Ferric Gluconate Yields Cost-Savings in Hemodialysis Patients with High Ferritin and Low TSAT: Results from the DRIVE Studies

Purpose: One third of hemodialysis patients have high serum ferritin levels and low transferrin saturation (TSAT). The purpose of this analysis was to determine the cost effectiveness of administering 1g of sodium ferric gluconate complex (SFGC: also referred to as ferric gluconate) to patients with serum ferritin \u3e500ng/mL and TSAT ≤25% based on the Dialysis Patients Response to IV Iron with Elevated Ferritin (DRIVE) study and its 6-week observational extension (DRIVE-II). In these studies, IV iron administration resulted in reduced epoetin requirements. Methods: Decision analysis was performed using a time horizon of 12 weeks, consistent with the combined duration of DRIVE and DRIVE II. Treatment effectiveness was based on mean increase in hemoglobin (Hb) for each group (SFGC plus epoetin or epoetin alone) in the intention to treat populations. Costs included drugs (SFGC and epoetin) and hospitalizations due to serious adverse events (SAEs) reported. The primary cost effectiveness measure was cost per g/dL of Hb increase at 12 weeks. Costs were computed from a Medicare perspective using projected 2007 reimbursements. Sensitivity analyses were performed to test the impact of using the safety population, median epoetin and SFGC doses, actual 2005 Medicare reimbursements, median increases in Hb, and SAE rate changes. The model was constructed using TreeAge Pro software. Results: Total cost per patient receiving SFGC plus epoetin was $3675 per g/dL Hb increase, while the total cost per patient receiving epoetin alone was$5065 per g/dL Hb increase. Net savings for SFGC plus epoetin was $1390 per g/dL Hb increase over the 12 week period Sensitivity analyses affirmed the robustness of the model. Conclusion: Administering 1g of SFGC plus epoetin in patients with high ferritin and low TSAT as defined in the DRIVE studies resulted in significant cost-savings compared to epoetin alone

Workflow Engineering in Materials Design within the BATTERY 2030+Project

In recent years, modeling and simulation of materials have become indispensable to complement experiments in materials design. High-throughput simulations increasingly aid researchers in selecting the most promising materials for experimental studies or by providing insights inaccessible by experiment. However, this often requires multiple simulation tools to meet the modeling goal. As a result, methods and tools are needed to enable extensive-scale simulations with streamlined execution of all tasks within a complex simulation protocol, including the transfer and adaptation of data between calculations. These methods should allow rapid prototyping of new protocols and proper documentation of the process. Here an overview of the benefits and challenges of workflow engineering in virtual material design is presented. Furthermore, a selection of prominent scientific workflow frameworks used for the research in the BATTERY 2030+ project is presented. Their strengths and weaknesses as well as a selection of use cases in which workflow frameworks significantly contributed to the respective studies are discussed

Workflow Engineering in Materials Design within the BATTERY 2030+ Project

In recent years, modeling and simulation of materials have become indispensable to complement experiments in materials design. High-throughput simulations increasingly aid researchers in selecting the most promising materials for experimental studies or by providing insights inaccessible by experiment. However, this often requires multiple simulation tools to meet the modeling goal. As a result, methods and tools are needed to enable extensive-scale simulations with streamlined execution of all tasks within a complex simulation protocol, including the transfer and adaptation of data between calculations. These methods should allow rapid prototyping of new protocols and proper documentation of the process. Here an overview of the benefits and challenges of workflow engineering in virtual material design is presented. Furthermore, a selection of prominent scientific workflow frameworks used for the research in the BATTERY 2030+ project is presented. Their strengths and weaknesses as well as a selection of use cases in which workflow frameworks significantly contributed to the respective studies are discussed

Substitution for Cu in the electron-doped infinite-layer superconductor Sr0.9La0.1CuO2, Ni reduces Tc much faster than Zn

We report on the effect of substitution for Cu on Tc of electron-doped infinite-layer superconductors Sr0.9La0.1Cu1-xRxO2, R = Zn and Ni. We found that Tc was nearly constant until x = 0.03 for R = Zn, while superconductivity was nearly suppressed for x = 0.02 with dTc/dx = 20 K/% for R = Ni. This behavior is very similar to that of conventional superconductors. These findings are discussed in terms of the superconducting gap symmetry in the cuprate superconductors including another electron-doped superconductor, (Nd,Ce)2CuO4-y.Comment: 5 pages and 2 EPS figures, [email protected] for material reques

Big-Data-Driven Materials Science and its FAIR Data Infrastructure

This chapter addresses the forth paradigm of materials research -- big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are discussed. For furthering the field, Open Data and an all-embracing sharing, an efficient data infrastructure, and the rich ecosystem of computer codes used in the community are of critical importance. For shaping this forth paradigm and contributing to the development or discovery of improved and novel materials, data must be what is now called FAIR -- Findable, Accessible, Interoperable and Re-purposable/Re-usable. This sets the stage for advances of methods from artificial intelligence that operate on large data sets to find trends and patterns that cannot be obtained from individual calculations and not even directly from high-throughput studies. Recent progress is reviewed and demonstrated, and the chapter is concluded by a forward-looking perspective, addressing important not yet solved challenges.Comment: submitted to the Handbook of Materials Modeling (eds. S. Yip and W. Andreoni), Springer 2018/201

Effects of monosodium-L-glutamate administration on serum levels of reproductive hormones and cholesterol, epididymal sperm reserves and testicular histomorphology of male albino rats

This study investigated the effects of administration of monosodium L-glutamate (MSG) on serum gonadotrophin-releasing hormone (GnRH), luteinising hormone (LH), testosterone and total cholesterol (TC), cauda epididymal sperm reserves (CESR) and testicular histomorphology of adult male albino rats. Eighty-four rats, randomly assigned to 7 groups of 12 rats each, were used for the study. Varying low doses (0.25, 0.50 or 1.00 g/kg body weight) of MSG were administered orally or subcutaneously at 48-h intervals for six weeks. Serum GnRH, LH, testosterone and TC, and CESR were evaluated on days 14, 28 and 42 of MSG administration. Testicular histomorphology was evaluated on day 42. The results showed that the mean serum GnRH, LH and testosterone levels, and the CESR of all the treated groups were significantly (P < 0.05) lower than those of the untreated control on days 14, 28 and 42 of MSG administration. The mean serum TC levels of all the treated groups were also significantly (P < 0.05) lower than those of the control group on days 14 and 28. No lesions were observed on sections of the testes. It was concluded that MSG administration for 14, 28 and 42 days led to significantly lower serum levels of GnRH, LH, testosterone and TC, and significantly lower CESR

The AFLOW Fleet for Materials Discovery

The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the deployment of new technologies, the AFLOW Fleet for computational materials design automates high-throughput first principles calculations, and provides tools for data verification and dissemination for a broad community of users. AFLOW incorporates different computational modules to robustly determine thermodynamic stability, electronic band structures, vibrational dispersions, thermo-mechanical properties and more. The AFLOW data repository is publicly accessible online at aflow.org, with more than 1.7 million materials entries and a panoply of queryable computed properties. Tools to programmatically search and process the data, as well as to perform online machine learning predictions, are also available.Comment: 14 pages, 8 figure

OPTIMADE, an API for exchanging materials data

The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification

The acetylation of RelA in Lys310 dictates the NF-κB-dependent response in post-ischemic injury

The activation of nuclear factor kappa B (NF-κB) p50/RelA is a key event in ischemic neuronal injury, as well as in brain ischemic tolerance. We tested whether epigenetic mechanisms affecting the acetylation state of RelA might discriminate between neuroprotective and neurotoxic activation of NF-κB during ischemia. NF-κB activation and RelA acetylation were investigated in cortices of mice subjected to preconditioning brain ischemia or lethal middle cerebral artery occlusion (MCAO) and primary cortical neurons exposed to preconditioning or lethal oxygen-glucose deprivation (OGD). In mice subjected to MCAO and in cortical neurons exposed to lethal OGD, activated RelA displayed a high level of Lys310 acetylation in spite of reduced total acetylation. Also, acetylated RelA on Lys310 interacted strongly with the CREB-binding protein (CBP). Conversely, RelA activated during preconditioning ischemia appeared deacetylated on Lys310. Overexpressing RelA increased Bim promoter activity and neuronal cell death both induced by lethal OGD, whereas overexpressing the acetylation-resistant RelA-K310R, carrying a mutation from Lys310 to arginine, prevented both responses. Pharmacological manipulation of Lys310 acetylation by the sirtuin 1 activator resveratrol repressed the activity of the Bim promoter and reduced the neuronal cell loss. We conclude that the acetylation of RelA in Lys310 dictates NF-κB-dependent pro-apoptotic responses and represents a suitable target to dissect pathological from neuroprotective NF-κB activation in brain ischemia

Doping-Free Arsenene Heterostructure Metal-Oxide-Semiconductor Field Effect Transistors Enabled by Thickness Modulated Semiconductor to Metal Transition in Arsenene

Two-dimensional (2-D) materials such as MoS2 and phosphorene provide an ideal platform to realize extremely thin body metal-oxide-semiconductor field effect transistors (MOSFETs) which is highly immune to short channel effects in the ultra-scaled regime. Even with the excellent electrostatic integrity inherent in 2-D system, however, 2-D materials suffer from the lack of efficient doping method which is crucial in MOSFETs technology. Recently, an unusual phase transition from semiconductor to metal driven by the thickness modulation has been predicted in mono-elemental 2-D material arsenene. Utilizing this extraordinary property, we propose doping-free arsenene heterostructure MOSFETs based on the lateral multilayer (metallic source)/monolayer (semiconducting channel)/multilayer (metallic drain) arsenene heterostructure. Metallic multilayer arsenene in the source and drain can serve as electrodes without doping. We investigate the potential performance of arsenene heterostructure MOSFETs through atomistic simulations using density functional theory and nonequilibrium Green&apos;s function. The intrinsic upper limit of the on-state current in arsenene heterostructure MOSFETs is estimated by studying the effect of layer number in the source and drain. We comprehensively analyze the competitiveness of arsenene heterostructure MOSFETs through benchmarking with monolayer arsenene homostructure MOSFETs equipped with the highly degenerate doped source and drain, suggesting superior performance of heterostructure MOSFETs over homostructure MOSFETs