The use of equine influenza pseudotypes for serological screening

Standard assays used for influenza serology present certain practical issues, such as inter-laboratory variability, complex protocols and the necessity for handling certain virus strains in high biological containment facilities. In an attempt to address this, avian and human influenza HA pseudotyped retroviruses have been successfully employed in antibody neutralization assays. In this study we generated an equine influenza pseudotyped lentivirus for serological screening. This was achieved by co-transfection of HEK293T cells with plasmids expressing the haemagglutinin (HA) protein of an H3N8 subtype equine influenza virus strain, HIV gag-pol and firefly luciferase reporter genes and harvesting virus from supernatant. In order to produce infective pseudotype particles it was necessary to additionally co-transfect a plasmid encoding the TMPRSS2 endoprotease to cleave the HA. High titre pseudotype virus (PV) was then used in PV antibody neutralization assays (PVNAs) to successfully distinguish between vaccinated and non-vaccinated equines. The sera were also screened by single radial haemolysis (SRH) assay. There was a 65% correlation between the results of the two assays, with the PVNA assay appearing slightly more sensitive. Future work will extend the testing of the PVNA with a larger number of serum samples to assess sensitivity/specificity, inter/intra-laboratory variability and to define a protective titre

The fuzzy theory and women writers in the late eighteenth century

'Fuzzy Theory and Women Writers in the Late Eighteenth Century' contends that women writers require more careful critical treatment, and suggests that critics are still bound by the outdated logic of the Law of the Excluded Middle. This law, first formulated by Aristotle, and developed by Gottfried Leibniz in the early eighteenth century, indicates that where there are two contradictory prepositions, one must be true and the other false; a female writer must, therefore, either be feminine or masculine, conservative or radical. The twentieth century concept of Fuzzy logic, however, helped mathematicians and engineers to manage reasoning that was only approximate, rather than exact. Borrowing from this, the thesis will employ the Fuzzy Set Theory, which permits the gradual assessment of elements in a set, rather than relying on elements that are assessed in binaric terms (the principle of bivalence, or, contradiction). Put simply, the Fuzzy Set Theory does away with binaries, the Law of the Excluded Middle, and the Law of Contradiction, allowing subjects to be imprecise, and changeable. Thus, each chapter will construct a Fuzzy Set by which a variety of eighteenth century debates, with which women writers engaged, can be examined. The thesis will show that all such concepts are subjective and unstable— changeable and open to personal interpretation, and will discuss such writers as Mary Wollstonecraft, Catherine Macaulay, Charlotte Smith, Anna Letitia Barbauld, Mary Hays, Lucy Aikin, Hannah More and Joanna Southcott

"I’ll Have One of Each": How Separating Rewards into (Meaningless) Categories Increases Motivation

We propose that separating rewards into categories can increase motivation, even when those categories are meaningless. Across six experiments, people were more motivated to obtain one reward from one category and another reward from another category than they were to obtain two rewards from a pool that included all items from either reward category. As a result, they worked longer when potential rewards for their work were separated into meaningless categories. This categorization effect persisted regardless of whether the rewards were presented using a gain or loss frame. Using both moderation and mediation analyses, we found that categorizing rewards had these positive effects on motivation by increasing the degree to which people felt they would "miss out" if they did not obtain the second reward. We discuss implications for research on motivation and incentives

TRENDS IN PARTICULATE MATTER AND MORTALITY: AN APPROACH TO THE ASSESSMENT OF UNMEASURED CONFOUNDING

We propose a method for diagnosing confounding bias under a model which links a spatially and temporally varying exposure and health outcome. We decompose the association into orthogonal components, corresponding to distinct spatial and temporal scales of variation. If the model fully controls for confounding, the exposure effect estimates should be equal at the different temporal and spatial scales. We show that the overall exposure effect estimate is a weighted average of the scale-specific exposure effect estimates. We use this approach to estimate the association between monthly averages of fine particles (PM2.5) over the preceding 12 months and monthly mortality rates in 113 U.S. counties from 2000-2002. We decompose the association between PM2.5 and mortality into two components: 1) the association between “national trends” in PM2.5 and mortality; and 2) the association between “local trends,” defined as county-specificdeviations from national trends. This second component provides evidence as to whether counties having steeper declines in PM2.5 also have steeper declines in mortality relative to their national trends. We find that the exposure effect estimates are different at these two spatio-temporalscales, which raises concerns about confounding bias. We believe that the association between trends in PM2.5 and mortality at the national scale is more likely to be confounded than is the association between trends in PM2.5 and mortality at the local scale. If the association at the national scale is set aside, there is little evidence of an association between 12-month exposure to PM2.5 and mortality

Shared Branding: Associated Use of Trademarks and Trade Dress Through Shared Retail Space

This Article explores the increasingly popular marketing strategy of two or more unrelated companies offering their separate and distinct mono-branded goods and services in a shared commercial space--herein referred to as “shared branding.

Underestimation of Standard Errors in Multi-Site Time Series Studies

Multi-site time series studies of air pollution and mortality and morbidity have figured prominently in the literature as comprehensive approaches for estimating acute effects of air pollution on health. Hierarchical models are generally used to combine site-specific information and estimate pooled air pollution effects taking into account both within-site statistical uncertainty, and across-site heterogeneity. Within a site, characteristics of time series data of air pollution and health (small pollution effects, missing data, highly correlated predictors, non linear confounding etc.) make modelling all sources of uncertainty challenging. One potential consequence is underestimation of the statistical variance of the site-specific effects to be combined. In this paper we investigate the impact of variance underestimation on the pooled relative rate estimate. We focus on two-stage normal-normal hierarchical models and on under- estimation of the statistical variance at the first stage. By mathematical considerations and simulation studies, we found that variance underestimation does not affect the pooled estimate substantially. However, some sensitivity of the pooled estimate to variance underestimation is observed when the number of sites is small and underestimation is severe. These simulation results are applicable to any two-stage normal-normal hierarchical model for combining information of site-specific results, and they can be easily extended to more general hierarchical formulations. We also examined the impact of variance underestimation on the national average relative rate estimate from the National Morbidity Mortality Air Pollution Study and we found that variance underestimation as much as 40% has little effect on the national average

A Spatio-Temporal Approach for Estimating Chronic Effects of Air Pollution

Estimating the health risks associated with air pollution exposure is of great importance in public health. In air pollution epidemiology, two study designs have been used mainly. Time series studies estimate acute risk associated with short-term exposure. They compare day-to-day variation of pollution concentrations and mortality rates, and have been criticized for potential confounding by time-varying covariates. Cohort studies estimate chronic effects associated with long-term exposure. They compare long-term average pollution concentrations and time-to-death across cities, and have been criticized for potential confounding by individual risk factors or city-level characteristics. We propose a new study design and a statistical model, which use spatio-temporal information to estimate the long-term effects of air pollution exposure on life expectancy. Our approach avoids confounding by time-varying covariates and individual or city-level risk factors. By estimating the increase in life expectancy due to decreases in long-term air pollution concentrations, it provides easily interpretable values for public policy purposes. We develop a suitable backfitting algorithm that permits efficient fitting of our model to large spatio-temporal data sets. We evaluate spatio-temporal correlation in the data and obtain appropriate standard errors. We apply our methods to the Medicare Cohort Air Pollution Study, including data on fine particulate matter (PM2.5) and mortality for 18.2 million Medicare enrollees from 814 locations in the U.S. during an average of 65 months in 2000-2006. Supplemental material including R code implementing our methods is provided in a web appendix

Phospho.ELM:a database of experimentally verified phosphorylation sites in eukaryotic proteins

BACKGROUND: Post-translational phosphorylation is one of the most common protein modifications. Phosphoserine, threonine and tyrosine residues play critical roles in the regulation of many cellular processes. The fast growing number of research reports on protein phosphorylation points to a general need for an accurate database dedicated to phosphorylation to provide easily retrievable information on phosphoproteins.DESCRIPTION: Phospho.ELM http://phospho.elm.eu.org is a new resource containing experimentally verified phosphorylation sites manually curated from the literature and is developed as part of the ELM (Eukaryotic Linear Motif) resource. Phospho.ELM constitutes the largest searchable collection of phosphorylation sites available to the research community. The Phospho.ELM entries store information about substrate proteins with the exact positions of residues known to be phosphorylated by cellular kinases. Additional annotation includes literature references, subcellular compartment, tissue distribution, and information about the signaling pathways involved as well as links to the molecular interaction database MINT. Phospho.ELM version 2.0 contains 1703 phosphorylation site instances for 556 phosphorylated proteins.CONCLUSION: Phospho.ELM will be a valuable tool both for molecular biologists working on protein phosphorylation sites and for bioinformaticians developing computational predictions on the specificity of phosphorylation reactions.</p

Dynamic reorganization of the genome shapes the recombination landscape in meiotic prophase.

In meiotic prophase, chromosomes are organized into compacted loop arrays to promote homolog pairing and recombination. Here, we probe the architecture of the mouse spermatocyte genome in early and late meiotic prophase using chromosome conformation capture (Hi-C). Our data support the established loop array model of meiotic chromosomes, and infer loops averaging 0.8-1.0 megabase pairs (Mb) in early prophase and extending to 1.5-2.0 Mb in late prophase as chromosomes compact and homologs undergo synapsis. Topologically associating domains (TADs) are lost in meiotic prophase, suggesting that assembly of the meiotic chromosome axis alters the activity of chromosome-associated cohesin complexes. While TADs are lost, physically separated A and B compartments are maintained in meiotic prophase. Moreover, meiotic DNA breaks and interhomolog crossovers preferentially form in the gene-dense A compartment, revealing a role for chromatin organization in meiotic recombination. Finally, direct detection of interhomolog contacts genome-wide reveals the structural basis for homolog alignment and juxtaposition by the synaptonemal complex