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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)
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)
Drought and low temperature are the two most significant causes of abiotic stress in agricultural crops and, therefore, they pose considerable challenges in plant science. Hence, it is crucial to study response mechanisms and to select genes for identification signaling pathways that lead from stimulus to response. The assessment of gene expression is often(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)
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)
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)
We have synthesized nickel nanoparticles using nickel chloride as a precursor in ethanol using PVP (Poly Vinyl Pyrrolidone) as a surfactant and hydrazine hydrate as reducing agent at 60 °C in a facile manner. The structural analysis showed that particles are face-centered cubic and monodisperse within the PVP matrix with average size about 3 nm. The(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)
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)
The most common way to deal with the uncertainty present in noisy sensorial perception and action is to model the problem with a probabilistic framework. 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)(More)