The Grizzly, March 21, 1995

Ursinus and PV District Announce Partnership • Cross-dressers, Polka Dancers, and the Jackson Five: Airband \u2795 Raises Over $2400 • No Ruby for Class of \u2796? • Spotlight on Dr. Hemphill • Fatal Talk Shows: Jenny Jones Show Provokes Homicide • Choral Ensemble Presents Annual Concert • Housing for Everyone • Student Spotlight: Kristen Baldini • Portrait of Venezuela • Experiencing proTheatre at U.C.! • Searching for a Topic • Letters to the Editor: It\u27s a Matter of Time; What Happened to B.Y.O.? • Princeton Concert Jazz Ensemble to Perform • Gilot Speaks About Paintings • ProTheatre to Perform Our Country\u27s Good • Baseball Finds Fun in the Sun • Sammartino Powers Softball Team on Southern Trip • Lax Team Routs Widener • Cosgrove Named Second-Team All American • Men\u27s Tennis Off to Tough Start • Courtney 11th on Beam • Cauley 18th at Swimming Championships • Ursinus Falls to Hopkins 77-67 in NCAA\u27shttps://digitalcommons.ursinus.edu/grizzlynews/1356/thumbnail.jp

A double-reprocessing high-level disinfection protocol does not eliminate positive cultures from the elevators of duodenoscopes

Background and study aim Duodenoscopes have been the source of serious infection, despite correct performance of high-level disinfection (HLD). This study aimed to observe the impact of performing HLD twice on the rate of positive cultures from duodenoscope elevators. Methods We performed double HLD (DHLD; i. e. complete manual cleaning followed by automated reprocessing, with the entire process repeated) and then randomly cultured the elevators of our duodenoscopes on about 30 % of occasions. Results DHLD was associated with positive elevator cultures for any microorganism in 9.4 % of cases, with a 0.8 % rate of known pathogens (627 cultures) between May 2015 and February 2016. After February 2016, and in association with changing the precleaning fluid, as well as use of a new FDA-recommended cleaning brush, the rate of positive cultures for any microorganism after DHLD was 4.8 % and 0.2 % for known pathogens (420 cultures). In a third phase, characterized by a change in personnel performing DHLD and retirement of a duodenoscope with a high rate of positive cultures, the rate of positive cultures for any microorganism was 4.9 % (783 cultures) and the rate of positive culture for known pathogens was 0.3 %. To our knowledge, no duodenoscope transmission of infection occurred during the study interval. Conclusions DHLD resulted in a low rate of positive cultures for known pathogens and for organisms of low pathogenic potential, but did not eliminate these, from duodenoscope elevators. Additional improvements in HLD protocols and/or duodenoscope design are needed

Systemic influences of mammary cancer on monocytes in mice

SIMPLE SUMMARY: Using a mouse model of breast cancer driven by the mammary epithelial expression of the polyoma middle T oncoprotein in which the tumors progress from benign to malignant metastatic stages, we show that cancer causes an increase in circulating monocytes and a splenomegaly. This increase in monocyte number is due to their increased proliferation in the bone marrow and not turnover rates in the blood. Single cell sequencing also shows that new populations of monocytes do not arise during cancer. Cancer also drives systemic changes in the monocyte transcriptome, with a notable down-regulation of interferon signaling. These systemic influences start in the bone marrow but intensify in the blood. Comparison of cancer prone and cancer resistant mouse inbred strains carrying the same oncogene reveals that the genetic background of the strain causes different monocyte transcriptional changes. Similarly, a comparison of the mouse transcriptome to human breast cancer monocyte profiles indicates limited similarities, to the extent that interferon signaling is enhanced in humans. Systemic responses are different in the same model of cancer on different genetic backgrounds within a species and even greater changes are found across species. These data suggest that at the very least this mouse model will be limited when it comes to exploring the mechanism behind systemic changes in humans. ABSTRACT: There is a growing body of evidence that cancer causes systemic changes. These influences are most evident in the bone marrow and the blood, particularly in the myeloid compartment. Here, we show that there is an increase in the number of bone marrow, circulating and splenic monocytes by using mouse models of breast cancer caused by the mammary epithelial expression of the polyoma middle T antigen. Cancer does not affect ratios of classical to non-classical populations of monocytes in the circulation nor does it affect their half-lives. Single cell RNA sequencing also indicates that cancer does not induce any new monocyte populations. Cancer does not change the monocytic progenitor number in the bone marrow, but the proliferation rate of monocytes is higher, thus providing an explanation for the expansion of the circulating numbers. Deep RNA sequencing of these monocytic populations reveals that cancer causes changes in the classical monocyte compartment, with changes evident in bone marrow monocytes and even more so in the blood, suggesting influences in both compartments, with the down-regulation of interferon type 1 signaling and antigen presentation being the most prominent of these. Consistent with this analysis, down-regulated genes are enriched with STAT1/STAT2 binding sites in their promoter, which are transcription factors required for type 1 interferon signaling. However, these transcriptome changes in mice did not replicate those found in patients with breast cancer. Consequently, this mouse model of breast cancer may be insufficient to study the systemic influences of human cancer

The Grizzly, September 12, 1995

Strassburger to Students: Be Responsible • Class of \u2799 Arrives, Survives Orientation • Seneca Falls: The Birthplace of Women\u27s Suffrage • Treasure Hunt, Anyone? • Students Dedicate Mural To Strassburger • Did You Get Your Invitation? • Reality 100 • Biology Boot Camp • Want to be a Tech-y? • WVOU: It\u27s up to You • Internet Site of the Week • A Whole New Dining Experience • Commuter Connections • Get Involved by Joining a Committee • Victory: Bears Defense Shuts Down WPI • Women\u27s soccer: The Spirit to Fight • New Look for UC Volleyball Team • Lady Bears Win Field Hockey Openerhttps://digitalcommons.ursinus.edu/grizzlynews/1361/thumbnail.jp

MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

ABSTRACT Integrative multi-omics analyses can empower more effective investigation and complete understanding of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Here we adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements. The m etabolite, p rotein, and l ipid ex traction (MPLEx) protocol proved to be robust and applicable to a diverse set of sample types, including cell cultures, microbial communities, and tissues. To illustrate the utility of this protocol, an integrative multi-omics analysis was performed using a lung epithelial cell line infected with Middle East respiratory syndrome coronavirus, which showed the impact of this virus on the host glycolytic pathway and also suggested a role for lipids during infection. The MPLEx method is a simple, fast, and robust protocol that can be applied for integrative multi-omic measurements from diverse sample types (e.g., environmental, in vitro , and clinical). IMPORTANCE In systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample

A Network Integration Approach to Predict Conserved Regulators Related to Pathogenicity of Influenza and SARS-CoV Respiratory Viruses

Respiratory infections stemming from influenza viruses and the Severe Acute Respiratory Syndrome corona virus (SARS-CoV) represent a serious public health threat as emerging pandemics. Despite efforts to identify the critical interactions of these viruses with host machinery, the key regulatory events that lead to disease pathology remain poorly targeted with therapeutics. Here we implement an integrated network interrogation approach, in which proteome and transcriptome datasets from infection of both viruses in human lung epithelial cells are utilized to predict regulatory genes involved in the host response. We take advantage of a novel "crowd-based" approach to identify and combine ranking metrics that isolate genes/proteins likely related to the pathogenicity of SARS-CoV and influenza virus. Subsequently, a multivariate regression model is used to compare predicted lung epithelial regulatory influences with data derived from other respiratory virus infection models. We predicted a small set of regulatory factors with conserved behavior for consideration as important components of viral pathogenesis that might also serve as therapeutic targets for intervention. Our results demonstrate the utility of integrating diverse 'omic datasets to predict and prioritize regulatory features conserved across multiple pathogen infection models

Spatial patterns and environmental constraints on ecosystem services at a catchment scale

Improved understanding and prediction of the fundamental environmental controls on ecosystem service supply across the landscape will help to inform decisions made by policy makers and land-water managers. To evaluate this issue for a local catchment case study, we explored metrics and spatial patterns of service supply for water quality regulation, agriculture production, carbon storage, and biodiversity for the Macronutrient Conwy catchment. Methods included using ecosystem models such as LUCI and JULES, integration of national scale field survey datasets, earth observation products and plant trait databases, to produce finely resolved maps of species richness and primary production. Analyses were done with both 1x1 km gridded and subcatchment data. A common single gradient characterised catchment scale ecosystem services supply with agricultural production and carbon storage at opposing ends of the gradient as reported for a national-scale assessment. Species diversity was positively related to production due to the below national average productivity levels in the Conwy combined with the unimodal relationship between biodiversity and productivity at the national scale. In contrast to the national scale assessment, a strong reduction in water quality as production increased was observed in these low productive systems. Various soil variables were tested for their predictive power of ecosystem service supply. Soil carbon, nitrogen, their ratio and soil pH all had double the power of rainfall and altitude, each explaining around 45% of variation but soil pH is proposed as a potential metric for ecosystem service supply potential as it is a simple and practical metric which can be carried out in the field with crowd-sourcing technologies now available. The study emphasises the importance of considering multiple ecosystem services together due to the complexity of covariation at local and national scales, and the benefits of exploiting a wide range of metrics for each service to enhance data robustness

Long-term ecological research on Colorado Shortgrass Steppe

The SGS-LTER research site was established in 1980 by researchers at Colorado State University as part of a network of long-term research sites within the US LTER Network, supported by the National Science Foundation. Scientists within the Natural Resource Ecology Lab, Department of Forest and Rangeland Stewardship, Department of Soil and Crop Sciences, and Biology Department at CSU, California State Fullerton, USDA Agricultural Research Service, University of Northern Colorado, and the University of Wyoming, among others, have contributed to our understanding of the structure and functions of the shortgrass steppe and other diverse ecosystems across the network while maintaining a common mission and sharing expertise, data and infrastructure.Poster presented at the LTER All Scientists Meeting held in Estes Park, CO on September 10-13, 2012

Release of Severe Acute Respiratory Syndrome Coronavirus Nuclear Import Block Enhances Host Transcription in Human Lung Cells

The severe acute respiratory syndrome coronavirus accessory protein ORF6 antagonizes interferon signaling by blocking karyopherin-mediated nuclear import processes. Viral nuclear import antagonists, expressed by several highly pathogenic RNA viruses, likely mediate pleiotropic effects on host gene expression, presumably interfering with transcription factors, cytokines, hormones, and/or signaling cascades that occur in response to infection. By bioinformatic and systems biology approaches, we evaluated the impact of nuclear import antagonism on host expression networks by using human lung epithelial cells infected with either wild-type virus or a mutant that does not express ORF6 protein. Microarray analysis revealed significant changes in differential gene expression, with approximately twice as many upregulated genes in the mutant virus samples by 48 h postinfection, despite identical viral titers. Our data demonstrated that ORF6 protein expression attenuates the activity of numerous karyopherin-dependent host transcription factors (VDR, CREB1, SMAD4, p53, EpasI, and Oct3/4) that are critical for establishing antiviral responses and regulating key host responses during virus infection. Results were confirmed by proteomic and chromatin immunoprecipitation assay analyses and in parallel microarray studies using infected primary human airway epithelial cell cultures. The data strongly support the hypothesis that viral antagonists of nuclear import actively manipulate host responses in specific hierarchical patterns, contributing to the viral pathogenic potential in vivo. Importantly, these studies and modeling approaches not only provide templates for evaluating virus antagonism of nuclear import processes but also can reveal candidate cellular genes and pathways that may significantly influence disease outcomes following severe acute respiratory syndrome coronavirus infection in vivo