1,069 research outputs found
Early-phase circulating miRNAs predict tumor recurrence and survival of hepatocellular carcinoma patients after liver transplantation
published_or_final_versio
A novel oxygen carrier 'YQ23' suppresses the liver tumor metastasis by decreasing circulating endothelial progenitor cells and regulatory T cells
published_or_final_versio
Antiferromagnetic spintronics
Antiferromagnetic materials are magnetic inside, however, the direction of
their ordered microscopic moments alternates between individual atomic sites.
The resulting zero net magnetic moment makes magnetism in antiferromagnets
invisible on the outside. It also implies that if information was stored in
antiferromagnetic moments it would be insensitive to disturbing external
magnetic fields, and the antiferromagnetic element would not affect
magnetically its neighbors no matter how densely the elements were arranged in
a device. The intrinsic high frequencies of antiferromagnetic dynamics
represent another property that makes antiferromagnets distinct from
ferromagnets. The outstanding question is how to efficiently manipulate and
detect the magnetic state of an antiferromagnet. In this article we give an
overview of recent works addressing this question. We also review studies
looking at merits of antiferromagnetic spintronics from a more general
perspective of spin-ransport, magnetization dynamics, and materials research,
and give a brief outlook of future research and applications of
antiferromagnetic spintronics.Comment: 13 pages, 7 figure
Predictors of functional deterioration in Chinese patients with Psoriatic arthritis: a longitudinal study
Characterization of MHz pulse repetition rate femtosecond laser-irradiated gold-coated silicon surfaces
In this study, MHz pulse repetition rate femtosecond laser-irradiated gold-coated silicon surfaces under ambient condition were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction analysis (XRD), and X-ray photoelectron spectroscopy (XPS). The radiation fluence used was 0.5 J/cm2 at a pulse repetition rate of 25 MHz with 1 ms interaction time. SEM analysis of the irradiated surfaces showed self-assembled intermingled weblike nanofibrous structure in and around the laser-irradiated spots. Further TEM investigation on this nanostructure revealed that the nanofibrous structure is formed due to aggregation of Au-Si/Si nanoparticles. The XRD peaks at 32.2°, 39.7°, and 62.5° were identified as (200), (211), and (321) reflections, respectively, corresponding to gold silicide. In addition, the observed chemical shift of Au 4f and Si 2p lines in XPS spectrum of the irradiated surface illustrated the presence of gold silicide at the irradiated surface. The generation of Si/Au-Si alloy fibrous nanoparticles aggregate is explained by the nucleation and subsequent condensation of vapor in the plasma plume during irradiation and expulsion of molten material due to high plasma pressure
Stationary Black Holes: Uniqueness and Beyond
The spectrum of known black-hole solutions to the stationary Einstein
equations has been steadily increasing, sometimes in unexpected ways. In
particular, it has turned out that not all black-hole-equilibrium
configurations are characterized by their mass, angular momentum and global
charges. Moreover, the high degree of symmetry displayed by vacuum and
electro-vacuum black-hole spacetimes ceases to exist in self-gravitating
non-linear field theories. This text aims to review some developments in the
subject and to discuss them in light of the uniqueness theorem for the
Einstein-Maxwell system.Comment: Major update of the original version by Markus Heusler from 1998.
Piotr T. Chru\'sciel and Jo\~ao Lopes Costa succeeded to this review's
authorship. Significantly restructured and updated all sections; changes are
too numerous to be usefully described here. The number of references
increased from 186 to 32
Bezielle Selectively Targets Mitochondria of Cancer Cells to Inhibit Glycolysis and OXPHOS
Bezielle (BZL101) is a candidate oral drug that has shown promising efficacy and excellent safety in the early phase clinical trials for advanced breast cancer. Bezielle is an aqueous extract from the herb Scutellaria barbata. We have reported previously that Bezielle was selectively cytotoxic to cancer cells while sparing non-transformed cells. In tumor, but not in non-transformed cells, Bezielle induced generation of ROS and severe DNA damage followed by hyperactivation of PARP, depletion of the cellular ATP and NAD, and inhibition of glycolysis. We show here that tumor cells' mitochondria are the primary source of reactive oxygen species induced by Bezielle. Treatment with Bezielle induces progressively higher levels of mitochondrial superoxide as well as peroxide-type ROS. Inhibition of mitochondrial respiration prevents generation of both types of ROS and protects cells from Bezielle-induced death. In addition to glycolysis, Bezielle inhibits oxidative phosphorylation in tumor cells and depletes mitochondrial reserve capacity depriving cells of the ability to produce ATP. Tumor cells lacking functional mitochondria maintain glycolytic activity in presence of Bezielle thus supporting the hypothesis that mitochondria are the primary target of Bezielle. The metabolic effects of Bezielle towards normal cells are not significant, in agreement with the low levels of oxidative damage that Bezielle inflicts on them. Bezielle is therefore a drug that selectively targets cancer cell mitochondria, and is distinguished from other such drugs by its ability to induce not only inhibition of OXPHOS but also of glycolysis. This study provides a better understanding of the mechanism of Bezielle's cytotoxicity, and the basis of its selectivity towards cancer cells
A statistical method for region-based meta-analysis of genome-wide association studies in genetically diverse populations
Genome-wide association studies (GWAS) have become the preferred experimental design in exploring the genetic etiology of complex human traits and diseases. Standard SNP-based meta-analytic approaches have been utilized to integrate the results from multiple experiments. This fundamentally assumes that the patterns of linkage disequilibrium (LD) between the underlying causal variants and the directly genotyped SNPs are similar across the populations for the same SNPs to emerge with surrogate evidence of disease association. We introduce a novel strategy for assessing regional evidence of phenotypic association that explicitly incorporates the extent of LD in the region. This provides a natural framework for combining evidence from multi-ethnic studies of both dichotomous and quantitative traits that (i) accommodates different patterns of LD, (ii) integrates different genotyping platforms and (iii) allows for the presence of allelic heterogeneity between the populations. Our method can also be generalized to perform gene-based or pathway-based analyses. Applying this method on real GWAS data in type 2 diabetes (T2D) boosted the association evidence in regions well-established for T2D etiology in three diverse South-East Asian populations, as well as identified two novel gene regions and a biologically convincing pathway that are subsequently validated with data from the Wellcome Trust Case Control Consortium
Exome-wide association analysis reveals novel coding sequence variants associated with lipid traits in Chinese
published_or_final_versio
Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin
One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution
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