N-glycosylation controls the function of junctional adhesion molecule-A

Junctional adhesion molecule-A (JAM-A) is an adherens and tight junction protein expressed by endothelial and epithelial cells. JAM-A serves many roles and contributes to barrier function and cell migration and motility, and it also acts as a ligand for the leukocyte receptor LFA-1. JAM-A is reported to contain N-glycans, but the extent of this modification and its contribution to the protein’s functions are unknown. We show that human JAM-A contains a single N-glycan at N185 and that this residue is conserved across multiple mammalian species. A glycomutant lacking all N-glycans, N185Q, is able to reach the cell surface but exhibits decreased protein half-life compared with the wild- type protein. N-glycosylation of JAM-A is required for the protein’s ability to reinforce barrier function and contributes to Rap1 activity. We further show that glycosylation of N185 is required for JAM-A–mediated reduction of cell migration. Finally, we show that N-glycosylation of JAM-A regulates leukocyte adhesion and LFA-1 binding. These findings identify N-glycosylation as critical for JAM-A’s many functions

Evaluation Research and Institutional Pressures: Challenges in Public-Nonprofit Contracting

This article examines the connection between program evaluation research and decision-making by public managers. Drawing on neo-institutional theory, a framework is presented for diagnosing the pressures and conditions that lead alternatively toward or away the rational use of evaluation research. Three cases of public-nonprofit contracting for the delivery of major programs are presented to clarify the way coercive, mimetic, and normative pressures interfere with a sound connection being made between research and implementation. The article concludes by considering how public managers can respond to the isomorphic pressures in their environment that make it hard to act on data relating to program performance.This publication is Hauser Center Working Paper No. 23. The Hauser Center Working Paper Series was launched during the summer of 2000. The Series enables the Hauser Center to share with a broad audience important works-in-progress written by Hauser Center scholars and researchers

Impact of exposure measurement error in air pollution epidemiology: effect of error type in time-series studies

<p>Abstract</p> <p>Background</p> <p>Two distinctly different types of measurement error are Berkson and classical. Impacts of measurement error in epidemiologic studies of ambient air pollution are expected to depend on error type. We characterize measurement error due to instrument imprecision and spatial variability as multiplicative (i.e. additive on the log scale) and model it over a range of error types to assess impacts on risk ratio estimates both on a per measurement unit basis and on a per interquartile range (IQR) basis in a time-series study in Atlanta.</p> <p>Methods</p> <p>Daily measures of twelve ambient air pollutants were analyzed: NO₂, NO_x, O₃, SO₂, CO, PM₁₀mass, PM_2.5mass, and PM_2.5components sulfate, nitrate, ammonium, elemental carbon and organic carbon. Semivariogram analysis was applied to assess spatial variability. Error due to this spatial variability was added to a reference pollutant time-series on the log scale using Monte Carlo simulations. Each of these time-series was exponentiated and introduced to a Poisson generalized linear model of cardiovascular disease emergency department visits.</p> <p>Results</p> <p>Measurement error resulted in reduced statistical significance for the risk ratio estimates for all amounts (corresponding to different pollutants) and types of error. When modelled as classical-type error, risk ratios were attenuated, particularly for primary air pollutants, with average attenuation in risk ratios on a per unit of measurement basis ranging from 18% to 92% and on an IQR basis ranging from 18% to 86%. When modelled as Berkson-type error, risk ratios per unit of measurement were biased away from the null hypothesis by 2% to 31%, whereas risk ratios per IQR were attenuated (i.e. biased toward the null) by 5% to 34%. For CO modelled error amount, a range of error types were simulated and effects on risk ratio bias and significance were observed.</p> <p>Conclusions</p> <p>For multiplicative error, both the amount and type of measurement error impact health effect estimates in air pollution epidemiology. By modelling instrument imprecision and spatial variability as different error types, we estimate direction and magnitude of the effects of error over a range of error types.</p

ERRATUM: "FERMI DETECTION OF γ-RAY EMISSION FROM THE M2 SOFT X-RAY FLARE ON 2010 JUNE 12" (2012, ApJ, 745, 144)

Due to an error at the publisher, the times given for the major tick marks in the X-axis in Figure 1 of the published article are incorrect. The correctly labeled times should be "00:52:00," "00:54:00," ... , and "01:04:00." The correct version of Figure 1 and its caption is shown below. IOP Publishing sincerely regrets this error

Virus genomes reveal factors that spread and sustained the Ebola epidemic.

The 2013-2016 West African epidemic caused by the Ebola virus was of unprecedented magnitude, duration and impact. Here we reconstruct the dispersal, proliferation and decline of Ebola virus throughout the region by analysing 1,610 Ebola virus genomes, which represent over 5% of the known cases. We test the association of geography, climate and demography with viral movement among administrative regions, inferring a classic 'gravity' model, with intense dispersal between larger and closer populations. Despite attenuation of international dispersal after border closures, cross-border transmission had already sown the seeds for an international epidemic, rendering these measures ineffective at curbing the epidemic. We address why the epidemic did not spread into neighbouring countries, showing that these countries were susceptible to substantial outbreaks but at lower risk of introductions. Finally, we reveal that this large epidemic was a heterogeneous and spatially dissociated collection of transmission clusters of varying size, duration and connectivity. These insights will help to inform interventions in future epidemics

Invasive tracheal neoplasia in eight cats: descriptive cases and review of the current literature

Case series summary This case series describes eight cases of invasive tracheal neoplasia that were recognized between the years 1989 and 2014 from a single tertiary referral hospital. This is a disproportionately high number of cases compared with the total number of reports in the current literature. Relevance and novel information Invasive tracheal neoplasia is uncommonly diagnosed in domestic cats. Feline tracheal tumors mimic other upper respiratory diseases making diagnosis challenging. Prognosis is guarded to grave, with most cats surviving less than 1 month after beginning treatment. Severe respiratory distress in cats often warrants humane euthanasia. Appropriate clinical suspicion and awareness can expedite diagnoses leading to prolonged survival rates with appropriate treatments. This case series represents the largest number of feline tracheal tumors reported and also describes the first unique histological presentation of what the authors believe to be a poorly differentiated tracheal carcinoma