Characterization of virus-like particles associated with the human faecal and caecal microbiota

This work represents an investigation into the presence, abundance and diversity of virus-like particles (VLPs) associated with human faecal and caecal samples. Various methodologies for the recovery of VLPs from faeces were tested and optimized, including successful down-stream processing of such samples for the purpose of an in-depth electron microscopic analysis, pulsed-field gel electrophoresis and efficient DNA recovery. The applicability of the developed VLP characterization method beyond the use of faecal samples was then verified using samples obtained from human caecal fluid.

Folding of graphene slit like pore walls—a simple method of improving CO2 separation from mixtures with CH4 or N2

We report for the first time a detailed procedure for creating a simulation model of energetically stable, folded graphene-like pores and simulation results of CO2/CH4 and CO2/N2 separation using these structures. We show that folding of graphene structures is a very promising method to improve the separation of CO2 from mixtures with CH4 and N2. The separation properties of the analyzed materials are compared with carbon nanotubes having similar diameters or S/V ratio. The presented results have potential importance in the field of CO2 capture and sequestration.

Using reanalysis data to quantify extreme wind power generation statistics : a 33 year case study in Great Britain

With a rapidly increasing fraction of electricity generation being sourced from wind, extreme wind power generation events such as prolonged periods of low (or high) generation and ramps in generation, are a growing concern for the efficient and secure operation of national power systems. As extreme events occur infrequently, long and reliable meteorological records are required to accurately estimate their characteristics. Recent publications have begun to investigate the use of global meteorological “reanalysis” data sets for power system applications, many of which focus on long-term average statistics such as monthly-mean generation. Here we demonstrate that reanalysis data can also be used to estimate the frequency of relatively short-lived extreme events (including ramping on sub-daily time scales). Verification against 328 surface observation stations across the United Kingdom suggests that near-surface wind variability over spatiotemporal scales greater than around 300 km and 6 h can be faithfully reproduced using reanalysis, with no need for costly dynamical downscaling. A case study is presented in which a state-of-the-art, 33 year reanalysis data set (MERRA, from NASA-GMAO), is used to construct an hourly time series of nationally-aggregated wind power generation in Great Britain (GB), assuming a fixed, modern distribution of wind farms. The resultant generation estimates are highly correlated with recorded data from National Grid in the recent period, both for instantaneous hourly values and for variability over time intervals greater than around 6 h. This 33 year time series is then used to quantify the frequency with which different extreme GB-wide wind power generation events occur, as well as their seasonal and inter-annual variability. Several novel insights into the nature of extreme wind power generation events are described, including (i) that the number of prolonged low or high generation events is well approximated by a Poission-like random process, and (ii) whilst in general there is large seasonal variability, the magnitude of the most extreme ramps is similar in both summer and winter. An up-to-date version of the GB case study data as well as the underlying model are freely available for download from our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/.

Flow in the high latitude ionosphere: measurements at 15s resolution made using the EISCAT ‘Polar’ experiment

We present a first overview of flows in the high latitude ionosphere observed at 15 s resolution using the U.K.-Polar EISCAT experiment. Data are described from experiments conducted on two days, 27 October 1984 and 29 August 1985, which together span the local times between about 0200 and 2130MLT and cover five different regions of ionospheric flow. With increasing local time, these are: the dawn auroral zone flow cell, the dayside region of low background flows equatorward of the flow cells, the dusk auroral zone flow cell, the boundary region between the dusk auroral zone and the polar cap, and the evening polar cap. Flows in both the equatorward and poleward portions of the auroral zone cells appear to be relatively smooth, while in the central region of high speed flow considerable variations are generally present. These have the form of irregular fluctuations on a wide range of time scales in the early morning dawn cell, and impulsive wave-like variations with periods of a few minutes in the afternoon dusk cell. In the dayside region between the flow cells, the ionosphere is often essentially stagnant for long intervals, but low amplitude ULF waves with a period of about 5 min can also occur and persist for many cycles. These conditions are punctuated at one to two hour intervals by sudden ‘flow burst’ events with impulsively generated damped wave trains. Initial burst flows are generally directed poleward and can peak at line-of-sight speeds in excess of 1 km s^{−1} after perhaps 45 s. Flows in the polar cap are reasonably smooth on time scales of a few minutes and show no evidence for the presence of ULF waves. Under most, but not all, of the above conditions, the beam-swinging algorithm used to determine background vector flows should produce meaningful results. Comparison of these flow data with simultaneous plasma and magnetic field measurements in the solar wind, made by the AMPTE IRM and UKS spacecraft, emphasizes the strong control exerted on high latitude flows by the north-south component of the IMF.

Nonlinear identification using orthogonal forward regression with nested optimal regularization

An efficient data based-modeling algorithm for nonlinear system identification is introduced for radial basis function (RBF) neural networks with the aim of maximizing generalization capability based on the concept of leave-one-out (LOO) cross validation. Each of the RBF kernels has its own kernel width parameter and the basic idea is to optimize the multiple pairs of regularization parameters and kernel widths, each of which is associated with a kernel, one at a time within the orthogonal forward regression (OFR) procedure. Thus, each OFR step consists of one model term selection based on the LOO mean square error (LOOMSE), followed by the optimization of the associated kernel width and regularization parameter, also based on the LOOMSE. Since like our previous state-of-the-art local regularization assisted orthogonal least squares (LROLS) algorithm, the same LOOMSE is adopted for model selection, our proposed new OFR algorithm is also capable of producing a very sparse RBF model with excellent generalization performance. Unlike our previous LROLS algorithm which requires an additional iterative loop to optimize the regularization parameters as well as an additional procedure to optimize the kernel width, the proposed new OFR algorithm optimizes both the kernel widths and regularization parameters within the single OFR procedure, and consequently the required computational complexity is dramatically reduced. Nonlinear system identification examples are included to demonstrate the effectiveness of this new approach in comparison to the well-known approaches of support vector machine and least absolute shrinkage and selection operator as well as the LROLS algorithm.

A scalable expressive ensemble learning using Random Prism: a MapReduce approach

The induction of classification rules from previously unseen examples is one of the most important data mining tasks in science as well as commercial applications. In order to reduce the influence of noise in the data, ensemble learners are often applied. However, most ensemble learners are based on decision tree classifiers which are affected by noise. The Random Prism classifier has recently been proposed as an alternative to the popular Random Forests classifier, which is based on decision trees. Random Prism is based on the Prism family of algorithms, which is more robust to noise. However, like most ensemble classification approaches, Random Prism also does not scale well on large training data. This paper presents a thorough discussion of Random Prism and a recently proposed parallel version of it called Parallel Random Prism. Parallel Random Prism is based on the MapReduce programming paradigm. The paper provides, for the first time, novel theoretical analysis of the proposed technique and in-depth experimental study that show that Parallel Random Prism scales well on a large number of training examples, a large number of data features and a large number of processors. Expressiveness of decision rules that our technique produces makes it a natural choice for Big Data applications where informed decision making increases the user’s trust in the system.

A cross layer protocol for energy aware and critical data delivered applications using Wireless Sensor Networks

Environment monitoring applications using Wireless Sensor Networks (WSNs) have had a lot of attention in recent years. In much of this research tasks like sensor data processing, environment states and events decision making and emergency message sending are done by a remote server. A proposed cross layer protocol for two different applications where, reliability for delivered data, delay and life time of the network need to be considered, has been simulated and the results are presented in this paper. A WSN designed for the proposed applications needs efficient MAC and routing protocols to provide a guarantee for the reliability of the data delivered from source nodes to the sink. A cross layer based on the design given in [1] has been extended and simulated for the proposed applications, with new features, such as routes discovery algorithms added. Simulation results show that the proposed cross layer based protocol can conserve energy for nodes and provide the required performance such as life time of the network, delay and reliability.

A cross layer protocol based on mac and routing protocols for healthcare applications using Wireless Sensor Networks

Using Wireless Sensor Networks (WSNs) in healthcare systems has had a lot of attention in recent years. In much of this research tasks like sensor data processing, health states decision making and emergency message sending are done by a remote server. Many patients with lots of sensor data consume a great deal of communication resources, bring a burden to the remote server and delay the decision time and notification time. A healthcare application for elderly people using WSN has been simulated in this paper. A WSN designed for the proposed healthcare application needs efficient MAC and routing protocols to provide a guarantee for the reliability of the data delivered from the patients to the medical centre. Based on these requirements, A cross layer based on the modified versions of APTEEN and GinMAC has been designed and implemented, with new features, such as a mobility module and routes discovery algorithms have been added. Simulation results show that the proposed cross layer based protocol can conserve energy for nodes and provide the required performance such as life time of the network, delay and reliability for the proposed healthcare application.

MAC protocols and mobility management module for healthcare applications using Wireless Sensor Networks

Using Wireless Sensor Networks (WSNs) in healthcare systems has had a lot of attention in recent years. In much of this research tasks like sensor data processing, health states decision making and emergency message sending are done by a remote server. Many patients with lots of sensor data consume a great deal of communication resources, bring a burden to the remote server and delay the decision time and notification time. A healthcare application for elderly people using WSN has been simulated in this paper. A WSN designed for the proposed healthcare application needs efficient Medium Access Control (MAC) and routing protocols to provide a guarantee for the reliability of the data delivered from the patients to the medical centre. Based on these requirements, the GinMAC protocol including a mobility module has been chosen, to provide the required performance such as reliability for data delivery and energy saving. Simulation results show that this modification to GinMAC can offer the required performance for the proposed healthcare application.

MAC protocols and mobility management module for healthcare applications using wireless sensor networks

Using Wireless Sensor Networks (WSNs) in healthcare systems has had a lot of attention in recent years. In much of this research tasks like sensor data processing, health states decision making and emergency message sending are done by a remote server. Many patients with lots of sensor data consume a great deal of communication resources, bring a burden to the remote server and delay the decision time and notification time. A healthcare application for elderly people using WSN has been simulated in this paper. A WSN designed for the proposed healthcare application needs efficient MAC and routing protocols to provide a guarantee for the reliability of the data delivered from the patients to the medical centre. Based on these requirements, the GinMAC protocol including a mobility module has been chosen, to provide the required performance such as reliability for data delivery and energy saving. Simulation results show that this modification to GinMAC can offer the required performance for the proposed healthcare application.

Inferring the structure of the solar corona and inner heliosphere during the Maunder minimum using global thermodynamic magnetohydrodynamic simulations

Observations of the Sun’s corona during the space era have led to a picture of relatively constant, but cyclically varying solar output and structure. Longer-term, more indirect measurements, such as from 10Be, coupled by other albeit less reliable contemporaneous reports, however, suggest periods of significant departure from this standard. The Maunder Minimum was one such epoch where: (1) sunspots effectively disappeared for long intervals during a 70 yr period; (2) eclipse observations suggested the distinct lack of a visible K-corona but possible appearance of the F-corona; (3) reports of aurora were notably reduced; and (4) cosmic ray intensities at Earth were inferred to be substantially higher. Using a global thermodynamic MHD model, we have constructed a range of possible coronal configurations for the Maunder Minimum period and compared their predictions with these limited observational constraints. We conclude that the most likely state of the corona during—at least—the later portion of the Maunder Minimum was not merely that of the 2008/2009 solar minimum, as has been suggested recently, but rather a state devoid of any large-scale structure, driven by a photospheric field composed of only ephemeral regions, and likely substantially reduced in strength. Moreover, we suggest that the Sun evolved from a 2008/2009-like configuration at the start of the Maunder Minimum toward an ephemeral-only configuration by the end of it, supporting a prediction that we may be on the cusp of a new grand solar minimum.

Optimisation of oat milk formulation to obtain fermented derivatives by using probiotic Lactobacillus reuteri microorganisms

Functional advantages of probiotics combined with interesting composition of oat were considered as an alternative to dairy products. In this study, fermentation of oat milk with Lactobacillus reuteri and Streptococcus thermophilus was analysed to develop a new probiotic product. Central composite design with response surface methodology was used to analyse the effect of different factors (glucose, fructose, inulin and starters) on the probiotic population in the product. Optimised formulation was characterised throughout storage time at 4 ℃ in terms of pH, acidity, β-glucan and oligosaccharides contents, colour and rheological behaviour. All formulations studied were adequate to produce fermented foods and minimum dose of each factor was considered as optimum. The selected formulation allowed starters survival above 107/cfu ml to be considered as a functional food and was maintained during the 28 days controlled. β-glucans remained in the final product with a positive effect on viscosity. Therefore, a new probiotic non-dairy milk was successfully developed in which high probiotic survivals were assured throughout the typical yoghurt-like shelf life.

Targeted activation of toll-like receptors: conjugation of a toll-like receptor 7 agonist to a monoclonal antibody maintains antigen binding and specificity

Therapeutic activation of Toll-like receptors (TLR) has potential for cancer immunotherapy, for augmenting the activity of anti-tumor monoclonal antibodies (mAbs), and for improved vaccine adjuvants. A previous attempt to specifically target TLR agonists to dendritic cells (DC) using mAbs failed because conjugation led to non-specific binding and mAbs lost specificity. We demonstrate here for the first time the successful conjugation of a small molecule TLR7 agonist to an anti-tumour mAb (the anti-hCD 20 rituximab) without compromising antigen specificity. The TLR7 agonist UC-1V150 was conjugated to rituximab using two conjugation methods and yield, molecular substitution ratio, retention of TLR7 activity and specificity of antigen binding were compared. Both conjugation methods produced rituximab-UC-1V150 conjugates with UC-1V150 : rituximab ratio ranging from 1:1 to 3:1 with drug loading quantified by UV spectroscopy and drug substitution ratio verified by MALDI TOF mass spectroscopy. The yield of purified conjugates varied with conjugation method, and dropped as low as 31% using a method previously described for conjugating UC-1V150 to proteins, where a bifunctional crosslinker was firstly reacted with rituximab, and secondly to the TLR7 agonist. We therefore developed a direct conjugation method by producing an amine-reactive UV active version of UC-1V150, termed NHS:UC-1V150. Direct conjugation with NHS:UC-1V150 was quick and simple and gave improved conjugate yields of 65-78%. Rituximab-UC-1V150 conjugates had the expected pro-inflammatory activity in vitro (EC50 28-53 nM) with a significantly increased activity over unconjugated UC-1V150 (EC50 547 nM). Antigen binding and specificity of the rituxuimab-UC-1V150 conjugates was retained, and after incubation with human peripheral blood leukocytes, all conjugates bound strongly only to CD20-expressing B cells whilst no non-specific binding to CD20-negative cells was observed. Selective targeting of Toll-like receptor activation directly within tumors or to DC is now feasible.

Activation of glycoprotein VI (GPVI) and C-type lectin-like receptor-2 (CLEC-2) underlies platelet activation by diesel exhaust particles and other charged/hydrophobic ligands

Platelets are activated by a range of stimuli that share little or no resemblance in structure to each other or to recognized ligands, including diesel exhaust particles (DEP), small peptides [4N1-1, Champs (computed helical anti-membrane proteins), LSARLAF (Leu-Ser-Ala-Arg-Leu-Ala-Phe)], proteins (histones) and large polysaccharides (fucoidan, dextran sulfate). This miscellaneous group stimulate aggregation of human and mouse platelets through the glycoprotein VI (GPVI)-FcR γ-chain complex and/or C-type lectin-like receptor-2 (CLEC-2) as shown using platelets from mice deficient in either or both of these receptors. In addition, all of these ligands stimulate tyrosine phosphorylation in GPVI/CLEC-2-double-deficient platelets, indicating that they bind to additional surface receptors, although only in the case of dextran sulfate does this lead to activation. DEP, fucoidan and dextran sulfate, but not the other agonists, activate GPVI and CLEC-2 in transfected cell lines as shown using a sensitive reporter assay confirming a direct interaction with the two receptors. We conclude that this miscellaneous group of ligands bind to multiple proteins on the cell surface including GPVI and/or CLEC-2, inducing activation. These results have pathophysiological significance in a variety of conditions that involve exposure to activating charged/hydrophobic agents.

G6f-like is an ITAM-containing collagen receptor in thrombocytes

Collagen activates mammalian platelets through a complex of the immunoglobulin (Ig) receptor GPVI and the Fc receptor γ-chain, which has an immunoreceptor tyrosine-based activation motif (ITAM). Cross-linking of GPVI mediates activation through the sequential activation of Src and Syk family kinases and activation of PLCγ2. Nucleated thrombocytes in fish are activated by collagen but lack an ortholog of GPVI. In this study we show that collagen activates trout thrombocytes in whole blood and under flow conditions through a Src kinase driven pathway. We identify the Ig receptor G6f-like as a collagen receptor and demonstrate in a cell line assay that it signals through its cytoplasmic ITAM. Using a morpholino for in vivo knock-down of G6f-like levels in zebrafish, we observed a marked delay or absence of occlusion of the venous and arterial systems in response to laser injury. Thus, G6f-like is a physiologically relevant collagen receptor in fish thrombocytes which signals through the same ITAM-based signalling pathway as mammalian GPVI, providing a novel example of convergent evolution.