The Intestinal Microbiota Contributes to the Ability of Helminths to Modulate Allergic Inflammation

We thank Manuel Kulagin for technical help, Pierre Bonnaventure for portal vein blood sampling, Francisco Sepulveda for technical assistance in GS-MS acquisition, and Dorothee Hahne (Metabolomics Australia, University of Western Australia) for human samples SCFA isolation, acquisition, and analysis. We also thank Cristina Cartoni (Phenotyping Unit, EPFL) for Milliplex analysis, Jessica Dessimoz and her team from the Histology Core Facility (EPFL), Miguel Garcia and his team from the Flow Cytometry Core Facility (EPFL), and staff from the EPFL CPG animal house for excellent animal care. The computations were partially performed at the Vital-IT Center for high-performance computing of the SIB Swiss Institute of Bioinformatics (http://www.vital-it.ch). The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 310948. Funding for A.W.W. and a subset of the 16S rRNA gene sequencing was provided by the Wellcome Trust (grant number WT 098051). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Exploring the Influence of Culture on Tourist Experiences with Robots in Service Delivery Environment

Robots and artificial intelligence represent a newly emerging trend in tourism and hospitality. However, studies examining how cultural perceptions influence tourists’ experiences interacting with service robots are lacking. In response to the industrial trend, the experiential components of robot-staffed hotels are assessed in this study. A qualitative approach is adopted to compare the semantic networks of Japanese and non-Japanese tourists’ online reviews, using 1,498 reviews from nine robot-staffed hotels in Japan. The results indicate that hotel guests’ interaction with robots is one of the main experiential components in robot-staffed hotels. The semantic network analysis results demonstrate noticeable differences, with Japanese reviews demonstrating more emotional responses to human-robot interaction and non-Japanese reviews valuing the functional and technical aspects of robot-provided services more

A descriptive study of Ohio superintendents\u27 views of the opioid epidemic, legal options and medical response in schools.

The opioid epidemic has reached all portions of society, including into the lives of youth. This is a descriptive study of the views of Ohio superintendents and other administrators. and their willingness to provide training of school staff to administer naloxone in drug induced overdoses on school property. The research explores variables of school district demographic classifications, as well as, education and drug related experience of school leaders. With other states,such as Massachusetts and West Virginia, serving as models of naloxone training into their school districts, it is imperative to start the research of perceptions of school leaders in implementing training programs for Ohio School Districts.https://ecommons.udayton.edu/stander_posters/1876/thumbnail.jp

Automatic vetting of planet candidates from ground based surveys : machine learning with NGTS

State of the art exoplanet transit surveys are producing ever increasing quantities of data. To make the best use of this resource, in detecting interesting planetary systems or in determining accurate planetary population statistics, requires new automated methods. Here we describe a machine learning algorithm that forms an integral part of the pipeline for the NGTS transit survey, demonstrating the efficacy of machine learning in selecting planetary candidates from multi-night ground based survey data. Our method uses a combination of random forests and self-organising-maps to rank planetary candidates, achieving an AUC score of 97.6% in ranking 12368 injected planets against 27496 false positives in the NGTS data. We build on past examples by using injected transit signals to form a training set, a necessary development for applying similar methods to upcoming surveys. We also make the autovet code used to implement the algorithm publicly accessible. autovet is designed to perform machine learned vetting of planetary candidates, and can utilise a variety of methods. The apparent robustness of machine learning techniques, whether on space-based or the qualitatively different ground-based data, highlights their importance to future surveys such as TESS and PLATO and the need to better understand their advantages and pitfalls in an exoplanetary context

Development of a Series of Kynurenine 3-Monooxygenase Inhibitors Leading to a Clinical Candidate for the Treatment of Acute Pancreatitis

Recently, we reported a novel role for KMO in the pathogenesis of acute pancreatitis (AP). A number of inhibitors of kynurenine 3-monooxygenase (KMO) have previously been described as potential treatments for neurodegenerative conditions and particularly for Huntington’s disease. However, the inhibitors reported to date have insufficient aqueous solubility relative to their cellular potency to be compatible with the intravenous (iv) dosing route required in AP. We have identified and optimized a novel series of high affinity KMO inhibitors with favorable physicochemical properties. The leading example is exquisitely selective, has low clearance in two species, prevents lung and kidney damage in a rat model of acute pancreatitis, and is progressing into preclinical development

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin