Adhesion of Salmonella enterica var Enteritidis strains lacking fimbriae and flagella to rat ileal explants cultured at the air interface or submerged in tissue culture medium

Rat ileal air interface and submerged explant models were developed and used to compare the adhesion of Salmonella enterica var Enteritidis wild-type strains with that of their isogenic single and multiple deletion mutants. The modified strains studied were defective for fimbriae, flagella, motility or chemotaxis and binding was assessed on tissues with and without an intact mucus layer. A multiple afimbriate/aflagellate (fim(-)/fla(-)) strain, a fimbriate but aflagellate (fla(-)) strain and a fimbriate/flagellate but non-motile (mot(-)) strain bound significantly less extensively to the explants than the corresponding wild-type strains. With the submerged explant model this difference was evident in tissues with or without a mucus layer, whereas in the air interface model it was observed only in tissues,vith an intact mucus layer. A smooth swimming chemotaxis-defective (che(-)) strain and single or multiple afimbriate strains bound to explants as well as their corresponding wild-type strain. This suggests that under the present experimental conditions fimbriae were not essential for attachment of S. enterica var Enteritidis to rat ileal explants, However; the possession of active flagella did appear to be an important factor. in enabling salmonellae to penetrate the gastrointestinal mucus layer and attach specifically to epithelial cells.

Virulence in the chick model and stress tolerance of Salmonella enterica serovar Orion var. 15+

Three Salmonella enterica serovar Orion var. 15+ isolates of distinct provenance were tested for survival in various stress assays. All were less able to survive desiccation than a virulent S. Enreritidis strain, with levels of survival similar to a rpoS mutant of the S. Enteritidis strain, whereas one isolate (F3720) was significantly more acid tolerant. The S. Orion var. 15+ isolates were motile by flagellae and elaborated type-1 and curli-like fimbriae; surface organelles that are considered virulence determinants in Salmonella pathogenesis. Each adhered and invaded HEp-2 tissue culture cells with similar proficiency to the S. Enteritidis control but were significantly less virulent than S. En teritidis in the one-day-old and seven-day-old chick model. Given an oral dose of 1 x 10(3) cfu to one-day-old chicken, S. Orion var. 15+ isolates colonised 25% of liver and spleens examined at 24 h whereas S. Enteritidis colonised 100% of organs by the same with the same dose. Given an oral dose of 1 x 10(7) cfu at seven-day old, S. Orion var. 15+ failed to colonise livers and spleens in any bird examined at 24 h whereas S. Enteritidis colonised 50% of organs by the same with the same dose. Based on the number of internal organs colonised, one of the three S. Orion var. 15+ isolates tested (strain F3720) was significantly more invasive than the other two (B1 and B7). Also, strain F3720 was shed less than either B1 or B7 supporting the concept that there may be an inverse relationship between the ability to colonise deep tissues and to persist in the gut. These data are discussed in the light that S. Orion var. 15+ is associated with sporadic outbreaks of human infection rather than epidemics.

Forecasting VaR using analytic higher moments for GARCH processes

It is widely accepted that some of the most accurate Value-at-Risk (VaR) estimates are based on an appropriately specified GARCH process. But when the forecast horizon is greater than the frequency of the GARCH model, such predictions have typically required time-consuming simulations of the aggregated returns distributions. This paper shows that fast, quasi-analytic GARCH VaR calculations can be based on new formulae for the first four moments of aggregated GARCH returns. Our extensive empirical study compares the Cornish–Fisher expansion with the Johnson SU distribution for fitting distributions to analytic moments of normal and Student t, symmetric and asymmetric (GJR) GARCH processes to returns data on different financial assets, for the purpose of deriving accurate GARCH VaR forecasts over multiple horizons and significance levels.

Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model

Operational forecasting centres are currently developing data assimilation systems for coupled atmosphere-ocean models. Strongly coupled assimilation, in which a single assimilation system is applied to a coupled model, presents significant technical and scientific challenges. Hence weakly coupled assimilation systems are being developed as a first step, in which the coupled model is used to compare the current state estimate with observations, but corrections to the atmosphere and ocean initial conditions are then calculated independently. In this paper we provide a comprehensive description of the different coupled assimilation methodologies in the context of four dimensional variational assimilation (4D-Var) and use an idealised framework to assess the expected benefits of moving towards coupled data assimilation. We implement an incremental 4D-Var system within an idealised single column atmosphere-ocean model. The system has the capability to run both strongly and weakly coupled assimilations as well as uncoupled atmosphere or ocean only assimilations, thus allowing a systematic comparison of the different strategies for treating the coupled data assimilation problem. We present results from a series of identical twin experiments devised to investigate the behaviour and sensitivities of the different approaches. Overall, our study demonstrates the potential benefits that may be expected from coupled data assimilation. When compared to uncoupled initialisation, coupled assimilation is able to produce more balanced initial analysis fields, thus reducing initialisation shock and its impact on the subsequent forecast. Single observation experiments demonstrate how coupled assimilation systems are able to pass information between the atmosphere and ocean and therefore use near-surface data to greater effect. We show that much of this benefit may also be gained from a weakly coupled assimilation system, but that this can be sensitive to the parameters used in the assimilation.

Thermal and pressure stability of myrosinase enzymes from black mustard (Brassica nigra L. W.D.J Koch. var. nigra), brown mustard (Brassica juncea L. Czern. var. juncea) and yellow mustard (Sinapsis alba L. Subsp Maire) seeds

This study investigates the effects of temperature and pressure on inactivation of myrosinase extracted from black, brown and yellow mustard seeds. Brown mustard had higher myrosinase activity (2.75 un/mL) than black (1.50 un/mL) and yellow mustard (0.63 un/mL). The extent of enzyme inactivation increased with pressure (600-800 MPa) and temperature (30-70 °C) for all the mustard seeds. However, at combinations of lower pressures (200-400 MPa) and high temperatures (60-80 °C), there was less inactivation. For example, application of 300 MPa and 70 °C for 10 minutes retained 20%, 80% and 65% activity in yellow, black and brown mustard, respectively, whereas the corresponding activity retentions when applying only heat (70 °C, 10min) were 0%, 59% and 35%. Thus, application of moderate pressures (200-400 MPa) can potentially be used to retain myrosinase activity needed for subsequent glucosinolate hydrolysis.

An idealized study of coupled atmosphere-ocean 4D-Var in the presence of model error

Atmosphere only and ocean only variational data assimilation (DA) schemes are able to use window lengths that are optimal for the error growth rate, non-linearity and observation density of the respective systems. Typical window lengths are 6-12 hours for the atmosphere and 2-10 days for the ocean. However, in the implementation of coupled DA schemes it has been necessary to match the window length of the ocean to that of the atmosphere, which may potentially sacrifice the accuracy of the ocean analysis in order to provide a more balanced coupled state. This paper investigates how extending the window length in the presence of model error affects both the analysis of the coupled state and the initialized forecast when using coupled DA with differing degrees of coupling. Results are illustrated using an idealized single column model of the coupled atmosphere-ocean system. It is found that the analysis error from an uncoupled DA scheme can be smaller than that from a coupled analysis at the initial time, due to faster error growth in the coupled system. However, this does not necessarily lead to a more accurate forecast due to imbalances in the coupled state. Instead coupled DA is more able to update the initial state to reduce the impact of the model error on the accuracy of the forecast. The effect of model error is potentially most detrimental in the weakly coupled formulation due to the inconsistency between the coupled model used in the outer loop and uncoupled models used in the inner loop.