Real-time Flu Tracking at South End Community Health Center

There is no real-time tracking of influenza or influenza vaccination in the United States. This project is to prototype and grow a real-time flu and flu vaccination tracking system for the state of the Vermont. This will help providers be more aware of the vaccination status of their patients and will allow for important real-time analysis of a burgeoning epidemic was it to occur.https://scholarworks.uvm.edu/fmclerk/1600/thumbnail.jp

Impact of Interactions Between First Responders and Opioid Drug Users

INTRODUCTION In 2017, First Responders (EMS, Police, and Fire Department) in Vermont administered 848 doses of naloxone (Narcan®), an opioid antagonist that can block the effects of opioids in overdose. However, the rate of opioid-related fatalities has continued to rise from 74 in 2015 to 101 in 2017. Vermont CARES, a nonprofit organization, helps address this issue by working “for and with Vermonters affected by HIV/AIDS to promote well-being through a continuum of prevention, support, and advocacy services.” Their syringe service programs throughout the state provide access to clean needles, overdose prevention education, and naloxone. AIMS 1. To better understand the perceived experience of opioid drug users (Vermont CARES clients) when interacting with First Responders following an overdose. 2. To explore how such interactions of a Vermont CARES client – essentially as positive or negative – affects the likelihood to request such help in the futurehttps://scholarworks.uvm.edu/comphp_gallery/1279/thumbnail.jp

Integrative epigenomics in Sjögren´s syndrome reveals novel pathways and a strong interaction between the HLA, autoantibodies and the interferon signature

Primary Sjögren's syndrome (SS) is a systemic autoimmune disease characterized by lymphocytic infiltration and damage of exocrine salivary and lacrimal glands. The etiology of SS is complex with environmental triggers and genetic factors involved. By conducting an integrated multi-omics study, we confirmed a vast coordinated hypomethylation and overexpression effects in IFN-related genes, what is known as the IFN signature. Stratified and conditional analyses suggest a strong interaction between SS-associated HLA genetic variation and the presence of Anti-Ro/SSA autoantibodies in driving the IFN epigenetic signature and determining SS. We report a novel epigenetic signature characterized by increased DNA methylation levels in a large number of genes enriched in pathways such as collagen metabolism and extracellular matrix organization. We identified potential new genetic variants associated with SS that might mediate their risk by altering DNA methylation or gene expression patterns, as well as disease-interacting genetic variants that exhibit regulatory function only in the SS population. Our study sheds new light on the interaction between genetics, autoantibody profiles, DNA methylation and gene expression in SS, and contributes to elucidate the genetic architecture of gene regulation in an autoimmune population

Machine learning of flow cytometry data encompassing seven systemic autoimmune diseases and controls

International audienc

POSIT: Flexible Shape-Guided Docking For Pose Prediction

We present a new approach to structure-based drug design (POSIT) rigorously built on the simple concept that pose prediction is intimately coupled to the quality and availability of experimental structural data. We demonstrate the feasibility of the approach by performing retrospective analyses on three data sets designed to explore the strengths and weaknesses of POSIT relative to existing methods. We then present results documenting 2.5 years of prospective use of POSIT across a variety of structure-based industrial drug-discovery research projects. We find that POSIT is well-suited to guiding research decision making for structure-based design and, in particular, excels at enabling lead-optimization campaigns. We show that the POSIT framework can drive superior pose-prediction performance and generate results that naturally lend themselves to prospective decision making during lead optimization. We believe the results presented here are (1) the largest prospective validation of a pose prediction method reported to date (71 crystal structures); (2) provide an unprecedented look at the scope of impact of a computational tool; and (3) represent a first-of-its-kind analysis. We hope that this work inspires additional studies that look at the real impact and performance of computational research tools on prospective drug design