Tailoring Graphene with Metals on Top

We study the effects of metallic doping on the electronic properties of graphene using density functional theory in the local density approximation in the presence of a local charging energy (LDA+U). The electronic properties are sensitive to whether graphene is doped with alkali or transition metals. We estimate the the charge transfer from a single layer of Potassium on top of graphene in terms of the local charging energy of the graphene sheet. The coating of graphene with a non-magnetic layer of Palladium, on the other hand, can lead to a magnetic instability in coated graphene due to the hybridization between the transition-metal and the carbon orbitals.Comment: 5 pages, 4 figure

Mapping Materials and Molecules

The visualization of data is indispensable in scientific research, from the early stages when human insight forms to the final step of communicating results. In computational physics, chemistry and materials science, it can be as simple as making a scatter plot or as straightforward as looking through the snapshots of atomic positions manually. However, as a result of the “big data” revolution, these conventional approaches are often inadequate. The widespread adoption of high-throughput computation for materials discovery and the associated community-wide repositories have given rise to data sets that contain an enormous number of compounds and atomic configurations. A typical data set contains thousands to millions of atomic structures, along with a diverse range of properties such as formation energies, band gaps, or bioactivities. It would thus be desirable to have a data-driven and automated framework for visualizing and analyzing such structural data sets. The key idea is to construct a low-dimensional representation of the data, which facilitates navigation, reveals underlying patterns, and helps to identify data points with unusual attributes. Such data-intensive maps, often employing machine learning methods, are appearing more and more frequently in the literature. However, to the wider community, it is not always transparent how these maps are made and how they should be interpreted. Furthermore, while these maps undoubtedly serve a decorative purpose in academic publications, it is not always apparent what extra information can be garnered from reading or making them. This Account attempts to answer such questions. We start with a concise summary of the theory of representing chemical environments, followed by the introduction of a simple yet practical conceptual approach for generating structure maps in a generic and automated manner. Such analysis and mapping is made nearly effortless by employing the newly developed software tool ASAP. To showcase the applicability to a wide variety of systems in chemistry and materials science, we provide several illustrative examples, including crystalline and amorphous materials, interfaces, and organic molecules. In these examples, the maps not only help to sift through large data sets but also reveal hidden patterns that could be easily missed using conventional analyses. The explosion in the amount of computed information in chemistry and materials science has made visualization into a science in itself. Not only have we benefited from exploiting these visualization methods in previous works, we also believe that the automated mapping of data sets will in turn stimulate further creativity and exploration, as well as ultimately feed back into future advances in the respective fields

Urine Proteomics Analysis of Patients with Neuronal Ceroid Lipofuscinoses

The Neuronal Ceroid Lipofuscinoses (NCL) are a group of 13 rare neurodegenerative disorders characterised by accumulation of cellular storage bodies. There are few therapeutic options and existing tests do not monitor disease progression and treatment response. However, urine biomarkers could address this need. Proteomic analysis of CLN2 patient urine revealed activation of immune response pathways and pathways associated with the unfolded protein response. Analysis of CLN5 and CLN6 sheep model urine showed subtle changes. To confirm and investigate the relevance of candidate biomarkers a targeted LC-MS/MS proteomic assay was created. We applied this assay to additional CLN2 samples as well as other NCL patients, (CLN1, CLN3, CLN5, CLN6 and CLN7) and demonstrated that Hexosaminidase-A, Aspartate Aminotransferase-1 and LAMP1, are increased in NCL samples and betaine-homocysteine S-methyltransferase-1 was specifically increased in CLN2 patients. These proteins could be used to monitor effectiveness of future therapies aimed at treating systemic NCL disease

Suppression of electron-electron repulsion and superconductivity in Ultra Small Carbon Nanotubes

Recently, ultra-small-diameter Single Wall Nano Tubes with diameter of $\sim 0.4 nm$ have been produced and many unusual properties were observed, such as superconductivity, leading to a transition temperature $T_c\sim 15^oK$, much larger than that observed in the bundles of larger diameter tubes. By a comparison between two different approaches, we discuss the issue whether a superconducting behavior in these carbon nanotubes can arise by a purely electronic mechanism. The first approach is based on the Luttinger Model while the second one, which emphasizes the role of the lattice and short range interaction, is developed starting from the Hubbard Hamiltonian. By using the latter model we predict a transition temperature of the same order of magnitude as the measured one.Comment: 7 pages, 3 figures, to appear in J. Phys.-Cond. Ma

Local Oxidative and Nitrosative Stress Increases in the Microcirculation during Leukocytes-Endothelial Cell Interactions

Leukocyte-endothelial cell interactions and leukocyte activation are important factors for vascular diseases including nephropathy, retinopathy and angiopathy. In addition, endothelial cell dysfunction is reported in vascular disease condition. Endothelial dysfunction is characterized by increased superoxide (O2•−) production from endothelium and reduction in NO bioavailability. Experimental studies have suggested a possible role for leukocyte-endothelial cell interaction in the vessel NO and peroxynitrite levels and their role in vascular disorders in the arterial side of microcirculation. However, anti-adhesion therapies for preventing leukocyte-endothelial cell interaction related vascular disorders showed limited success. The endothelial dysfunction related changes in vessel NO and peroxynitrite levels, leukocyte-endothelial cell interaction and leukocyte activation are not completely understood in vascular disorders. The objective of this study was to investigate the role of endothelial dysfunction extent, leukocyte-endothelial interaction, leukocyte activation and superoxide dismutase therapy on the transport and interactions of NO, O2•− and peroxynitrite in the microcirculation. We developed a biotransport model of NO, O2•− and peroxynitrite in the arteriolar microcirculation and incorporated leukocytes-endothelial cell interactions. The concentration profiles of NO, O2•− and peroxynitrite within blood vessel and leukocytes are presented at multiple levels of endothelial oxidative stress with leukocyte activation and increased superoxide dismutase accounted for in certain cases. The results showed that the maximum concentrations of NO decreased ∼0.6 fold, O2•− increased ∼27 fold and peroxynitrite increased ∼30 fold in the endothelial and smooth muscle region in severe oxidative stress condition as compared to that of normal physiologic conditions. The results show that the onset of endothelial oxidative stress can cause an increase in O2•− and peroxynitrite concentration in the lumen. The increased O2•− and peroxynitrite can cause leukocytes priming through peroxynitrite and leukocytes activation through secondary stimuli of O2•− in bloodstream without endothelial interaction. This finding supports that leukocyte rolling/adhesion and activation are independent events

X chromosome inactivation does not necessarily determine the severity of the phenotype in Rett syndrome patients

Rett syndrome (RTT) is a severe neurological disorder usually caused by mutations in the MECP2 gene. Since the MECP2 gene is located on the X chromosome, X chromosome inactivation (XCI) could play a role in the wide range of phenotypic variation of RTT patients; however, classical methylation-based protocols to evaluate XCI could not determine whether the preferentially inactivated X chromosome carried the mutant or the wild-type allele. Therefore, we developed an allele-specific methylation-based assay to evaluate methylation at the loci of several recurrent MECP2 mutations. We analyzed the XCI patterns in the blood of 174 RTT patients, but we did not find a clear correlation between XCI and the clinical presentation. We also compared XCI in blood and brain cortex samples of two patients and found differences between XCI patterns in these tissues. However, RTT mainly being a neurological disease complicates the establishment of a correlation between the XCI in blood and the clinical presentation of the patients. Furthermore, we analyzed MECP2 transcript levels and found differences from the expected levels according to XCI. Many factors other than XCI could affect the RTT phenotype, which in combination could influence the clinical presentation of RTT patients to a greater extent than slight variations in the XCI pattern

Cause of Death and Predictors of All-Cause Mortality in Anticoagulated Patients With Nonvalvular Atrial Fibrillation : Data From ROCKET AF

M. Kaste on työryhmän ROCKET AF Steering Comm jäsen.Background-Atrial fibrillation is associated with higher mortality. Identification of causes of death and contemporary risk factors for all-cause mortality may guide interventions. Methods and Results-In the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) study, patients with nonvalvular atrial fibrillation were randomized to rivaroxaban or dose-adjusted warfarin. Cox proportional hazards regression with backward elimination identified factors at randomization that were independently associated with all-cause mortality in the 14 171 participants in the intention-to-treat population. The median age was 73 years, and the mean CHADS(2) score was 3.5. Over 1.9 years of median follow-up, 1214 (8.6%) patients died. Kaplan-Meier mortality rates were 4.2% at 1 year and 8.9% at 2 years. The majority of classified deaths (1081) were cardiovascular (72%), whereas only 6% were nonhemorrhagic stroke or systemic embolism. No significant difference in all-cause mortality was observed between the rivaroxaban and warfarin arms (P=0.15). Heart failure (hazard ratio 1.51, 95% CI 1.33-1.70, P= 75 years (hazard ratio 1.69, 95% CI 1.51-1.90, P Conclusions-In a large population of patients anticoagulated for nonvalvular atrial fibrillation, approximate to 7 in 10 deaths were cardiovascular, whereasPeer reviewe