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Search Results: 1 - 10 of 465444 matches for " Rebecca A. Hall "
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CO2 Acts as a Signalling Molecule in Populations of the Fungal Pathogen Candida albicans
Rebecca A. Hall,Luisa De Sordi,Donna M. MacCallum,Hüsnü Topal,Rebecca Eaton,James W. Bloor,Gary K. Robinson,Lonny R. Levin,Jochen Buck,Yue Wang,Neil A. R. Gow,Clemens Steegborn,Fritz A. Mühlschlegel
PLOS Pathogens , 2010, DOI: 10.1371/journal.ppat.1001193
Abstract: When colonising host-niches or non-animated medical devices, individual cells of the fungal pathogen Candida albicans expand into significant biomasses. Here we show that within such biomasses, fungal metabolically generated CO2 acts as a communication molecule promoting the switch from yeast to filamentous growth essential for C. albicans pathology. We find that CO2-mediated intra-colony signalling involves the adenylyl cyclase protein (Cyr1p), a multi-sensor recently found to coordinate fungal responses to serum and bacterial peptidoglycan. We further identify Lys 1373 as essential for CO2/bicarbonate regulation of Cyr1p. Disruption of the CO2/bicarbonate receptor-site interferes selectively with C. albicans filamentation within fungal biomasses. Comparisons between the Drosophila melanogaster infection model and the mouse model of disseminated candidiasis, suggest that metabolic CO2 sensing may be important for initial colonisation and epithelial invasion. Our results reveal the existence of a gaseous Candida signalling pathway and its molecular mechanism and provide insights into an evolutionary conserved CO2-signalling system.
Online Optimization in Dynamic Environments
Eric C. Hall,Rebecca M. Willett
Mathematics , 2013,
Abstract: High-velocity streams of high-dimensional data pose significant ``big data'' analysis challenges across a range of applications and settings. Online learning and online convex programming play a significant role in the rapid recovery of important or anomalous information from these large datastreams. While recent advances in online learning have led to novel and rapidly converging algorithms, these methods are unable to adapt to nonstationary environments arising in real-world problems. This paper describes a dynamic mirror descent framework which addresses this challenge, yielding low theoretical regrets bounds and accurate, adaptive, and computationally efficient algorithms which are applicable to broad classes of problems. The methods are capable of learning and adapting to an underlying and possibly time-varying dynamical model. Empirical results in the context of dynamic texture analysis, sequential compressed sensing of a dynamic scene, and tracking self-exciting point processes support the core theoretical findings.
Tracking Dynamic Point Processes on Networks
Eric C. Hall,Rebecca M. Willett
Computer Science , 2014,
Abstract: Cascading chains of events are a salient feature of many real-world social, biological, and financial networks. In social networks, social reciprocity accounts for retaliations in gang interactions, proxy wars in nation-state conflicts, or Internet memes shared via social media. Neuron spikes stimulate or inhibit spike activity in other neurons. Stock market shocks can trigger a contagion of volatility throughout a financial network. In these and other examples, only individual events associated with network nodes are observed, usually without knowledge of the underlying dynamic relationships between nodes. This paper addresses the challenge of tracking how events within such networks stimulate or influence future events. The proposed approach is an online learning framework well-suited to streaming data, using a multivariate Hawkes point process model to encapsulate autoregressive features of observed events within the social network. Recent work on online learning in dynamic environments is leveraged not only to exploit the dynamics within the underlying network, but also to track that network structure as it evolves. Regret bounds and experimental results demonstrate that the proposed method performs nearly as well as an oracle or batch algorithm.
Dynamical Models and Tracking Regret in Online Convex Programming
Eric C. Hall,Rebecca M. Willett
Computer Science , 2013,
Abstract: This paper describes a new online convex optimization method which incorporates a family of candidate dynamical models and establishes novel tracking regret bounds that scale with the comparator's deviation from the best dynamical model in this family. Previous online optimization methods are designed to have a total accumulated loss comparable to that of the best comparator sequence, and existing tracking or shifting regret bounds scale with the overall variation of the comparator sequence. In many practical scenarios, however, the environment is nonstationary and comparator sequences with small variation are quite weak, resulting in large losses. The proposed Dynamic Mirror Descent method, in contrast, can yield low regret relative to highly variable comparator sequences by both tracking the best dynamical model and forming predictions based on that model. This concept is demonstrated empirically in the context of sequential compressive observations of a dynamic scene and tracking a dynamic social network.
The Mnn2 Mannosyltransferase Family Modulates Mannoprotein Fibril Length, Immune Recognition and Virulence of Candida albicans
Rebecca A. Hall,Steven Bates,Megan D. Lenardon,Donna M. MacCallum,Jeanette Wagener,Douglas W. Lowman,Michael D. Kruppa,David L. Williams,Frank C. Odds,Alistair J. P. Brown,Neil A. R. Gow
PLOS Pathogens , 2013, DOI: 10.1371/journal.ppat.1003276
Abstract: The fungal cell wall is the first point of interaction between an invading fungal pathogen and the host immune system. The outer layer of the cell wall is comprised of GPI anchored proteins, which are post-translationally modified by both N- and O-linked glycans. These glycans are important pathogen associated molecular patterns (PAMPs) recognised by the innate immune system. Glycan synthesis is mediated by a series of glycosyl transferases, located in the endoplasmic reticulum and Golgi apparatus. Mnn2 is responsible for the addition of the initial α1,2-mannose residue onto the α1,6-mannose backbone, forming the N-mannan outer chain branches. In Candida albicans, the MNN2 gene family is comprised of six members (MNN2, MNN21, MNN22, MNN23, MNN24 and MNN26). Using a series of single, double, triple, quintuple and sextuple mutants, we show, for the first time, that addition of α1,2-mannose is required for stabilisation of the α1,6-mannose backbone and hence regulates mannan fibril length. Sequential deletion of members of the MNN2 gene family resulted in the synthesis of lower molecular weight, less complex and more uniform N-glycans, with the sextuple mutant displaying only un-substituted α1,6-mannose. TEM images confirmed that the sextuple mutant was completely devoid of the outer mannan fibril layer, while deletion of two MNN2 orthologues resulted in short mannan fibrils. These changes in cell wall architecture correlated with decreased proinflammatory cytokine induction from monocytes and a decrease in fungal virulence in two animal models. Therefore, α1,2-mannose of N-mannan is important for both immune recognition and virulence of C. albicans.
Identification of Novel High-Frequency DNA Methylation Changes in Breast Cancer
Jared M. Ordway, Muhammad A. Budiman, Yulia Korshunova, Rebecca K. Maloney, Joseph A. Bedell, Robert W. Citek, Blaire Bacher, Seth Peterson, Tracy Rohlfing, Jacqueline Hall, Robert Brown, Nathan Lakey, Rebecca W. Doerge, Robert A. Martienssen, Jorge Leon, John D. McPherson, Jeffrey A. Jeddeloh
PLOS ONE , 2007, DOI: 10.1371/journal.pone.0001314
Abstract: Recent data have revealed that epigenetic alterations, including DNA methylation and chromatin structure changes, are among the earliest molecular abnormalities to occur during tumorigenesis. The inherent thermodynamic stability of cytosine methylation and the apparent high specificity of the alterations for disease may accelerate the development of powerful molecular diagnostics for cancer. We report a genome-wide analysis of DNA methylation alterations in breast cancer. The approach efficiently identified a large collection of novel differentially DNA methylated loci (~200), a subset of which was independently validated across a panel of over 230 clinical samples. The differential cytosine methylation events were independent of patient age, tumor stage, estrogen receptor status or family history of breast cancer. The power of the global approach for discovery is underscored by the identification of a single differentially methylated locus, associated with the GHSR gene, capable of distinguishing infiltrating ductal breast carcinoma from normal and benign breast tissues with a sensitivity and specificity of 90% and 96%, respectively. Notably, the frequency of these molecular abnormalities in breast tumors substantially exceeds the frequency of any other single genetic or epigenetic change reported to date. The discovery of over 50 novel DNA methylation-based biomarkers of breast cancer may provide new routes for development of DNA methylation-based diagnostics and prognostics, as well as reveal epigenetically regulated mechanism involved in breast tumorigenesis.
The Global Epidemiology and Contribution of Cannabis Use and Dependence to the Global Burden of Disease: Results from the GBD 2010 Study
Louisa Degenhardt, Alize J. Ferrari, Bianca Calabria, Wayne D. Hall, Rosana E. Norman, John McGrath, Abraham D. Flaxman, Rebecca E. Engell, Greg D. Freedman, Harvey A. Whiteford, Theo Vos
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0076635
Abstract: Aims Estimate the prevalence of cannabis dependence and its contribution to the global burden of disease. Methods Systematic reviews of epidemiological data on cannabis dependence (1990-2008) were conducted in line with PRISMA and meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Culling and data extraction followed protocols, with cross-checking and consistency checks. DisMod-MR, the latest version of generic disease modelling system, redesigned as a Bayesian meta-regression tool, imputed prevalence by age, year and sex for 187 countries and 21 regions. The disability weight associated with cannabis dependence was estimated through population surveys and multiplied by prevalence data to calculate the years of life lived with disability (YLDs) and disability-adjusted life years (DALYs). YLDs and DALYs attributed to regular cannabis use as a risk factor for schizophrenia were also estimated. Results There were an estimated 13.1 million cannabis dependent people globally in 2010 (point prevalence0.19% (95% uncertainty: 0.17-0.21%)). Prevalence peaked between 20-24 yrs, was higher in males (0.23% (0.2-0.27%)) than females (0.14% (0.12-0.16%)) and in high income regions. Cannabis dependence accounted for 2 million DALYs globally (0.08%; 0.05-0.12%) in 2010; a 22% increase in crude DALYs since 1990 largely due to population growth. Countries with statistically higher age-standardised DALY rates included the United States, Canada, Australia, New Zealand and Western European countries such as the United Kingdom; those with lower DALY rates were from Sub-Saharan Africa-West and Latin America. Regular cannabis use as a risk factor for schizophrenia accounted for an estimated 7,000 DALYs globally. Conclusion Cannabis dependence is a disorder primarily experienced by young adults, especially in higher income countries. It has not been shown to increase mortality as opioid and other forms of illicit drug dependence do. Our estimates suggest that cannabis use as a risk factor for schizophrenia is not a major contributor to population-level disease burden.
An Explosive Epidemic of DENV-3 in Cairns, Australia
Scott A. Ritchie, Alyssa T. Pyke, Sonja Hall-Mendelin, Andrew Day, Christopher N. Mores, Rebecca C. Christofferson, Duane J. Gubler, Shannon N. Bennett, Andrew F. van den Hurk
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0068137
Abstract: From November 2008-May 2009 Cairns Queensland Australia was struck by an explosive epidemic of DENV-3 that exceeded the capacity of highly skilled dengue control team to control it. We describe the environmental, virological and entomological factors associated with this outbreak to better understand the circumstances leading to its occurrence. Patient interviews, serological results and viral sequencing strongly suggest that the imported index case was infected in Kalimantan, Indonesia. A delay in notification of 27 days from importation of the index case until Queensland Health was notified of dengue transmission allowed the virus to amplify and spread unchecked through November 2008. Unseasonably warm weather, with daily mean temperatures exceeding 30°C, occurred in late November and would have shortened the extrinsic incubation period of the virus and enhanced transmission. Analysis of case movements early in the outbreak indicated that the total incubation period was as low as 9–11 days. This was supported by laboratory vector competence studies that found transmission by Aedes aegypti occurred within 5 days post exposure at 28°C. Effective vector competence rates calculated from these transmission studies indicate that early transmission contributed to the explosive dengue transmission observed in this outbreak. Collections from BG sentinel traps and double sticky ovitraps showed that large populations of the vector Ae. aegypti occurred in the transmission areas from November – December 2008. Finally, the seasonal movement of people around the Christmas holiday season enhanced the spread of DENV-3. These results suggest that a strain of DENV-3 with an unusually rapid transmission cycle was able to outpace vector control efforts, especially those reliant upon delayed action control such as lethal ovitraps.
Support for Altruistic Behavior in Rats  [PDF]
Shayna A. Wrighten, Chelsea R. Hall
Open Journal of Social Sciences (JSS) , 2016, DOI: 10.4236/jss.2016.412009
Abstract: Evidence for altruistic behaviors in rats has been continually building over many years, with a large surge in the past 10 years. Many researchers have posited that rats have the cognitive capabilities to engage in these altruistic behaviors that were at one time only attributed to species that are more complex. The results of many of the studies on altruistic behaviors in rats show parallels with non-human primate studies suggesting that what has been observed in rats is indeed altruism as it has been defined in primates. Research focused on rat altruism has provided evidence that these behaviors are influenced by familiarity, similar to findings among primates. Other evidence for altruistic behavior in rats is apparent in their ability to apply a cost-benefit analysis when an opportunity to provide help is presented. There is also evidence that rats rely on previous experiences and predictions of future behaviors of others to make judgments when engaging in altruistic behaviors. Studies have also shown that rats exhibit these altruistic behaviors without the presence of a tangible reward, a primary component in the definition of altruism. The findings presented and the parallels with non-human primate studies provide good evidence that rats are capable of engaging in altruistic behaviors, and that rats may be good candidates for an alternative animal model for further studying altruism. Having rats as a valid model for the study of altruism opens the door to study facets of this behavior that otherwise would not be able to be studied. Because of the important contribution of altruism to social interactions, better understanding of this behavior will hopefully aid in positively influencing social societies such as those lived in by humans and other primates.
How Staff RNs Perceive Nurse Manager Roles  [PDF]
Rebecca A. Feather, Patricia R. Ebright
Open Journal of Leadership (OJL) , 2013, DOI: 10.4236/ojl.2013.23008

Purpose: Nurse managers’ behaviors and job satisfaction are commonly addressed in the literature; however, registered nurse perceptions of nurse manager behaviors provide a unique perspective that may inform future strategies designed to enhance RN job satisfaction. The purpose of this study was to assess the perceptions of registered nurses that were explored through focus groups to learn the behaviors of nurse managers that most influence registered nurse’s job satisfaction. Methods: Five focus groups were conducted through semi-structured interviews of a total of 28 RNs to provide data that were coded through qualitative content analysis for themes. Findings: The findings provide nurse managers with data related to the perceptions of RNs and the behaviors of managers that influence job satisfaction. In relation to the focus group’s discussions, a disconnection was identified between the perceptions of the RNs regarding their actual work issues and the nurse manager’s role on the hospital unit. There were five themes that emerged in the category of RNs perceived disconnect between work issues and the manager’s role. The daily role, manager meeting time, visibility of nurse managers, no longer a nurse, and RN preferences for the nurse manager role. Conclusion: Findings support past research in relation to the perceptions of RNs wanting to be respected, included in communication, and the need to feel cared for by nurse managers to have higher levels of job satisfaction. This study provided findings important to staff nurses, nurse managers and administration. There is a need for administrator support for nurse manager’s ability to spend more time on the unit with RNs to attend to direct care provider relationships and team building through communication with staff is a recommended approach for decreasing the disconnect between RNs and nurse managers.

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