Miracle-dz/UniFAR-FTUs huggingface dataset:
An Orthologue of Bacteroides fragilis NanH Is the Principal Sialidase in Tannerella forsythia

ABSTRACT Sialidase activity is a putative virulence factor of the anaerobic periodontal pathogen Tannerella forsythia, but it is uncertain which genes encode this activity. Characterization of a putative sialidase, SiaHI, by others, indicated that this protein alone may not be responsible for all of the sialidase activity. We describe a second sialidase in T. forsythia (TF0035), an orthologue of Bacteroides fragilis NanH, and its expression in Escherichia coli. Sialidase activity of the expressed NanH was confirmed by using 2′-(4-methylumbelliferyl)-α-d-N-acetylneuraminic acid as a substrate. Biochemical characterization of the recombinant T. forsythia NanH indicated that it was active over a broad pH range, with optimum activity at pH 5.5. This enzyme has high affinity for 2′-(4-methylumbelliferyl)-α-d-N-acetylneuraminic acid (Km of 32.9 ± 10.3 μM) and rapidly releases 4-methylumbelliferone (V max of 170.8 ± 11.8 nmol of 4-methylumbelliferone min−1 mg of protein−1). E. coli lysates containing recombinant T. forsythia NanH cleave sialic acid from a range of substrates, with a preference for α2-3 glycosidic linkages. The genes adjacent to nanH encode proteins apparently involved in the metabolism of sialic acid, indicating that the NanH sialidase is likely to be involved in nutrient acquisition.
Pseudomonas syringae HrpP Is a Type III Secretion Substrate Specificity Switch Domain Protein That Is Translocated into Plant Cells but Functions Atypically for a Substrate-Switching Protein

ABSTRACT Pseudomonas syringae delivers virulence effector proteins into plant cells via an Hrp1 type III secretion system (T3SS). P. syringae pv. tomato DC3000 HrpP has a C-terminal, putative T3SS substrate specificity switch domain, like Yersinia YscP. A ΔhrpP DC3000 mutant could not cause disease in tomato or elicit a hypersensitive response (HR) in tobacco, but the HR could be restored by expression of HrpP in trans. Though HrpP is a relatively divergent protein in the T3SS of different P. syringae pathovars, hrpP from P. syringae pv. syringae 61 and P. syringae pv. phaseolicola 1448A restored HR elicitation and pathogenicity to DC3000 ΔhrpP. HrpP was translocated into Nicotiana benthamiana cells via the DC3000 T3SS when expressed from its native promoter, but it was not secreted in culture. N- and C-terminal truncations of HrpP were tested for their ability to be translocated and to restore HR elicitation activity to the ΔhrpP mutant. No N-terminal truncation completely abolished translocation, implying that HrpP has an atypical T3SS translocation signal. Deleting more than 20 amino acids from the C terminus abolished the ability to restore HR elicitation. HrpP fused to green fluorescent protein was no longer translocated but could restore HR elicitation activity to the ΔhrpP mutant, suggesting that translocation is not essential for the function of HrpP. No T3SS substrates were detectably secreted by DC3000 ΔhrpP except the pilin subunit HrpA, which unexpectedly was secreted poorly. HrpP may function somewhat differently than YscP because the P. syringae T3SS pilus likely varies in length due to differing plant cell walls.
Cloud Computing Applications for Smart Grid: A Survey

The fast-paced development of power systems necessitates smart grids to facilitate real-time control and monitoring with bidirectional communication and electricity flows. Future smart grids are expected to have reliable, efficient, secured, and cost-effective power management with the implementation of distributed architecture. To focus on these requirements, we provide a comprehensive survey on different cloud computing applications for the smart grid architecture, in three different areas-energy management, information management, and security. In these areas, the utility of cloud computing applications is discussed, while giving directions on future opportunities for the development of the smart grid. We also highlight different challenges existing in the conventional smart grid (without cloud application) that can be overcome using cloud. In this survey, we present a synthesized overview of the current state of research on smart grid development. We also identify the current research problems in the areas of cloud-based energy management, information management, and security in smart grid.
The Pseudomonas aeruginosa Diguanylate Cyclase GcbA, a Homolog of P. fluorescens GcbA, Promotes Initial Attachment to Surfaces, but Not Biofilm Formation, via Regulation of Motility

ABSTRACT Cyclic di-GMP is a conserved signaling molecule regulating the transitions between motile and sessile modes of growth in a variety of bacterial species. Recent evidence suggests that Pseudomonas species harbor separate intracellular pools of c-di-GMP to control different phenotypic outputs associated with motility, attachment, and biofilm formation, with multiple diguanylate cyclases (DGCs) playing distinct roles in these processes, yet little is known about the potential conservation of functional DGCs across Pseudomonas species. In the present study, we demonstrate that the P. aeruginosa homolog of the P. fluorescens DGC GcbA involved in promoting biofilm formation via regulation of swimming motility likewise synthesizes c-di-GMP to regulate surface attachment via modulation of motility, however, without affecting subsequent biofilm formation. P. aeruginosa GcbA was found to regulate flagellum-driven motility by suppressing flagellar reversal rates in a manner independent of viscosity, surface hardness, and polysaccharide production. P. fluorescens GcbA was found to be functional in P. aeruginosa and was capable of restoring phenotypes associated with inactivation of gcbA in P. aeruginosa to wild-type levels. Motility and attachment of a gcbA mutant strain could be restored to wild-type levels via overexpression of the small regulatory RNA RsmZ. Furthermore, epistasis analysis revealed that while both contribute to the regulation of initial surface attachment and flagellum-driven motility, GcbA and the phosphodiesterase DipA act within different signaling networks to regulate these processes. Our findings expand the complexity of c-di-GMP signaling in the regulation of the motile-sessile switch by providing yet another potential link to the Gac/Rsm network and suggesting that distinct c-di-GMP-modulating signaling pathways can regulate a single phenotypic output.
Algorithms and Applications for Community Detection in Weighted Networks

Community detection is an important issue due to its wide use in designing network protocols such as data forwarding in Delay Tolerant Networks (DTN) and worm containment in Online Social Networks (OSN). However, most of the existing community detection algorithms focus on binary networks. Since most networks are naturally weighted such as DTN or OSN, in this article, we address the problems of community detection in weighted networks, exploit community for data forwarding in DTN and worm containment in OSN, and demonstrate how community can facilitate these network designs. Specifically, we propose a novel community detection algorithm, and introduce two metrics: intra-centrality and inter-centrality, to characterize nodes in communities, based on which we propose an efficient data forwarding algorithm for DTN and a worm containment strategy for OSN. Extensive trace-driven simulation results show that the proposed community detection algorithm, the data forwarding algorithm, and the worm containment strategy significantly outperform existing works.
Characterization of the Functional Domains of the SloR Metalloregulatory Protein in Streptococcus mutans

ABSTRACT Streptococcus mutans is a commensal member of the healthy plaque biofilm and the primary causative agent of dental caries. The present study is an investigation of SloR, a 25-kDa metalloregulatory protein that modulates genes responsible for S. mutans-induced cariogenesis. Previous studies of SloR homologues in other bacterial pathogens have identified three domains critical to repressor functionality: an N-terminal DNA-binding domain, a central dimerization domain, and a C-terminal FeoA (previously SH3-like) domain. We used site-directed mutagenesis to identify critical amino acid residues within each of these domains of the SloR protein. Select residues were targeted for mutagenesis, and nonconservative amino acid substitutions were introduced by overlap extension PCR. Furthermore, three C-terminally truncated SloR variants were generated using conventional PCR. The repressor functionality and DNA-binding ability of each variant was assessed using CAT reporter gene assays, real-time semiquantitative reverse transcriptase (qRT)-PCR, and electrophoretic mobility shift assays. We identified 12 residues within SloR that cause significant derepression of sloABC promoter activity (P < 0.05) compared to the results for wild-type SloR. Derepression was particularly noteworthy in metal ion-binding site 1 mutants, consistent with the site's importance in gene repression by SloR. In addition, a hyperactive SloR(E169A/Q170A) mutant was identified as having significantly heightened repression of sloABC promoter activity, and experiments with C-terminal deletion mutants support involvement of the FeoA domain in SloR-mediated gene repression. Given these results, we describe the functional domains of the S. mutans SloR protein and propose that the hyperactive mutant could serve as a target for rational drug design aimed at repressing SloR-mediated virulence gene expression.
A Simple Yet Effective Baseline for 3d Human Pose Estimation

Following the success of deep convolutional networks, state-of-the-art methods for 3d human pose estimation have focused on deep end-to-end systems that predict 3d joint locations given raw image pixels. Despite their excellent performance, it is often not easy to understand whether their remaining error stems from a limited 2d pose (visual) understanding, or from a failure to map 2d poses into 3- dimensional positions. ,,With the goal of understanding these sources of error, we set out to build a system that given 2d joint locations predicts 3d positions. Much to our surprise, we have found that, with current technology, "lifting" ground truth 2d joint locations to 3d space is a task that can be solved with a remarkably low error rate: a relatively simple deep feedforward network outperforms the best reported result by about 30% on Human3.6M, the largest publicly available 3d pose estimation benchmark. Furthermore, training our system on the output of an off-the-shelf state-of-the-art 2d detector (i.e., using images as input) yields state of the art results – this includes an array of systems that have been trained end-to-end specifically for this task. Our results indicate that a large portion of the error of modern deep 3d pose estimation systems stems from their visual analysis, and suggests directions to further advance the state of the art in 3d human pose estimation.
Cluster Headache: On the Mechanism Behind Attack-Related Sweating

Eighteen cluster headache patients were studied using body heating or exercise tests; all but two of them were also studied with a pilocarpine test (0.1 mg/kg body wt, s.c.). Evaporimeter measurements were made on both sides of the forehead under standard conditions in a thermo room. Heat- and exercise-induced sweating was dearly less pronounced on the symptomatic side than on the non-symptomatic side of the forehead, and was significantly different compared to controls. Pilocarpine on the other hand induced a clearly more pronounced response on the symptomatic side than on the non-symptomatic side, which was also statistically significantly higher than in the control group. These findings suggest a supersensitivity of the sweat glands to pilocarpine on the symptomatic side of the forehead in most cases of cluster headache.
CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training

Since the network G is able to reconstruct the input image only with the latent vector z and category label c. Therefore, it is expected that it can conveniently encode all the attribute information, such as pose, color, illumination, and even more complex high level styles, in the latent vector. In this section, we will introduce some interesting findings about the latent vector. The same latent variable represents the same attribute. One important finding is that, although we do not use any supervision on the attributes, the same latent vector for different labels will generate images with different category labels but with similar attributes. The reason for this phenomenon may be that images with the same attribute present certain resemblance at the pixel level. So the network automatically put them together through unsupervised clustering. To confirm this, we train a model on a face dataset, FaceScrub, and then extract the latent vector of all the face images. In order to clearly present the distribution, we project all the latent vectors into a two dimensional space by PCA. As shown in Figure S1, the distribution of latent vector is a Gaussian as expected, and the attribute of images, include face pose, illumination, and the background is the same for the same latent vector. With this property, our algorithm can be used in many other applications, such as attributes transformation which generates images with different category labels but with similar attributes, and attributes retrieval which searches for other images with similar attributes.
Uso de álcool entre estudantes de medicina da Universidade Federal do Maranhão

This study aims to evaluate alcohol consumption among medical students at the Federal University of Maranhao (UFMA), Sao Luis, Brazil, in 2010. Students completed two self-reported questionnaires: the first containing general information to be collected; and the second an AUDIT test, tracking the risks of their consumption. The research involved 337 students: 54.8% male and 45.2% female. Two hundred and seventeen (64.2%) reported consuming alcohol. The situations considered most suitable for drinking were college parties. Most of the drinkers (55.8%) fell within Zone I according to the AUDIT score (low-risk alcohol consumption); 38.2% were in Zone II (medium risk); 4.6% in Zone III (high risk); and 1,4% in Zone IV (very high risk). It was found that alcohol consumption was higher among students who were further advanced in their course and among those who did not live with their parents, who showed statistically significant p values. Medical students should therefore be educated on the detrimental risks of alcohol consumption and the consequences that these may entail for their profession.
Feasibility of two-dimensional speckle tracking in evaluation of arterial stiffness: Comparison with pulse wave velocity and conventional sonographic markers of atherosclerosis

Objective Arterial stiffening is an early marker of atherosclerosis that has a prognostic value for cardiovascular morbidity and mortality. Although many markers of arterial hardening have been proposed, the search is on for newer, more user-friendly and reliable surrogates. One such potential candidate has emerged from cardiology, the speckle-tracking technique. The aim of this study was to evaluate the feasibility of the two-dimensional speckle tracking for the evaluation of arterial wall stiffness in comparison with standard stiffness parameters. Methods Carotid ultrasound and applanation tonometry were performed in 188 patients with no cardiovascular risk factors. The following parameters were then evaluated: the intima-media complex thickness, distensibility coefficient, β-stiffness index, circumferential strain/strain rate, and pulse wave velocity and augmentation index. These variables were compared with each other and with patient age, and their reliability was assessed with Bland-Altman plots. Results Strain parameters derived from two-dimensional speckle tracking and intima-media complex thickness correlated better with age and pulse wave velocity than standard makers of arterial stiffness. Moreover, the reliability of these measurements was significantly higher than conventional surrogates. Conclusions Two-dimensional speckle tracing is a reliable method for the evaluation of arterial stiffness. Therefore, together with intima-media complex thickness measurement, it offers great potential in clinical practice as an early marker of atherosclerosis.
Heavy-Metal Resistance of a France Vineyard Soil Bacterium, Pseudomonas mendocina Strain S5.2, Revealed by Whole-Genome Sequencing

ABSTRACT Here we present the draft genome of Pseudomonas mendocina strain S5.2, possessing tolerance to a high concentration of copper. In addition to being copper resistant, the genome of P. mendocina strain S5.2 contains a number of heavy-metal-resistant genes known to confer resistance to multiple heavy-metal ions.
EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis

Single image super-resolution is the task of inferring a high-resolution image from a single low-resolution input. Traditionally, the performance of algorithms for this task is measured using pixel-wise reconstruction measures such as peak signal-to-noise ratio (PSNR) which have been shown to correlate poorly with the human perception of image quality. As a result, algorithms minimizing these metrics tend to produce over-smoothed images that lack highfrequency textures and do not look natural despite yielding high PSNR values. ,,We propose a novel application of automated texture synthesis in combination with a perceptual loss focusing on creating realistic textures rather than optimizing for a pixelaccurate reproduction of ground truth images during training. By using feed-forward fully convolutional neural networks in an adversarial training setting, we achieve a significant boost in image quality at high magnification ratios. Extensive experiments on a number of datasets show the effectiveness of our approach, yielding state-of-the-art results in both quantitative and qualitative benchmarks.
GneZ, a UDP-GlcNAc 2-Epimerase, Is Required for S-Layer Assembly and Vegetative Growth of Bacillus anthracis

ABSTRACT Bacillus anthracis, the causative agent of anthrax, forms an S-layer atop its peptidoglycan envelope and displays S-layer proteins and Bacillus S-layer-associated (BSL) proteins with specific functions to support cell separation of vegetative bacilli and growth in infected mammalian hosts. S-layer and BSL proteins bind via the S-layer homology (SLH) domain to the pyruvylated secondary cell wall polysaccharide (SCWP) with the repeat structure [→4)-β-ManNAc-(1→4)-β-GlcNAc-(1→6)-α-GlcNAc-(1→]n, where α-GlcNAc and β-GlcNAc are substituted with two and one galactosyl residues, respectively. B. anthracis gneY (BAS5048) and gneZ (BAS5117) encode nearly identical UDP-GlcNAc 2-epimerase enzymes that catalyze the reversible conversion of UDP-GlcNAc and UDP-ManNAc. UDP-GlcNAc 2-epimerase enzymes have been shown to be required for the attachment of the phage lysin PlyG with the bacterial envelope and for bacterial growth. Here, we asked whether gneY and gneZ are required for the synthesis of the pyruvylated SCWP and for S-layer assembly. We show that gneZ, but not gneY, is required for B. anthracis vegetative growth, rod cell shape, S-layer assembly, and synthesis of pyruvylated SCWP. Nevertheless, inducible expression of gneY alleviated all the defects associated with the gneZ mutant. In contrast to vegetative growth, neither germination of B. anthracis spores nor the formation of spores in mother cells required UDP-GlcNAc 2-epimerase activity.
Tube Convolutional Neural Network (T-CNN) for Action Detection in Videos

Deep learning has been demonstrated to achieve excellent results for image classification and object detection. However, the impact of deep learning on video analysis has been limited due to complexity of video data and lack of annotations. Previous convolutional neural networks (CNN) based video action detection approaches usually consist of two major steps: frame-level action proposal generation and association of proposals across frames. Also, most of these methods employ two-stream CNN framework to handle spatial and temporal feature separately. In this paper, we propose an end-to-end deep network called Tube Convolutional Neural Network (T-CNN) for action detection in videos. The proposed architecture is a unified deep network that is able to recognize and localize action based on 3D convolution features. A video is first divided into equal length clips and next for each clip a set of tube proposals are generated based on 3D Convolutional Network (ConvNet) features. Finally, the tube proposals of different clips are linked together employing network flow and spatio-temporal action detection is performed using these linked video proposals. Extensive experiments on several video datasets demonstrate the superior performance of T-CNN for classifying and localizing actions in both trimmed and untrimmed videos compared to state-of-the-arts.
Patterns for Distributed Real-Time Stream Processing

In recent years, big data systems have become an active area of research and development. Stream processing is one of the potential application scenarios of big data systems where the goal is to process a continuous, high velocity flow of information items. High frequency trading (HFT) in stock markets or trending topic detection in Twitter are some examples of stream processing applications. In some cases (like, for instance, in HFT), these applications have end-to-end quality-of-service requirements and may benefit from the usage of real-time techniques. Taking this into account, the present article analyzes, from the point of view of real-time systems, a set of patterns that can be used when implementing a stream processing application. For each pattern, we discuss its advantages and disadvantages, as well as its impact in application performance, measured as response time, maximum input frequency and changes in utilization demands due to the pattern.
THE COLLOIDAL GOLD REACTION OF BLOOD SERUM IN DISEASES OF THE LIVER

The purpose of this paper is to report studies of the colloidal gold reaction of blood serum in diseases of the liver. Zsigmondy,1in 1901, laid the foundation for the diagnostic use of the colloidal gold reaction by observing that "certain colloids, especially proteins," prevented the precipitation of colloidal gold suspensions by electrolytes, each protein exerting a specific degree of protection against precipitation. On the other hand, Lange,2in 1912, found that proteins within certain dilutions did not prevent but actually caused the precipitation. The mechanism of the colloidal gold reaction has been the subject of much investigation. Numerous workers, including Felton,3Weston,4Cruickshank5and others,6have shown that the globulin content is the determining factor in the precipitation of colloidal gold and that albumin protects the colloidal suspension from precipitation. The varying colloidal gold curves obtained with spinal fluids in different pathologic conditions result from variations in the balance