Nefroprotective properties of febuxostat in chronic renal failure

Urgency. Chronic renal failure poses medical, social and organizational problem because of high mortality, disability and complexity of modern treating methods technical support. The objective: to evaluate the effectiveness of febuxostat in controlling hyperuricemia in patients with end-stage chronic renal failure. Material and methods. 90 patients were divided into three groups in accordance with the use of febuxostat at a dose of 40 mg to reduce uric acid level: group 1 (n=30) - terminal chronic renal failure patients who are not yet receiving renal replacement therapy; Group 2 (n=30) peritoneal dialysis patients; 3 group (n=30)- hemodialysis patients. Results and discussion. Febuxostat use led to uric acid level decrease in all groups under study, increase of the  functional renal reserve level in the 1st and 2nd groups. In the 3rd group patients (hemodialysis patients), only uric acid level changes were studied in connection with the absence of in this cohort residual functional renal reserve. The use of febuxostat determines, with decrease in uric acid levels, increase in the residual functional renal reserve and improvement the patients’ quality of life according to the questionnaire data. These results are best reflected in pre-dialysis patients with terminal chronic renal failure. Conclusion: treatment with febuxostat leads to a marked decrease in the level of serum uric acid, increase of residual functional renal reserve and improvement of chronic renal failure patients quality of life, which indicates its good nephroprotective properties

Febuxsostat as a renoprotector in patients with chronic renal insufficiency

In the article presented the data about dependence of uricemia’s level and the subjective assessment of the quality of life in patients with end stage renal disease (ESRD) and an increase ofresidual functional renal reserve in 90 patients under the influence of febuxsostat at a dose of 40 mg are given. It has been proved that by reducing the level of uric acid, the residual functional renal reserve increases and the quality of life of patients improves (according to the questionnaire). This is best reflected in predialysis patients with ESRD. The data obtained allow febuxsostat consider to be effective urates-reductive therapy

Meta-Tracker: Fast and Robust Online Adaptation for Visual Object Trackers

This paper improves state-of-the-art visual object trackers that use online adaptation. Our core contribution is an offline meta-learning-based method to adjust the initial deep networks used in online adaptation-based tracking. The meta learning is driven by the goal of deep networks that can quickly be adapted to robustly model a particular target in future frames. Ideally the resulting models focus on features that are useful for future frames, and avoid overfitting to background clutter, small parts of the target, or noise. By enforcing a small number of update iterations during meta-learning, the resulting networks train significantly faster. We demonstrate this approach on top of the high performance tracking approaches: tracking-by-detection based MDNet and the correlation based CREST. Experimental results on standard benchmarks, OTB2015 and VOT2016, show that our meta-learned versions of both trackers improve speed, accuracy, and robustness.Comment: Code: https://github.com/silverbottlep/meta_tracker

Long-Term Visual Object Tracking Benchmark

We propose a new long video dataset (called Track Long and Prosper - TLP) and benchmark for single object tracking. The dataset consists of 50 HD videos from real world scenarios, encompassing a duration of over 400 minutes (676K frames), making it more than 20 folds larger in average duration per sequence and more than 8 folds larger in terms of total covered duration, as compared to existing generic datasets for visual tracking. The proposed dataset paves a way to suitably assess long term tracking performance and train better deep learning architectures (avoiding/reducing augmentation, which may not reflect real world behaviour). We benchmark the dataset on 17 state of the art trackers and rank them according to tracking accuracy and run time speeds. We further present thorough qualitative and quantitative evaluation highlighting the importance of long term aspect of tracking. Our most interesting observations are (a) existing short sequence benchmarks fail to bring out the inherent differences in tracking algorithms which widen up while tracking on long sequences and (b) the accuracy of trackers abruptly drops on challenging long sequences, suggesting the potential need of research efforts in the direction of long-term tracking.Comment: ACCV 2018 (Oral

Learning Rotation Adaptive Correlation Filters in Robust Visual Object Tracking

Visual object tracking is one of the major challenges in the field of computer vision. Correlation Filter (CF) trackers are one of the most widely used categories in tracking. Though numerous tracking algorithms based on CFs are available today, most of them fail to efficiently detect the object in an unconstrained environment with dynamically changing object appearance. In order to tackle such challenges, the existing strategies often rely on a particular set of algorithms. Here, we propose a robust framework that offers the provision to incorporate illumination and rotation invariance in the standard Discriminative Correlation Filter (DCF) formulation. We also supervise the detection stage of DCF trackers by eliminating false positives in the convolution response map. Further, we demonstrate the impact of displacement consistency on CF trackers. The generality and efficiency of the proposed framework is illustrated by integrating our contributions into two state-of-the-art CF trackers: SRDCF and ECO. As per the comprehensive experiments on the VOT2016 dataset, our top trackers show substantial improvement of 14.7% and 6.41% in robustness, 11.4% and 1.71% in Average Expected Overlap (AEO) over the baseline SRDCF and ECO, respectively.Comment: Published in ACCV 201

Studying the Fe-Al-Si system in relation to ferrosilicon-aluminum alloy crystallization

In the work there have been calculated the values of enthalpies for a number of ternary compounds and carried out triangulation of the Fe–Al–Si system. The main areas of the compounds crystallization have been determined in relation to industrial compositions of ferrosilicon-aluminum. There has been carried out the analysis of possible causes of some alloy compositions self-grinding and recommended compositions with guaranteed stable physical characteristics

Dynamic changes in microbiome composition following Mare's milk intake for prevention of collateral antibiotic effect

INTRODUCTION: Probiotics and prebiotics are widely used for recovery of the human gut microbiome after antibiotic treatment. High antibiotic usage is especially common in children with developing microbiome. We hypothesized that dry Mare's milk, which is rich in biologically active substances without containing live bacteria, could be used as a prebiotic in promoting microbial diversity following antibiotic treatment in children. The present pilot study aims to determine the impacts of dry Mare's milk on the diversity of gut bacterial communities when administered during antibiotic treatment and throughout the subsequent recovery phase. METHODS: Six children aged 4 to 5 years and diagnosed with bilateral bronchopneumonia were prescribed cephalosporin antibiotics. During the 60 days of the study, three children consumed dry Mare's milk whereas the other three did not. Fecal samples were collected daily during antibiotic therapy and every 5 days after antibiotic therapy. Total DNA was isolated and taxonomic composition of gut microbiota was analyzed by 16S rRNA amplicon sequencing. To assess the immune status of the gut, stool samples were analyzed by bead-based multiplex assays. RESULTS: Mare's milk treatment seems to prevent the bloom of Mollicutes, while preventing the loss of Coriobacteriales. Immunological analysis of the stool reveals an effect of Mare’s milk on local immune parameters under the present conditions

Occlusion and Motion Reasoning for Long-Term Tracking

International audienceObject tracking is a reoccurring problem in computer vision. Tracking-by-detection approaches, in particular Struck (Hare et al., 2011), have shown to be competitive in recent evaluations. However, such approaches fail in the presence of long-term occlusions as well as severe viewpoint changes of the object. In this paper we propose a principled way to combine occlusion and motion reasoning with a tracking-by-detection approach. Occlusion and motion reasoning is based on state-of-the-art long-term trajectories which are labeled as object or background tracks with an energy-based formulation. The overlap between labeled tracks and detected regions allows to identify occlusions. The motion changes of the object between consecutive frames can be estimated robustly from the geometric relation between object trajectories. If this geometric change is significant, an additional detector is trained. Experimental results show that our tracker obtains state-of-the-art results and handles occlusion and viewpoints changes better than competing tracking methods