University of Rijeka

About: University of Rijeka is a education organization based out in Rijeka, Croatia. It is known for research contribution in the topics: Population & Tourism. The organization has 3471 authors who have published 7993 publications receiving 110386 citations. The organization is also known as: Rijeka University & Sveučilište u Rijeci.

Nano-HPLC–MS analysis of phospholipids in cerebrospinal fluid of Alzheimer’s disease patients—a pilot study

Abstract: There is emerging evidence that lipids play an important role in many neurodegenerative processes, for example in Alzheimer’s disease (AD). Although different lipid alterations in the AD brain have been reported, there have only been very few investigations of lipid changes in the cerebrospinal fluid (CSF). Recent developments in mass spectrometry (MS) have enabled fast and sensitive detection of lipid species in different biological matrixes. In this study we developed an on-line HPLC–MS method for phospholipid profiling in the CSF based on nano-HPLC separation using an Amide column and detection with electrospray (ESI) quadrupole–time of flight (QTOF) MS. We achieved good separation, reproducibility, and sensitivity in monitoring of the major phospholipid classes, phosphatidylethanolamine (PE), phosphatidylcholine (PC), phosphatidylinositol (PI), and sphingomyelin (SM) in CSF. To emphasize the applicability of the method, a pilot study was performed on a group of CSF samples (N = 16) from individuals with probable AD and non-demented controls. We observed a statistically significant increase of SM levels (24.3 ± 2.4%) in CSF from probable AD individuals vs. controls. Our findings indicate that SM levels in the CSF could potentially provide a new lead in AD biomarker research, and show the potential of the method for disease-associated CSF phospholipid screening.

Novel functions of tyrosine kinase 2 in the antiviral defense against murine cytomegalovirus.

Abstract: We have recently reported that tyrosine kinase 2 (Tyk2)-deficient mice have a selective defect in the in vivo defense against certain viruses. In our current study we show that Tyk2 is essential for the defense against murine CMV (MCMV). In vivo challenges with MCMV revealed impaired clearance of virus from organs and decreased survival of mice in the absence of Tyk2. Our in vitro studies demonstrate that MCMV replicates to dramatically higher titers in Tyk2-deficient macrophages compared with wild-type cells. We show an essential role of type I IFN (IFN-αβ) in the control of MCMV replication, with a prominent role of IFN-β. MCMV infection leads to the activation of STAT1 and STAT2 in an IFN-αβ receptor 1-dependent manner. Consistent with the role of Tyk2 in IFN-αβ signaling, activation of STAT1 and STAT2 is reduced in Tyk2-deficient cells. However, lack of Tyk2 results in impaired MCMV-mediated gene induction of only a subset of MCMV-induced IFN-αβ-responsive genes. Taken together, our data demonstrate a requirement for Tyk2 in the in vitro and in vivo antiviral defense against MCMV infection. In addition to the established role of Tyk2 as an amplifier of Jak/Stat signaling upon IFN-αβ stimulation, we provide evidence for a novel role of Tyk2 as a modifier of host responses.

Human Detection in Thermal Imaging Using YOLO

Abstract: In this paper, we consider the problem of automatic detection of humans in thermal videos and images. The thermal videos are recorded on a meadow with a small forest with up to three persons present on the scene at different positions and ranges from the camera. To simulate realistic conditions that can happen during surveillance and monitoring of protected areas, all videos are recorded at night but different weather conditions--clear weather, rain, and fog. We present the results of human detection on a custom dataset of thermal videos using the out-of-the-box YOLO convolutional neural network and the YOLO network trained on a subset of our dataset. YOLO is an object detector pretrained on the COCO image dataset of RGB images of various object classes. Test experimental results have shown significantly improved performance of human detection in thermal imaging in terms of average precision for trained YOLO model over the original model.

Microlensing Discovery of a Population of very Tight, very Low Mass Binary Brown Dwarfs

Abstract: Although many models have been proposed, the physical mechanisms responsible for the formation of low-mass brown dwarfs (BDs) are poorly understood. The multiplicity properties and minimum mass of the BD mass function provide critical empirical diagnostics of these mechanisms. We present the discovery via gravitational microlensing of two very low mass, very tight binary systems. These binaries have directly and precisely measured total system masses of 0.025 M ☉ and 0.034 M ☉, and projected separations of 0.31 AU and 0.19 AU, making them the lowest-mass and tightest field BD binaries known. The discovery of a population of such binaries indicates that BD binaries can robustly form at least down to masses of ~0.02 M ☉. Future microlensing surveys will measure a mass-selected sample of BD binary systems, which can then be directly compared to similar samples of stellar binaries.