Artificial Topological Superconductor by the Proximity Effect

published_or_final_versio

Circular Permutation in the Ω-Loop of TEM-1 β-Lactamase Results in Improved Activity and Altered Substrate Specificity

Generating diverse protein libraries that contain improved variants at a sufficiently high frequency is critical for improving the properties of proteins using directed evolution. Many studies have illustrated how random mutagenesis, cassette mutagenesis, DNA shuffling and similar approaches are effective diversity generating methods for directed evolution. Very few studies have explored random circular permutation, the intramolecular relocation of the N- and C-termini of a protein, as a diversity-generating step for directed evolution. We subjected a library of random circular permutations of TEM-1 β-lactamase to selections on increasing concentrations of a variety of β-lactam antibiotics including cefotaxime. We identified two circularly permuted variants that conferred elevated resistance to cefotaxime but decreased resistance to other antibiotics. These variants were circularly permuted in the Ω-loop proximal to the active site. Remarkably, one variant was circularly permuted such that the key catalytic residue Glu166 was located at the N-terminus of the mature protein

Comparing the performance of FA, DFA and DMA using different synthetic long-range correlated time series

Notwithstanding the significant efforts to develop estimators of long-range correlations (LRC) and to compare their performance, no clear consensus exists on what is the best method and under which conditions. In addition, synthetic tests suggest that the performance of LRC estimators varies when using different generators of LRC time series. Here, we compare the performances of four estimators [Fluctuation Analysis (FA), Detrended Fluctuation Analysis (DFA), Backward Detrending Moving Average (BDMA), and centred Detrending Moving Average (CDMA)]. We use three different generators [Fractional Gaussian Noises, and two ways of generating Fractional Brownian Motions]. We find that CDMA has the best performance and DFA is only slightly worse in some situations, while FA performs the worst. In addition, CDMA and DFA are less sensitive to the scaling range than FA. Hence, CDMA and DFA remain "The Methods of Choice" in determining the Hurst index of time series.Comment: 6 pages (including 3 figures) + 3 supplementary figure

A QM/MM approach for the study of monolayer-protected gold clusters

We report the development and implementation of hybrid methods that combine quantum mechanics (QM) with molecular mechanics (MM) to theoretically characterize thiolated gold clusters. We use, as training systems, structures such as Au25(SCH2-R)18 and Au38(SCH2-R)24, which can be readily compared with recent crystallographic data. We envision that such an approach will lead to an accurate description of key structural and electronic signatures at a fraction of the cost of a full quantum chemical treatment. As an example, we demonstrate that calculations of the 1H and 13C NMR shielding constants with our proposed QM/MM model maintain the qualitative features of a full DFT calculation, with an order-of-magnitude increase in computational efficiency.Comment: Journal of Materials Science, 201

Cancer-selective, single agent chemoradiosensitising gold nanoparticles

Two nanometre gold nanoparticles (AuNPs), bearing sugar moieties and/or thiol-polyethylene glycol-amine (PEG-amine), were synthesised and evaluated for their in vitro toxicity and ability to radiosensitise cells with 220 kV and 6 MV X-rays, using four cell lines representing normal and cancerous skin and breast tissues. Acute 3 h exposure of cells to AuNPs, bearing PEG-amine only or a 50:50 ratio of alpha-galactose derivative and PEG-amine resulted in selective uptake and toxicity towards cancer cells at unprecedentedly low nanomolar concentrations. Chemotoxicity was prevented by co-administration of N-acetyl cysteine antioxidant, or partially prevented by the caspase inhibitor Z-VAD-FMK. In addition to their intrinsic cancer-selective chemotoxicity, these AuNPs acted as radiosensitisers in combination with 220 kV or 6 MV X-rays. The ability of AuNPs bearing simple ligands to act as cancer-selective chemoradiosensitisers at low concentrations is a novel discovery that holds great promise in developing low-cost cancer nanotherapeutics

Foundations of Black Hole Accretion Disk Theory

This review covers the main aspects of black hole accretion disk theory. We begin with the view that one of the main goals of the theory is to better understand the nature of black holes themselves. In this light we discuss how accretion disks might reveal some of the unique signatures of strong gravity: the event horizon, the innermost stable circular orbit, and the ergosphere. We then review, from a first-principles perspective, the physical processes at play in accretion disks. This leads us to the four primary accretion disk models that we review: Polish doughnuts (thick disks), Shakura-Sunyaev (thin) disks, slim disks, and advection-dominated accretion flows (ADAFs). After presenting the models we discuss issues of stability, oscillations, and jets. Following our review of the analytic work, we take a parallel approach in reviewing numerical studies of black hole accretion disks. We finish with a few select applications that highlight particular astrophysical applications: measurements of black hole mass and spin, black hole vs. neutron star accretion disks, black hole accretion disk spectral states, and quasi-periodic oscillations (QPOs).Comment: 91 pages, 23 figures, final published version available at http://www.livingreviews.org/lrr-2013-

Allelopathic interactions of linoleic acid and nitric oxide increase the competitive ability of Microcystis aeruginosa

The frequency and intensity of cyanobacterial blooms are increasing worldwide with major societal and economic costs. Interactions between toxic cyanobacteria and eukaryotic algal competitors can affect toxic bloom formation, but the exact mechanisms of interspecies interactions remain unknown. Using metabolomic and proteomic profiling of co-cultures of the toxic cyanobacterium Microcystis aeruginosa with a green alga as well as of microorganisms collected in a Microcystis spp. bloom in Lake Taihu (China), we disentangle novel interspecies allelopathic interactions. We describe an interspecies molecular network in which M. aeruginosa inhibits growth of Chlorella vulgaris, a model green algal competitor, via the release of linoleic acid. In addition, we demonstrate how M. aeruginosa takes advantage of the cell signaling compound nitric oxide produced by C. vulgaris, which stimulates a positive feedback mechanism of linoleic acid release by M. aeruginosa and its toxicity. Our high-throughput system-biology approach highlights the importance of previously unrecognized allelopathic interactions between a broadly distributed toxic cyanobacterial bloom former and one of its algal competitors

Fungal iron availability during deep seated candidiasis is defined by a complex interplay involving systemic and local events

Peer reviewedPublisher PD

Leveraging the performance of LBM-HPC for large sizes on GPUs using ghost cells

Today, we are living a growing demand of larger and more efficient computational resources from the scientific community. On the other hand, the appearance of GPUs for general purpose computing supposed an important advance for covering such demand. These devices offer an impressive computational capacity at low cost and an efficient power consumption. However, the memory available in these devices is (sometimes) not enough, and so it is necessary computationally expensive memory transfers from (to) CPU to (from) GPU, causing a dramatic fall in performance. Recently, the Lattice-Boltzmann Method has positioned as an efficient methodology for fluid simulations. Although this method presents some interesting features particularly amenable to be efficiently exploited on parallel computers, it requires a considerable memory capacity, which can suppose an important drawback, in particular, on GPUs. In the present paper, it is proposed a new GPU-based implementation, which minimizes such requirements with respect to other state-of-the-art implementations. It allows us to execute almost 2$x$ bigger problems without additional memory transfers, achieving faster executions when dealing with large problems