The presence of Helicobacter pylori in the liver depends on the Th1, Th17 and Treg cytokine profile of the patient

The hypothesis that Helicobactermight be a risk factor for human liver diseases has arisen after the detection of Helicobacter DNA in hepatic tissue of patients with hepatobiliary diseases. Nevertheless, no explanation that justifies the presence of the bacterium in the human liver has been proposed. We evaluated the presence of Helicobacterin the liver of patients with hepatic diseases of different aetiologies. We prospectively evaluated 147 patients (106 with primary hepatic diseases and 41 with hepatic metastatic tumours) and 20 liver donors as controls. Helicobacter species were investigated in the liver by culture and specific 16S rDNA nested-polymerase chain reaction followed by sequencing. Serum and hepatic levels of representative cytokines of T regulatory cell, T helper (Th)1 and Th17 cell lineages were determined using enzyme linked immunosorbent assay. The data were evaluated using logistic models. Detection of Helicobacter pylori DNA in the liver was independently associated with hepatitis B virus/hepatitis C virus, pancreatic carcinoma and a cytokine pattern characterised by high interleukin (IL)-10, low/absent interferon-γ and decreased IL-17A concentrations (p < 10-3). The bacterial DNA was never detected in the liver of patients with alcoholic cirrhosis and autoimmune hepatitis that are associated with Th1/Th17 polarisation. H. pylori may be observed in the liver of patients with certain hepatic and pancreatic diseases, but this might depend on the patient cytokine profile.

Heel and toe clearance estimation for gait analysis using wireless inertial sensors.

Tripping is considered a major cause of fall in older people. Therefore, foot clearance (i.e., height of the foot above ground during swing phase) could be a key factor to better understand the complex relationship between gait and falls. This paper presents a new method to estimate clearance using a foot-worn and wireless inertial sensor system. The method relies on the computation of foot orientation and trajectory from sensors signal data fusion, combined with the temporal detection of toe-off and heel-strike events. Based on a kinematic model that automatically estimates sensor position relative to the foot, heel and toe trajectories are estimated. 2-D and 3-D models are presented with different solving approaches, and validated against an optical motion capture system on 12 healthy adults performing short walking trials at self-selected, slow, and fast speed. Parameters corresponding to local minimum and maximum of heel and toe clearance were extracted and showed accuracy ± precision of 4.1 ± 2.3 cm for maximal heel clearance and 1.3 ± 0.9 cm for minimal toe clearance compared to the reference. The system is lightweight, wireless, easy to wear and to use, and provide a new and useful tool for routine clinical assessment of gait outside a dedicated laboratory.

Development of a two-step screening ESI-TOF-MS method for rapid determination of significant stress-induced metabolome modifications in plant leaf extracts: the wound response in Arabidopsis thaliana as a case study.

To study the stress-induced effects caused by wounding under a new perspective, a metabolomic strategy based on HPLC-MS has been devised for the model plant Arabidopsis thaliana. To detect induced metabolites and precisely localise these compounds among the numerous constitutive metabolites, HPLC-MS analyses were performed in a two-step strategy. In a first step, rapid direct TOF-MS measurements of the crude leaf extract were performed with a ballistic gradient on a short LC-column. The HPLC-MS data were investigated by multivariate analysis as total mass spectra (TMS). Principal components analysis (PCA) and hierarchical cluster analysis (HCA) on principal coordinates were combined for data treatment. PCA and HCA demonstrated a clear clustering of plant specimens selecting the highest discriminating ions given by the complete data analysis, leading to the specific detection of discrete-induced ions (m/z values). Furthermore, pool constitution with plants of homogeneous behaviour was achieved for confirmatory analysis. In this second step, long high-resolution LC profilings on an UPLC-TOF-MS system were used on pooled samples. This allowed to precisely localise the putative biological marker induced by wounding and by specific extraction of accurate m/z values detected in the screening procedure with the TMS spectra.

Characterization and management of rockslide hazard at Turtle Mountain, Alberta, Canada

In 1903, more than 30 million m3 of rock fell from the east slopes of Turtle Mountain in Alberta, Canada, causing a rock avalanche that killed about 70 people in the town of Frank. The Alberta Government, in response to continuing instabilities at the crest of the mountain, established a sophisticated field laboratory where state-of-the-art monitoring techniques have been installed and tested as part of an early-warning system. In this chapter, we provide an overview of the causes, trigger, and extreme mobility of the landslide. We then present new data relevant to the characterization and detection of the present-day instabilities on Turtle Mountain. Fourteen potential instabilities have been identified through field mapping and remote sensing. Lastly, we provide a detailed review of the different in-situ and remote monitoring systems that have been installed on the mountain. The implications of the new data for the future stability of Turtle Mountain and related landslide runout, and for monitoring strategies and risk management, are discussed.

Microwave-assisted solvent extraction and analysis of shikimic acid from plant tissues

A better method for determination of shikimate in plant tissues is needed to monitor exposure of plants to the herbicide glyphosate [N-(phosphonomethyl)glycine] and to screen the plant kingdom for high levels of this valuable phytochemical precursor to the pharmaceutical oseltamivir. A simple, rapid, and efficient method using microwave-assisted extraction (MWAE) with water as the extraction solvent was developed for the determination of shikimic acid in plant tissues. High performance liquid chromatography was used for the separation of shikimic acid, and chromatographic data were acquired using photodiode array detection. This MWAE technique was successful in recovering shikimic acid from a series of fortified plant tissues at more than 90% efficiency with an interference-free chromatogram. This allowed the use of lower amounts of reagents and organic solvents, reducing the use of toxic and/or hazardous chemicals, as compared to currently used methodologies. The method was used to determine the level of endogenous shikimic acid in several species of Brachiaria and sugarcane (Saccharum officinarum) and on B. decumbens and soybean (Glycine max) after treatment with glyphosate. The method was sensitive, rapid and reliable in all cases.

Novel regulatory SNPs in the promoter region of the TNFRSF18 gene in a Gabonese population

Parasites are accountable for driving diversity within immune gene families. We identified and investigated regulatory single nucleotide polymorphisms (SNPs) in the promoter regions of the tumor necrosis factor receptor superfamily member 18 (TNFRSF18) gene by direct sequencing in a group of male Gabonese individuals exposed to a wide array of parasitic diseases such as malaria, filariasis and schistosomiasis. Two new promoter variants were identified in 40 individuals. Both novel variants were heterozygous and were linked to SNP #rs3753344 (C/T), which has been described. One of the SNP variants (ss2080581728) was close to the general transcription factor site, the TATA box. We further validated these new promoter variants for their allelic gene expression using transient transfection assays. One new promoter variant with two base changes (C/T - ss2080581728/rs3753344) displayed an altered expression of the marker gene. Both novel variants remained less active at the non-induced state in comparison to the major allele. The allele frequencies observed in this study were consistent with data for other African populations. The detection and analysis of these human immune gene polymorphisms contribute to a better understanding of the interaction between host-parasite and expression of Treg activity.

AN ARTIFICIAL NEURAL NETWORK FOR SONAR TARGET DETECTION

Neural Network has emerged as the topic of the day. The spectrum of its application is as wide as from ECG noise filtering to seismic data analysis and from elementary particle detection to electronic music composition. The focal point of the proposed work is an application of a massively parallel connectionist model network for detection of a sonar target. This task is segmented into: (i) generation of training patterns from sea noise that contains radiated noise of a target, for teaching the network;(ii) selection of suitable network topology and learning algorithm and (iii) training of the network and its subsequent testing where the network detects, in unknown patterns applied to it, the presence of the features it has already learned in. A three-layer perceptron using backpropagation learning is initially subjected to a recursive training with example patterns (derived from sea ambient noise with and without the radiated noise of a target). On every presentation, the error in the output of the network is propagated back and the weights and the bias associated with each neuron in the network are modified in proportion to this error measure. During this iterative process, the network converges and extracts the target features which get encoded into its generalized weights and biases.In every unknown pattern that the converged network subsequently confronts with, it searches for the features already learned and outputs an indication for their presence or absence. This capability for target detection is exhibited by the response of the network to various test patterns presented to it.Three network topologies are tried with two variants of backpropagation learning and a grading of the performance of each combination is subsequently made.

News from compositions, the R package

The R-package “compositions”is a tool for advanced compositional analysis. Its basic functionality has seen some conceptual improvement, containing now some facilities to work with and represent ilr bases built from balances, and an elaborated subsys- tem for dealing with several kinds of irregular data: (rounded or structural) zeroes, incomplete observations and outliers. The general approach to these irregularities is based on subcompositions: for an irregular datum, one can distinguish a “regular” sub- composition (where all parts are actually observed and the datum behaves typically) and a “problematic” subcomposition (with those unobserved, zero or rounded parts, or else where the datum shows an erratic or atypical behaviour). Systematic classification schemes are proposed for both outliers and missing values (including zeros) focusing on the nature of irregularities in the datum subcomposition(s). To compute statistics with values missing at random and structural zeros, a projection approach is implemented: a given datum contributes to the estimation of the desired parameters only on the subcompositon where it was observed. For data sets with values below the detection limit, two different approaches are provided: the well-known imputation technique, and also the projection approach. To compute statistics in the presence of outliers, robust statistics are adapted to the characteristics of compositional data, based on the minimum covariance determinant approach. The outlier classification is based on four different models of outlier occur- rence and Monte-Carlo-based tests for their characterization. Furthermore the package provides special plots helping to understand the nature of outliers in the dataset. Keywords: coda-dendrogram, lost values, MAR, missing data, MCD estimator, robustness, rounded zeros

Biologically motivated model for object detection and identification in real-world scenes

The classical computer vision methods can only weakly emulate some of the multi-level parallelisms in signal processing and information sharing that takes place in different parts of the primates’ visual system thus enabling it to accomplish many diverse functions of visual perception. One of the main functions of the primates’ vision is to detect and recognise objects in natural scenes despite all the linear and non-linear variations of the objects and their environment. The superior performance of the primates’ visual system compared to what machine vision systems have been able to achieve to date, motivates scientists and researchers to further explore this area in pursuit of more efficient vision systems inspired by natural models. In this paper building blocks for a hierarchical efficient object recognition model are proposed. Incorporating the attention-based processing would lead to a system that will process the visual data in a non-linear way focusing only on the regions of interest and hence reducing the time to achieve real-time performance. Further, it is suggested to modify the visual cortex model for recognizing objects by adding non-linearities in the ventral path consistent with earlier discoveries as reported by researchers in the neuro-physiology of vision.

Design and evaluation of intelligent classifier based intrusion detection system

We have discovered a novel approach of intrusion detection system using an intelligent data classifier based on a self organizing map (SOM). We have surveyed all other unsupervised intrusion detection methods, different alternative SOM based techniques and KDD winner IDS methods. This paper provides a robust designed and implemented intelligent data classifier technique based on a single large size (30x30) self organizing map (SOM) having the capability to detect all types of attacks given in the DARPA Archive 1999 the lowest false positive rate being 0.04 % and higher detection rate being 99.73% tested using full KDD data sets and 89.54% comparable detection rate and 0.18% lowest false positive rate tested using corrected data sets.

Nickel hydroxide electrodes as amperometric detectors for carbohydrates in flow injection analysis and liquid chromatography

The present paper describes the utilization of nickel hydroxide modified electrodes toward the catalytic oxidation of carbohydrates (glucose, fructose, lactose and sucrose) and their utilization as electrochemical sensor. The modified electrodes were employed as a detector in flow injection analysis for individual carbohydrate detection, and to an ionic column chromatography system for multi-analyte samples aiming a prior separation step. Kinetic studies were performed on a rotating disk electrode (RDE) in order to determine both the heterogeneous rate constant and number of electrons transferred for each carbohydrate. Many advantages were found for the proposed system including fast and easy handling of the electrode modification, low cost procedure, a wide range of linearity (0.5-50 ppm), low detection limits (ppb level) and high sensitivities. (C) 2009 Elsevier B.V. All rights reserved.

Orientação indireta de imagens com uso de apoio fotogramétrico extraído a partir da integração de dados derivados do sistema lidar e fotogrametria

In this work a method is proposed to allow the indirect orientation of images using photogrammetric control extracted through integration of data derived from Photogrammetry and Light Detection and Ranging (LiDAR) system. The photogrammetric control is obtained by using an inverse photogrammetric model, which allows the projection of image space straight lines onto the object space. This mathematical model is developed based on the intersection between the collinearity-based straight line and a DSM of region, derived from LiDAR data. The mathematical model used in the indirect orientation of the image is known as the model of equivalent t planes. This mathematical model is based on the equivalence between the vector normal to the projection plane in the image space and to the vector normal to the rotated projection plane in the object space. The goal of this work is to verify the quality, efficiency and potential of photogrammetric control straight lines obtained with proposed method applied to the indirect orientation of images. The quality of generated photogrammetric control was statistically available and the results showed that proposed method is promising and it has potential for the indirect orientation of images.

Toward the Optimization of an e-Tongue System Using Information Visualization: A Case Study with Perylene Tetracarboxylic Derivative Films in the Sensing Units

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Occurrence of fungi in water used at a haemodialysis centre

Aims: The aim of this study was to identify and determine the diversity, occurrence and distribution of fungi in water used at a haemodialysis centre.Methods and Results: Samples in the hydraulic circuit for the distribution of the water, dialysate samples and samples of sterilization solution from dialysers were collected over a 3-month period, and 500 ml of each sample was filtered through membranes. All together 116 isolates of fungi were recovered from 89% of all water samples collected inside the haemodialysis unit, with prevalence of moulds in tap water samples and of yeasts in dialysate samples. Fusarium spp. was the most abundant genus found, whereas Candida parapsilosis was the predominant yeast species.Conclusions: This study demonstrated that various fungi were present in the water system. These data suggest the inclusion of the detection and quantification of fungi in the water of haemodialysis.Significance and Impact of the Study: The recovery of fungi from aqueous haemodialysis environments implies a potential risk for haemodialysis patients and indicates the need for continuous maintenance and monitoring. Further studies on fungi in haemodialysis water systems are required to investigate the organism ability to persist, their role in biofilm formation and their clinical significance.

An attack signature model to computer security intrusion detection

Internal and external computer network attacks or security threats occur according to standards and follow a set of subsequent steps, allowing to establish profiles or patterns. This well-known behavior is the basis of signature analysis intrusion detection systems. This work presents a new attack signature model to be applied on network-based intrusion detection systems engines. The AISF (ACME! Intrusion Signature Format) model is built upon XML technology and works on intrusion signatures handling and analysis, from storage to manipulation. Using this new model, the process of storing and analyzing information about intrusion signatures for further use by an IDS become a less difficult and standardized process.