The effects of alpha-lactalbumin and glycomacropeptide on the association of CaCo-2 cells by enteropathogenic Escherichia coli, Salmonella typhimurium and Shigella flexneri

Two milk components, alpha-lactalbumin (alpha-La) and glycomacropeptide (GMP) may inhibit intestinal infection/intoxification. (3)[H] thymidine-labeled enteropathogenic Escherichia coli (EPEC), Salmonella typhimurium (ATCC 6994) or Shigella flexneri (ATCC 9199) were introduced to CaCo-2 cultures and their association with CaCo-2 cells was assessed. Undigested, pepsin-digested and pepsin- and pancreatin-digested alpha-lactalbumin and glycomacropeptide inhibited association. Thus, milk supplemented with alpha-lactalbumin and glycomacropeptide might be effective in inhibiting associations of the pathogens EPEC, Salmonella typhimurium, and Shigella flexneri to intestinal cells.

Informing people about the risks and benefits of medicines: implications for the safe and effective use of medicinal products

Providing effective information about drug risks and benefits has become a major challenge for health professionals, as many people are ill equipped to understand, retain and use the information effectively. This paper reviews the growing evidence that people’s understanding (and health behaviour) is not only affected by the content of medicines information, but also by the particular way in which it is presented. Such presentational factors include whether information is presented verbally or numerically, framed positively or negatively, whether risk reductions are described in relative or absolute terms (and baseline information included), and whether information is personalized or tailored in any way. It also looks at how understanding is affected by the order in which information is presented, and the way in which it is processed. The paper concludes by making a number of recommendations for providers of medicines information, about both the content and presentation of such information, that should enhance safe and effective medicines usage.

Robustness and applicability of Markov chain Monte Carlo algorithms for eigenvalue problems

In this paper we analyse applicability and robustness of Markov chain Monte Carlo algorithms for eigenvalue problems. We restrict our consideration to real symmetric matrices. Almost Optimal Monte Carlo (MAO) algorithms for solving eigenvalue problems are formulated. Results for the structure of both - systematic and probability error are presented. It is shown that the values of both errors can be controlled independently by different algorithmic parameters. The results present how the systematic error depends on the matrix spectrum. The analysis of the probability error is presented. It shows that the close (in some sense) the matrix under consideration is to the stochastic matrix the smaller is this error. Sufficient conditions for constructing robust and interpolation Monte Carlo algorithms are obtained. For stochastic matrices an interpolation Monte Carlo algorithm is constructed. A number of numerical tests for large symmetric dense matrices are performed in order to study experimentally the dependence of the systematic error from the structure of matrix spectrum. We also study how the probability error depends on the balancing of the matrix. (c) 2007 Elsevier Inc. All rights reserved.

Verification of cloud-fraction forecasts

Cloud radar and lidar can be used to evaluate the skill of numerical weather prediction models in forecasting the timing and placement of clouds, but care must be taken in choosing the appropriate metric of skill to use due to the non- Gaussian nature of cloud-fraction distributions. We compare the properties of a number of different verification measures and conclude that of existing measures the Log of Odds Ratio is the most suitable for cloud fraction. We also propose a new measure, the Symmetric Extreme Dependency Score, which has very attractive properties, being equitable (for large samples), difficult to hedge and independent of the frequency of occurrence of the quantity being verified. We then use data from five European ground-based sites and seven forecast models, processed using the ‘Cloudnet’ analysis system, to investigate the dependence of forecast skill on cloud fraction threshold (for binary skill scores), height, horizontal scale and (for the Met Office and German Weather Service models) forecast lead time. The models are found to be least skillful at predicting the timing and placement of boundary-layer clouds and most skilful at predicting mid-level clouds, although in the latter case they tend to underestimate mean cloud fraction when cloud is present. It is found that skill decreases approximately inverse-exponentially with forecast lead time, enabling a forecast ‘half-life’ to be estimated. When considering the skill of instantaneous model snapshots, we find typical values ranging between 2.5 and 4.5 days. Copyright c 2009 Royal Meteorological Society

In vitro fermentation of rice bran combined with Lactobacillus acidophilus 14 150B or Bifidobacterium longum 05 by the canine faecal microbiota

The fermentability of rice bran (RB), alone or in combination with one of two probiotics, by canine faecal microbiota was evaluated in stirred, pH-controlled, anaerobic batch cultures. RB enhanced the levels of bacteria detected by probes Bif164 (bifidobacteria) and Lab158 (lactic acid bacteria); however, addition of the probiotics did not have a significant effect on the predominant microbial counts compared with RB alone. RB sustained levels of Bifidobacterium longum 05 throughout the fermentation; in contrast, Lactobacillus acidophilus 14 150B levels decreased significantly after 5-h fermentation. RB fermentation induced changes in the short-chain fatty acid (SCFA) profile. However, RB combined with probiotics did not alter the SCFA levels compared with RB alone. Denaturing gradient gel electrophoresis analysis of samples obtained at 24 h showed a treatment effect with RB, which was not observed in the RB plus probiotic systems. Overall, the negative controls displayed lower species richness than the treatment systems and their banding profiles were distinct. This study illustrates the ability of a common ingredient found in pet food to modulate the canine faecal microbiota and highlights that RB may be an economical alternative to prebiotics for use in dog food.

In vitro effects of synbiotic fermentation on the canine faecal microbiota.

Stirred, pH-controlled anaerobic batch cultures were used to investigate the in vitro effects of galacto-oligosaccharides (GOS) alone or combined with the probiotic Bifidobacterium bifidum 02 450B on the canine faecal microbiota of three different donors. GOS supported the growth of B. bifidum 02 450B throughout the fermentation. Quantitative analysis of bacterial populations by FISH revealed significant increases in Bifidobacterium spp. counts (Bif164) and a concomitant decrease in Clostridium histolyticum counts (Chis150) in the synbiotic-containing vessels compared with the controls and GOS vessels. Vessels containing probiotic alone displayed a transient increase in Bifidobacterium spp. and a transient decrease in Bacteroides spp. Denaturing gradient gel electrophoresis analysis showed that GOS elicited similar alterations in the microbial profiles of the three in vitro runs. However, the synbiotic did not alter the microbial diversity of the three runs to the same extent as GOS alone. Nested PCR using universal primers, followed by bifidobacterial-specific primers illustrated low bifidobacterial diversity in dogs, which did not change drastically during the in vitro fermentation. This study illustrates that the canine faecal microbiota can be modulated in vitro by GOS supplementation and that GOS can sustain the growth of B. bifidum 02 450B in a synbiotic combination.

Investigation of the faecal microbiota associated with canine chronic diarrhoea.

Diarrhoea is a common problem in dogs and can result in disturbance of the normal intestinal microbiota. However, little is known about the gastrointestinal microbiota of dogs with chronic diarrhoea and controlled canine studies of dietary management are scarce. The aims of this study were to investigate the predominant faecal microbiota of chronic diarrhoea dogs and to examine the effect(s) of a fibre blend on the canine faecal microbiota. A 3-week fibre supplementation feeding study was performed in nine chronic diarrhoea and eight control dogs. Atopobium cluster, Lactobacillus-Enterococcus group and Clostridium cluster XIV were the predominant bacterial groups in all dogs. Chronic diarrhoea dogs had significantly higher Bacteroides counts at baseline and significantly lower Atopobium cluster counts following fibre supplementation compared with control dogs. Atopobium cluster levels increased significantly in control dogs, while counts of sulphate-reducing bacteria decreased significantly and Clostridium clusters I and II counts increased significantly in chronic diarrhoea dogs during fibre supplementation. Microbial profiles (detected by denaturing gradient gel electrophoresis) demonstrated interindividual variation, with greater similarity seen between the chronic diarrhoea and control dogs' profiles after fibre supplementation compared with baseline. In conclusion, fibre supplementation induced changes in the canine faecal microbiota, with greater resemblance between the microbiota of chronic diarrhoea and control dogs after this dietary modulation.

Relation between neuronal morphology and electrophysiology in the Kainate lesion model of Alzheimer's Disease

This paper describes a computational and statistical study of the influence of morphological changes on the electrophysiological response of neurons from an animal model of Alzheimer's Disease (AD). We combined experimental morphological data from rat hippocampal CA1 pyramidal cells with a well-established model of active membrane properties. Dendritic morphology and the somatic response to simulated current clamp conditions were then compared for cells from the control and the AD group. The computational approach allowed us to single out the influences of neuromorphology on neuronal response by eliminating the effects of active channel variability. The results did not reveal a simple relationship between morphological changes associated with AD and changes in neural response. However, they did suggest the existence of more complex than anticipated relationships between dendritic morphology and single-cell electrophysiology.

Generation, description and storage of dendritic morphology data

It is generally assumed that the variability of neuronal morphology has an important effect on both the connectivity and the activity of the nervous system, but this effect has not been thoroughly investigated. Neuroanatomical archives represent a crucial tool to explore structure–function relationships in the brain. We are developing computational tools to describe, generate, store and render large sets of three–dimensional neuronal structures in a format that is compact, quantitative, accurate and readily accessible to the neuroscientist. Single–cell neuroanatomy can be characterized quantitatively at several levels. In computer–aided neuronal tracing files, a dendritic tree is described as a series of cylinders, each represented by diameter, spatial coordinates and the connectivity to other cylinders in the tree. This ‘Cartesian’ description constitutes a completely accurate mapping of dendritic morphology but it bears little intuitive information for the neuroscientist. In contrast, a classical neuroanatomical analysis characterizes neuronal dendrites on the basis of the statistical distributions of morphological parameters, e.g. maximum branching order or bifurcation asymmetry. This description is intuitively more accessible, but it only yields information on the collective anatomy of a group of dendrites, i.e. it is not complete enough to provide a precise ‘blueprint’ of the original data. We are adopting a third, intermediate level of description, which consists of the algorithmic generation of neuronal structures within a certain morphological class based on a set of ‘fundamental’, measured parameters. This description is as intuitive as a classical neuroanatomical analysis (parameters have an intuitive interpretation), and as complete as a Cartesian file (the algorithms generate and display complete neurons). The advantages of the algorithmic description of neuronal structure are immense. If an algorithm can measure the values of a handful of parameters from an experimental database and generate virtual neurons whose anatomy is statistically indistinguishable from that of their real counterparts, a great deal of data compression and amplification can be achieved. Data compression results from the quantitative and complete description of thousands of neurons with a handful of statistical distributions of parameters. Data amplification is possible because, from a set of experimental neurons, many more virtual analogues can be generated. This approach could allow one, in principle, to create and store a neuroanatomical database containing data for an entire human brain in a personal computer. We are using two programs, L–NEURON and ARBORVITAE, to investigate systematically the potential of several different algorithms for the generation of virtual neurons. Using these programs, we have generated anatomically plausible virtual neurons for several morphological classes, including guinea pig cerebellar Purkinje cells and cat spinal cord motor neurons. These virtual neurons are stored in an online electronic archive of dendritic morphology. This process highlights the potential and the limitations of the ‘computational neuroanatomy’ strategy for neuroscience databases.

Effects of dendritic morphology on CA3 pyramidal cell electrophysiology: a simulation study

We investigated the effect of morphological differences on neuronal firing behavior within the hippocampal CA3 pyramidal cell family by using three-dimensional reconstructions of dendritic morphology in computational simulations of electrophysiology. In this paper, we report for the first time that differences in dendritic structure within the same morphological class can have a dramatic influence on the firing rate and firing mode (spiking versus bursting and type of bursting). Our method consisted of converting morphological measurements from three-dimensional neuroanatomical data of CA3 pyramidal cells into a computational simulator format. In the simulation, active channels were distributed evenly across the cells so that the electrophysiological differences observed in the neurons would only be due to morphological differences. We found that differences in the size of the dendritic tree of CA3 pyramidal cells had a significant qualitative and quantitative effect on the electrophysiological response. Cells with larger dendritic trees: (1) had a lower burst rate, but a higher spike rate within a burst, (2) had higher thresholds for transitions from quiescent to bursting and from bursting to regular spiking and (3) tended to burst with a plateau. Dendritic tree size alone did not account for all the differences in electrophysiological responses. Differences in apical branching, such as the distribution of branch points and terminations per branch order, appear to effect the duration of a burst. These results highlight the importance of considering the contribution of morphology in electrophysiological and simulation studies.

Pseudomonas genomes: diverse and adaptable

Members of the genus Pseudomonas inhabit a wide variety of environments, which is reflected in their versatile metabolic capacity and broad potential for adaptation to fluctuating environmental conditions. Here, we examine and compare the genomes of a range of Pseudomonas spp. encompassing plant, insect and human pathogens, and environmental saprophytes. In addition to a large number of allelic differences of common genes that confer regulatory and metabolic flexibility, genome analysis suggests that many other factors contribute to the diversity and adaptability of Pseudomonas spp. Horizontal gene transfer has impacted the capability of pathogenic Pseudomonas spp. in terms of disease severity (Pseudomonas aeruginosa) and specificity (Pseudomonas syringae). Genome rearrangements likely contribute to adaptation, and a considerable complement of unique genes undoubtedly contributes to strain- and species-specific activities by as yet unknown mechanisms. Because of the lack of conserved phenotypic differences, the classification of the genus has long been contentious. DNA hybridization and genome-based analyses show close relationships among members of P. aeruginosa, but that isolates within the Pseudomonas fluorescens and P. syringae species are less closely related and may constitute different species. Collectively, genome sequences of Pseudomonas spp. have provided insights into pathogenesis and the genetic basis for diversity and adaptation.