A systematic analysis of the role of GGDEF-EAL domain proteins in virulence and motility in Xanthomonas oryzae pv. oryzicola

The second messenger c-di-GMP is implicated in regulation of various aspects of the lifestyles and virulence of Gram-negative bacteria. Cyclic di-GMP is formed by diguanylate cyclases with a GGDEF domain and degraded by phosphodiesterases with either an EAL or HD-GYP domain. Proteins with tandem GGDEF-EAL domains occur in many bacteria, where they may be involved in c-di-GMP turnover or act as enzymatically-inactive c-di-GMP effectors. Here, we report a systematic study of the regulatory action of the eleven GGDEF-EAL proteins in Xanthomonas oryzae pv. oryzicola, an important rice pathogen causing bacterial leaf streak. Mutational analysis revealed that XOC_2335 and XOC_2393 positively regulate bacterial swimming motility, while XOC_2102, XOC_2393 and XOC_4190 negatively control sliding motility. The ΔXOC_2335/XOC_2393 mutant that had a higher intracellular c-di-GMP level than the wild type and the ΔXOC_4190 mutant exhibited reduced virulence to rice after pressure inoculation. In vitro purified XOC_4190 and XOC_2102 have little or no diguanylate cyclase or phosphodiesterase activity, which is consistent with unaltered c-di-GMP concentration in ΔXOC_4190. Nevertheless, both proteins can bind to c-di-GMP with high affinity, indicating a potential role as c-di-GMP effectors. Overall our findings advance understanding of c-di-GMP signaling and its links to virulence in an important rice pathogen.

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013 : a systematic analysis for the Global Burden of Disease Study 2013

Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015 : a systematic analysis for the Global Burden of Disease Study 2015

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015 : a systematic analysis for the Global Burden of Disease Study 2015

Global, regional, national, and selected subnational levels of stillbirths, neonatal, infant, and under-5 mortality, 1980–2015 : a systematic analysis for the Global Burden of Disease Study 2015

Global, regional, and national comparative risk assessment of 79 behavioral, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015 : a systematic analysis for the Global Burden of Disease Study 2015

Global, regional, and national levels of maternal mortality,1990–2015 : a systematic analysis for the Global Burden of Disease Study 2015

Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990–2015 : a systematic analysis for the Global Burden of Disease Study 2015

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

Party competition in regional elections: a framework for analysis

Whilst scholars have long recognised that processes of decentralisation create new regional arenas where distinct patterns of party competition are likely to emerge, there has been little systematic analysis of the dynamics of such competition. This working paper thus proposes a framework for analysing party competition between regional branches of state-wide parties, and autonomist parties, in regional arenas. Firstly, the different strategies political parties may adopt in response to their perceptions of voter preferences and to the strategies pursued by their competitors are identified. Secondly, different factors that impact on parties' strategic choices, and which may constrain a party's ability to select electorally optimal strategies in a given political context, are proposed.

Centralized Motion Control of a Linear Tooth Belt Drive: Analysis of the Performance and Limitations

A centralized robust position control for an electrical driven tooth belt drive is designed in this doctoral thesis. Both a cascaded control structure and a PID based position controller are discussed. The performance and the limitations of the system are analyzed and design principles for the mechanical structure and the control design are given. These design principles are also suitable for most of the motion control applications, where mechanical resonance frequencies and control loop delays are present. One of the major challenges in the design of a controller for machinery applications is that the values of the parameters in the system model (parameter uncertainty) or the system model it self (non-parametric uncertainty) are seldom known accurately in advance. In this thesis a systematic analysis of the parameter uncertainty of the linear tooth beltdrive model is presented and the effect of the variation of a single parameter on the performance of the total system is shown. The total variation of the model parameters is taken into account in the control design phase using a Quantitative Feedback Theory (QFT). The thesis also introduces a new method to analyze reference feedforward controllers applying the QFT. The performance of the designed controllers is verified by experimentalmeasurements. The measurements confirm the control design principles that are given in this thesis.

Approaches to Supply Chain Risk Management: Identification, Analysis and Control

Supply chain risk management has emerged as an increasingly important issue in logistics as disruptions in the supply chain have become critical issues for many companies. The scientific literature on the subject is developing and in many respects the understanding of it is still in its infancy. Thus, there is a need for more information in order for scholars and practitioners to understand the causalities and interrelations that characterise the phenomenon. The aim of this dissertation is to narrow this gap by exploring key aspects of supply chain risk management through two maritime supply chains in the immediate region of the Gulf of Finland. The study contributes to the field in three different ways. Firstly, it facilitates the identification of risks on different levels of the supply chain through a systematic analysis of the processes and actors, and of the cognitive barriers that limit the actors’ visibility and their understanding of the operations and the risks involved. There is a clear need to increase collaboration and information exchange in order to improve visibility in the chain. Risk management should be a collaborative effort among the individual actors, aimed at obtaining a holistic picture. Secondly, the study contributes to the literature on risk analysis through the use of systemic frameworks that illustrate the causalities and linkages in the system, thereby making it easier to perceive the vulnerabilities. Thirdly, the study enhances current knowledge of risk control in identifying actor roles, risk visibility and risk controllability as being among the key factors determining risk-management effectiveness against supply-chain vulnerability. This dissertation is divided into two parts. The first part gives a general overview of the relevant literature, the research design and the conclusions of the study, and the second part comprises six research publications. Case-study methodology with systematic combining approach is used, where in-depth interviews, questionnaires and expert panel sessions are the main data collection methods. The study illustrates the current state of risk management in multimodal maritime supply chains, and develops frameworks for further analysis. The results imply that there are major differences between organizations in their ability to execute supply chain risk management. Further collaboration should be considered in order to facilitate the development of systematic and effective management processes.

Analysis of wheat SAGE tags reveals evidence for widespread antisense transcription

BACKGROUND: Serial Analysis of Gene Expression (SAGE) is a powerful tool for genome-wide transcription studies. Unlike microarrays, it has the ability to detect novel forms of RNA such as alternatively spliced and antisense transcripts, without the need for prior knowledge of their existence. One limitation of using SAGE on an organism with a complex genome and lacking detailed sequence information, such as the hexaploid bread wheat Triticum aestivum, is accurate annotation of the tags generated. Without accurate annotation it is impossible to fully understand the dynamic processes involved in such complex polyploid organisms. Hence we have developed and utilised novel procedures to characterise, in detail, SAGE tags generated from the whole grain transcriptome of hexaploid wheat. RESULTS: Examination of 71,930 Long SAGE tags generated from six libraries derived from two wheat genotypes grown under two different conditions suggested that SAGE is a reliable and reproducible technique for use in studying the hexaploid wheat transcriptome. However, our results also showed that in poorly annotated and/or poorly sequenced genomes, such as hexaploid wheat, considerably more information can be extracted from SAGE data by carrying out a systematic analysis of both perfect and "fuzzy" (partially matched) tags. This detailed analysis of the SAGE data shows first that while there is evidence of alternative polyadenylation this appears to occur exclusively within the 3' untranslated regions. Secondly, we found no strong evidence for widespread alternative splicing in the developing wheat grain transcriptome. However, analysis of our SAGE data shows that antisense transcripts are probably widespread within the transcriptome and appear to be derived from numerous locations within the genome. Examination of antisense transcripts showing sequence similarity to the Puroindoline a and Puroindoline b genes suggests that such antisense transcripts might have a role in the regulation of gene expression. CONCLUSION: Our results indicate that the detailed analysis of transcriptome data, such as SAGE tags, is essential to understand fully the factors that regulate gene expression and that such analysis of the wheat grain transcriptome reveals that antisense transcripts maybe widespread and hence probably play a significant role in the regulation of gene expression during grain development.

Targeting medication non-adherence behavior in selected autoimmune diseases: a systematic approach to digital health program development

Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns.