Changes in urinary metabolomic profile during relapsing renal vasculitis

Current biomarkers of renal disease in systemic vasculitis lack predictive value and are insensitive to early damage. To identify novel biomarkers of renal vasculitis flare, we analysed the longitudinal urinary metabolomic profile of a rat model of anti-neutrophil cytoplasmic antibody (ANCA) vasculitis. Wistar-Kyoto (WKY) rats were immunised with human myeloperoxidase (MPO). Urine was obtained at regular intervals for 181 days, after which relapse was induced by re-challenge with MPO. Urinary metabolites were assessed in an unbiased fashion using nuclear magnetic resonance (NMR) spectroscopy, and analysed using partial least squares discriminant analysis (PLS-DA) and partial least squares regression (PLS-R). At 56 days post-immunisation, we found that rats with vasculitis had a significantly different urinary metabolite profile than control animals; the observed PLS-DA clusters dissipated between 56 and 181 days, and re-emerged with relapse. The metabolites most altered in rats with active or relapsing vasculitis were trimethylamine N-oxide (TMAO), citrate and 2-oxoglutarate. Myo-inositol was also moderately predictive. The key urine metabolites identified in rats were confirmed in a large cohort of patients using liquid chromatography-mass spectrometry (LC-MS). Hypocitraturia and elevated urinary myo-inositol remained associated with active disease, with the urine myo-inositol:citrate ratio being tightly correlated with active renal vasculitis

Global burden of human brucellosis : a systematic review of disease frequency

BACKGROUND: This report presents a systematic review of scientific literature published between 1990-2010 relating to the frequency of human brucellosis, commissioned by WHO. The objectives were to identify high quality disease incidence data to complement existing knowledge of the global disease burden and, ultimately, to contribute towards the calculation of a Disability-Adjusted Life Years (DALY) estimate for brucellosis.METHODS/PRINCIPAL FINDINGS: Thirty three databases were searched, identifying 2,385 articles relating to human brucellosis. Based on strict screening criteria, 60 studies were selected for quality assessment, of which only 29 were of sufficient quality for data analysis. Data were only available from 15 countries in the regions of Northern Africa and Middle East, Western Europe, Central and South America, Sub-Saharan Africa, and Central Asia. Half of the studies presented incidence data, six of which were longitudinal prospective studies, and half presented seroprevalence data which were converted to incidence rates. Brucellosis incidence varied widely between, and within, countries. Although study biases cannot be ruled out, demographic, occupational, and socioeconomic factors likely play a role. Aggregated data at national or regional levels do not capture these complexities of disease dynamics and, consequently, at-risk populations or areas may be overlooked. In many brucellosis-endemic countries, health systems are weak and passively-acquired official data underestimate the true disease burden.CONCLUSIONS: High quality research is essential for an accurate assessment of disease burden, particularly in Eastern Europe, the Asia-Pacific, Central and South America and Africa where data are lacking. Providing formal epidemiological and statistical training to researchers is essential for improving study quality. An integrated approach to disease surveillance involving both human health and veterinary services would allow a better understand of disease dynamics at the animal-human interface, as well as a more cost-effective utilisation of resources

On Random Sampling and Fourier Transform Estimation in Sea Waves Prediction

Improving the safety of a wide range of launch and recovery operations is of great international maritime interest. Deterministic sea wave prediction (DSWP) is a relatively new branch of science that can offer such opportunities by predicting the actual shape of the sea surface and its evolution for short time in the future. Fourier transform technique is the main building block in DSWP, which requires measurements of the sea surface. Nonetheless, uniformly sampled measurements of the sea surface cannot be practically achieved for various reasons. Conventional X-band radars are the most realistic candidate to provide a low-cost convenient source of two-dimensional wave profile information for DSWP purposes. Ship movement and mechanically rotating scanning antennas are among sources of irregularity in sea surface sampling. This in turn introduces errors when traditional Fourier transform based wave prediction methods are used. In this paper we show that by modelling the radar sampling instants as random variables and using the estimator of Tarczynski and Allay to process the samples, a reliable solution for DSWP can be constituted

Adjusted Location Privacy Scheme in VANET Safety Applications

The primary aim of Vehicular Ad hoc NETworks (VANET) is to enhance traffic safety by enabling frequent broadcasting of location information between vehicles. In VANET safety applications, a vehicle requires to broadcast messages, which usually contain its location information, every (1-10 Hz) with other vehicles in its communication area (300m) to facilitate cooperative awareness. This would arise privacy issues because vehicles are vulnerable to tracking attacks via their locations. To prevent long-term linking, many privacy schemes have adopted a silent period in which a vehicle stops sharing its locations for a period. However, silent periods could have a negative impact on safety applications as an accident could have happened if a vehicle stop sharing its locations with other neighbours. Thus, in this paper, we first discuss three privacy schemes (RSP, SLOW and CAPS), which adopted silent periods but in different concepts. Then, we improve the privacy and safety level of CAPS. A privacy simulator PREXT is used to evaluate and compare the performance of schemes

A multimodal deep learning framework using local feature representations for face recognition

YesThe most recent face recognition systems are mainly dependent on feature representations obtained using either local handcrafted-descriptors, such as local binary patterns (LBP), or use a deep learning approach, such as deep belief network (DBN). However, the former usually suffers from the wide variations in face images, while the latter usually discards the local facial features, which are proven to be important for face recognition. In this paper, a novel framework based on merging the advantages of the local handcrafted feature descriptors with the DBN is proposed to address the face recognition problem in unconstrained conditions. Firstly, a novel multimodal local feature extraction approach based on merging the advantages of the Curvelet transform with Fractal dimension is proposed and termed the Curvelet–Fractal approach. The main motivation of this approach is that theCurvelet transform, a newanisotropic and multidirectional transform, can efficiently represent themain structure of the face (e.g., edges and curves), while the Fractal dimension is one of the most powerful texture descriptors for face images. Secondly, a novel framework is proposed, termed the multimodal deep face recognition (MDFR)framework, to add feature representations by training aDBNon top of the local feature representations instead of the pixel intensity representations. We demonstrate that representations acquired by the proposed MDFR framework are complementary to those acquired by the Curvelet–Fractal approach. Finally, the performance of the proposed approaches has been evaluated by conducting a number of extensive experiments on four large-scale face datasets: the SDUMLA-HMT, FERET, CAS-PEAL-R1, and LFW databases. The results obtained from the proposed approaches outperform other state-of-the-art of approaches (e.g., LBP, DBN, WPCA) by achieving new state-of-the-art results on all the employed datasets

SPARC 2017 retrospect & prospects : Salford postgraduate annual research conference book of abstracts

Welcome to the Book of Abstracts for the 2017 SPARC conference. This year we not only celebrate the work of our PGRs but also the 50th anniversary of Salford as a University, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 130 presenters, the conference truly showcases a vibrant PGR community at Salford. These abstracts provide a taster of the research strengths of their works, and provide delegates with a reference point for networking and initiating critical debate. With such wide-ranging topics being showcased, we encourage you to exploit this great opportunity to engage with researchers working in different subject areas to your own. To meet global challenges, high impact research inevitably requires interdisciplinary collaboration. This is recognised by all major research funders. Therefore engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers

The efficacy of aspirin versus low‐molecular‐weight heparin for venous thromboembolism prophylaxis after knee and hip arthroplasty: A systematic review and meta‐analysis of randomized controlled trials

Purpose: The purpose of this study was to assess the efficacy of aspirin versus low‐molecular‐weight heparin (LMWH) in preventing venous thromboembolism (VTE) following hip and knee arthroplasty. Methods: PubMed/Medline, Embase, Cochrane Library and Google Scholar databases were searched from inception till June 2024 for original trials investigating the outcomes of aspirin versus LMWH in hip and knee arthroplasty. The primary outcome was VTE. Secondary outcomes included minor and major bleeding events, and postoperative mortality within 90 days. This review was conducted per the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines. Results: A total of 7 randomized controlled trials with 12,134 participants were included. The mean ages for the aspirin and LMWH cohorts were 66.6 (57.6–69.0) years and 66.8 (57.9–68.9) years, respectively. There was no statistically significant difference in the overall risk of VTE between the aspirin and the LMWH cohorts (odds ratio [OR]: 0.95; 95% confidence interval [CI]: 0.48–1.89; p: 0.877). A subanalysis based on the specific VTE entity (pulmonary embolism [PE] or deep venous thrombosis) showed a significantly higher PE risk for patients receiving aspirin than the LMWH cohort (OR: 1.79; 95% CI: 1.11–2.89; p: 0.017). There was no difference in minor (OR: 0.64; 95% CI: 0.40–1.04; p: 0.072) and major bleeding (OR: 0.77; 95% CI: 0.40–1.47; p: 0.424) episodes across both groups. Furthermore, subanalysis among the total knee arthroplasty group showed that the aspirin cohort was significantly more likely to suffer VTEs than their LMWH counterparts (OR: 1.55; 95% CI: 1.21–1.98; p < 0.001). Conclusion: This study demonstrated a significantly higher risk of PE among patients receiving aspirin compared to LMWH following hip or knee arthroplasty for osteoarthritis. Aspirin was associated with a significantly higher overall VTE risk among patients undergoing knee arthroplasty, in particular. This might suggest the inferiority of aspirin compared to LMWH in preventing VTE following such procedures. Level of Evidence: Level I

Detection of Nicotine in Equisetum arvense Grown Naturally in Iraq

Equisetum arvense L, Family: Equisetaceae, common name hoarse tails. The plant is used traditionally to stop bleeding, heal ulcers and wounds, and treat tuberculosis and kidney problems.             The new approach is the investigation of cytotoxic and anti HIV activities of this plant. The aerial part of the plant was extracted to investigate the presence of alkaloids in it. Powdered plant was macerated with 2N HCl overnight.             The alkaloids were detected with Dragendorrf reagent and were found to be one spot. Investigation of the extracted alkaloids using GC/MS reveal the presence of nicotine as the single alkaloids found in the plant