Interfering directed paths and the sign phase transition

We revisit the question of the "sign phase transition" for interfering directed paths with real amplitudes in a random medium. The sign of the total amplitude of the paths to a given point may be viewed as an Ising order parameter, so we suggest that a coarse-grained theory for system is a dynamic Ising model coupled to a Kardar-Parisi-Zhang (KPZ) model. It appears that when the KPZ model is in its strong-coupling ("pinned") phase, the Ising model does not have a stable ferromagnetic phase, so there is no sign phase transition. We investigate this numerically for the case of {\ss}1+1 dimensions, demonstrating the instability of the Ising ordered phase there.Comment: 4 pages, 4 figure

Functional rescue of dystrophin deficiency in mice caused by frameshift mutations using Campylobacter jejuni Cas9

Duchenne muscular dystrophy (DMD) is a fatal, X-linked muscle wasting disease caused by mutations in the DMD gene. In 51% of DMD cases, a reading frame is disrupted because of deletion of several exons. Here, we show that CjCas9 derived from Campylobacter jejuni can be used as a gene editing tool to correct an out-of-frame Dmd exon in Dmd knockout mice. Herein, we used Cas9 derived from S. pyogenes to generate Dmd knockout (KO) mice with a frameshift mutation in Dmd gene. Then, we expressed CjCas9, its single-guide RNA, and the eGFP gene in the tibialis anterior muscle of the Dmd KO mice using an all-in-one adeno-associated virus (AAV) vector. CjCas9 cleaved the target site in the Dmd gene efficiently in vivo and induced small insertions or deletions at the target site. This treatment resulted in conversion of the disrupted Dmd reading frame from out-of-frame to in-frame, leading to the expression of dystrophin in the sarcolemma. Importantly, muscle strength was enhanced in the CjCas9-treated muscles, without off-target mutations, indicating high efficiency and specificity of CjCas9. This work suggests that in vivo DMD frame correction, mediated by CjCas9 has great potential for the treatment of DMD and other neuromuscular diseases

Cognitive Computing supported Medical Decision Support System for Patient’s Driving Assessment

To smartly utilize a huge and constantly growing volume of data, improve productivity and increase competitiveness in various fields of life; human requires decision making support systems that efficiently process and analyze the data, and, as a result, significantly speed up the process. Similarly to all other areas of human life, healthcare domain also is lacking Artificial Intelligence (AI) based solution. A number of supervised and unsupervised Machine Learning and Data Mining techniques exist to help us to deal with structured data. However, in a real life, we pretty much deal with unstructured data that hides useful knowledge and valuable information inside human-readable plain texts, images, audio and video. Therefore, such IT giants as IBM, Google, Microsoft, Intel, Facebook, etc., as well as variety of SMEs are actively elaborating different Cognitive Computing services and tools to get a value from unstructured data. Thus, the paper presents feasibility study of IBM Watson cognitive computing services and tools to address the issue of automated health records processing to support doctor’s decision for patient’s driving assessment

A heparin-mimicking polymer conjugate stabilizes basic fibroblast growth factor.

Basic fibroblast growth factor (bFGF) is a protein that plays a crucial role in diverse cellular functions, from wound healing to bone regeneration. However, a major obstacle to the widespread application of bFGF is its inherent instability during storage and delivery. Here, we describe the stabilization of bFGF by covalent conjugation with a heparin-mimicking polymer, a copolymer consisting of styrene sulfonate units and methyl methacrylate units bearing poly(ethylene glycol) side chains. The bFGF conjugate of this polymer retained bioactivity after synthesis and was stable to a variety of environmentally and therapeutically relevant stressors--such as heat, mild and harsh acidic conditions, storage and proteolytic degradation--unlike native bFGF. Following the application of stress, the conjugate was also significantly more active than the control conjugate system in which the styrene sulfonate units were omitted from the polymer structure. This research has important implications for the clinical use of bFGF and for the stabilization of heparin-binding growth factors in general

Canonical description of incompressible fluid -- Dirac brackets approach

We present a novel canonical description of the incompressible fluid dynamics. This description uses the dynamical constraints, in our case reflecting "incompressibility" assumption, and leads to replacement of usual hydrodynamical Poisson brackets for density and velocity fields with Dirac brackets. The resulting equations are then known nonlinear, and non-local in space, equations for incompressible fluid velocity.Comment: 7 pages, late

Macrophage apoptosis in the central nervous system in experimental autoimmune encephalomyelitis

Using light and electron microscopy, we have demonstrated that macrophage apoptosis (programmed cell death) occurs in the central nervous system (CNS) in Lewis rats with acute experimental autoimmune encephalomyelitis (EAE) and chronic relapsing EAE. Apoptotic macrophages were identified by the presence of an apoptotic nucleus in a cell with cytoplasm containing myelin debris but no intermediate filaments. They were found in the meninges, perivascular spaces and in the parenchyma of the white and grey matter of the spinal cord. In acute EAE the apoptotic macrophages were most frequently seen at the time of maximal neurological signs and during the early stages of clinical recovery. Several possible mechanisms may be responsible for the macrophage apoptosis: the release or withdrawal of cytokines; T-cell cytotoxicity; the effect of activated macrophage products, such as nitric oxide; and a direct effect of endogenous glucocorticoids. Macrophage apoptosis, together with the T-cell apoptosis we have previously described in the CNS in EAE, may contribute to the down-regulation of this autoimmune disease

Deterministic Assembly of Arrays of Lithographically Defined WS2 and MoS2 Monolayer Features Directly from Multilayer Sources into Van der Waals Heterostructures

One of the major challenges in the van der Waals (vdW) integration of two-dimensional (2D) materials is achieving high-yield and high-throughput assembly of predefined sequences of monolayers into heterostructure arrays. Mechanical exfoliation has recently been studied as a promising technique to transfer monolayers from a multilayer source synthesized by other techniques, allowing the deposition of a wide variety of 2D materials without exposing the target substrate to harsh synthesis conditions. Although a variety of processes have been developed to exfoliate the 2D materials mechanically from the source and place them deterministically onto a target substrate, they can typically transfer only either a wafer-scale blanket or one small flake at a time with uncontrolled size and shape. Here, we present a method to assemble arrays of lithographically defined monolayer WS2 and MoS2 features from multilayer sources and directly transfer them in a deterministic manner onto target substrates. This exfoliate-align-release process - without the need of an intermediate carrier substrate - is enabled by combining a patterned, gold-mediated exfoliation technique with a new optically transparent, heat-releasable adhesive. WS2/MoS2 vdW heterostructure arrays produced by this method show the expected interlayer exciton between the monolayers. Light-emitting devices using WS2 monolayers were also demonstrated, proving the functionality of the fabricated materials. Our work demonstrates a significant step toward developing mechanical exfoliation as a scalable dry transfer technique for the manufacturing of functional, atomically thin materials

Innovative in silico approaches to address avian flu using grid technology

The recent years have seen the emergence of diseases which have spread very quickly all around the world either through human travels like SARS or animal migration like avian flu. Among the biggest challenges raised by infectious emerging diseases, one is related to the constant mutation of the viruses which turns them into continuously moving targets for drug and vaccine discovery. Another challenge is related to the early detection and surveillance of the diseases as new cases can appear just anywhere due to the globalization of exchanges and the circulation of people and animals around the earth, as recently demonstrated by the avian flu epidemics. For 3 years now, a collaboration of teams in Europe and Asia has been exploring some innovative in silico approaches to better tackle avian flu taking advantage of the very large computing resources available on international grid infrastructures. Grids were used to study the impact of mutations on the effectiveness of existing drugs against H5N1 and to find potentially new leads active on mutated strains. Grids allow also the integration of distributed data in a completely secured way. The paper presents how we are currently exploring how to integrate the existing data sources towards a global surveillance network for molecular epidemiology.Comment: 7 pages, submitted to Infectious Disorders - Drug Target