Featured Piece

This year the General Editors decided to create a feature piece to show our appreciation for the History Department. We selected four professors from the faculty to answer a question about history: what figure/event/idea inspires your interest in history? Reading their responses helped give us insight into the thoughts of these brilliant minds and further help us understand their passion for the subject we all share a common love and interest in. We hope that you enjoy reading their responses as much as we did. The four members of the faculty we spoke with are Dr. Timothy Shannon, Dr. Ian Isherwood, Dr. Jill Titus, and Dr. Scott Hancock

Single Photon Counting UV Solar-Blind Detectors Using Silicon and III-Nitride Materials

Ultraviolet (UV) studies in astronomy, cosmology, planetary studies, biological and medical applications often require precision detection of faint objects and in many cases require photon-counting detection. We present an overview of two approaches for achieving photon counting in the UV. The first approach involves UV enhancement of photon-counting silicon detectors, including electron multiplying charge-coupled devices and avalanche photodiodes. The approach used here employs molecular beam epitaxy for delta doping and superlattice doping for surface passivation and high UV quantum efficiency. Additional UV enhancements include antireflection (AR) and solar-blind UV bandpass coatings prepared by atomic layer deposition. Quantum efficiency (QE) measurements show QE > 50% in the 100–300 nm range for detectors with simple AR coatings, and QE ≅ 80% at ~206 nm has been shown when more complex AR coatings are used. The second approach is based on avalanche photodiodes in III-nitride materials with high QE and intrinsic solar blindness

Systems-Level Comparison of Host-Responses Elicited by Avian H5N1 and Seasonal H1N1 Influenza Viruses in Primary Human Macrophages

Human disease caused by highly pathogenic avian influenza (HPAI) H5N1 can lead to a rapidly progressive viral pneumonia leading to acute respiratory distress syndrome. There is increasing evidence from clinical, animal models and in vitro data, which suggests a role for virus-induced cytokine dysregulation in contributing to the pathogenesis of human H5N1 disease. The key target cells for the virus in the lung are the alveolar epithelium and alveolar macrophages, and we have shown that, compared to seasonal human influenza viruses, equivalent infecting doses of H5N1 viruses markedly up-regulate pro-inflammatory cytokines in both primary cell types in vitro. Whether this H5N1-induced dysregulation of host responses is driven by qualitative (i.e activation of unique host pathways in response to H5N1) or quantitative differences between seasonal influenza viruses is unclear. Here we used microarrays to analyze and compare the gene expression profiles in primary human macrophages at 1, 3, and 6 h after infection with H5N1 virus or low-pathogenic seasonal influenza A (H1N1) virus. We found that host responses to both viruses are qualitatively similar with the activation of nearly identical biological processes and pathways. However, in comparison to seasonal H1N1 virus, H5N1 infection elicits a quantitatively stronger host inflammatory response including type I interferon (IFN) and tumor necrosis factor (TNF)-α genes. A network-based analysis suggests that the synergy between IFN-β and TNF-α results in an enhanced and sustained IFN and pro-inflammatory cytokine response at the early stage of viral infection that may contribute to the viral pathogenesis and this is of relevance to the design of novel therapeutic strategies for H5N1 induced respiratory disease

Identification of IncA/C plasmid replication and maintenance genes and development of a plasmid multilocus sequence typing scheme

Plasmids of incompatibility group A/C (IncA/C) are becoming increasingly prevalent within pathogenic Enterobacteriaceae. They are associated with the dissemination of multiple clinically relevant resistance genes, including blaCMY and blaNDM. Current typing methods for IncA/C plasmids offer limited resolution. In this study, we present the complete sequence of a blaNDM-1-positive IncA/C plasmid, pMS6198A, isolated from a multidrug-resistant uropathogenic Escherichia coli strain. Hypersaturated transposon mutagenesis, coupled with transposon-directed insertion site sequencing (TraDIS), was employed to identify conserved genetic elements required for replication and maintenance of pMS6198A. Our analysis of TraDIS data identified roles for the replicon, including repA, a toxin-antitoxin system; two putative partitioning genes, parAB; and a putative gene, 053. Construction of mini-IncA/C plasmids and examination of their stability within E. coli confirmed that the region encompassing 053 contributes to the stable maintenance of IncA/C plasmids. Subsequently, the four major maintenance genes (repA, parAB, and 053) were used to construct a new plasmid multilocus sequence typing (PMLST) scheme for IncA/C plasmids. Application of this scheme to a database of 82 IncA/C plasmids identified 11 unique sequence types (STs), with two dominant STs. The majority of blaNDM-positive plasmids examined (15/17; 88%) fall into ST1, suggesting acquisition and subsequent expansion of this blaNDM-containing plasmid lineage. The IncA/C PMLST scheme represents a standardized tool to identify, track, and analyze the dissemination of important IncA/C plasmid lineages, particularly in the context of epidemiological studies

A Neutralizing Human Monoclonal Antibody Protects against Lethal Disease in a New Ferret Model of Acute Nipah Virus Infection

Nipah virus is a broadly tropic and highly pathogenic zoonotic paramyxovirus in the genus Henipavirus whose natural reservoirs are several species of Pteropus fruit bats. Nipah virus has repeatedly caused outbreaks over the past decade associated with a severe and often fatal disease in humans and animals. Here, a new ferret model of Nipah virus pathogenesis is described where both respiratory and neurological disease are present in infected animals. Severe disease occurs with viral doses as low as 500 TCID50 within 6 to 10 days following infection. The underlying pathology seen in the ferret closely resembles that seen in Nipah virus infected humans, characterized as a widespread multisystemic vasculitis, with virus replicating in highly vascular tissues including lung, spleen and brain, with recoverable virus from a variety of tissues. Using this ferret model a cross-reactive neutralizing human monoclonal antibody, m102.4, targeting the henipavirus G glycoprotein was evaluated in vivo as a potential therapeutic agent. All ferrets that received m102.4 ten hours following a high dose oral-nasal Nipah virus challenge were protected from disease while all controls died. This study is the first successful post-exposure passive antibody therapy for Nipah virus using a human monoclonal antibody

Adverse childhood experience and adult persistent pain and disability: protocol for a systematic review and meta-analysis

A growing body of research highlights the pervasive harms of adverse childhood experiences (ACEs) on health throughout the life-course. However, findings from prior reviews and recent longitudinal studies investigating the association between types of ACEs and persistent pain have yielded inconsistent findings in the strength and direction of associations. The purpose of this review is to appraise and summarize evidence on the relationship between ACEs and persistent pain and disability outcomes in adulthood. The specific aims are (1) to determine whether there is a relationship between exposure to ACE and persistent pain and disability in adults and (2) to determine whether unique and cumulative ACEs exposures (number and type) increase the risk of developing persistent pain and disability in adulthood

A markov classification model for metabolic pathways

<p>Abstract</p> <p>Background</p> <p>This paper considers the problem of identifying pathways through metabolic networks that relate to a specific biological response. Our proposed model, HME3M, first identifies frequently traversed network paths using a Markov mixture model. Then by employing a hierarchical mixture of experts, separate classifiers are built using information specific to each path and combined into an ensemble prediction for the response.</p> <p>Results</p> <p>We compared the performance of HME3M with logistic regression and support vector machines (SVM) for both simulated pathways and on two metabolic networks, glycolysis and the pentose phosphate pathway for <it>Arabidopsis thaliana</it>. We use AltGenExpress microarray data and focus on the pathway differences in the developmental stages and stress responses of <it>Arabidopsis</it>. The results clearly show that HME3M outperformed the comparison methods in the presence of increasing network complexity and pathway noise. Furthermore an analysis of the paths identified by HME3M for each metabolic network confirmed known biological responses of <it>Arabidopsis</it>.</p> <p>Conclusions</p> <p>This paper clearly shows HME3M to be an accurate and robust method for classifying metabolic pathways. HME3M is shown to outperform all comparison methods and further is capable of identifying known biologically active pathways within microarray data.</p

Identifying Neighborhoods of Coordinated Gene Expression and Metabolite Profiles

In this paper we investigate how metabolic network structure affects any coordination between transcript and metabolite profiles. To achieve this goal we conduct two complementary analyses focused on the metabolic response to stress. First, we investigate the general size of any relationship between metabolic network gene expression and metabolite profiles. We find that strongly correlated transcript-metabolite profiles are sustained over surprisingly long network distances away from any target metabolite. Secondly, we employ a novel pathway mining method to investigate the structure of this transcript-metabolite relationship. The objective of this method is to identify a minimum set of metabolites which are the target of significantly correlated gene expression pathways. The results reveal that in general, a global regulation signature targeting a small number of metabolites is responsible for a large scale metabolic response. However, our method also reveals pathway specific effects that can degrade this global regulation signature and complicates the observed coordination between transcript-metabolite profiles