Cytotoxicity screening of 23 engineered nanomaterials using a test matrix of ten cell lines and three different assays

<p>Abstract</p> <p>Background</p> <p>Engineered nanomaterials display unique properties that may have impact on human health, and thus require a reliable evaluation of their potential toxicity. Here, we performed a standardized <it>in vitro </it>screening of 23 engineered nanomaterials. We thoroughly characterized the physicochemical properties of the nanomaterials and adapted three classical <it>in vitro </it>toxicity assays to eliminate nanomaterial interference. Nanomaterial toxicity was assessed in ten representative cell lines.</p> <p>Results</p> <p>Six nanomaterials induced oxidative cell stress while only a single nanomaterial reduced cellular metabolic activity and none of the particles affected cell viability. Results from heterogeneous and chemically identical particles suggested that surface chemistry, surface coating and chemical composition are likely determinants of nanomaterial toxicity. Individual cell lines differed significantly in their response, dependent on the particle type and the toxicity endpoint measured.</p> <p>Conclusion</p> <p><it>In vitro </it>toxicity of the analyzed engineered nanomaterials cannot be attributed to a defined physicochemical property. Therefore, the accurate identification of nanomaterial cytotoxicity requires a matrix based on a set of sensitive cell lines and <it>in vitro </it>assays measuring different cytotoxicity endpoints.</p

SnO2:Sb transparent conducting coatings made by different sol-gel processes

Single and multilayer sol-gel coatings of transparent antimony-doped tin oxide (SnO2:Sb) have been prepared on borosilicate and fused silica substrates using either a 5 mole% SbCl3 doped 0.5 M solution of SnCl2(OAc)2 in ethanol or a water suspension of crystalline Sb-doped tin oxide nanoparticles. The nanoscale morphology and the electrical parameters of the layers have been determined after different firing procedures and heating rates varying from 0.2 to 4300 K/s obtained either in a furnace or by cw carbon- dioxide laser irradiation. For a given sintering temperature (approximately 540 degrees Celsius) a slow heating process in furnace leads to porous, homogeneous single and multilayers consisting of small crystallites. They present a high resistivity of about &Rho;=4 X 10-2 &Omega;cm. With increasing heating rate the layers become denser with larger crystallites and the resistivity value decrease down to approximately 7 X 10-3 &Omega;cm for 4300 K/s (carbon-dioxide laser sintering). It is proposed that the densification of the coatings is determined by a competition between nucleation at low temperatures and the growth of the crystallites at high temperatures

Transparent conducting, anti-static and anti-static-anti-glare coatings on plastic substrates

In2O3:Sn (ITO) sols made of crystalline nanoparticles, fully redispersable in an ethanol solution containing hydrolyzed organosilanes, have been developed to deposit conducting transparent and anti-glare coatings on plastic (PMMA, polycarbonate) and glass substrates by spin, dip and spray coating processes. The coatings are cured by UV irradiation and/or by a low temperature heat treatment (T=130°C) in air or reducing atmosphere. The electrical, optical, textural and mechanical properties of the coatings are reported. A stable sheet resistance as low as 5 k&Omega;(open square), was obtained with a single 500-nm thick transparent layer. Anti-glare—anti-static coatings exhibiting a 40-k&Omega;(open square) sheet resistance, a gloss of 60—70 GU, a clarity of 75—90% and an optical resolution >8 lines/mm were obtained by a room temperature spraying process. The abrasion resistance of both coatings is in agreement with DIN 58196-H25-class 1

Generalized Energy Budget Equations for Large-Eddy Simulations of Scalar Turbulence

The energy transfer between different scales of a passive scalar advected by homogeneous isotropic turbulence is studied by an exact generalized transport equation for the second moment of the scalar increment. This equation can be interpreted as a scale-by-scale energy budget equation, as it relates at a certain scale r terms representing the production, turbulent transport, diffusive transport and dissipation of scalar energy. These effects are analyzed by means of direct numerical simulation where each term is directly accessible. To this end, a variation of the Taylor micro-scale based Reynolds number between 88 and 754 is performed. Understanding the energy transport between scales is crucial for Large-Eddy Simulation (LES). For an analysis of the energy transfer in LES, a transport equation for the second moment of the filtered scalar increment is introduced. In this equation new terms appear due to the interaction between resolved and unresolved scales, which are analyzed in the context of an a priori and an a posteriori test. It is further shown that LES using an eddy viscosity approach is able to fulfill the correct inter-scale energy transport for the present configuration

Performance Optimization of Parallel Applications in Diverse On-Demand Development Teams

Current supercomputing platforms and scientific application codes have grown rapidly in complexity over the past years. Multi-scale, multi-domain simulations on one hand and deep hierarchies in large-scale computing platforms on the other make it exceedingly harder to map the former onto the latter and fully exploit the available computational power. The complexity of the software and hardware components involved calls for in-depth expertise that can only be met by diversity in the application development teams. With its model of simulation labs and cross-sectional groups, JARA-HPC enables such diverse teams to form on demand to solve concrete development problems. This work showcases the effectiveness of this model with two application case studies involving the JARA-HPC cross-sectional group “Parallel Efficiency” and simulation labs and domain-specific development teams. For one application, we show the results of a completed optimization and the estimated financial impact of the combined efforts. For the other application, we present results from an ongoing engagement, where we show how an on-demand team investigates the behavior of dynamic load balancing schemes for an MD particle simulation, leading to a better overall understanding of the application and revealing targets for further investigation

Operation of Hybrid Membranes for the Removal of Pharmaceuticals and Pollutants from Water and Wastewater

Hybrid ceramic membranes (i.e., membranes with a layer-by-layer (LbL) coating) are an emerging technology to remove diverse kinds of micropollutants from water. Hybrid ceramic membranes were tested under laboratory conditions as single-channel (filter area = 0.00754 m2) and multi-channel (0.35 m2) variants for the removal of pharmaceuticals (sulfamethoxazole, diclofenac, clofibric acid, and ibuprofen) and typical wastewater pollutants (i.e., COD, TOC, PO4-P, and TN) from drinking water and treated wastewater. The tests were conducted with two low transmembrane pressures (TMP) of 2 and 4 bar and constant temperatures and flow velocities, which showed rejections above 80% for all the tested pharmaceuticals as well for organic pollutants and phosphorous in the treated wastewater. Tests regarding sufficient cleaning regimes also showed that the LbL coating is stable and resistant to pHs between 2 and 10 with the use of typical cleaning agents (citric acid and NaOH) but not to higher pHs, a commercially available enzymatic solution, or backwashing. The hybrid membranes can contribute to the advanced treatment of water and wastewater with low operational costs, and their application at a larger scale is viable. However, the cleaning of the membranes must be further investigated to assure the stability and durability of the LbL coating

An effective simulation- and measurement-based workflow for enhanced diagnostics in rhinology

Physics-based analyses have the potential to consolidate and substantiate medical diagnoses in rhinology. Such methods are frequently subject to intense investigations in research. However, they are not used in clinical applications, yet. One issue preventing their direct integration is that these methods are commonly developed as isolated solutions which do not consider the whole chain of data processing from initial medical to higher valued data. This manuscript presents a workflow that incorporates the whole data processing pipeline based on a environment. Therefore, medical image data are fully automatically pre-processed by machine learning algorithms. The resulting geometries employed for the simulations on high-performance computing systems reach an accuracy of up to 99.5% compared to manually segmented geometries. Additionally, the user is enabled to upload and visualize 4-phase rhinomanometry data. Subsequent analysis and visualization of the simulation outcome extend the results of standardized diagnostic methods by a physically sound interpretation. Along with a detailed presentation of the methodologies, the capabilities of the workflow are demonstrated by evaluating an exemplary medical case. The pipeline output is compared to 4-phase rhinomanometry data. The comparison underlines the functionality of the pipeline. However, it also illustrates the influence of mucosa swelling on the simulation