Wheat glutenin proteins assemble into a nanostructure with unusual structural features

The proteins of wheat have a known propensity to aggregate into a variety of forms. We report here a novel nanostructure from wheat proteins, derived from a crude extract of high molecular weight glutenins. The structure was characterised by a significant thioflavin T (ThT) fluorescence and a fibrillar morphology by transmission electron microscopy (TEM). The ThT fluorescence and TEM data are suggestive of an amyloid structure, but the X-ray fibre diffraction data show a reflection pattern (4.02, 4.2-4.3, 4.6, 12.9,19.3 and 38.7 angstrom) inconsistent with both the classic amyloid form and the previously described beta-helix structure. The 4.6 angstrom reflection is consistent with that predicted for the amyloid inter-beta-strand, and the absence of the inter-beta-sheet distance at approximate to 10-11 angstrom is not unprecedented in amyloid-like structures. However, our observed X-ray reflection pattern has not been previously reported and suggests a novel wheat glutenin nanostructure. (C) 2008 Elsevier Ltd. All rights reserved.

Artichoke leaf extract (Cynara scolymus) reduces plasma cholesterol in otherwise healthy hypercholesterolemic adults: A randomized, double blind placebo controlled trial

Cardiovascular diseases are the chief causes of death in the UK, and are associated with high circulating levels of total cholesterol in the plasma. Artichoke leaf extracts (ALEs) have been reported to reduce plasma lipids levels, including total cholesterol, although high quality data is lacking. The objective of this trial was to assess the effect of ALE on plasma lipid levels and general well-being in otherwise healthy adults with mild to moderate hypercholesterolemia. 131 adults were screened for total plasma cholesterol in the range 6.0-8.0 mmol/l, with 75 suitable volunteers randomised onto the trial. Volunteers consumed 1280 mg of a standardised ALE, or matched placebo, daily for 12 weeks. Plasma total cholesterol decreased in the treatment group by an average of 4.2% (from 7.16 (SD 0.62) mmol/l to 6.86 (SD 0.68) mmol/l) and increased in the control group by an average of 1.9% (6.90 (SD 0.49) mmol/l to 7.03 (0.61) mmol/l), the difference between groups being statistically significant (p = 0.025). No significant differences between groups were observed for LDL cholesterol, HDL cholesterol or triglyceride levels. General well-being improved significantly in both the treatment (11%) and control groups (9%) with no significant differences between groups. In conclusion, ALE consumption resulted in a modest but favourable statistically significant difference in total cholesterol after 12 weeks. In comparison with a previous trial, it is suggested that the apparent positive health status of the study population may have contributed to the modesty of the observed response. (C) 2008 Elsevier GmbH. All rights reserved.

Artichoke leaf extract reduces symptoms of irritable bowel syndrome and improves quality of life in otherwise healthy volunteers suffering from concomitant dyspepsia: a subset analysis

Objectives: Does artichoke leaf extract (ALE) ameliorate symptoms of Irritable bowel syndrome (IBS) in otherwise healthy volunteers suffering concomitant dyspepsia? Methods: A subset analysis of a previous dose-ranging, open, postal study, in adults suffering dyspepsia. Two hundred and eight (208) adults were identified post hoc as suffering with IBS. IBS incidence, self-reported usual bowel pattern, and the Nepean Dyspepsia Index (NDI) were compared before and after a 2-month intervention period. Results: There was a significant fall in IBS incidence of 26.4% (p<0.001) after treatment. A significant shift in self-reported usual bowel pattern away from "alternating constipation/diarrhea" toward "normal" (p<0.001) was observed. NDI total symptom score significantly decreased by 41% (p<0.001) after treatment. Similarly, there was a significant 20% improvement in the NDI total quality-of-life (QOL) score in the subset after treatment. Conclusion: This report supports previous findings that ALE ameliorates symptoms of IBS, plus improves health-related QOL.

Unsupervised segmentation using Gabor wavelets and statistical features in LIDAR data analysis

In this paper, we address issues in segmentation Of remotely sensed LIDAR (LIght Detection And Ranging) data. The LIDAR data, which were captured by airborne laser scanner, contain 2.5 dimensional (2.5D) terrain surface height information, e.g. houses, vegetation, flat field, river, basin, etc. Our aim in this paper is to segment ground (flat field)from non-ground (houses and high vegetation) in hilly urban areas. By projecting the 2.5D data onto a surface, we obtain a texture map as a grey-level image. Based on the image, Gabor wavelet filters are applied to generate Gabor wavelet features. These features are then grouped into various windows. Among these windows, a combination of their first and second order of statistics is used as a measure to determine the surface properties. The test results have shown that ground areas can successfully be segmented from LIDAR data. Most buildings and high vegetation can be detected. In addition, Gabor wavelet transform can partially remove hill or slope effects in the original data by tuning Gabor parameters.

Evolving features-algorithms knowledge map to support NIDS data intelligence and learning loop architecting – a generalised approach to NIDS pattern feature space knowledge processing

This paper describes a proposed new approach to the Computer Network Security Intrusion Detection Systems (NIDS) application domain knowledge processing focused on a topic map technology-enabled representation of features of the threat pattern space as well as the knowledge of situated efficacy of alternative candidate algorithms for pattern recognition within the NIDS domain. Thus an integrative knowledge representation framework for virtualisation, data intelligence and learning loop architecting in the NIDS domain is described together with specific aspects of its deployment.

Inhibition of 125I-epidermal growth factor binding to murine fibroblasts and keratinocytes by irradiation with ultraviolet-B light

Treatment of murine Swiss 3T3 fibroblasts and XB/2 keratinocytes with UV-B light (302 nm) resulted in a dose-dependent inhibition of [125I] epidermal growth factor (EGF) binding. The light dose required to achieve 50% inhibition of binding in both cell types was 80–85 J/m2 Decreased [125I] platelet-derived growth factor binding was not evoked even by light doses of up to 280 J/m2 UV-B irradiation did not stimultate phosphorylation of the 80 kd protein substrate for protein kinase C. Furthermore, its effect on [125I]EGF binding was not altered as a consequence of protein kinase C down-regulation following prolonged exposure of cells to phorbol esters. These results indicate that UV-B-induced transmodulation of the epidermal growth factor receptor is a specific event mediated through a protein kinase C-indepen dent pathway. Transfer of culture medium from irradiated cells to untreated control cells showed this effect was not induced as a result of transforming growth factor α release and subsequent binding to the EGF receptor in these cells.

The role of seeds and airborne inoculum in the initiation of leaf blotch (Rhynchosporium secalis) epidemics in winter barley

Both airborne spores of Rhynchosporium secalis and seed infection have been implied as major sources of primary inoculum for barley leaf blotch (scald) epidemics in fields without previous history of barley cropping. However, little is known about their relative importance in the onset of disease. Results from both quantitative real-time PCR and visual assessments indicated that seed infection was the main source of inoculum in the field trial conducted in this study. Glasshouse studies established that the pathogen can be transmitted from infected seeds into roots, shoots and leaves without causing symptoms. Plants in the field trial remained symptomless for approximately four months before symptoms were observed in the crop. Covering the crop during part of the growing season was shown to prevent pathogen growth, despite the use of infected seed, indicating that changes in the physiological condition of the plant and/or environmental conditions may trigger disease development. However, once the disease appeared in the field it quickly became uniform throughout the cropping area. Only small amounts of R. secalis DNA were measured in 24 h spore-trap tape samples using PCR. Inoculum levels equivalent to spore concentrations between 30 and 60 spores per m3 of air were only detected on three occasions during the growing season. The temporal pattern and level of detection of R. secalis DNA in spore tape samples indicated that airborne inoculum was limited and most likely represented rain-splashed conidia rather than putative ascospores.

Gas-phase reactions of NO3 and N2O5 with (Z)-hex-4-en-1-ol, (Z)-hex-3-en-1-ol ('leaf alcohol'), (E)-hex-3-en-1-ol, (Z)-hex-2-en-1-ol and (E)-hex-2-en-1-ol

The night-time atmospheric chemistry of the biogenic volatile organic compounds (Z)-hex-4-en-1-ol, (Z)-hex-3-en-1-ol ('leaf alcohol'), (E)-hex-3-en-1-ol, (Z)-hex-2-en-1-ol and (E)-hex-2-en-1-ol, has been studied at room temperature. Rate coefficients for reactions of the nitrate radical (NO3) with these stress-induced plant emissions were measured using the discharge-flow technique. We employed off-axis continuous-wave cavity-enhanced absorption spectroscopy (CEAS) for the detection of NO3, which enabled us to work in excess of the hexenol compounds over NO3. The rate coefficients determined were (2.93 +/- 0.58) x 10(-13) cm(3) molecule(-1) s(-1), (2.67 +/- 0.42) x 10(-13) cm(3) molecule(-1) s(-1), (4.43 +/- 0.91) x 10(-13) cm(3) molecule(-1) s(-1), (1.56 +/- 0.24) x 10(-13) cm(3) molecule(-1) s(-1), and (1.30 +/- 0.24) x 10(-13) cm(3) molecule(-1) s(-1) for (Z)-hex-4-en-1-ol, (Z)-hex-3en-1-ol, (E)-hex-3-en-1-ol, (Z)-hex-2-en-1-ol and (E)-hex-2-en-1-ol. The rate coefficient for the reaction of NO3 with (Z)-hex-3-en-1-ol agrees with the single published determination of the rate coefficient using a relative method. The other rate coefficients have not been measured before and are compared to estimated values. Relative-rate studies were also performed, but required modification of the standard technique because N2O5 (used as the source of NO3) itself reacts with the hexenols. We used varying excesses of NO2 to determine simultaneously rate coefficients for reactions of NO3 and N2O5 with (E)-hex-3-en-1-ol of (5.2 +/- 1.8) x 10(-13) cm(3) molecule(-1) s(-1) and (3.1 +/- 2.3) x 10(-18) cm(3) molecule(-1) s(-1). Our new determinations suggest atmospheric lifetimes with respect to NO3-initiated oxidation of roughly 1-4 h for the hexenols, comparable with lifetimes estimated for the atmospheric degradation by OH and shorter lifetimes than for attack by O-3. Recent measurements of [N2O5] suggest that the gas-phase reactions of N2O5 with unsaturated alcohols will not be of importance under usual atmospheric conditions, but they certainly can be in laboratory systems when determining rate coefficients.

Integrating features for man-made target tracking from FLIR image sequence using particle filter

A new man-made target tracking algorithm integrating features from (Forward Looking InfraRed) image sequence is presented based on particle filter. Firstly, a multiscale fractal feature is used to enhance targets in FLIR images. Secondly, the gray space feature is defined by Bhattacharyya distance between intensity histograms of the reference target and a sample target from MFF (Multi-scale Fractal Feature) image. Thirdly, the motion feature is obtained by differencing between two MFF images. Fourthly, a fusion coefficient can be automatically obtained by online feature selection method for features integrating based on fuzzy logic. Finally, a particle filtering framework is developed to fulfill the target tracking. Experimental results have shown that the proposed algorithm can accurately track weak or small man-made target in FLIR images with complicated background. The algorithm is effective, robust and satisfied to real time tracking.

Final report on research project PS2010, proof of concept of automated mapping of weeds in arable fields

Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).