OBJECTIVES IgA vasculitis (IgAV, formerly known as Henoch-Schönlein purpura) is the most common cause of systemic vasculitis in childhood. To date, there are no internationally agreed, evidence-based guidelines concerning the appropriate diagnosis and treatment of IgAV in children. Accordingly, treatment regimens differ widely. The European initiative SHARE (Single Hub and Access point for paediatric Rheumatology in Europe) aims to optimize care for children with rheumatic diseases. The aim therefore was to provide internationally agreed consensus recommendations for diagnosis and treatment for children with IgAV. METHODS Recommendations were developed by a consensus process in accordance with the EULAR standard operating procedures. An extensive systematic literature review was performed, and evidence-based recommendations were extrapolated from the included papers. These were evaluated by a panel of 16 international experts via online surveys and subsequent consensus meeting, using nominal group technique. Recommendations were accepted when ⩾80% of experts agreed. RESULTS In total, 7 recommendations for diagnosis and 19 for treatment of paediatric IgAV were accepted. Diagnostic recommendations included: appropriate use of skin and renal biopsy, renal work-up and imaging. Treatment recommendations included: the importance of appropriate analgesia and angiotensin-converting enzyme inhibitor use and non-renal indications for CS use, as well as a structured approach to treating IgAV nephritis, including appropriate use of CS and second-line agents in mild, moderate and severe disease along with use of angiotensin-converting enzyme inhibitors and maintenance therapy. CONCLUSION The SHARE initiative provides international, evidence-based recommendations for the diagnosis and treatment of IgAV that will facilitate improvement and uniformity of care.

Introduction: Congenital hydronephrosis (CH) is a condition with dilated renal pelvis with or without dilation of renal calyces. Aim: To examine the role of magnetic resonance urography in the detection of congenital hydronephrosis in comparison to dynamic renal scintigraphy (DRS). Patients and methods: Resarch included 58 (n=58) patients with diagnosis of congenital unilateral or bilateral dilatation of kidney duct system. Each patient had a one-time or multiple hospitalization at the Nephrology Department of the Pediatric Clinic, with performed: ultrasound which confirmed CH, voiding cystourethrography / voiding urosonography was confirmed based on which the vesicoureteral reflux (VUR) was established / excluded, dynamic renal scintigraphy and magnetic urography (analysis was made by CHOP-fMRU software) on the basis of which the uterine anatomy and the relative renal function were evaluated. Results: Male patients were represented in 40 cases (69%). The average age was 4.4 ± 4.3 years with the youngest patient at the age of 2 months, and the oldest was 17 years old. According to diagnostic entities, the most common diagnosis was ureteropelvic junction (UPJ) obstruction in over half of cases (30 or 51.7%), followed by subjects with ureterovesical junction (UVJ) obstruction (11 or 19%), VUR was recorded in 9 (15.5%) cases, and pyelon fissus in 7 (12.1%), and one case (1.7%) was recorded with bilateral megaureter. Comparison of the value of the renal function obtained with DRS and CHOP-fMRU methods shows that there were no statistically significant differences between two methods. In the case of right kidney, the mean DRS value was 53.4 ± 18.4% (range 13-100%), while CHOP-fMRU was 51.8 ± 22.4 (range 0-96.7%). In the case of left kidney, the average value according to the DRS method was 46.9 ± 18.9% (range 0-87%) and according to CHOP-fMRU 47.6 ± 21.5% (range 8.3-100%). The correlation coefficients of both right and left kidneys show a highly statistically significant correlation between these two methods. Conclusion: Magnetic resonance urography in the pediatric population in CH based on results should be an integral part of the management of these patients, especially in congenital obstructive uropathy, in complex and associated congenital anomalies, as it provides morphological and functional data on the state of the kidneys and urinary tract.

SUMMARY Pandemic influenza A virus (H1N1) 2009 causes a disease that is epidemiologically and clinically not significantly different from seasonal influenza, but there are differences. The aim of the study was to display and compare epidemiological and clinical characteristics of pandemic influenza in children. At Dr. Fran Mihaljević University Hospital for Infectious Diseases in Zagreb, in the first two seasons, the incidence of pandemic influenza virus A (H1N1) in particular was exhaustively analyzed only in patients with laboratory-confirmed pandemic influenza A virus (H1N1) 2009. In hospitalized children with documented influenza pandemic, moderate form of the disease predominated, which ultimately meant shorter hospital stay and fewer complications. Otitis media was the rarest complication in children in both seasons. In conclusion, children younger than 5 years, especially boys, were vulnerable groups for pandemic influenza, presenting as a mild disease with low mortality and few complications. Most of the affected children with influenza did not have important risk factors such as asthma and obesity, highlighted by other authors as significant risk factors.

Background and objectives: Pharmacotherapy literacy (PHTL) is an individual’s capacity to obtain, evaluate, calculate, and comprehend basic information about pharmacotherapy and pharmacy-related services necessary to make appropriate medication-related decisions, regardless of the mode of content delivery (e.g., written, oral, visual images and symbols). It is already proven that low PHTL of parents can cause serious problems in the treatment of a pediatric population. We aimed to identify the differences in parental PHTL levels, socio-demographic and health-related characteristics (chronic disease of a child, breastfeeding of a child, annual visits to a pediatrician, parental-self-estimation of health status) between rural and urban areas and to investigate the influence of living in rural areas on a low PHTL level. Materials and methods: Our study was cross-sectional with a validated 14-item instrument (“Parental pharmacotherapy literacy questionnaire—Serbian”), which assessed overall PHTL and its three domains of knowledge, understanding and numerical skills necessary for the safe use of medicines. We analyzed 250 parents of pre-school children (1–7 years old) in rural areas and 182 parents from urban areas in Serbia. Results: Every tenth parent from rural and every fourth parent from urban areas had the highest PHTL level or more than 85% correct answers. However, 51% and 28% of parents in rural and urban areas, respectively, had a low PHTL level (less than 65% correct answers), [Х2(1, n = 432) = 33.2; p < 0.001]. Parents from different areas statistically differed in age, education level, employment, breastfeeding and annual visits to pediatrician rate. Those from rural areas had almost twice the probability of low PHTL levels (ORa = 2.033; p = 0.003) than their urban counterparts, independently of other examined parental characteristics. Conclusions: Parents from rural areas have more difficulties to obtain, evaluate, calculate and comprehend basic information related to pharmacotherapy than parents from urban areas.

The objective of this study was to evaluate impact of light and available oxygen on the chemical composition of three selected essential oils. Aliquots of immortelle (Helichrysum italicum), silver fir (Abies alba) and prickly juniper (Juniperus oxycedrus) essential oils were exposed to UV-A irradiation in the presence of atmospheric oxygen as well as in the presence of inert gas. The compositions of fresh and irradiated samples were studied by GC/MS. Each oil showed an individual response to the applied conditions. In immortelle oil, dominant process was phototransformation of g-curcumene to italicene, isoitalicene and ?-curcumene. Since g-curcumene is one of the major components of immortelle essential oil, exposure of this oil to light can cause significant changes in primary composition and thus quality. In silver fir and prickly juniper oil irradiation caused only slight changes among sesquiterpenes that are present as minor components. Both oils were found to be photostabile and insensitive to the presence of atmospheric oxygen.

Cytochromes P450 are major metabolic enzymes involved in the biotransformation of xenobiotics. The majority of xenobiotics are metabolized in the liver, in which the highest levels of cytochromes P450 are expressed. Flavonoids are natural compounds to which humans are exposed through everyday diet. In the previous study, selected flavonoid aglycones showed inhibition of CYP3A4 enzyme. Thus, the objective of this study was to determine if these flavonoids inhibit metabolic activity of CYP1A2, CYP2A6, CYP2C8, and CYP2D6 enzymes. For this purpose, the O-deethylation reaction of phenacetin was used for monitoring CYP1A2 enzyme activity, coumarin 7-hydroxylation for CYP2A6 enzyme activity, 6-α-hydroxylation of paclitaxel for CYP2C8 enzyme activity, and dextromethorphan O-demethylation for CYP2D6 enzyme activity. The generated metabolites were monitored by high-performance liquid chromatography coupled with diode array detection. Hesperetin, pinocembrin, chrysin, isorhamnetin, and morin inhibited CYP1A2 activity; apigenin, tangeretin, galangin, and isorhamnetin inhibited CYP2A6 activity; and chrysin, chrysin-dimethylether, and galangin inhibited CYP2C8. None of the analyzed flavonoids showed inhibition of CYP2D6. The flavonoids in this study were mainly reversible inhibitors of CYP1A2 and CYP2A6, while the inhibition of CYP2C8 was of mixed type (reversible and irreversible). The most prominent reversible inhibitor of CYP1A2 was chrysin, and this was confirmed by the docking study.

Background Recognition of total elbow arthroplasties (TEAs) on plain radiographs is difficult due to a multitude of different types and models. Especially if surgery reports and documentation are not available, lost or when the primary surgery was performed in another hospital the prosthesis type may be undeterminable. Therefore we investigated in this platform study if a flowchart aids in recognition of thirteen different total elbow arthroplasty models on plain radiographs. Methods An online questionnaire on the Shoulder and Elbow Platform was developed. Plain radiographs of thirteen TEA models were shown with and without the help of an especially developed flowchart describing distinguishing features. Results Ten orthopedic surgeons specialized in upper extremity surgery completed the study. Recognition rates of the thirteen total elbow arthroplasty models ranged between 20 and 100 percent without the flowchart. Using the flowchart recognition varied between 40 and 90 percent. The recognition rates with the flowchart were not significantly higher. Inter-observer reliability did not increase on a significant level. Conclusion Correct recognition of total elbow arthroplasty models with plain radiographs remains imperfect with our developed flowchart. The flowchart increased correct recognition rates and inter-observer reliability.

The process of beer brewing is very complex as it has to fulfill strict demands on the product quality as well as on the availability and the performance of the plant. As a consequence, a condition monitoring of the beer brewing process and its visualization plays an important role such that all relevant deviations are detected as early as possible by the production manager. While a general process for condition monitoring already exists, there currently exists no approach to realize this process for the domain of beer brewing.Therefore, this paper presents a condition monitoring system for the beer brewing process developed in an industrial project. This condition monitoring system is based on Key Performance Indicators (KPIs) that support the production manager in evaluating the actual state of the production processes. A set of brewery-specific KPIs are determined and discussed in the paper. In addition, software architecture and visualization of the KPIs in a brewery-specific dashboard are presented. We evaluate our concept at various beer breweries and report about lessons that we have learned.

Condition monitoring enables companies from all industrial branches to maintain high availability of their automation systems. Thus, condition monitoring is a fundamental technology to maximize operational productivity by predicting potential fault occurrences that lead to unavailability of the automation systems. Today, performing condition monitoring is successfully achieved using custom-developed software solutions. However, the development of these software solutions is a challenging task as it requires extensive knowledge from multiple engineering disciplines. In this context, there is a high need for a systematic way to formalize this knowledge. Ontologies have had significant success in fulfilling this need by providing a formal model of domain concepts and their relations.In this paper, we present our condition monitoring ontology for automation systems and contribute with a conceptual model. This ontology incorporates ISO standards for condition monitoring and key performance indicators (KPIs). KPIs aggregate numerous sensor values in a few understandable numbers and, therefore, provide more efficient insight in condition of automation systems. To evaluate our work, we developed a condition monitoring knowledge-based system for a centrifugal separator based on the proposed ontology in an industrial project and report about lessons learned.

The aim of this research is to create fully functional environment for real-life testing of various algorithms in mobile robotic. Main advantage, beside low-cost, is dealing with challenges of real-life implementation. Unlike simulation environments (e.g. MathLab), this setting will allow researchers to test their path planning, collision detection and other algorithms with real challenges, real robots and real static and dynamic obstacles. Environment is particularly adapted for swarm robotics and any other mobile robotics including 2D and 3D scenarios. Enabling researches to prove their algorithms in this environment allows significantly faster path to real implementation in industry, military and science. Concept is based on OpenCV library and low-cost hardware. Solution is based on visual positioning and motion vector detection. System allows controlling mobile robots via radio communication with the range up to 100m which allows practical application of the system. This research paper should be considered as a part of series of research papers published earlier.

Abstract The majority of past studies assessed the impact of oil price on stock returns using aggregate stock price index from different countries and assuming the effects to be symmetric. In this paper, we investigate asymmetric causality not only from oil price to stock returns but also from stock returns to oil price. To reduce aggregation bias, we use data from nine different sectors of the U.S. economy. We found that an increase in oil price causes returns of three sectors, while a decrease in oil price causes returns of four sectors, all in the short run. On the other hand, we found that an increase in returns in three sectors causes oil price to rise, while a decrease in returns in six sectors causes oil price to decline. We do not discover significant long-run causal relationship in either direction.

Abstract Poorly regulated and insufficiently supervised medical devices (MDs) carry high risk of performance accuracy and safety deviations effecting the clinical accuracy and efficiency of patient diagnosis and treatments. Even with the increase of technological sophistication of devices, incidents involving defibrillator malfunction are unfortunately not rare. To address this, we have developed an automated system based on machine learning algorithms that can predict performance of defibrillators and possible performance failures of the device which can affect performance. To develop an automated system, with high accuracy, overall dataset containing safety and performance measurements data was acquired from periodical safety and performance inspections of 1221 defibrillator. These inspections were carried out in period 2015–2017 in private and public healthcare institutions in Bosnia and Herzegovina by ISO 17,020 accredited laboratory. Out of overall number of samples, 974 of them were used during system development and 247 samples were used for subsequent validation of system performance. During system development, 5 different machine learning algorithms were used, and resulting systems were compared by obtained performance. The results of this study demonstrate that clinical engineering and health technology management benefit from application of machine learning in terms of cost optimization and medical device management. Automated systems, based on machine learning algorithms, can predict defibrillator performance with high accuracy. Systems based on Random Forest classifier with Genetic Algorithm feature selection yielded highest accuracy among other machine learning systems. Adoption of such systems will help in overcoming challenges of adapting maintenance and medical device supervision mechanism protocols to rapid technological development of these devices. Due to increased complexity of healthcare institution environment and increased technological complexity of medical devices, performing maintenance strategies in traditional manner is causing a lot of difficulties.