Miracle-dz/UniFAR-FTUs huggingface dataset:
A conserved RxLR effector interacts with host RABA‐type GTPases to inhibit vesicle‐mediated secretion of antimicrobial proteins

Plant pathogens of the oomycete genus Phytophthora produce virulence factors, known as RxLR effector proteins that are transferred into host cells to suppress disease resistance. Here, we analyse the function of the highly conserved RxLR24 effector of Phytophthora brassicae. RxLR24 was expressed early in the interaction with Arabidopsis plants and ectopic expression in the host enhanced leaf colonization and zoosporangia formation. Co-immunoprecipitation (Co-IP) experiments followed by mass spectrometry identified different members of the RABA GTPase family as putative RxLR24 targets. Physical interaction of RxLR24 or its homologue from the potato pathogen Phytophthora infestans with different RABA GTPases of Arabidopsis or potato, respectively, was confirmed by reciprocal Co-IP. In line with the function of RABA GTPases in vesicular secretion, RxLR24 co-localized with RABA1a to vesicles and the plasma membrane. The effect of RxLR24 on the secretory process was analysed with fusion constructs of secreted antimicrobial proteins with a pH-sensitive GFP tag. PATHOGENESIS RELATED PROTEIN 1 (PR-1) and DEFENSIN (PDF1.2) were efficiently exported in control tissue, whereas in the presence of RxLR24 they both accumulated in the endoplasmic reticulum. Together our results imply a virulence function of RxLR24 effectors as inhibitors of RABA GTPase-mediated vesicular secretion of antimicrobial PR-1, PDF1.2 and possibly other defence-related compounds.
Synthesis and Application of Nanorods

In nanotechnology, nanorods are morphology of nanoscale objects. Each of their dimension ranges from 1–100 nm. Nanorods may be synthesized from metals or semiconducting materials with ratios (length divided by width) are 3-5. One way for synthesis of nanorods is produced by direct chemical synthesis. The combinations of ligands act as shape control agents and bond to different facets of the nanorod with different strengths. This allows different faces of the nanorod to grow at different rates, producing an elongated object.
Parallel transmit excitation at 1.5 T based on the minimization of a driving function for device heating.

PURPOSE To provide a rapid method to reduce the radiofrequency (RF) E-field coupling and consequent heating in long conductors in an interventional MRI (iMRI) setup. METHODS A driving function for device heating (W) was defined as the integration of the E-field along the direction of the wire and calculated through a quasistatic approximation. Based on this function, the phases of four independently controlled transmit channels were dynamically changed in a 1.5 T MRI scanner. During the different excitation configurations, the RF induced heating in a nitinol wire immersed in a saline phantom was measured by fiber-optic temperature sensing. Additionally, a minimization of W as a function of phase and amplitude values of the different channels and constrained by the homogeneity of the RF excitation field (B1) over a region of interest was proposed and its results tested on the benchtop. To analyze the validity of the proposed method, using a model of the array and phantom setup tested in the scanner, RF fields and SAR maps were calculated through finite-difference time-domain (FDTD) simulations. In addition to phantom experiments, RF induced heating of an active guidewire inserted in a swine was also evaluated. RESULTS In the phantom experiment, heating at the tip of the device was reduced by 92% when replacing the body coil by an optimized parallel transmit excitation with same nominal flip angle. In the benchtop, up to 90% heating reduction was measured when implementing the constrained minimization algorithm with the additional degree of freedom given by independent amplitude control. The computation of the optimum phase and amplitude values was executed in just 12 s using a standard CPU. The results of the FDTD simulations showed similar trend of the local SAR at the tip of the wire and measured temperature as well as to a quadratic function of W, confirming the validity of the quasistatic approach for the presented problem at 64 MHz. Imaging and heating reduction of the guidewire were successfully performed in vivo with the proposed hardware and phase control. CONCLUSIONS Phantom and in vivo data demonstrated that additional degrees of freedom in a parallel transmission system can be used to control RF induced heating in long conductors. A novel constrained optimization approach to reduce device heating was also presented that can be run in just few seconds and therefore could be added to an iMRI protocol to improve RF safety.
Compressed Sensing Classification in Online Social Networks

In this technical report we introduce a novel low dimensional method to perform topic detection and classification in Twitter. The proposed method first employs Joint Complexity to perform topic detection. Then, based on the nature of the data, we apply the theory of Compressive Sensing to perform topic classification by recovering an indicator vector, while reducing significantly the amount of information from tweets. We exploit datasets in various languages collected by using the Twitter streaming API, and achieve increased classification accuracy when comparing to state-of-the-art methods based on bag-of-words, along with several reconstruction techniques.
Multi-scale Weighted Nuclear Norm Image Restoration

A prominent property of natural images is that groups of similar patches within them tend to lie on low-dimensional subspaces. This property has been previously used for image denoising, with particularly notable success via weighted nuclear norm minimization (WNNM). In this paper, we extend the WNNM method into a general image restoration algorithm, capable of handling arbitrary degradations (e.g. blur, missing pixels, etc.). Our approach is based on a novel regularization term which simultaneously penalizes for high weighted nuclear norm values of all the patch groups in the image. Our regularizer is isolated from the data-term, thus enabling convenient treatment of arbitrary degradations. Furthermore, it exploits the fractal property of natural images, by accounting for patch similarities also across different scales of the image. We propose a variable splitting method for solving the resulting optimization problem. This leads to an algorithm that is quite different from "plug-and-play" techniques, which solve image-restoration problems using a sequence of denoising steps. As we verify through extensive experiments, our algorithm achieves state of the art results in deblurring and inpainting, outperforming even the recent deep net based methods.
(Iso-)form Matters: Differential Implication of Vav3 Variants in Ovarian Cancer.

Ovarian Cancer MAXIMILIAN BOESCH , DANIEL REIMER, SIEGHART SOPPER, DOMINIK WOLF, ALAIN G. ZEIMET Institute of Immunobiology, Kantonsspital St. Gallen, St. Gallen, Switzerland; Internal Medicine V, Medical University of Innsbruck, Innsbruck, Austria; Oncotyrol – Center for Personalized Cancer Medicine GmbH, Innsbruck, Austria; Tyrolean Cancer Research Institute (TKFI), Innsbruck, Austria; Department of Gynecology and Obstetrics, Medical University of Innsbruck, Innsbruck, Austria; Medical Clinic III, University Clinic Bonn (UKB), Bonn, Germany Contributed equally
Parallel Computing of Polymer Chains Based on Monte Carlo Method

Computer simulation of polymer chain is carried out by Monte Carlo method in this paper. The properties of polymer chain are simulated by self avoiding walk and bond fluctuation model. The parallel computing model is established to solve the physical problems of the polymer chains. We analyze the algorithms for polymer chains to parallel computing at high performance computing center. Gustafson law is analyzed and is applied to obtain linear speedup. Copyright © 2013 IFSA.
Classification of self-assembling protein nanoparticle architectures for applications in vaccine design

We introduce here a mathematical procedure for the structural classification of a specific class of self-assembling protein nanoparticles (SAPNs) that are used as a platform for repetitive antigen display systems. These SAPNs have distinctive geometries as a consequence of the fact that their peptide building blocks are formed from two linked coiled coils that are designed to assemble into trimeric and pentameric clusters. This allows a mathematical description of particle architectures in terms of bipartite (3,5)-regular graphs. Exploiting the relation with fullerene graphs, we provide a complete atlas of SAPN morphologies. The classification enables a detailed understanding of the spectrum of possible particle geometries that can arise in the self-assembly process. Moreover, it provides a toolkit for a systematic exploitation of SAPNs in bioengineering in the context of vaccine design, predicting the density of B-cell epitopes on the SAPN surface, which is critical for a strong humoral immune response.
Competitive docking model for prediction of the human nicotinic acetylcholine receptor α7 binding of tobacco constituents

The detrimental health effects associated with tobacco use constitute a major public health concern. The addiction associated with nicotine found in tobacco products has led to difficulty in quitting among users. Nicotinic acetylcholine receptors (nAChRs) are the targets of nicotine and are responsible for addiction to tobacco products. However, it is unknown if the other >8000 tobacco constituents are addictive. Since it is time-consuming and costly to experimentally assess addictive potential of such larger number of chemicals, computationally predicting human nAChRs binding is important for in silico evaluation of addiction potential of tobacco constituents and needs structures of human nAChRs. Therefore, we constructed three-dimensional structures of the ligand binding domain of human nAChR α7 subtype and then developed a predictive model based on the constructed structures to predict human nAChR α7 binding activity of tobacco constituents. The predictive model correctly predicted 11 out of 12 test compounds to be binders of nAChR α7. The model is a useful tool for high-throughput screening of potential addictive tobacco constituents. These results could inform regulatory science research by providing a new validated predictive tool using cutting-edge computational methodology to high-throughput screen tobacco additives and constituents for their binding interaction with the human α7 nicotinic receptor. The tool represents a prediction model capable of screening thousands of chemicals found in tobacco products for addiction potential, which improves the understanding of the potential effects of additives.
A Formal Specification of DSM-CC Interfaces

This paper explores an application of formal methods to the standard description in the context of DSM-CC (Digital Storage Media Command and Control). DSM-CC is a recent ISO/IEC standard developed for the delivery of multimedia broadband services such as video on demand and home shopping. The standard specifies the user-to-network (U-N) protocols and the user-to-user (U-U) interfaces. We suggest a technique for formally specifying the U-U interfaces, provide a concrete example and show the benefits of applying formal techniques to the standard descriptions. In particular, we demonstrate that a declarative interface specification method tailored to CORBA-IDL is well suited to specifying the behavioral semantics of DSM-CC interfaces. Abstract models for interface types are defined by a family of mathematical functions and the interface operations are specified by a pair of pre and postconditions written in terms of the abstract models. An explicit connection is established between the abstract world and the interface world by an abstraction function that maps interface values to abstract values. Keywords—DSM-CC, U-U interface, abstraction, formal methods, interface specification, stream
Molecular Epidemiology of Methicillin-Resistant Staphylococcus hominis (MRSHo): Low Clonality and Reservoirs of SCCmec Structural Elements

Background Methicillin resistant Staphylococcus hominis (MRSHo) are important human pathogens in immunocompromised patients. However, little is known regarding its population structure and staphylococcal chromosomal cassette mec (SCCmec) content. Methodology/Principal Findings To assess the population structure and the SCCmec content of S. hominis, 34 MRSHo and 11 methicillin-susceptible S. hominis (MSSHo) from neutropenic patients collected over a 3-year period were studied. The genetic backgrounds of S. hominis isolates were analyzed by pulsed-field gel electrophoresis (PFGE) and SCCmec types were determined by PCR. Cassette chromosome recombinases (ccr) were characterized by PCR and ccrB sequencing. The 34 S. hominis isolates were classified into as many as 28 types and 32 subtypes (SID = 99.82%); clonal dissemination was occasionally observed. The main SCCmec structures identified were SCCmec type VI (4B) (20%), SCCmec VIII (4A) (15%), and a new SCCmec composed of mec complex A in association with ccrAB1 (38%); 27% of the isolates harbored non-typeable SCCmec. Overall, a high prevalence of mec complex A (73.5%), ccrAB1 (50%) and ccrAB4 (44%) were found. Importantly, ccrB1 and ccrB4 from both MRSHo and MSSHo showed a high nucleotide sequence homology with those found in S. aureus SCCmec I, VI and VIII respectively (>95%). Conclusions/Significance The S. hominis population showed a limited clonality and a low genetic diversity in the allotypes of ccr and classes of mec complex. Moreover, our data suggest that S. hominis might have been a privileged source of mec complex A, ccrB1 and ccrB4, for the assembly of primordial SCCmec types.
EURASIAN JOURNAL OF BUSINESS AND MANAGEMENT

The economic, social, and cultural changes in the modern world have made adolescents between the ages of 12 and 18 important influences on family purchasing decisions. No longer solely users of products and services, adolescents now influence purchasing decisions and have attracted the attention of marketers and researchers. The purpose of this study is to analyze changes in the influence of adolescents aged between 12 and 18 on family purchasing decisions depending on socio-economic and demographic factors. This study aims to determine whether changes occur regarding different product groups by establishing at which stage of the decision process adolescent influence predominates. To achieve this goal, a survey method was used as a data collection tool. Using the convenience sampling method, adolescents within the age range of 12 and 18 were interviewed in Mersin, Turkey. The research results indicate that the influence of adolescents on family purchasing decisions occurs at different stages and depends on the type of product to be purchased. The analysis further shows that adolescents’ age, gender, and number of siblings, and the family's total income, the father's level of education, and the mother's employment status also affect adolescent influence on family purchasing decisions.
Communicating effectively about CSR on Twitter: The power of engaging strategies and storytelling elements

Purpose Corporate social responsibility (CSR) communication is becoming increasingly important for brands and companies. Social media such as Twitter may be platforms particularly suited to this topic, given their ability to foster dialogue and content diffusion. The purpose of this paper is to investigate factors driving the effectiveness of CSR communication on Twitter, with a focus on the communication strategies and elements of storytelling. Design/methodology/approach Using a sample of 281,291 tweets from top global companies in the food sector, automated content analysis (including supervised machine learning) was used to investigate the influence of CSR communication, emotion, and aspirational talk on the likelihood that Twitter users will retweet and like tweets from the companies. Findings The findings highlight the importance of aspirational talk and engaging users in CSR messages. Furthermore, the study revealed that the companies and brands on Twitter that tweeted more frequently about CSR were associated with higher overall levels of content diffusion and endorsement. Originality/value This study provides important insights into key aspects of communicating about CSR issues on social networking sites such as Twitter and makes several practical recommendations for companies.
String Cosmology - Large-Field Inflation in String Theory

This is a short review of string cosmology. We wish to connect string-scale physics as closely as possible to observables accessible to current or near-future experiments. Our possible best hope to do so is a description of inflation in string theory. The energy scale of inflation can be as high as that of Grand Unification (GUT). If this is the case, this is the closest we can possibly get in energy scales to string-scale physics. Hence, GUT-scale inflation may be our best candidate phenomenon to preserve traces of string-scale dynamics. Our chance to look for such traces is the primordial gravitational wave, or tensor mode signal produced during inflation. For GUT-scale inflation this is strong enough to be potentially visible as a B-mode polarization of the cosmic microwave background (CMB). Moreover, a GUT-scale inflation model has a trans-Planckian excursion of the inflaton scalar field during the observable amount of inflation. Such large-field models of inflation have a clear need for symmetry protection against quantum corrections. This makes them ideal candidates for a description in a candidate fundamental theory like string theory. At the same time the need of large-field inflation models for UV completion makes them particularly susceptible to preserve imprints of their string-scale dynamics in the inflationary observables, the spectral index $n_s$ and the fractional tensor mode power $r$. Hence, we will focus this review on axion monodromy inflation as a mechanism of large-field inflation in string theory.
Chilean Gastric Cancer Task Force

Abstract Gastric cancer (GC) is the world's second-leading cause of neoplastic mortality. Genetic alterations, response to treatments, and mortality rates are highly heterogeneous across different regions. Within Latin America, GC is the leading cause of cancer death in Chile, affecting 17.6 per 100,000 people and causing >3000 deaths/y. Clinical outcomes and response to “one size fits all” therapies are highly heterogeneous and thus a better stratification of patients may aid cancer treatment and response. The Gastric Cancer Task Force is a Chilean collaborative, noninterventional study that seeks to stratify gastric adenocarcinomas using clinical outcomes and genomic, epigenomic, and protein alterations in a cohort of 200 patients. Tumor samples from the Pathology Department and the Cancer Center at UC-Christus healthcare network, Pontificia Universidad Católica de Chile will be analyzed using a panel of 143 known cancer genes (Oncomine Comprehensive Assay) at the Center of Excellence in Precision Medicine in Santiago, Chile. In addition, promoter methylation for selected genes will be performed along with tissue microarray for clinically relevant proteins (e.g., PD-L1, Erb-2, VEGFR2, among others) and Helicobacter pylori and Epstein–Barr virus status. Obtained data will be correlated to 120 clinical parameters retrieve from medical records, including general patient information, cancer history, laboratory studies, comorbidity index, chemotherapy, targeted therapies, efficacy, and follow-up. The development of a clinically meaningful classification that encompasses comprehensive clinical and molecular parameters may improve patient treatment, predict clinical outcomes, aid patient selection/stratification for clinical trials and may offer insights into future preventive and/or therapeutic strategies in patients from Latin America region. Trial registration: ClinicalTrials.gov Identifier: NCT03158571, Registered on May 18, 2017.
Attenuation of Oxidative Stress-Induced Cell Apoptosis in Schwann RSC96 Cells by Ocimum Gratissimum Aqueous Extract

Objectives:Cell transplantation therapy of Schwann cells (SCs) is a promising therapeutic strategy after spinal cord injury. However, challenges such as oxidative stress hinder satisfactory cell viability and intervention for enhancing SCs survival is critical throughout the transplantation procedures. Ocimum gratissimum, widely used as a folk medicine in many countries, has therapeutic and anti-oxidative properties and may protect SCs survival. Methods:We examined the protective effects of aqueous O. gratissimum extract (OGE) against cell damage caused by H2O2-induced oxidative stress in RSC96 Schwann cells. Results:Our results showed that the RSC96 cells, damaged by H2O2 oxidative stress, decreased their viability up to 32% after treatment with different concentrations of up to 300 μM H2O2, but OGE pretreatment (150 or 200 μg/mL) increased cell viability by approximately 62% or 66%, respectively. Cell cycle analysis indicated a high (43%) sub-G1 cell population in the H2O2-treated RSC96 cells compared with untreated cells (1%); whereas OGE pretreatment (150 and 200 μg/mL) of RSC96 cells significantly reduced the sub-G1 cells (7% and 8%, respectively). Furthermore, Western blot analysis revealed that OGE pretreatment inhibited H2O2-induced apoptotic protein caspase-3 activation and PARP cleavage, as well as it reversed Bax up-regulation and Bcl-2 down-regulation. The amelioration of OGE of cell stress and stress-induced apoptosis was proved by the HSP70 and HSP72 decrease. Conclusion: Our data suggest that OGE may minimize the cytotoxic effects of H2O2-induced SCs apoptosis by modulating the apoptotic pathway and could potentially supplement cell transplantation therapy.
Melanoma Therapeutic St rategies that Select against Resistance by Exploiting MYC-Driven Evolutionary Convergence Graphical

In Brief Diverse pathways drive resistance to BRAF/MEK inhibitors in BRAF-mutant melanoma, but by combining statistical modeling of tumor data with functional interrogation of resistance models, Singleton et al. show that these pathways converge to activate MYC. BRAFiresistant cells are hypersensitive to the inhibition of MYC synthetic lethal partners, informing therapies that select against resistance.