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  • Varough M. Deyde, Rangarajan Sampath, Rebecca J. Garten, Patrick J. Blair, Christopher A. Myers, Christian Massire +6 others
  • 2010
BACKGROUND The emergence and rapid spread of the 2009 H1N1 pandemic influenza A virus (H1N1pdm) in humans highlights the importance of enhancing the capability of existing influenza surveillance systems with tools for rapid identification of emerging and re-emerging viruses. One of the new approaches is the RT-PCR electrospray ionization mass spectrometry(More)
  • Peter G. Barlow, Pavel Svoboda, Annie Mackellar, Anthony A. Nash, Ian A. York, Jan Pohl +2 others
  • 2011
The extensive world-wide morbidity and mortality caused by influenza A viruses highlights the need for new insights into the host immune response and novel treatment approaches. Cationic Host Defense Peptides (CHDP, also known as antimicrobial peptides), which include cathelicidins and defensins, are key components of the innate immune system that are(More)
We recently reported that HIV-1 infection can be inhibited by innate antimicrobial components of human seminal plasma (SP). Conversely, naturally occurring peptidic fragments from the SP-derived prostatic acid phosphatase (PAP) have been reported to form amyloid fibrils called "SEVI" and enhance HIV-1 infection in vitro. In order to understand the(More)
Capsular polysaccharides (CPS) are a major virulence factor in meningococcal infections and form the basis for serogroup designation and protective vaccines. Our work has identified meningococcal CPS as a pro-inflammatory ligand that functions through TLR2 and TLR4-MD2-dependent activation. We hypothesized that human cationic host defense peptides interact(More)
In this work we explore the previously proposed approach of direct blind deconvolution and denoising with convolu-tional neural networks in a situation where the blur kernels are partially constrained. We focus on blurred images from a real-life traffic surveillance system, on which we, for the first time, demonstrate that neural networks trained on(More)
This paper shows that it is possible to train large and deep convolutional neural networks (CNN) for JPEG compression artifacts reduction, and that such networks can provide significantly better reconstruction quality compared to previously used smaller networks as well as to any other state-of-the-art methods. We were able to train networks with 8 layers(More)
Maximum likelihood estimation (MLE) is a well-known estimation method used in many robotic and computer vision applications. Under Gaussian assumption, the MLE converts to a nonlinear least squares (NLS) problem. Efficient solutions to NLS exist and they are based on iteratively solving sparse linear systems until convergence. In general, the existing(More)
OBJECTIVE The infliximab biosimilar CT-P13 (Remsima(®), Inflectra(®)) was approved in Europe for the treatment of inflammatory bowel disease (IBD) based on extrapolation of data from patients with rheumatic disease. Because there are limited published reports on clinical outcomes for IBD patients treated with CT-P13, we monitored responses to induction(More)
Respiratory syncytial virus (RSV) is a major cause of severe lower respiratory tract illness in young children worldwide. Treatment options for severe RSV disease remain limited and the development of therapeutic treatment strategies remains a priority. LL-37, a small cationic host defense peptide involved in anti-inflammatory and anti-bacterial responses,(More)
Protegrins are porcine antimicrobial peptides (AMPs) that belong to the cathelicidin family of host defense peptides. Protegrin-1 (PG-1), the most investigated member of the protegrin family, is an arginine-rich peptide consisting of 18 amino acid residues, its main chain adopting a β-hairpin structure that is linked by two disulfide bridges. We report on(More)