can motivate the advance of the research and the industrial practice of industrial CPS in the future. We start with defining our understanding of an industrial CPS, specifying the components and key technological aspects of the industrial CPS, as well as explaining the alignment with existing work such as Industrie 4.0 concepts, followed by several use cases of industrial CPS in practice. The roles of each component and key technological aspect are described and the differences between traditional industrial systems and industrial CPS are elaborated. The multidisciplinary nature of industrial CPS leads to challenges when developing such systems, and we present a detailed description of several major sub-challenges that are key to the long-term sustainability of industrial CPS design. Since the research of industrial CPS is still emerging, we also discuss existing approaches and novel solutions to overcome these sub-challenges. These insights will help researchers and industrial practitioners to develop and commercialize industrial CPS.
Journal Article
Alteration of Intestinal Dysbiosis by Fecal Microbiota Transplantation Does not Induce Remission in Patients with Chronic Active Ulcerative Colitis
In patients with ulcerative colitis (UC), alterations of the intestinal microbiota, termed dysbiosis, have been postulated to contribute to intestinal inflammation. Fecal microbiota transplantation (FMT) has been used as effective therapy for recurrent Clostridium difficile colitis also caused by dysbiosis. The aims of the present study were to investigate if patients with UC benefit from FMT and if dysbiosis can be reversed.MethodsSix patients with chronic active UC nonresponsive to standard medical therapy were treated with FMT by colonoscopic administration. Changes in the colonic microbiota were assessed by 16S rDNA–based microbial community profiling using high-throughput pyrosequencing from mucosal and stool samples.ResultsAll patients experienced short-term clinical improvement within the first 2 weeks after FMT. However, none of the patients achieved clinical remission. Microbiota profiling showed differences in the modification of the intestinal microbiota between individual patients after FMT. In 3 patients, the colonic microbiota changed toward the donor microbiota; however, this did not correlate with clinical response. On phylum level, there was a significant reduction of Proteobacteria and an increase in Bacteroidetes after FMT.ConclusionsFMT by a single colonoscopic donor stool application is not effective in inducing remission in chronic active therapy–refractory UC. Changes in the composition of the intestinal microbiota were significant and resulted in a partial improvement of UC-associated dysbiosis. The results suggest that dysbiosis in UC is at least in part a secondary phenomenon induced by inflammation and diarrhea rather than being causative for inflammation in this disease.
Journal Article
Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions
The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.
Journal Article
Highly Selective Tilted Triangular Springs with Constant Force Reaction
Guiding mechanisms are among the most elementary components of MEMS. Usually, a spring is required to be compliant in only one direction and stiff in all other directions. We introduce triangular springs with a preset tilting angle. The tilting angle lowers the reaction force and implements a constant reaction force. We show the influence of the tilting angle on the reaction force, on the spring stiffness and spring selectivity. Furthermore, we investigate the influence of the different spring geometry parameters on the spring reaction force. We experimentally show tilted triangular springs exhibiting constant force reactions in a large deflection range and a comb-drive actuator guided by tilted triangular springs.
Journal Article