Inhibition of Xanthomonas fragariae, Causative Agent of Angular Leaf Spot of Strawberry, through Iron Deprivation.

In commercial production settings, few options exist to prevent or treat angular leaf spot (ALS) of strawberry, a disease of economic importance and caused by the bacterial pathogen Xanthomonas fragariae. In the process of isolating and identifying X. fragariae bacteria from symptomatic plants, we observed growth inhibition of X. fragariae by bacterial isolates from the same leaf macerates. Identified as species of Pseudomonas and Rhizobium, these isolates were confirmed to suppress growth of X. fragariae in agar overlay plates and in microtiter plate cultures, as did our reference strain Pseudomonas putida KT2440. Screening of a transposon mutant library of KT2440 revealed that disruption of the biosynthetic pathway for the siderophore pyoverdine resulted in complete loss of X. fragariae antagonism, suggesting iron competition as a mode of action. Antagonism could be replicated on plate and in culture by addition of purified pyoverdine or by addition of the chelating agents tannic acid and dipyridyl, while supplementing the medium with iron negated the inhibitory effects of pyoverdine, tannic acid and dipyridyl. When co-inoculated with tannic acid onto strawberry plants, X. fragariae's ability to cause foliar symptoms was greatly reduced, suggesting a possible opportunity for iron-based management of ALS. We discuss our findings in the context of 'nutritional immunity,' the idea that plant hosts restrict pathogen access to iron, either directly, or indirectly through their associated microbiota

Numerical Analysis of an Intercity Bus Structure: A Simple Unifilar Model Proposal to Assess Frontal and Semifrontal Crash Scenarios

Abstract To improve the safety of the intercity bus structure against impact scenarios and to reduce the injuries and death in traffic accidents it is crucial in a country with continental dimensions like Brazil, where the road transport matrix is fundamental in the traffic of people and goods. In this context in the present article, a numerical model of an intercity bus was built with elastoplastic beam implemented in a commercial software Ls-Dyna. This model was submitted to different frontal and semi frontal impact crash scenarios. With this model were analyzed different accidents which happened in the Brazilian highways, it was also simulated a frontal impact test and the results obtained were compared with the experimental results. Finally two numerical approaches were compared, they are: a simple model made with lumped masses and non-linear springs series connected, and the elastoplastic beam model. The different comparisons carried out let us validate the intercity bus model created using elastoplastic beam elements and propose to use this model as an effective tool to search for more efficient bus structural configurations against impact scenarios

Gene prediction in metagenomic fragments: A large scale machine learning approach

<p>Abstract</p> <p>Background</p> <p>Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions.</p> <p>Results</p> <p>We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability.</p> <p>Conclusion</p> <p>Large scale machine learning methods are well-suited for gene prediction in metagenomic DNA fragments. In particular, the combination of linear discriminants and neural networks is promising and should be considered for integration into metagenomic analysis pipelines. The data sets can be downloaded from the URL provided (see Availability and requirements section).</p

Increasing health worker capacity through distance learning: a comprehensive review of programmes in Tanzania

<p>Abstract</p> <p>Background</p> <p>Tanzania, like many developing countries, faces a crisis in human resources for health. The government has looked for ways to increase the number and skills of health workers, including using distance learning in their training. In 2008, the authors reviewed and assessed the country's current distance learning programmes for health care workers, as well as those in countries with similar human resource challenges, to determine the feasibility of distance learning to meet the need of an increased and more skilled health workforce.</p> <p>Methods</p> <p>Data were collected from 25 distance learning programmes at health training institutions, universities, and non-governmental organizations throughout the country from May to August 2008. Methods included internet research; desk review; telephone, email and mail-in surveys; on-site observations; interviews with programme managers, instructors, students, information technology specialists, preceptors, health care workers and Ministry of Health and Social Welfare representatives; and a focus group with national HIV/AIDS care and treatment organizations.</p> <p>Results</p> <p>Challenges include lack of guidelines for administrators, instructors and preceptors of distance learning programmes regarding roles and responsibilities; absence of competencies for clinical components of curricula; and technological constraints such as lack of access to computers and to the internet. Insufficient funding resulted in personnel shortages, lack of appropriate training for personnel, and lack of materials for students.</p> <p>Nonetheless, current and prospective students expressed overwhelming enthusiasm for scale-up of distance learning because of the unique financial and social benefits offered by these programs. Participants were retained as employees in their health care facilities, and remained in their communities and supported their families while advancing their careers. Space in health training institutions was freed up for new students entering in-residence pre-service training.</p> <p>Conclusions</p> <p>A blended print-based distance learning model is most feasible at the national level due to current resource and infrastructure constraints. With an increase in staffing; improvement of infrastructure, coordination and curricula; and decentralization to the zonal or district level, distance learning can be an effective method to increase both the skills and the numbers of qualified health care workers capable of meeting the health care needs of the Tanzanian population.</p

Prodigal: prokaryotic gene recognition and translation initiation site identification

<p>Abstract</p> <p>Background</p> <p>The quality of automated gene prediction in microbial organisms has improved steadily over the past decade, but there is still room for improvement. Increasing the number of correct identifications, both of genes and of the translation initiation sites for each gene, and reducing the overall number of false positives, are all desirable goals.</p> <p>Results</p> <p>With our years of experience in manually curating genomes for the Joint Genome Institute, we developed a new gene prediction algorithm called Prodigal (PROkaryotic DYnamic programming Gene-finding ALgorithm). With Prodigal, we focused specifically on the three goals of improved gene structure prediction, improved translation initiation site recognition, and reduced false positives. We compared the results of Prodigal to existing gene-finding methods to demonstrate that it met each of these objectives.</p> <p>Conclusion</p> <p>We built a fast, lightweight, open source gene prediction program called Prodigal <url>http://compbio.ornl.gov/prodigal/</url>. Prodigal achieved good results compared to existing methods, and we believe it will be a valuable asset to automated microbial annotation pipelines.</p

MetWAMer: eukaryotic translation initiation site prediction

<p>Abstract</p> <p>Background</p> <p>Translation initiation site (TIS) identification is an important aspect of the gene annotation process, requisite for the accurate delineation of protein sequences from transcript data. We have developed the MetWAMer package for TIS prediction in eukaryotic open reading frames of non-viral origin. MetWAMer can be used as a stand-alone, third-party tool for post-processing gene structure annotations generated by external computational programs and/or pipelines, or directly integrated into gene structure prediction software implementations.</p> <p>Results</p> <p>MetWAMer currently implements five distinct methods for TIS prediction, the most accurate of which is a routine that combines weighted, signal-based translation initiation site scores and the contrast in coding potential of sequences flanking TISs using a perceptron. Also, our program implements clustering capabilities through use of the <it>k</it>-medoids algorithm, thereby enabling cluster-specific TIS parameter utilization. In practice, our static weight array matrix-based indexing method for parameter set lookup can be used with good results in data sets exhibiting moderate levels of 5'-complete coverage.</p> <p>Conclusion</p> <p>We demonstrate that improvements in statistically-based models for TIS prediction can be achieved by taking the class of each potential start-methionine into account pending certain testing conditions, and that our perceptron-based model is suitable for the TIS identification task. MetWAMer represents a well-documented, extensible, and freely available software system that can be readily re-trained for differing target applications and/or extended with existing and novel TIS prediction methods, to support further research efforts in this area.</p

Temporary techno-social gatherings? A (hacked) discussion about open practices

This paper is rooted in an experimental inquiry of issue-oriented temporary techno-social gatherings or TTGs, which are typically referred to as hackathons, workshops or pop-ups and employ rapid design and development practices to tackle technical challenges while engaging with social issues. Based on a collaboration between three digital practitioners (a producer, a researcher and a designer), qualitative and creative data was gathered across five different kinds of TTG events in London and in Tartu which were held in partnership with large institutions, including Art:Work at Tate Exchange within Tate Modern, the Mozilla Festival at Ravensbourne College and the 2017 Association of Internet Researchers conference hosted in Tartu. By analysing data using an open and discursive approach manifested in both text and visual formats, we reflect on the dynamic and generative characteristics of TTG gatherings while also arriving at our own conclusions as situated researchers and practitioners who are ourselves engaged in increasingly messy webs where new worlds of theory and practice are built

On the influence of the cosmological constant on gravitational lensing in small systems

The cosmological constant Lambda affects gravitational lensing phenomena. The contribution of Lambda to the observable angular positions of multiple images and to their amplification and time delay is here computed through a study in the weak deflection limit of the equations of motion in the Schwarzschild-de Sitter metric. Due to Lambda the unresolved images are slightly demagnified, the radius of the Einstein ring decreases and the time delay increases. The effect is however negligible for near lenses. In the case of null cosmological constant, we provide some updated results on lensing by a Schwarzschild black hole.Comment: 8 pages, 1 figure; v2: extended discussion on the lens equation, references added, results unchanged, in press on PR

RoboHound:developing sample collection and preconcentration hardware for a remote trace explosives detection system.

The RoboHound{trademark} Project was a three-year, multiphase project at Sandia National Laboratories to build and refine a working prototype trace explosive detection system as a tool for a commercial robot. The RoboHound system was envisioned to be a tool for emergency responders to test suspicious items (i.e., packages or vehicles) for explosives while maintaining a safe distance. The project investigated combining Sandia's expertise in trace explosives detection with a wheeled robotic platform that could be programmed to interrogate suspicious items remotely for the presence of explosives. All of the RoboHound field tests were successful, especially with regards to the ability to collect and detect trace samples of RDX. The project has gone from remote sampling with human intervention to a fully automatic system that requires no human intervention until the robot returns from a sortie. A proposal is being made for additional work leading towards commercialization