Comparative genetic analyses point to HCP5 as susceptibility locus for HCV-associated hepatocellular carcinoma

BACKGROUND & AIMS: Recently, genetic variations in MICA (lead single nucleotide polymorphism [SNP] rs2596542) were identified by a genome-wide association study (GWAS) to be associated with hepatitis C virus (HCV)-related hepatocellular carcinoma (HCC) in Japanese patients. In the present study, we sought to determine whether this SNP is predictive of HCC development in the Caucasian population as well. METHODS: An extended region around rs2596542 was genotyped in 1924 HCV-infected patients from the Swiss Hepatitis C Cohort Study (SCCS). Pair-wise correlation between key SNPs was calculated both in the Japanese and European populations (HapMap3: CEU and JPT). RESULTS: To our surprise, the minor allele A of rs2596542 in proximity of MICA appeared to have a protective impact on HCC development in Caucasians, which represents an inverse association as compared to the one observed in the Japanese population. Detailed fine-mapping analyses revealed a new SNP in HCP5 (rs2244546) upstream of MICA as strong predictor of HCV-related HCC in the SCCS (univariable p=0.027; multivariable p=0.0002, odds ratio=3.96, 95% confidence interval=1.90-8.27). This newly identified SNP had a similarly directed effect on HCC in both Caucasian and Japanese populations, suggesting that rs2244546 may better tag a putative true variant than the originally identified SNPs. CONCLUSIONS: Our data confirms the MICA/HCP5 region as susceptibility locus for HCV-related HCC and identifies rs2244546 in HCP5 as a novel tagging SNP. In addition, our data exemplify the need for conducting meta-analyses of cohorts of different ethnicities in order to fine map GWAS signals.

Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches

In patients diagnosed with pharmaco-resistant epilepsy, cerebral areas responsible for seizure generation can be defined by performing implantation of intracranial electrodes. The identification of the epileptogenic zone (EZ) is based on visual inspection of the intracranial electroencephalogram (IEEG) performed by highly qualified neurophysiologists. New computer-based quantitative EEG analyses have been developed in collaboration with the signal analysis community to expedite EZ detection. The aim of the present report is to compare different signal analysis approaches developed in four different European laboratories working in close collaboration with four European Epilepsy Centers. Computer-based signal analysis methods were retrospectively applied to IEEG recordings performed in four patients undergoing pre-surgical exploration of pharmaco-resistant epilepsy. The four methods elaborated by the different teams to identify the EZ are based either on frequency analysis, on nonlinear signal analysis, on connectivity measures or on statistical parametric mapping of epileptogenicity indices. All methods converge on the identification of EZ in patients that present with fast activity at seizure onset. When traditional visual inspection was not successful in detecting EZ on IEEG, the different signal analysis methods produced highly discordant results. Quantitative analysis of IEEG recordings complement clinical evaluation by contributing to the study of epileptogenic networks during seizures. We demonstrate that the degree of sensitivity of different computer-based methods to detect the EZ in respect to visual EEG inspection depends on the specific seizure pattern.

Computed Ultrasound Tomography in Echo mode (CUTE) of speed of sound for diagnosis and for aberration correction in pulse-echo sonography

Sound speed as a diagnostic marker for various diseases of human tissue has been of interest for a while. Up to now, mostly transmission ultrasound computed tomography (UCT) was able to detect spatially resolved sound speed, and its promise as a diagnostic tool has been demonstrated. However, UCT is limited to acoustically transparent samples such as the breast. We present a novel technique where spatially resolved detection of sound speed can be achieved using conventional pulse-echo equipment in reflection mode. For this purpose, pulse-echo images are acquired under various transmit beam directions and a two-dimensional map of the sound speed is reconstructed from the changing phase of local echoes using a direct reconstruction method. Phantom results demonstrate that a high spatial resolution (1 mm) and contrast (0.5 % of average sound speed) can be achieved suitable for diagnostic purposes. In comparison to previous reflection-mode based methods, CUTE works also in a situation with only diffuse echoes, and its direct reconstruction algorithm enables real-time application. This makes it suitable as an addition to conventional clinical ultrasound where it has the potential to benefit diagnosis in a multimodal approach. In addition, knowledge of the spatial distribution of sound speed allows full aberration correction and thus improved spatial resolution and contrast of conventional B-mode ultrasound. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

A review of fluorescent ligands for studying 5-HT3 receptors

The use of fluorescence is a valuable and increasingly accessible means of probing the pharmacology and physiology of cells and their receptors. To date, the use of fluorescence-based methods for 5-HT3 receptor research has been quite limited and, although a variety of approaches have been described, these are broadly distributed throughout the literature. In this review we condense these findings into a single, accessible source of reference with the hope of promoting the use of these valuable molecular probes.

Kuishi Pamoja: To live together

Comic book for farmers demonstrating community-based methods for alleviating human-elephant conflict.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as a fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range-based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranges and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1:3m for mean accuracy and 2:2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

Microbiota at teeth and implants in partially edentulous patients. A 10-year retrospective study.

OBJECTIVE To determine the microbiota at implants and adjacent teeth 10 years after placement of implants with a sandblasted and acid-etched surface. MATERIAL AND METHODS Plaque samples obtained from the deepest sites of 504 implants and of 493 adjacent teeth were analyzed for certain bacterial species associated with periodontitis, for staphylococci, for aerobic gram-negative rods, and for yeasts using nucleic acid-based methods. RESULTS Species known to be associated with periodontitis were detectable at 6.2-78.4% of the implants. Significantly higher counts at implants in comparison with teeth were assessed for Tannerella forsythia, Parvimonas micra, Fusobacterium nucleatum/necrophorum, and Campylobacter rectus. Higher counts of periodontopathogenic species were detectable at implants of current smokers than at those of non-smokers. In addition, those species were found in higher quantities at implants of subjects with periodontitis. The prevalence of Prevotella intermedia, Treponema denticola, C. rectus, and moreover of Staphylococcus warneri might be associated with peri-implant inflammation. Selected staphylococcal species (not Staphylococcus aureus), aerobic gram-negative rods, and yeasts were frequently detected, but with the exception of S. warneri, they did not show any association with periodontal or peri-implant diseases. CONCLUSIONS Smoking and periodontal disease are risk factors for colonization of periodontopathic bacteria at implants. Those bacterial species may play a potential role in peri-implant inflammation. The role of S. warneri needs further validation.

Methodologies for the Analysis of HCV-Specific CD4(+) T Cells

Virus-specific CD4(+) T cells play a major role in viral infections, such as hepatitis C virus (HCV). Viral clearance is associated with vigorous and multi-specific CD4(+) T-cell responses, while chronic infection has been shown to be associated with weak or absent T-cell responses. Most of these studies have used functional assays to analyze virus-specific CD4(+) T-cell responses; however, these and other detection methods have various limitations. Therefore, the important question of whether virus-specific CD4(+) T cells are completely absent or primarily impaired in specific effector functions during chronic infection, has yet to be analyzed in detail. A novel assay, in which virus-specific CD4(+) T-cell frequencies can be determined by de novo CD154 (CD40 ligand) expression in response to viral antigens, can help to overcome some of the limitations of functional assays and restrictions of multimer-based methods. This and other current established methods for the detection of HCV-specific CD4(+) T cells will be discussed in this review.

SOP: Parallel surrogate global optimization with Pareto center selection for computationally expensive single objective problems

This paper presents a parallel surrogate-based global optimization method for computationally expensive objective functions that is more effective for larger numbers of processors. To reach this goal, we integrated concepts from multi-objective optimization and tabu search into, single objective, surrogate optimization. Our proposed derivative-free algorithm, called SOP, uses non-dominated sorting of points for which the expensive function has been previously evaluated. The two objectives are the expensive function value of the point and the minimum distance of the point to previously evaluated points. Based on the results of non-dominated sorting, P points from the sorted fronts are selected as centers from which many candidate points are generated by random perturbations. Based on surrogate approximation, the best candidate point is subsequently selected for expensive evaluation for each of the P centers, with simultaneous computation on P processors. Centers that previously did not generate good solutions are tabu with a given tenure. We show almost sure convergence of this algorithm under some conditions. The performance of SOP is compared with two RBF based methods. The test results show that SOP is an efficient method that can reduce time required to find a good near optimal solution. In a number of cases the efficiency of SOP is so good that SOP with 8 processors found an accurate answer in less wall-clock time than the other algorithms did with 32 processors.

Citrullination in the periodontium-a possible link between periodontitis and rheumatoid arthritis

OBJECTIVES The aim of the present study was to assess human and bacterial peptidylarginine deiminase (PAD) activity in the gingival crevicular fluid (GCF) in the context of serum levels of antibodies against citrullinated epitopes in rheumatoid arthritis and periodontitis. MATERIALS AND METHODS Human PAD and Porphyromonas gingivalis-derived enzyme (PPAD) activities were measured in the GCF of 52 rheumatoid arthritis (RA) patients (48 with periodontitis and 4 without) and 44 non-RA controls (28 with periodontitis and 16 without). Serum antibodies against citrullinated epitopes were measured by ELISA. Bacteria being associated with periodontitis were determined by nucleic-acid-based methods. RESULTS Citrullination was present in 26 (50 %) RA patients and 23 (48 %) controls. PAD and PPAD activities were detected in 36 (69 %) and 30 (58 %) RA patients, respectively, and in 30 (68 %) and 21 (50 %) controls, respectively. PPAD activity was higher in RA and non-RA patients with periodontitis than in those without (p = 0.038; p = 0.004), and was detected in 35 of 59 P. gingivalis-positive samples, and in 16 of 37 P. gingivalis-negative samples in association with high antibody levels against that species. CONCLUSIONS PAD and PPAD activities within the periodontium are elevated in RA and non-RA patients with periodontitis. PPAD secreted by P. gingivalis residing in epithelial cells may exert its citrullinating activity in distant regions of the periodontium or even distant tissues. CLINICAL RELEVANCE In periodontitis, the citrullination of proteins/peptides by human and bacterial peptidylarginine deiminases may generate antibodies after breaching immunotolerance in susceptible individuals.

Fine-grained indoor positioning and tracking systems

Indoor positioning has attracted considerable attention for decades due to the increasing demands for location based services. In the past years, although numerous methods have been proposed for indoor positioning, it is still challenging to find a convincing solution that combines high positioning accuracy and ease of deployment. Radio-based indoor positioning has emerged as a dominant method due to its ubiquitousness, especially for WiFi. RSSI (Received Signal Strength Indicator) has been investigated in the area of indoor positioning for decades. However, it is prone to multipath propagation and hence fingerprinting has become the most commonly used method for indoor positioning using RSSI. The drawback of fingerprinting is that it requires intensive labour efforts to calibrate the radio map prior to experiments, which makes the deployment of the positioning system very time consuming. Using time information as another way for radio-based indoor positioning is challenged by time synchronization among anchor nodes and timestamp accuracy. Besides radio-based positioning methods, intensive research has been conducted to make use of inertial sensors for indoor tracking due to the fast developments of smartphones. However, these methods are normally prone to accumulative errors and might not be available for some applications, such as passive positioning. This thesis focuses on network-based indoor positioning and tracking systems, mainly for passive positioning, which does not require the participation of targets in the positioning process. To achieve high positioning accuracy, we work on some information of radio signals from physical-layer processing, such as timestamps and channel information. The contributions in this thesis can be divided into two parts: time-based positioning and channel information based positioning. First, for time-based indoor positioning (especially for narrow-band signals), we address challenges for compensating synchronization offsets among anchor nodes, designing timestamps with high resolution, and developing accurate positioning methods. Second, we work on range-based positioning methods with channel information to passively locate and track WiFi targets. Targeting less efforts for deployment, we work on range-based methods, which require much less calibration efforts than fingerprinting. By designing some novel enhanced methods for both ranging and positioning (including trilateration for stationary targets and particle filter for mobile targets), we are able to locate WiFi targets with high accuracy solely relying on radio signals and our proposed enhanced particle filter significantly outperforms the other commonly used range-based positioning algorithms, e.g., a traditional particle filter, extended Kalman filter and trilateration algorithms. In addition to using radio signals for passive positioning, we propose a second enhanced particle filter for active positioning to fuse inertial sensor and channel information to track indoor targets, which achieves higher tracking accuracy than tracking methods solely relying on either radio signals or inertial sensors.

How specific is apprenticeship training? Evidence from inter-firm and occupational mobility after graduation

Do apprenticeships convey mainly general or also firm- and occupation-specific human capital? Specific human capital may allow for specialization gains, but may also lead to allocative inefficiency due to mobility barriers. We analyse the case of Switzerland, which combines a comprehensive, high-quality apprenticeship system with a lightly regulated labour market. To assess human capital transferability after standardized firm-based apprenticeship training, we analyse inter-firm and occupational mobility and their effects on post-training wages. Using a longitudinal data set based on the PISA 2000 survey, we find high inter-firm and low occupational mobility within one year after graduation. Accounting for endogenous changes, we find a negative effect of occupation changes on wages, but no significant wage effect for firm changes. This indicates that occupation-specific human capital is an important component of apprenticeship training and that skills are highly transferable within an occupational field.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranging and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1.3m for mean accuracy and 2.2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

Derivation of Change from Sequences of Snapshots

Current research in the domain of geographic information science considers possibilities of including another dimension, time, which is generally missing to this point. Users interested in changes have few functions available to compare datasets of spatial configurations at different points in time. Such a comparison of spatial configurations requires large amounts of manual labor. An automatic derivation of changes would decrease amounts of manual labor. The thesis introduces a set of methods that allows for an automatic derivation of changes. These methods analyze identity and topological states of objects in snapshots and derive types of change for the specific configuration of data. The set of change types that can be computed by the methods presented includes continuous changes such as growing, shrinking, and moving of objects. For these continuous changes identity remains unchanged, while topological relations might be altered over time. Also discrete changes such as merging and splitting where both identity and topology are affected can be derived. Evaluation of the methods using a prototype application with simple examples suggests that the methods compute uniquely and correctly the type of change that applied in spatial scenarios captured in two snapshots.

Delineating the molecular basis of human genetic diseases: Epigenetic and functional studies

Identifying and characterizing the genes responsible for inherited human diseases will ultimately lead to a more holistic understanding of disease pathogenesis, catalyze new diagnostic and treatment modalities, and provide insights into basic biological processes. This dissertation presents research aimed at delineating the genetic and molecular basis of human diseases through epigenetic and functional studies and can be divided into two independent areas of research. The first area of research describes the development of two high-throughput melting curve based methods to assay DNA methylation, referred to as McMSP and McCOBRA. The goal of this project was to develop DNA methylation methods that can be used to rapidly determine the DNA methylation status at a specific locus in a large number of samples. McMSP and McCOBRA provide several advantages over existing methods, as they are simple, accurate, robust, and high-throughput making them applicable to large-scale DNA methylation studies. McMSP and McCOBRA were then used in an epigenetic study of the complex disease Ankylosing spondylitis (AS). Specifically, I tested the hypothesis that aberrant patterns of DNA methylation in five AS candidate genes contribute to disease susceptibility. While no statistically significant methylation differences were observed between cases and controls, this is the first study to investigate the hypothesis that epigenetic variation contributes to AS susceptibility and therefore provides the conceptual framework for future studies. ^ In the second area of research, I performed experiments to better delimit the function of aryl hydrocarbon receptor-interacting protein-like 1 (AIPL1), which when mutated causes various forms of inherited blindness such as Leber congenital amaurosis. A yeast two-hybrid screen was performed to identify putative AIPL1-interacting proteins. After screening 2 × 106 bovine retinal cDNA library clones, 6 unique putative AIPL1-interacting proteins were identified. While these 6 AIPL1 protein-protein interactions must be confirmed, their identification is an important step in understanding the functional role of AIPL1 within the retina and will provide insight into the molecular mechanisms underlying inherited blindness. ^