Observation of ionization trends in a laboratory photoionized plasma experiment at Z

We report experimental and modeling results for the charge state distribution of laboratory photoionized neon plasmas in the first systematic study over nearly an order of magnitude range of ionization parameter ξ∝F/N_{e}. The range of ξ is achieved by flexibility in the experimental platform to adjust either the x-ray drive flux F at the sample or the electron number density N_{e} or both. Experimental measurements of photoionized plasma conditions over such a range of parameters enable a stringent test of atomic kinetics models used within codes that are applied to photoionized plasmas in the laboratory and astrophysics. From experimental transmission data, ion areal densities are extracted by spectroscopic analysis that is independent of atomic kinetics modeling. The measurements reveal the net result of the competition between photon-driven ionization and electron-driven recombination atomic processes as a function of ξ as it affects the charge state distribution. Results from radiation-hydrodynamics modeling calculations with detailed inline atomic kinetics modeling are compared with the experimental results. There is good agreement in the mean charge and overall qualitative similarities in the trends observed with ξ but significant quantitative differences in the fractional populations of individual ions.

X-ray heating and electron temperature of laboratory photoionized plasmas

We discuss the experimental and modeling results for the x-ray heating and temperature of laboratory photoionized plasmas. A method is used to extract the electron temperature based on the analysis of transmission spectroscopy data that is independent of atomic kinetics modeling. The results emphasized the critical role of x-ray heating and radiation cooling in determining the energy balance of the plasma. They also demonstrated the dramatic impact of photoexcitation on excited-state populations, line emissivity, and radiation cooling. Modeling calculations performed with astrophysical codes significantly overestimated the measured temperature.

A dose and time response Markov model for the in-host dynamics of infection with intracellular bacteria following inhalation: with application to Francisella tularensis

In a novel approach, the standard birth–death process is extended to incorporate a fundamental mechanism undergone by intracellular bacteria, phagocytosis. The model accounts for stochastic interaction between bacteria and cells of the immune system and heterogeneity in susceptibility to infection of individual hosts within a population. Model output is the dose–response relation and the dose-dependent distribution of time until response, where response is the onset of symptoms. The model is thereafter parametrized with respect to the highly virulent Schu S4 strain of Francisella tularensis, in the first such study to consider a biologically plausible mathematical model for early human infection with this bacterium. Results indicate a median infectious dose of about 23 organisms, which is higher than previously thought, and an average incubation period of between 3 and 7 days depending on dose. The distribution of incubation periods is right-skewed up to about 100 organisms and symmetric for larger doses. Moreover, there are some interesting parallels to the hypotheses of some of the classical dose–response models, such as independent action (single-hit model) and individual effective dose (probit model). The findings of this study support experimental evidence and postulations from other investigations that response is, in fact, influenced by both in-host and between-host variability.

A case-association cluster detection and visualisation tool with an application to Legionnaires' disease

Statistical methods used in spatio-temporal surveillance of disease are able to identify abnormal clusters of cases but typically do not provide a measure of the degree of association between one case and another. Such a measure would facilitate the assignment of cases to common groups and be useful in outbreak investigations of diseases that potentially share the same source. This paper presents a model-based approach, which on the basis of available location data, provides a measure of the strength of association between cases in space and time and which is used to designate and visualise the most likely groupings of cases. The method was developed as a prospective surveillance tool to signal potential outbreaks, but it may also be used to explore groupings of cases in outbreak investigations. We demonstrate the method by using a historical case series of Legionnaires' disease amongst residents of England and Wales.

The application of geographic information systems and spatial data during Legionnaires’ disease outbreak responses

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Evidence for two independent associations with type 1 diabetes at the 12q13 locus

Genome-wide association studies have identified associations between type 1 diabetes and single nucleotide polymorphisms (SNPs) at chromosome 12q13, surrounding the gene ERBB3. Our objective was to fine map this region to further localize causative variants. Re-sequencing identified more than 100 putative SNPs in an 80 kb region at 12q13. By genotyping 42 SNPs, spanning approximately 214 kb, in 382 affected sibling pair type 1 diabetes families, we were able to genotype or tag 67 common SNPs (MAF ≥ 0.05) identified from HapMap CEU data and CEU data from the 1000 Genomes Project, plus additional rare coding variants identified from our re-sequencing efforts. Fifteen SNPs provided nominal evidence for association (P≤ 0.05) with type 1 diabetes. The most significant associations were observed with rs2271189 (P = 4.22×10⁻⁵), located in exon 27 of the ERBB3 gene, and an intergenic SNP rs11171747 (P= 1.70×10⁻⁴). Follow-up genotyping of these SNPs in 2 740 multiplex type 1 diabetes families validated these findings.

After analyzing variants spanning more than 200 kb, we have replicated associations from previous GWAS and provide evidence for novel associations with type 1 diabetes. The associations across this region could be entirely accounted for by two common SNPs, rs2271189 and rs11171747.

Data processing of absorption spectra from photoionized plasma experiments at Z

We discuss the processing of x-ray absorption spectra from photoionized plasma experiments at Z. The data was recorded with an imaging spectrometer equipped with two elliptically bent potassium acid phthalate (KAP) crystals. Both time-integrated and time-resolved data were recorded. In both cases, the goal is to obtain the transmission spectra for quantitative analysis of plasma conditions.

Real-time epidemic forecasting for pandemic influenza

The ongoing worldwide spread of the H5N1 influenza virus in birds has increased concerns of a new human influenza pandemic and a number of surveillance initiatives are planned, or are in place, to monitor the impact of a pandemic in near real-time. Using epidemiological data collected during the early stages of an outbreak, we show how the timing of the maximum prevalence of the pandemic wave, along with its amplitude and duration, might be predicted by fitting a mass-action epidemic model to the surveillance data by standard regression analysis. This method is validated by applying the model to routine data collected in the United Kingdom during the different waves of the previous three pandemics. The success of the method in forecasting historical prevalence suggests that such outbreaks conform reasonably well to the theoretical model, a factor which may be exploited in a future pandemic to update ongoing planning and response.