34 research outputs found

    Role of the Two Component Signal Transduction System CpxAR in Conferring Cefepime and Chloramphenicol Resistance in Klebsiella pneumoniae NTUH-K2044

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    Background: Klebsiella pneumoniae is a Gram-negative, non-motile, facultative anaerobe belonging to the Enterobacteriaceae family of the c-Proteobacteria class in the phylum Proteobacteria. Multidrug resistant K. pneumoniae have caused major therapeutic problems worldwide due to emergence of extended-spectrum b-lactamase producing strains. Twocomponent systems serve as a basic stimulus-response coupling mechanism to allow organisms to sense and respond to changes in many different environmental conditions including antibiotic stress. Principal Findings: In the present study, we investigated the role of an uncharacterized cpxAR operon in bacterial physiology and antimicrobial resistance by generating isogenic mutant (DcpxAR) deficient in the CpxA/CpxR component derived from the hyper mucoidal K1 strain K. pneumoniae NTUH-K2044. The behaviour of DcpxAR was determined under hostile conditions, reproducing stresses encountered in the gastrointestinal environment and deletion resulted in higher sensitivity to bile, osmotic and acid stresses. The DcpxAR was more susceptible to b-lactams and chloramphenicol than the wild-type strain, and complementation restored the altered phenotypes. The relative change in expression of acrB, acrD, eefB efflux genes were decreased in cpxAR mutant as evidenced by qRT-PCR. Comparison of outer membrane protein profiles indicated a conspicuous difference in the knock out background. Gel shift assays demonstrated direct binding of CpxR KP to promoter region of ompC KP in a concentration dependent manner

    Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019

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    Five insights from the Global Burden of Disease Study 2019

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    The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3.5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.Peer reviewe

    Performance of the ATLAS muon trigger in pp collisions at [Formula: see text] TeV

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    The performance of the ATLAS muon trigger system is evaluated with proton-proton collision data collected in 2012 at the Large Hadron Collider at a centre-of-mass energy of 8 TeV. It is primarily evaluated using events containing a pair of muons from the decay of [Formula: see text] bosons. The efficiency of the single-muon trigger is measured for muons with transverse momentum [Formula: see text] GeV, with a statistical uncertainty of less than 0.01 % and a systematic uncertainty of 0.6 %. The [Formula: see text] range for efficiency determination is extended by using muons from decays of [Formula: see text] mesons, [Formula: see text] bosons, and top quarks. The muon trigger shows highly uniform and stable performance. The performance is compared to the prediction of a detailed simulation

    Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

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    In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

    Five insights from the Global Burden of Disease Study 2019

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    The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3·5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers
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