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Search Results: 1 - 10 of 200839 matches for " Johnna P. Fay "
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Seasonal Levels of the Vibrio Predator Bacteriovorax in Atlantic, Pacific, and Gulf Coast Seawater
Gary P. Richards,Michael A. Watson,E. Fidelma Boyd,William Burkhardt III,Ronald Lau,Joseph Uknalis,Johnna P. Fay
International Journal of Microbiology , 2013, DOI: 10.1155/2013/375371
Abstract: Bacteriovorax were quantified in US Atlantic, Gulf, and Pacific seawater to determine baseline levels of these predatory bacteria and possible seasonal fluctuations in levels. Surface seawater was analyzed monthly for 1 year from Kailua-Kona, Hawaii; the Gulf Coast of Alabama; and four sites along the Delaware Bay. Screening for Bacteriovorax was performed on lawns of V. parahaemolyticus host cells. Direct testing of 7.5?mL portions of seawater from the Atlantic, Pacific, and Gulf coasts gave mean annual counts ≤12.2 PFU. Spikes in counts were observed at 3 out of 4 sites along the Delaware Bay 1 week after Hurricane Sandy. A comparison of summer versus winter counts showed significantly more Bacteriovorax ( ) in the Delaware Bay during the summer and significantly more ( ) in the Gulf during the winter, but no significant seasonal differences ( ) for Hawaiian seawater. Bacteriovorax counts only correlated with seawater salinity and temperature at one Delaware site ( and , resp.). There was a relatively strong negative correlation between temperature and Bacteriovorax levels ( ) for Gulf seawater. Selected isolates were sequenced and identified by phylogenetic analysis as Bacteriovorax clusters IX, X, XI, and XII. 1. Introduction Vibrio parahaemolyticus and Vibrio vulnificus are important foodborne pathogens associated with the consumption of fish and shellfish, especially oysters, which have long been known to bioconcentrate vibrios within their edible tissues [1, 2]. Vibrio vulnificus also causes life-threatening illness from wound infections acquired in the marine environment [3]. Pathogenic vibrios show seasonal predilection in seawater and shellfish, with high counts during warmer months and low to negligible counts during the colder months [2, 4, 5]. Recently, we showed that naturally occurring Bdellovibrio and like organisms (BALOs) from coastal seawater significantly reduced the levels of V. parahaemolyticus and V. vulnificus in seawater and V. parahaemolyticus in seawater and oysters [6]. Among the BALOs are marine and terrestrial forms, with the marine forms associated with Bacteriovorax, which are exclusively saltwater predators [7, 8]. Bacteriovorax have shown preferential predation toward V. parahaemolyticus when compared to a broad range of potential host bacteria [9–12]. This suggests that Bacteriovorax may invade and kill V. parahaemolyticus in seawater more efficiently than other bacterial pathogens. The life cycle of Bacteriovorax and other BALOs usually involve intracellular invasion of and replication within a host cell, although
Estimating age conditional probability of developing disease from surveillance data
Michael P Fay
Population Health Metrics , 2004, DOI: 10.1186/1478-7954-2-6
Abstract: Fay, Pfeiffer, Cronin, Le, and Feuer [1] showed how to calculate the age-conditional probabilities of developing a disease (ACPDvD) from registry data. Throughout this paper we use "cancer" as our disease of interest, but the method applies to specific types of cancer as well as other diseases where information is collected by population based surveillance methods. Fay et al [1] provided a formula (see equation 1 below) to calculate ACPDvD after inputing the rate function by age of (1) first incidence of cancer per person-years alive, (2) death from cancer per person-years alive, and (3) death from other causes per person-years alive. Fay et al [1] used a simple piecewise constant model for the three rate functions, which have constant rates within each age group.Here we detail two more complicated models for the rates. The first model is a segmented regression model or joinpoint model for the rates, where the rate function is a series of linear functions that join at the mid-points of the age groups, and the rate function is constant before the first mid-point and after the last "mid-point" (because the last interval goes to infinity, the last "mid-point" is not really a mid-point at all, see below). We will call this model the MAJ (mid-age group joinpoint) model for the rates. In Figure 1 we show how both the piecewise constant model and the mid-age group joinpoint model apply to all invasive cancer incidence from the Surveillance Epidemiology and End Results (SEER) program of the U.S. National Cancer Institute in 1998–2000. Figure 1 uses the SEER 12 registries which cover about 14 percent of the U.S. population, covering 5 states (Connecticut, Hawaii, Iowa, New Mexico, Utah), 6 metropolitan areas (Atlanta, Detroit, Los Angeles, San Francisco-Oakland, San Jose-Monterey, Seattle-Puget Sound) and the Alaska Native Registry (see [2]). Similar graphs showing the MAJ model can be made for the other rates required in the calculations, death from cancer and death from ot
Linking inflammation and thrombosis: Role of C-reactive protein
William P Fay
World Journal of Cardiology , 2010,
Abstract: C-reactive protein (CRP) is a biomarker of inflammation. Increased plasma levels of CRP are associated with an increased risk of myocardial infarction. However, the correlation between plasma CRP concentration and atherosclerotic plaque burden is poor. Based on these observations, it has been hypothesized that CRP increases the risk of myocardial infarction by promoting thrombosis. This article reviews available data that link enhanced CRP expression to increased risk of thrombosis, with a focus on the effects of CRP on hemostasis, platelet function, and fibrinolysis. Overall, the available data support the hypothesis that CRP is an important mechanistic link between inflammation
Human Immunity and the Design of Multi-Component, Single Target Vaccines
Allan Saul, Michael P. Fay
PLOS ONE , 2007, DOI: 10.1371/journal.pone.0000850
Abstract: Background Inclusion of multiple immunogens to target a single organism is a strategy being pursued for many experimental vaccines, especially where it is difficult to generate a strongly protective response from a single immunogen.?Although there are many human vaccines that contain multiple defined immunogens, in almost every case each component targets a different pathogen. As a consequence, there is little practical experience for deciding where the increased complexity of vaccines with multiple defined immunogens vaccines targeting single pathogens will be justifiable. Methodology/Principal Findings A mathematical model, with immunogenicity parameters derived from a database of human responses to established vaccines, was used to predict the increase in the efficacy and the proportion of the population protected resulting from addition of further immunogens. The gains depended on the relative protection and the range of responses in the population to each immunogen and also to the correlation of the responses between immunogens. In most scenarios modeled, the gain in overall efficacy obtained by adding more immunogens was comparable to gains obtained from a single immunogen through the use of better formulations or adjuvants. Multi-component single target vaccines were more effective at decreasing the proportion of poor responders than increasing the overall efficacy of the vaccine in a population. Conclusions/Significance Inclusion of limited number of antigens in a vaccine aimed at targeting a single organism will increase efficacy, but the gains are relatively modest and for a practical vaccine there are constraints that are likely to limit multi-component single target vaccines to a small number of key antigens. The model predicts that this type of vaccine will be most useful where the critical issue is the reduction in proportion of poor responders.
Wilcoxon-Mann-Whitney or t-test? On assumptions for hypothesis tests and multiple interpretations of decision rules
Michael P. Fay,Michael A. Proschan
Statistics Surveys , 2010,
Abstract: In a mathematical approach to hypothesis tests, we start with a clearly defined set of hypotheses and choose the test with the best properties for those hypotheses. In practice, we often start with less precise hypotheses. For example, often a researcher wants to know which of two groups generally has the larger responses, and either a t-test or a Wilcoxon-Mann-Whitney (WMW) test could be acceptable. Although both t-tests and WMW tests are usually associated with quite different hypotheses, the decision rule and p-value from either test could be associated with many different sets of assumptions, which we call perspectives. It is useful to have many of the different perspectives to which a decision rule may be applied collected in one place, since each perspective allows a different interpretation of the associated p-value. Here we collect many such perspectives for the two-sample t-test, the WMW test and other related tests. We discuss validity and consistency under each perspective and discuss recommendations between the tests in light of these many different perspectives. Finally, we briefly discuss a decision rule for testing genetic neutrality where knowledge of the many perspectives is vital to the proper interpretation of the decision rule.
Exact and Asymptotic Weighted Logrank Tests for Interval Censored Data: The interval R Package
Michael P. Fay,Pamela A. Shaw
Journal of Statistical Software , 2010,
Abstract: For right-censored data perhaps the most commonly used tests are weighted logrank tests, such as the logrank and Wilcoxon-type tests. In this paper we review several generalizations of those weighted logrank tests to interval-censored data and present an R package, interval, to implement many of them. The interval package depends on the perm package, also presented here, which performs exact and asymptotic linear permutation tests. The perm package performs many of the tests included in the already available coin package, and provides an independent validation of coin. We review analysis methods for interval-censored data, and we describe and show how to use the interval and perm packages.
Precise polynomial heuristic for an NP-complete problem
P. M. Duxbury,C. W. Fay IV
Physics , 2003,
Abstract: We introduce a simple, efficient and precise polynomial heuristic for a key NP complete problem, minimum vertex cover. Our method is iterative and operates in probability space. Once a stable probability solution is found we find the true combinatorial solution from the probabilities. For system sizes which are amenable to exact solution by conventional means, we find a correct minimum vertex cover for all cases which we have tested, which include random graphs and diluted triangular lattices of up to 100 sites. We present precise data for minimum vertex cover on graphs of up to 50,000 sites. Extensions of the method to hard core lattices gases and other NP problems are discussed.
Pair Creation of Dilaton Black Holes
Fay Dowker,Jerome P. Gauntlett,David A. Kastor,Jennie Traschen
Physics , 1993, DOI: 10.1103/PhysRevD.49.2909
Abstract: We consider dilaton gravity theories in four spacetime dimensions parametrised by a constant $a$, which controls the dilaton coupling, and construct new exact solutions. We first generalise the C-metric of Einstein-Maxwell theory ($a=0$) to solutions corresponding to oppositely charged dilaton black holes undergoing uniform acceleration for general $a$. We next develop a solution generating technique which allows us to ``embed" the dilaton C-metrics in magnetic dilaton Melvin backgrounds, thus generalising the Ernst metric of Einstein-Maxwell theory. By adjusting the parameters appropriately, it is possible to eliminate the nodal singularities of the dilaton C-metrics. For $a<1$ (but not for $a\ge 1$), it is possible to further restrict the parameters so that the dilaton Ernst solutions have a smooth euclidean section with topology $S^2\times S^2-{\rm\{pt\}}$, corresponding to instantons describing the pair production of dilaton black holes in a magnetic field. A different restriction on the parameters leads to smooth instantons for all values of $a$ with topology $S^2\times \R^2$.
Self heating and nonlinear current-voltage characteristics in bilayer graphene
J. K. Viljas,A. Fay,M. Wiesner,P. J. Hakonen
Physics , 2011, DOI: 10.1103/PhysRevB.83.205421
Abstract: We demonstrate by experiments and numerical simulations that the low-temperature current-voltage characteristics in diffusive bilayer graphene (BLG) exhibit a strong superlinearity at finite bias voltages. The superlinearity is weakly dependent on doping and on the length of the graphene sample. This effect can be understood as a result of Joule heating. It is stronger in BLG than in monolayer graphene (MLG), since the conductivity of BLG is more sensitive to temperature due to the higher density of electronic states at the Dirac point.
Decoherence processes in a current biased dc SQUID
J. Claudon,A. Fay,L. P. Lévy,O. Buisson
Physics , 2006, DOI: 10.1103/PhysRevB.73.180502
Abstract: A current bias dc SQUID behaves as an anharmonic quantum oscillator controlled by a bias current and an applied magnetic flux. We consider here its two level limit consisting of the two lower energy states $| 0 \right>$ and $| 1 \right>$. We have measured energy relaxation times and microwave absorption for different bias currents and fluxes in the low microwave power limit. Decoherence times are extracted. The low frequency flux and current noise have been measured independently by analyzing the probability of current switching from the superconducting to the finite voltage state, as a function of applied flux. The high frequency part of the current noise is derived from the electromagnetic environment of the circuit. The decoherence of this quantum circuit can be fully accounted by these current and flux noise sources.
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