Beyond Intercalation‐Based Li‐Ion Batteries: The State of the Art and Challenges of Electrode Materials Reacting Through Conversion Reactions (Adv. Mater. 35/2010)

Despite the imminent commercial introduction of Li‐ion batteries in electric drive vehicles and their proposed use as enablers of smart grids based on renewable energy technologies, an intensive quest for new electrode materials that bring about improvements in energy density, cycle life, cost, and safety is still underway. This Progress Report highlights the recent developments and the future prospects of the use of phases that react through conversion reactions as both positive and negative electrode materials in Li‐ion batteries. By moving beyond classical intercalation reactions, a variety of low cost compounds with gravimetric specific capacities that are two‐to‐five times larger than those attained with currently used materials, such as graphite and LiCoO₂, can be achieved. Nonetheless, several factors currently handicap the applicability of electrode materials entailing conversion reactions. These factors, together with the scientific breakthroughs that are necessary to fully assess the practicality of this concept, are reviewed in this report.     

Surface Charge of Supramolecular Nanosystems for In Vivo Biodistribution: A MicroSPECT/CT Imaging Study

Bioimaging has revolutionized medicine by providing accurate information for disease diagnosis and treatment. Nanotechnology‐based bioimaging is expected to further improve imaging sensitivity and specificity. In this context, supramolecular nanosystems based on self‐assembly of amphiphilic dendrimers for single photon emission computed tomography (SPECT) bioimaging are developed. These dendrimers bear multiple In³⁺ radionuclides at their terminals as SPECT reporters. By replacing the macrocyclic 1,4,7,10‐tetraazacyclododecane‐1,4,7,10‐tetraacetic acid cage with the smaller 1,4,7‐triazacyclononane‐1,4,7‐triacetic acid scaffold as the In³⁺ chelator, the corresponding dendrimer exhibits neutral In³⁺‐complex terminals in place of negatively charged In³⁺‐complex terminals. This negative‐to‐neutral surface charge alteration completely reverses the zeta‐potential of the nanosystems from negative to positive. As a consequence, the resulting SPECT nanoprobe generates a highly sought‐after biodistribution profile accompanied by a drastically reduced uptake in liver, leading to significantly improved tumor imaging. This finding contrasts with current literature reporting that positively charged nanoparticles have preferential accumulation in the liver. As such, this study provides new perspectives for improving the biodistribution of positively charged nanosystems for biomedical applications.     

From Discrete Duration Calculus to Symbolic Automata

The goal of this paper is to translate (fragments of) the quantified discrete duration calculus QDDC, proposed by P. Pandya, into symbolic acceptors with counters. Acceptors are written in the synchronous programming language Lustre, in order to allow available symbolic verification tools (model-checkers, abstract interpreters) to be applied to properties expressed in QDDC. We show that important constructs of QDDC need non-deterministic acceptors, in order to be translated with a bounded number of counters, and an expressive fragment of the logic is identified and translated. Then, we consider a more restricted fragment, which only needs deterministic acceptors.     

Approximating the max-edge-coloring problem

The max-edge-coloring problem is a natural weighted generalization of the classical edge-coloring problem arising in the domain of communication systems. In this problem each color class is assigned the weight of the heaviest edge in this class and the objective is to find a proper edge-coloring of the input graph minimizing the sum of all color classes’ weights. We present new approximation results, that improve substantially the known ones, for several variants of the problem with respect to the class of the underlying graph. In particular, we deal with variants which are known to be NP-hard (general and bipartite graphs) or are proven to be NP-hard in this paper (complete graphs with bi-valued edge weights) or whose complexity question still remains open (trees).     

Scalability analysis of Dalton,a molecular structure program

Dalton is a molecular electronic structure program featuring common methods of computational chemistry that are based on pure quantum mechanics (QM) as well as hybrid quantum mechanics/molecular mechanics (QM/MM). It is specialized and has a leading position in calculation of molecular properties with a large world-wide user community (over 2000 licenses issued). In this paper, we present a performance characterization and optimization of Dalton. We also propose a solution to avoid the master/worker design of Dalton to become a performance bottleneck for larger process numbers. With these improvements we obtain speedups of 4x, increasing the parallel efficiency of the code and being able to run in it in a much bigger number of cores.     

A genetic algorithm-based method for feature subset selection

As a commonly used technique in data preprocessing, feature selection selects a subset of informative attributes or variables to build models describing data. By removing redundant and irrelevant or noise features, feature selection can improve the predictive accuracy and the comprehensibility of the predictors or classifiers. Many feature selection algorithms with different selection criteria has been introduced by researchers. However, it is discovered that no single criterion is best for all applications. In this paper, we propose a framework based on a genetic algorithm (GA) for feature subset selection that combines various existing feature selection methods. The advantages of this approach include the ability to accommodate multiple feature selection criteria and find small subsets of features that perform well for a particular inductive learning algorithm of interest to build the classifier. We conducted experiments using three data sets and three existing feature selection methods. The experimental results demonstrate that our approach is a robust and effective approach to find subsets of features with higher classification accuracy and/or smaller size compared to each individual feature selection algorithm.     

Effects of a Novel Cold Atmospheric Plasma Treatment of Titanium on the Proliferation and Adhesion Behavior of Fibroblasts

Cold plasma treatment increases the hydrophilicity of the surfaces of implants and may enhance their integration with the surrounding tissues. The implaPrep prototype device from Relyon Plasma generates cold atmospheric plasma via dielectric barrier discharge (DBD). In this study, titanium surfaces were treated with the implaPrep device for 20 s and assessed as a cell culture surface for fibroblasts. One day after seeding, significantly more cells were counted on the surfaces treated with cold plasma than on the untreated control titanium surface. Additionally, the viability assay revealed significantly higher viability on the treated surfaces. Morphological observation of the cells showed certain differences between the treated and untreated titanium surfaces. While conventional plasma devices require compressed gas, such as oxygen or argon, the implaPrep device uses atmospheric air as the gas source. It is, therefore, compact in size and simple to handle, and may provide a safe and convenient tool for treating the surfaces of dental implants, which may further improve the implantation outcome.     

Gremlin-1 and BMP-4 Overexpressed in Osteoarthritis Drive an Osteochondral-Remodeling Program in Osteoblasts and Hypertrophic Chondrocytes

Osteoarthritis (OA) is a whole joint disease characterized by an important remodeling of the osteochondral junction. It includes cartilage mineralization due to chondrocyte hypertrophic differentiation and bone sclerosis. Here, we investigated whether gremlin-1 (Grem-1) and its BMP partners could be involved in the remodeling events of the osteochondral junction in OA. We found that Grem-1, BMP-2, and BMP-4 immunostaining was detected in chondrocytes from the deep layer of cartilage and in subchondral bone of knee OA patients, and was positively correlated with cartilage damage. ELISA assays showed that bone released more Grem-1 and BMP-4 than cartilage, which released more BMP-2. In vitro experiments evidenced that compression stimulated the expression and the release of Grem-1 and BMP-4 by osteoblasts. Grem-1 was also overexpressed during the prehypertrophic to hypertrophic differentiation of murine articular chondrocytes. Recombinant Grem-1 stimulated Mmp-3 and Mmp-13 expression in murine chondrocytes and osteoblasts, whereas recombinant BMP-4 stimulated the expression of genes associated with angiogenesis (Angptl4 and osteoclastogenesis (Rankl and Ccl2). In conclusion, Grem-1 and BMP-4, whose expression at the osteochondral junction increased with OA progression, may favor the pathological remodeling of the osteochondral junction by inducing a catabolic and tissue remodeling program in hypertrophic chondrocytes and osteoblasts.