45 research outputs found

    Genomic characterization and assessment of pathogenic potential of Legionella spp. isolates from environmental monitoring

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    Several species in the genus Legionella are known to cause an acute pneumonia when the aerosols containing the bacteria from man-made water systems are inhaled. The disease is usually caused by Legionella pneumophila, but other species have been implicated in the infection. The disease is frequently manifested as an outbreak, which means several people are affected when exposed to the common source of Legionella contamination. Therefor environmental surveillance which includes isolation and identification of Legionella is performed routinely. However, usually no molecular or genome-based methods are employed in further characterization of the isolates during routine environmental monitoring. During several years of such monitoring, isolates from different geographical locations were collected and 39 of them were sequenced by hybrid de novo approach utilizing short and long sequencing reads. In addition, the isolates were typed by standard culture and MALDI-TOF method. The sequencing reads were assembled and annotated to produce high-quality genomes. By employing discriminatory genome typing, four potential new species in the Legionella genus were identified, which are yet to be biochemically and morphologically characterized. Moreover, functional annotations concerning virulence and antimicrobial resistance were performed on the sequenced genomes. The study contributes to the knowledge on little-known non-pneumophila species present in man-made water systems and establishes support for future genetic relatedness studies as well as understanding of their pathogenic potential

    Antiproliferative activity and mode of action analysis of novel amino and amido substituted phenantrene and naphtho[2,1-b]thiophene derivatives

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    Herein we present and describe the design and synthesis of novel phenantrene derivatives substituted with either amino or amido side chains and their biological activity. Antiproliferative activities were assessed in vitro on a panel of human cancer cell lines. Tested compounds showed moderate activity against cancer cells in comparison with 5-fluorouracile. Among all tested compounds, some compounds substituted with cyano groups showed a pronounced and selective activity in the nanomolar range of inhibitory concentrations against HeLa and HepG2. The strongest selective activity against HeLa cells was observed for acrylonitriles 8 and 11 and their cyclic analogues 15 and 17 substituted with two cyano groups with a corresponding IC50 = 0.33, 0.21, 0.65 and 0.45 μM, respectively. Compounds 11 showed the most pronounced selectivity being almost non cytotoxic to normal fibroblasts. Additionally, mode of biological action analysis was performed in silico and in vitro by Western blot analysis of HIF-1-α relative expression for compounds 8 and 11

    Feasibility Study for Bicycle Safety: Data Assessment and Network Evaluation

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    Bicycles offer a promising transportation alternative to private motor vehicles, especially in areas with congestion, poor air quality, and high fuel prices. This study sought rational methods for evaluating the benefits of incorporating bicycle-friendly features into highway project designs. Data on recent bicyclist fatalities and other collisions involving bicyclists in Indiana were analyzed to determine factors that could help to explain the incidents and offer insights into countermeasures or remedies. Human error – on the part of the bicyclist or the motorist – was found to be the most common factor. Poor lighting and noncompliance with sidewalk ordinances also were frequent causes of bicycle crashes. A Bicycle Network Analysis Tool was developed to assess the level of service offered to bicyclists in a study area. The tool uses route length and measures of perceived safety to quantify the bicycle friendliness of a street network. The tool can be used to compare networks and assist in the selection of locations for bicycle facility improvements

    Using self-organizing maps in the visualization and analysis of forest inventory

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    A lot of useful data on forest condition can be gathered from the Forest Inven­tory (FI). Without the help of data analysis tools, human experts cannot ma­nually interpret information in such a large data set. Conventional multivariate statistical analyses provide results that are difficult to interpret and often do not represent the information in a satisfactory way. Our goal is to identify an alternative approach that will enable fast and efficient interpretation and analysis of the FI data. Such interpretation and analysis can be performed automatically with a clustering method, but all clustering methods have some shortcomings. Therefore, our aim was also to provide information in a form suitable for fast and intuitive visualization. Kohonen’s Self Organizing Map (SOM) is an alternative approach to data visualization and analysis of large multidimensional data sets. SOM provides different possibilities and our experiments are presented with component matrices of individual stand parameters and label matrices. In forming data clusters, we experimented with hierarchi­cal and non hierarchical clustering methods. Our experiments showed that SOM provides useful information in a form suitable for data clustering and data vi­sualization. This enables an efficient analysis of large FI data sets at different analysis scales. Clustering results obtained with SOM and two clustering algorithms are in accordance with ground truth. We have also considered the efficiency of SOM component matrices by visual comparison and correlation among structural parameters and by determining contributions of individual stand parameters to clustering input data. SOM application in visualization and analysis of stand structural parameters enables gathering quickly and efficiently holistic information on the current condition of forest stands and forest ecosystem development. Therefore we recommend the application of Kohonen’s SOM for visualization and analysis of FI data

    Ice sliding games

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    International audienceThis paper deals with sliding games, which are a variant of the better known pushpush game. On a given structure (grid, torus...), a robot can move in a specific set of directions, and stops when it hits a block or boundary of the structure. The objective is to place the minimum number of blocks such that the robot can visit all the possible positions of the structure. In particular, we give the exact value of this number when playing on a rectangular grid and a torus. Other variants of this game are also considered, by constraining the robot to stop on each case, or by replacing blocks by walls

    A learning analytics approach to correlate the academic achievements of students with interaction data from an educational simulator

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    This paper presents a Learning Analytics approach for understanding the learning behavior of students while interacting with Technology Enhanced Learning tools. In this work we show that it is possible to gain insight into the learning processes of students from their interaction data. We base our study on data collected through six laboratory sessions where first-year students of Computer Engineering at the University of Genoa were using a digital electronics simulator. We exploit Process Mining methods to investigate and compare the learning processes of students. For this purpose, we measure the understandability of their process models through a complexity metric. Then we compare the various clusters of students based on their academic achievements. The results show that the measured complexity has positive correlation with the final grades of students and negative correlation with the difficulty of the laboratory sessions. Consequently, complexity of process models can be used as an indicator of variations of student learning paths

    Bariatric endoscopy: current state of the art, emerging technologies, and challenges

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    Over the last few decades obesity has become a major health issue worldwide. Although dietary and lifestyle changes are the cornerstone of obesity management, it still poses a huge challenge for the majority of patients to permanently change their eating habits. Bariatric endoscopy represents an evolving filed of minimally invasive techniques and procedures for weight loss trying to respond to these challenges by developing new methods with the increasing role of endoscopists in the management of obesity. Areas covered: The aim of this article is to review the role and the advantages of bariatric endoscopy in the management of obesity by providing a comprehensive reference source and evaluating the currently available and emerging endoscopic devices and techniques for weight loss. Expert commentary: Endoscopic methods for weight loss represent a useful armamentarium in the management of obesity by providing improved effectiveness compared with medications, with a lower risk profile than traditional bariatric surgery. Although preliminary results of recently introduced methods are encouraging, many questions remain regarding the safety and efficacy of such interventions. Combining scientific background with advancements in technology is the key strategy for the further development of bariatric endoscopy
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