Chemical characterisation and determination of sensory attributes of hydrolysates produced by enzymatic hydrolysis of whey proteins following a novel integrative process

The overall aim of this work was to characterize the major angiotensin converting enzyme (ACE) inhibitory peptides produced by enzymatic hydrolysis of whey proteins, through the application of a novel integrative process. This process consisted of the combination of adsorption and microfiltration within a stirred cell unit for the selective immobilization of β-lactoglobulin and casein derived peptides (CDP) from whey. The adsorbed proteins were hydrolyzed in-situ which resulted in the separation of peptide products from the substrate and fractionation of peptides. Two different hydrolysates were produced: (i) from CDP (IC50 =287μg/mL) and (ii) from β-lactoglobulin (IC50=128μg/mL). IC50 is the concentration of inhibitor needed to inhibit ACE by half. The well known antihypertensive peptide IPP and several novel peptides that have structural similarities with reported ACE inhibitory peptides were identified and characterized in both hydrolysates. Furthermore, the hydrolysates were assessed for bitterness. No significant difference was found between the control (milk with no hydrolysate) and hydrolysate samples at different concentrations (at, below and above the IC50).

Characterisation of connective tissue from the hypertrophic skeletal muscle of myostatin null mice

Myostatin is a potent inhibitor of muscle development. Genetic deletion of myostatin in mice results in muscle mass increase, with muscles often weighing three times their normal values. Contracting muscle transfers tension to skeletal elements through an elaborate connective tissue network. Therefore, the connective tissue of skeletal muscle is an integral component of the contractile apparatus. Here we examine the connective tissue architecture in myostatin null muscle. We show that the hypertrophic muscle has decreased connective tissue content compared with wild-type muscle. Secondly, we show that the hypertrophic muscle fails to show the normal increase in muscle connective tissue content during ageing. Therefore, genetic deletion of myostatin results in an increase in contractile elements but a decrease in connective tissue content. We propose a model based on the contractile profile of muscle fibres that reconciles this apparent incompatible tissue composition phenotype.

Integration of a 3D Variational data assimilation scheme with a coastal area morphodynamic model of Morecambe Bay

This paper describes the implementation of a 3D variational (3D-Var) data assimilation scheme for a morphodynamic model applied to Morecambe Bay, UK. A simple decoupled hydrodynamic and sediment transport model is combined with a data assimilation scheme to investigate the ability of such methods to improve the accuracy of the predicted bathymetry. The inverse forecast error covariance matrix is modelled using a Laplacian approximation which is calibrated for the length scale parameter required. Calibration is also performed for the Soulsby-van Rijn sediment transport equations. The data used for assimilation purposes comprises waterlines derived from SAR imagery covering the entire period of the model run, and swath bathymetry data collected by a ship-borne survey for one date towards the end of the model run. A LiDAR survey of the entire bay carried out in November 2005 is used for validation purposes. The comparison of the predictive ability of the model alone with the model-forecast-assimilation system demonstrates that using data assimilation significantly improves the forecast skill. An investigation of the assimilation of the swath bathymetry as well as the waterlines demonstrates that the overall improvement is initially large, but decreases over time as the bathymetry evolves away from that observed by the survey. The result of combining the calibration runs into a pseudo-ensemble provides a higher skill score than for a single optimized model run. A brief comparison of the Optimal Interpolation assimilation method with the 3D-Var method shows that the two schemes give similar results.

Phenotype MicroArray (TM) in the metabolic characterisation of Salmonella serotypes Agona, Enteritidis, Give, Hvittingfoss, Infantis, Newport and Typhimurium

The Phenotype MicroArray (TM) (PM) technology was used to study the metabolic characteristics of 29 Salmonella strains belonging to seven serotypes of S. enterica spp. enterica. Strains of serotypes Typhimurium (six strains among definite phage types DTs 1, 40 and 104) and Agona (two strains) were tested for 949 substrates, Enteritidis (six strains of phage type PT1), Give, Hvittingfoss, Infantis and Newport strains (two of each) were tested for 190 substrates and seven other Agona strains for 95 substrates. The strains represented 18 genotypes in pulsed-field gel electrophoresis (PFGE). Among 949 substrates, 18 were identified that could be used to differentiate between the strains of those seven serotypes or within a single serotype. Unique metabolic differences between the Finnish endemic Typhimurium DT1 and Agona strains were detected, for example, in the metabolism of d-tagatose, d-galactonic acid gamma-lactone and l-proline as a carbon source. Thus, the PM technique is a useful tool for identifying potential differential markers on a metabolic basis that could be used for epidemiological surveillance.

Characterisation of Escherichia fergusonii isolates from farm animals using an Escherichia coli virulence gene array and tissue culture adherence assays

Escherichia fergusonii has been associated with a wide variety of intestinal and extra-intestinal infections in both humans and animals but, despite strong circumstantial evidence, the degree to which the organism is responsible for the pathologies identified remains uncertain. Thirty isolates of E fergusonii collected between 2003 and 2004 were screened using an Escherichia coli virulence gene array to test for the presence of homologous virulence genes in E. fergusonii. The iss (increased serum survival) gene was present in 13/30 (43%) of the test strains and the prfB (P-related fimbriae regulatory) and ireA (siderophore receptor IreA) genes were also detected jointly in 3/30 (10%) strains. No known virulence genes were detected in 14/30 (47%) of strains. Following confirmatory PCR and sequence analysis, the E. fergusonii prfB, iss and ireA genes shared a high degree of sequence similarity to their counterparts in E. coli, and a particular resemblance was noted with the E. coli strain APEC O1 pathogenicity island. In tissue culture adherence assays, nine E. fergusonii isolates associated with HEp-2 cells with a 'localised adherence' or 'diffuse adherence' phenotype, and they proved to be moderately invasive. The E fergusonii isolates in this study possess both some phenotypic and genotypic features linked to known pathotypes of E coli, and support existing evidence that strains of E fergusonii may act as an opportunistic pathogens, although their specific virulence factors may need to be explored. Crown Copyright (c) 2008 Published by Elsevier Ltd. All rights reserved.

A variational method to retrieve the extinction profile in liquid clouds using multiple field-of-view lidar

Liquid clouds play a profound role in the global radiation budget but it is difficult to remotely retrieve their vertical profile. Ordinary narrow field-of-view (FOV) lidars receive a strong return from such clouds but the information is limited to the first few optical depths. Wideangle multiple-FOV lidars can isolate radiation scattered multiple times before returning to the instrument, often penetrating much deeper into the cloud than the singly-scattered signal. These returns potentially contain information on the vertical profile of extinction coefficient, but are challenging to interpret due to the lack of a fast radiative transfer model for simulating them. This paper describes a variational algorithm that incorporates a fast forward model based on the time-dependent two-stream approximation, and its adjoint. Application of the algorithm to simulated data from a hypothetical airborne three-FOV lidar with a maximum footprint width of 600m suggests that this approach should be able to retrieve the extinction structure down to an optical depth of around 6, and total opticaldepth up to at least 35, depending on the maximum lidar FOV. The convergence behavior of Gauss-Newton and quasi-Newton optimization schemes are compared. We then present results from an application of the algorithm to observations of stratocumulus by the 8-FOV airborne “THOR” lidar. It is demonstrated how the averaging kernel can be used to diagnose the effective vertical resolution of the retrieved profile, and therefore the depth to which information on the vertical structure can be recovered. This work enables exploitation of returns from spaceborne lidar and radar subject to multiple scattering more rigorously than previously possible.

Characterisation of the intracellular-glutamate decarboxylase system (GAD): analysis of its function, transcription and role in the acid resistance of various strains of Listeria monocytogenes

The glutamate decarboxylase (GAD) system is important for the acid resistance of Listeria monocytogenes. We previously showed that under acidic conditions, glutamate (Glt)/γ-aminobutyrate (GABA) antiport is impaired in minimal media but not in rich ones, like brain heart infusion. Here we demonstrate that this behavior is more complex and it is subject to strain and medium variation. Despite the impaired Glt/GABA antiport, cells accumulate intracellular GABA (GABA(i)) as a standard response against acid in any medium, and this occurs in all strains tested. Since these systems can occur independently of one another, we refer to them as the extracellular (GAD(e)) and intracellular (GAD(i)) systems. We show here that GAD(i) contributes to acid resistance since in a ΔgadD1D2 mutant, reduced GABA(i) accumulation coincided with a 3.2-log-unit reduction in survival at pH 3.0 compared to that of wild-type strain LO28. Among 20 different strains, the GAD(i) system was found to remove 23.11% ± 18.87% of the protons removed by the overall GAD system. Furthermore, the GAD(i) system is activated at milder pH values (4.5 to 5.0) than the GAD(e) system (pH 4.0 to 4.5), suggesting that GAD(i) is the more responsive of the two and the first line of defense against acid. Through functional genomics, we found a major role for GadD2 in the function of GAD(i), while that of GadD1 was minor. Furthermore, the transcription of the gad genes in three common reference strains (10403S, LO28, and EGD-e) during an acid challenge correlated well with their relative acid sensitivity. No transcriptional upregulation of the gadT2D2 operon, which is the most important component of the GAD system, was observed, while gadD3 transcription was the highest among all gad genes in all strains. In this study, we present a revised model for the function of the GAD system and highlight the important role of GAD(i) in the acid resistance of L. monocytogenes.

On variational data assimilation in continuous time

Variational data assimilation in continuous time is revisited. The central techniques applied in this paper are in part adopted from the theory of optimal nonlinear control. Alternatively, the investigated approach can be considered as a continuous time generalization of what is known as weakly constrained four-dimensional variational assimilation (4D-Var) in the geosciences. The technique allows to assimilate trajectories in the case of partial observations and in the presence of model error. Several mathematical aspects of the approach are studied. Computationally, it amounts to solving a two-point boundary value problem. For imperfect models, the trade-off between small dynamical error (i.e. the trajectory obeys the model dynamics) and small observational error (i.e. the trajectory closely follows the observations) is investigated. This trade-off turns out to be trivial if the model is perfect. However, even in this situation, allowing for minute deviations from the perfect model is shown to have positive effects, namely to regularize the problem. The presented formalism is dynamical in character. No statistical assumptions on dynamical or observational noise are imposed.

Resolution of sharp fronts in the presence of model error in variational data assimilation

We show that the four-dimensional variational data assimilation method (4DVar) can be interpreted as a form of Tikhonov regularization, a very familiar method for solving ill-posed inverse problems. It is known from image restoration problems that L1-norm penalty regularization recovers sharp edges in the image more accurately than Tikhonov, or L2-norm, penalty regularization. We apply this idea from stationary inverse problems to 4DVar, a dynamical inverse problem, and give examples for an L1-norm penalty approach and a mixed total variation (TV) L1–L2-norm penalty approach. For problems with model error where sharp fronts are present and the background and observation error covariances are known, the mixed TV L1–L2-norm penalty performs better than either the L1-norm method or the strong constraint 4DVar (L2-norm)method. A strength of the mixed TV L1–L2-norm regularization is that in the case where a simplified form of the background error covariance matrix is used it produces a much more accurate analysis than 4DVar. The method thus has the potential in numerical weather prediction to overcome operational problems with poorly tuned background error covariance matrices.