In vitro examination of the effect of Orlistat on the ability of the faecal microbiota to utilize dietary lipids

Orlistat is an anti-obesity treatment with which several gastrointestinal (GI) side-effects are commonly associated in the initial stages of therapy. There is no physiological explanation as to why two-thirds of those who take the drug experience one or more side-effects. It has been hypothesized that the GI microbiota may protect from or contribute to these GI disturbances. Using in vitro batch culture and human gut model systems, studies were conducted to determine whether increased availability of dietary lipids and/or orlistat affect the composition and/or activity of the faecal microbiota. Results from 24-h batch culture fermentation experiments demonstrated no effect of orlistat in the presence or absence of a dietary lipid (olive oil) on the composition of bacterial communities [as determined by fluorescence in situ hybridization (FISH) and denaturing gradient gel electrophoresis (DGGE) analyses], but did show there was great variability in the lipolytic activities of the microbiotas of individuals, as determined by gas chromatography analysis of long-chain fatty acids in samples. Subsequent studies focused on the effect of orlistat in the presence and absence of lipid in in vitro human gut model systems. Systems were run for 14 days with gut model medium (GMM) only (to steady state, SS), then fed at 12-h intervals with 50 mg orlistat, 2 g olive oil or a mixture of both for 14 days. FISH and DGGE were used to monitor changes in bacterial populations. Bacteria were cultivated from the GMM only (control) systems at SS. All strains isolated were screened for lipolytic activity using tributyrin agar. FISH and DGGE demonstrated that none of the compounds (singly or in combination) added to the systems had any notable effect on microbial population dynamics for any of the donors, although Subdoligranulum populations appeared to be inhibited by orlistat in the presence or absence of lipid. Orlistat had little or no effect on the metabolism of indigenous and added lipids in the fermentation systems, but there was great variability in the way the faecal microbiotas of the donors were able to degrade added lipids. Variability in lipid degradation could be correlated with the number and activity of isolated lipolytic bacteria. The mechanism by which orlistat and the GI microbiota cause side-effects in individuals is unknown, but several hypotheses have been proposed to account for their manifestation. The demonstration of great variability in the lipolytic activity of microbiotas to degrade lipids led to a large-scale cultivation-based study of lipolytic/lipase-positive bacteria present in the human faecal microbiota. Of 4,000 colonies isolated from 15 donors using five different agars, 378 strains were identified that had lipase activity. Molecular identification of strains isolated from five donors demonstrated that lipase activity is more prevalent in the human GI microbiota than previously thought, with members of the phyla Firmicutes, Bacteroidetes and Actinobacteria identified. Molecular identification and characterization of the substrate specificities of the strains will be carried out as part of ongoing work.

Microprocessor systems: an introduction

The aim of this book is to provide and introduction to microprocessor systems, their operation and design. It covers those topics needed by engineers and computer scientists who are interested in applying microprocessors in practical situations, namely computer hardware including logic and interfacing, software, in particular high level and assembly language programming, and the design and testing of such systems. The fundamental principles of micrprocessor systems are described and these are illustrated with reference to two microprocessors, the 32-bit MC68020 from Motorola and a single chip microcomputer, the 8051 from Intel; and in addition, interfacing to the general purpose STE bus is described. The details of the processors and the bus are concentrated in three chapters, thus allowing the presentation of the material to be independent of the microprocessors if that is desired, and permitting the specific details to be found easily.

Feedback design for regularizing descriptor systems

This paper surveys numerical techniques for the regularization of descriptor (generalized state-space) systems by proportional and derivative feedback. We review generalizations of controllability and observability to descriptor systems along with definitions of regularity and index in terms of the Weierstraß canonical form. Three condensed forms display the controllability and observability properties of a descriptor system. The condensed forms are obtained through orthogonal equivalence transformations and rank decisions, so they may be computed by numerically stable algorithms. In addition, the condensed forms display whether a descriptor system is regularizable, i.e., when the system pencil can be made to be regular by derivative and/or proportional output feedback, and, if so, what index can be achieved. Also included is a a new characterization of descriptor systems that can be made to be regular with index 1 by proportional and derivative output feedback.

Thermodynamic derivation of the fluctuation theorem and Jarzynski equality

A thermodynamic expression for the analog of the canonical ensemble for nonequilibrium systems is described based on a purely information theoretical interpretation of entropy. It is shown that this nonequilibrium canonical distribution implies some important results from nonequilibrium thermodynamics, specifically, the fluctuation theorem and the Jarzynski equality. Those results are therefore expected to be more widely applicable, for example, to macroscopic systems.

Conductance of amyloid β based peptide filaments: structure–function relations.

Controlling the morphology of self-assembled peptide nanostructures, particularly those based on amyloid peptides, has been the focus of intense research. In order to exploit these structures in electronic applications, further understanding of their electronic behavior is required. In this work, the role of peptide morphology in determining electronic conduction along self-assembled peptide nanofilament networks is demonstrated. The peptides used in this work were based on the sequence AAKLVFF, which is an extension of a core sequence from the amyloid b peptide. We show that the incorporation of a non-natural amino acid, 2-thienylalanine, instead of phenylalanine improves the obtained conductance with respect to that obtained for a similar structure based on the native sequence, which was not the case for the incorporation of 3-thienylalanine. Furthermore, we demonstrate that the morphology of the self-assembled structures, which can be controlled by the solvent used in the assembly process, strongly affects the conductance, with larger conduction obtained for a morphology of long, straight filaments. Our results demonstrate that, similar to natural systems, the assembly and folding of peptides could be of great importance for optimizing their function as components of electronic devices. Hence, sequence design and assembly conditions can be used to control the performance of peptide based structures in such electronic applications.

Fault tolerant decentralised K-Means clustering for asynchronous large-scale networks

The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks, such as massively parallel processors and clusters of workstations. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. The lack of scalable and fault tolerant global communication and synchronisation methods in large-scale systems has hindered the adoption of the K-Means algorithm for applications in large networked systems such as wireless sensor networks, peer-to-peer systems and mobile ad hoc networks. This work proposes a fully distributed K-Means algorithm (EpidemicK-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art sampling methods and shows that the proposed method overcomes the limitations of the sampling-based approaches for skewed clusters distributions. The experimental analysis confirms that the proposed algorithm is very accurate and fault tolerant under unreliable network conditions (message loss and node failures) and is suitable for asynchronous networks of very large and extreme scale.

System dynamics mapping of acute patient flows

Department of Health staff wished to use systems modelling to discuss acute patient flows with groups of NHS staff. The aim was to assess the usefulness of system dynamics (SD) in a healthcare context and to elicit proposals concerning ways of improving patient experience. Since time restrictions excluded simulation modelling, a hybrid approach using stock/flow symbols from SD was created. Initial interviews and hospital site visits generated a series of stock/flow maps. A ‘Conceptual Framework’ was then created to introduce the mapping symbols and to generate a series of questions about different patient paths and what might speed or slow patient flows. These materials formed the centre of three workshops for NHS staff. The participants were able to propose ideas for improving patient flows and the elicited data was subsequently employed to create a finalized suite of maps of a general acute hospital. The maps and ideas were communicated back to the Department of Health and subsequently assisted the work of the Modernization Agency.

Fundamental deficits of auditory perception in Wernicke’s aphasia

Objective: This work investigates the nature of the comprehension impairment in Wernicke’s aphasia, by examining the relationship between deficits in auditory processing of fundamental, non-verbal acoustic stimuli and auditory comprehension. Wernicke’s aphasia, a condition resulting in severely disrupted auditory comprehension, primarily occurs following a cerebrovascular accident (CVA) to the left temporo-parietal cortex. Whilst damage to posterior superior temporal areas is associated with auditory linguistic comprehension impairments, functional imaging indicates that these areas may not be specific to speech processing but part of a network for generic auditory analysis. Methods: We examined analysis of basic acoustic stimuli in Wernicke’s aphasia participants (n = 10) using auditory stimuli reflective of theories of cortical auditory processing and of speech cues. Auditory spectral, temporal and spectro-temporal analysis was assessed using pure tone frequency discrimination, frequency modulation (FM) detection and the detection of dynamic modulation (DM) in “moving ripple” stimuli. All tasks used criterion-free, adaptive measures of threshold to ensure reliable results at the individual level. Results: Participants with Wernicke’s aphasia showed normal frequency discrimination but significant impairments in FM and DM detection, relative to age- and hearing-matched controls at the group level (n = 10). At the individual level, there was considerable variation in performance, and thresholds for both frequency and dynamic modulation detection correlated significantly with auditory comprehension abilities in the Wernicke’s aphasia participants. Conclusion: These results demonstrate the co-occurrence of a deficit in fundamental auditory processing of temporal and spectrotemporal nonverbal stimuli in Wernicke’s aphasia, which may have a causal contribution to the auditory language comprehension impairment Results are discussed in the context of traditional neuropsychology and current models of cortical auditory processing.

Analysis of frequency and intensity of European winter storm events from a multi-model perspective, at synoptic and regional scales

This study focuses on the analysis of winter (October-November-December-January-February-March; ONDJFM) storm events and their changes due to increased anthropogenic greenhouse gas concentrations over Europe. In order to assess uncertainties that are due to model formulation, 4 regional climate models (RCMs) with 5 high resolution experiments, and 4 global general circulation models (GCMs) are considered. Firstly, cyclone systems as synoptic scale processes in winter are investigated, as they are a principal cause of the occurrence of extreme, damage-causing wind speeds. This is achieved by use of an objective cyclone identification and tracking algorithm applied to GCMs. Secondly, changes in extreme near-surface wind speeds are analysed. Based on percentile thresholds, the studied extreme wind speed indices allow a consistent analysis over Europe that takes systematic deviations of the models into account. Relative changes in both intensity and frequency of extreme winds and their related uncertainties are assessed and related to changing patterns of extreme cyclones. A common feature of all investigated GCMs is a reduced track density over central Europe under climate change conditions, if all systems are considered. If only extreme (i.e. the strongest 5%) cyclones are taken into account, an increasing cyclone activity for western parts of central Europe is apparent; however, the climate change signal reveals a reduced spatial coherency when compared to all systems, which exposes partially contrary results. With respect to extreme wind speeds, significant positive changes in intensity and frequency are obtained over at least 3 and 20% of the European domain under study (35–72°N and 15°W–43°E), respectively. Location and extension of the affected areas (up to 60 and 50% of the domain for intensity and frequency, respectively), as well as levels of changes (up to +15 and +200% for intensity and frequency, respectively) are shown to be highly dependent on the driving GCM, whereas differences between RCMs when driven by the same GCM are relatively small.

Predicting solar disturbance effects on navigation systems

A variety of operational systems are vulnerable to disruption by solar disturbances brought to the Earth by the solar wind. Of particular importance to navigation systems are energetic charged particles which can generate temporary malfunctions and permanent damage in satellites. Modern spacecraft technology may prove to be particularly at risk during the next maximum of the solar cycle. In addition, the associated ionospheric disturbances cause phase shifts of transionospheric and ionosphere-reflected signals, giving positioning errors and loss of signal for GPS and Loran-C positioning systems and for over-the-horizon radars. We now have sufficient understanding of the solar wind, and how it interacts with the Earth's magnetic field, to predict statistically the likely effects on operational systems over the next solar cycle. We also have a number of advanced ways of detecting and tracking these disturbances through space but we cannot, as yet, provide accurate forecasts of individual disturbances that could be used to protect satellites and to correct errors. In addition, we have recently discovered long-term changes in the Sun, which mean that the number and severity of the disturbances to operational systems are increasing.

Integrating risks of climate change into water management

The Working Group II contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change critically reviewed and assessed tens of thousands of recent publications to inform about the assess current scientific knowledge on climate change impacts, vulnerability and adaptation. Chapter 3 of the report focuses on freshwater resources, but water issues are also prominent in other sectoral chapters and in the regional chapters of the Working Group II report as well as in various chapters of Working Group I. With this paper, the lead authors, a review editor and the chapter scientist of the freshwater chapter of the WGII AR5 wish to summarize their assessment of the most relevant risks of climate change related to freshwater systems and to show how assessment and reduction of those risks can be integrated into water management.

A global empirical system for probabilistic seasonal climate prediction

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961–2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño–Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

Entrepreneurial ecosystems in cities: establishing the framework conditions

This study focuses on regional entrepreneurial ecosystems and offers a complex model of start-ups, Regional Entrepreneurship and Development Index (REDI) and six domains of the entrepreneurial ecosystem (culture, formal institutions, infrastructure and amenities, IT, Melting Pot and demand). Altogether they capture the contextual features of socioeconomic, institutional and information environment in cities. To explain variations in entrepreneurship in a cross-section of 70 European cities, we utilize exploratory factor analysis and structural equation modelling for regional systems of entrepreneurship using individual perception surveys by Eurostat and the REDI. This study supports policymakers and scholars in development of new policies conducive to regional systems of innovation and entrepreneurship and serves as a basis for future research on urban entrepreneurial ecosystems.

Segregation effects according to the evolutionary stage of galaxy groups

We study segregation phenomena in 57 groups selected from the 2dF Percolation-Inferred Galaxy Groups (2PIGG) catalogue of galaxy groups. The sample corresponds to those systems located in areas of at least 80 per cent redshift coverage out to 10 times the radius of the groups. The dynamical state of the galaxy systems was determined after studying their velocity distributions. We have used the Anderson-Darling test to distinguish relaxed and non-relaxed systems. This analysis indicates that 84 per cent of groups have galaxy velocities consistent with the normal distribution, while 16 per cent of them have more complex underlying distributions. Properties of the member galaxies are investigated taking into account this classification. Our results indicate that galaxies in Gaussian groups are significantly more evolved than galaxies in non-relaxed systems out to distances of similar to 4R(200), presenting significantly redder (B - R) colours. We also find evidence that galaxies with M(R) <= -21.5 in Gaussian groups are closer to the condition of energy equipartition.

A structure-dynamic approach to cortical organization: Number of paths and accessibility

A structure-dynamic approach to cortical systems is reported which is based on the number of paths and the accessibility of each node. The latter measurement is obtained by performing self-avoiding random walks in the respective networks, so as to simulate dynamics, and then calculating the entropies of the transition probabilities for walks starting from each node. Cortical networks of three species, namely cat, macaque and humans, are studied considering structural and dynamical aspects. It is verified that the human cortical network presents the highest accessibility and number of paths (in terms of z-scores). The correlation between the number of paths and accessibility is also investigated as a mean to quantify the level of independence between paths connecting pairs of nodes in cortical networks. By comparing the cortical networks of cat, macaque and humans, it is verified that the human cortical network tends to present the largest number of independent paths of length larger than four. These results suggest that the human cortical network is potentially the most resilient to brain injures. (C) 2009 Elsevier B.V. All rights reserved.