Low cholesterol along with inflammation predicts morbidity and mortality in hemodialysis patients

Low and not high cholesterol seems to predict high mortality in hemodialysis (HD) patients. The confirmation of this reverse epidemiology as well as its possible interconnection with the increased inflammatory activity observed in this population is being explored in the present study. A group of 136 HD patients was prospectively studied for 2 years, and cardiovascular disease (CVD) as well as all-cause mortality and morbidity were recorded. Baseline lipid profile, inflammatory status, and patients' characteristics were studied as potential survival and hospitalization predictors. During the 24-month follow-up, 21 deaths (52.4% due to CVD) and 38 hospitalizations (55.3% due to CVD) were recorded. In multivariate Cox regression analysis, decreased interleukin-10 (IL-10) and decreased total serum cholesterol (TChol) were the only independent predictors of CVD mortality while C-reactive protein and decreased TChol predicted all-cause mortality. Interleukin-10 at baseline was 11.29 ± 21.49 vs. 5.51 ± 4.57 pg/mL (P<0.018) and TChol 167.37 ± 47.84 vs.122.04 ± 26.48 mg/dL (P<0.000) in survivors vs. nonsurvivors from CVD, while C-reactive protein at baseline was 9.37 ± 11.54 vs. 23.15 ± 18.76 mg/L (P<0.000) and TChol 169.26 ± 46.42 vs. 133.26 ± 46.33 mg/dL (P<0.003) in survivors vs. nonsurvivors from any cause of death. Using the same method of statistical analysis, IL-6 and decreased soluble gp130 (sgp130)—an antagonist of IL-6 action—were found to be the only independent prognostic factors for hospitalization due to CVD while decreased soluble gp130 remained the sole predictor of hospitalization due to any cause. In conclusion, reverse epidemiology regarding cholesterol is confirmed in the present study. Furthermore, inflammatory activity also predicts, independently of or in conjunction with low-cholesterol, CVD and all-cause morbidity and mortality in HD patients.     

Development of a database system for the calculation of indicators of environmental pressure caused by transport

The scope of this paper is to summarise a methodology developed for TRENDS (TRansport and ENvironment Database System-TRENDS). The main objective of TRENDS was the calculation of environmental pressure indicators caused by transport. The environmental pressures considered are associated with air emissions from the four main transport modes, i.e. road, rail, ships and air. In order to determine these indicators a system for calculating a range of environmental pressures due to transport was developed within a PC-based MS Access environment. Emphasis is given on the latest features incorporated in the model and their applications. One of the recently developed features of the software provides an option for simple scenario analysis including vehicle dynamics (such as turnover and evolution) for all EU15 member states. This feature is called the Transport Activity Balance module (TAB) and enables the production of collective results for all transport modes as well as a comparative assessment of air emissions produced by the various modes. Traffic activity and emission data obtained according to a basic (reference) scenario are displayed for the time period 1970-2020. In addition, a detailed assessment of the results produced by TRENDS was conducted by means of comparison with data found in the literature. Finally, vehicle emissions produced by the model for the EU15 member states were spatially disaggregated for the base year, 1995 and GIS maps were generated. Examples of these maps are displayed in this document, for the various modes of transport considered in the study.     

CD28null and Regulatory T Cells Are Substantially Disrupted in Patients with End-Stage Renal Disease Due to Diabetes Mellitus

Background: End-stage renal disease (ESRD) is associated with alterations in T-cell immunity, including increased CD28null and reduced regulatory T cells (Tregs). However, whether immune disturbances are due to ESRD or primary disease is not yet clear. As diabetes mellitus is the leading cause of ESRD, we evaluated its impact on the immune profile of ESRD patients. Methods: CD28null, Tregs, and natural killer cells were initially analyzed by flow cytometry in 30 predialysis ESRD patients due to diabetes (DM), 30 non-DM (NDM), and 25 healthy controls. Measurements were repeated after 6 months on hemodialysis (HD) or peritoneal dialysis (CAPD). Results: The percentage of CD4 + CD28null cells, CD8 + CD28null cells, and Tregs showed significant differences in DM, NDM, and controls; mean rank 33.71 vs. 25.68 vs. 18.88, p = 0.006, 37.79 vs. 28.82 vs. 17.08, p = 0.008, and 20.79 vs. 26.12 vs. 41.33, p = 0.001, respectively. DM vs. NDM had increased CD4 + CD28null and CD8 + CD28null cells, 11.5% (1.5%–24%) vs. 4.1% (0–42.3%), p = 0.02 and 61.3% (24%–76%) vs. 43% (5.7%–85%), p = 0.04, respectively. After 6 months on HD but not CAPD, DM showed a significant further increase in CD4 + CD28null cells, from 30 (14–100) to 52.7 (15–203), p = 0.02; and CD8 + CD28null cells, from 137 (56–275) to 266 (103–456), p = 0.01. Conclusions: Diabetes mellitus affects T-cell subtypes even at predialysis stage, though changes become more prominent after commencement on HD.     

Experimental investigation of bidensity slurries on an incline

We investigate the dynamics of bidensity slurries on an incline. The particle-fluid mixture consists of two species of negatively buoyant particles that have roughly the same size but significantly variant densities. This mismatch in particle densities induces or prevents settling depending on the relative amount of heavy to light particles, leading to complex regimes also found in the monodisperse case. In addition, when settling effects dominate within the thin film, we observe the phase separation down the incline between the particles and the liquid, as well as between two particle types.     

Design, simulation and performance evaluation of a single-electron 2-4 decoder

In this paper, we present a single-electron 2-4 decoder built using single-electron devices. The circuit is designed using a proper tool based on a Monte Carlo technique. First a single-electron AND gate is studied and then the 2-D decoder circuit is designed and studied. The results proved that the circuit was a 2-4 decoder, while the behaviour of the free energy of the system (which was calculated to be 4.90×10⁻¹ eV) and the stability diagram verified the correct functioning of the circuit.     

Production of biodegradable polyesters via enzymatic polymerization and solid state finishing

The synthesis of aliphatic polyesters (PEs) derived from diols (1,4‐butanediol and 1,8‐octanediol) and diacids or their derivatives (diethyl succinate, sebacic acid, 1,12‐dodecanedioic acid, and 1,14‐tetradecanedioic acid) was achieved in order to produce poly(butylene succinate) (PE 4.4), poly(octylene sebacate) (PE 8.10), poly(octylene dodecanate) (PE 8.12), and poly(octylene tetradecanate) (PE 8.14). The herein suggested procedure involved two stages, both sustainable and in accordance with the principles of “green” polymerization. The first comprised an enzymatic prepolymerization under vacuum, in the presence of diphenylether as solvent using Candida antarctica lipase B as biocatalyst, whereas a low‐temperature postpolymerization step [solid state polymerization (SSP)] followed in order to upgrade the PEs quality. In the enzymatically synthesized prepolymers, the range of number–average molecular weight attained was from 3700 to 8000 g/mol with yields reaching even 97%. Subsequently, SSP of PE 4.4 and 8.12 took place under vacuum or flowing nitrogen and lasted 10–48 h, at temperatures close to the prepolymer melting point (T_m ? T_SSP varied between 4°C and 14°C). The solid state finishing led to increase in the molecular weight depending on the prepolymer type, and it also contributed to improvement of the physical characteristics and the thermal properties of the enzymatically synthesized PEs. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40820.     

Integrating Model Information in UML Sequence Diagrams

In a UML model, different aspects of a system are covered by different types of diagrams. Nevertheless, it is important to provide means to check the consistency and completeness of the UML model. This problem is addressed in this paper by integrating the information specified in class and statechart diagrams into sequence diagrams. The representation as constraints attached to certain locations of the objects lifelines in the sequence diagram allows the identification of gaps and contradictory specifications. Furthermore, dependencies between the sequence diagrams can be investigated based on the previous analysis.     

European new build and fuel cycles in the 21st century

Nuclear energy is back on the agenda worldwide. In order to prepare for the next decades and to set priorities in nuclear R&D and investment, it is important to assess the future nuclear fuel cycle. This allows to identify the triggers which influence the market penetration of future nuclear reactor technologies.To this purpose, fuel cycle scenarios for a future nuclear reactor park in Europe have been analysed applying an integrated dynamic process modelling technique. The assessment was undertaken using the DANESS code (Dynamic Analysis of Nuclear Energy System Strategies, developed by Argonne National Laboratory (US)). This code allows to provide a complete picture of mass flows and economics of the various nuclear fuel cycle scenarios.The present assessment recognizes the integrated nuclear fuel cycle and concentrates on the evolution under consideration of increased uranium prices, increased costs for geological disposal, lifetime extension of the current reactor park, and various nuclear energy demand scenarios. The analyses show that the future European nuclear park will consist of a mix of Gen-III and Gen-IV reactors. The relative shares of the reactor types in the total mix depend on the applied boundary conditions such as the future nuclear energy demand, the reactor characteristics, and the assumed economical factors. Furthermore, the analyses highlight the triggers influencing the choices between different nuclear energy deployment scenarios, and enable an evaluation of future types and amounts of nuclear waste. In addition, a dynamic assessment is made with regard to employment of manpower for a future nuclear fleet in the different scenarios. Finally an estimate is provided of the radiological impact on the regional population due to the release of potentially hazardous radionuclides during the different steps in the nuclear fuel cycle.     

Hybrid control of vibrations of a smart von Kármán plate

The suppression of large vibrations of a smart thin elastic rectangular von Kármán’s plate is considered. The plate is subjected to external disturbances and generalized control forces produced by electromechanical feedback. The considered nonlinear initial-boundary value problem is spatially discretized by means of the time spectral method. The implicit Newmark-β iterative method is employed for the time integration of the obtained system of nonlinear equations of motion. Nonlinear controllers are designed, based on a fuzzy inference system. Two numerical algorithms involving a general control of displacement/velocity and a direct control of the Fourier coefficients are proposed. The techniques have been implemented within MATLAB environment with the use of the fuzzy logic toolbox. Numerical examples are presented.     

Increasing the power of the high temperature reactor module

To alleviate the economic problems of the modular pebble bed high temperature reactor, its design was modified in such a way that the power output was increased from 200 to 350 MWth. The core geometry was changed from cylindrical to annular, and the pressure vessel diameter was increased to 6.7 m. Control rods are placed in both the outer reflector and the graphite central column. In a safety analysis, loss of heat sink, loss of coolant and water ingress accident were examined. Reactor shutdown and decay heat removal take place passively, and the maximum fuel temperature stays theoreticallybelow 1600 °C, implying full retention of the fission products in the fuel elements. The central column has a diminishing effect on the positive reactivity effect of water ingress. A cost analysis shows that the specific investment costs of a four-module plant would decrease by 26% and the electricity generating costs would reduce by 19%.