The Acute STroke Registry and Analysis of Lausanne (ASTRAL): design and baseline analysis of an ischemic stroke registry including acute multimodal imaging.

BACKGROUND AND PURPOSE: Stroke registries are valuable tools for obtaining information about stroke epidemiology and management. The Acute STroke Registry and Analysis of Lausanne (ASTRAL) prospectively collects epidemiological, clinical, laboratory and multimodal brain imaging data of acute ischemic stroke patients in the Centre Hospitalier Universitaire Vaudois (CHUV). Here, we provide design and methods used to create ASTRAL and present baseline data of our patients (2003 to 2008). METHODS: All consecutive patients admitted to CHUV between January 1, 2003 and December 31, 2008 with acute ischemic stroke within 24 hours of symptom onset were included in ASTRAL. Patients arriving beyond 24 hours, with transient ischemic attack, intracerebral hemorrhage, subarachnoidal hemorrhage, or cerebral sinus venous thrombosis, were excluded. Recurrent ischemic strokes were registered as new events. RESULTS: Between 2003 and 2008, 1633 patients and 1742 events were registered in ASTRAL. There was a preponderance of males, even in the elderly. Cardioembolic stroke was the most frequent type of stroke. Most strokes were of minor severity (National Institute of Health Stroke Scale [NIHSS] score ≤ 4 in 40.8% of patients). Cardioembolic stroke and dissections presented with the most severe clinical picture. There was a significant number of patients with unknown onset stroke, including wake-up stroke (n=568, 33.1%). Median time from last-well time to hospital arrival was 142 minutes for known onset and 759 minutes for unknown-onset stroke. The rate of intravenous or intraarterial thrombolysis between 2003 and 2008 increased from 10.8% to 20.8% in patients admitted within 24 hours of last-well time. Acute brain imaging was performed in 1695 patients (97.3%) within 24 hours. In 1358 patients (78%) who underwent acute computed tomography angiography, 717 patients (52.8%) had significant abnormalities. Of the 1068 supratentorial stroke patients who underwent acute perfusion computed tomography (61.3%), focal hypoperfusion was demonstrated in 786 patients (73.6%). CONCLUSIONS: This hospital-based prospective registry of consecutive acute ischemic strokes incorporates demographic, clinical, metabolic, acute perfusion, and arterial imaging. It is characterized by a high proportion of minor and unknown-onset strokes, short onset-to-admission time for known-onset patients, rapidly increasing thrombolysis rates, and significant vascular and perfusion imaging abnormalities in the majority of patients.

The design and characterization of receptor-selective APRIL variants.

A proliferation-inducing ligand (APRIL), a member of the TNF ligand superfamily with an important role in humoral immunity, is also implicated in several cancers as a prosurvival factor. APRIL binds two different TNF receptors, B cell maturation antigen (BCMA) and transmembrane activator and cylclophilin ligand interactor (TACI), and also interacts independently with heparan sulfate proteoglycans. Because APRIL shares binding of the TNF receptors with B cell activation factor, separating the precise signaling pathways activated by either ligand in a given context has proven quite difficult. In this study, we have used the protein design algorithm FoldX to successfully generate a BCMA-specific variant of APRIL, APRIL-R206E, and two TACI-selective variants, D132F and D132Y. These APRIL variants show selective activity toward their receptors in several in vitro assays. Moreover, we have used these ligands to show that BCMA and TACI have a distinct role in APRIL-induced B cell stimulation. We conclude that these ligands are useful tools for studying APRIL biology in the context of individual receptor activation.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

From e-voting to smart-voting : e-Tools in and for elections and direct democracy in Switzerland

To what extent do and could e-tools contribute to a democracy like Switzerland? This paper puts forward experiences and visions concerning the application of e-tools for the most traditional democratic processes- elections and, of special importance in Switzerland, direct-democratic votes.Having the particular voting behaviour of the Swiss electorate in mind (low voter turnout - especially among the youngest age group, low political knowledge, etc.) we believe that e-tools which provide information in the forefront of elections or direct-democratic votes offer an enormous service to the voter. As soon as e-voting will be possible in Switzerland (as planned by the government), those e-tools for gathering information online will become indispensable and will gain power enormously. Therefore political scientists should not only focus on potential effects of e-voting itself but rather on the combination of (connected)e-tools of the pre-voting and the voting sphere. In the case of Switzerland, we argue in this paper, the offer of VAAs such as smartvote for elections and direct-democratic votes can provide the voter with more balanced and qualitatively higher information and thereby make a valuable contribution to the Swiss democracy.

Design and evaluation of a solid sampler for the monitoring of airborne 1,6-hexamethylene diisocyanate (HDI) and its prepolymers in 2-component spray painting

An active, solvent-free solid sampler was developed for the collection of 1,6-hexamethylene diisocyanate (HDI) aerosol and prepolymers. The sampler was made of a filter impregnated with 1-(2-methoxyphenyl)piperazine contained in a filter holder. Interferences with HDI were observed when a set of cellulose acetate filters and a polystyrene filter holder were used; a glass fiber filter and polypropylene filter cassette gave better results. The applicability of the sampling and analytical procedure was validated with a test chamber, constructed for the dynamic generation of HDI aerosol and prepolymers in commercial two-component spray paints (Desmodur(R) N75) used in car refinishing. The particle size distribution, temporal stability, and spatial uniformity of the simulated aerosol were established in order to test the sample. The monitoring of aerosol concentrations was conducted with the solid sampler paired to the reference impinger technique (impinger flasks contained 10 mL of 0.5 mg/mL 1-(2-methoxyphenyl)piperazine in toluene) under a controlled atmosphere in the test chamber. Analyses of derivatized HDI and prepolymers were carried out by using high-performance liquid chromatography and ultraviolet detection. The correlation between the solvent-free and the impinger techniques appeared fairly good (Y = 0.979X - 0.161; R = 0.978), when the tests were conducted in the range of 0.1 to 10 times the threshold limit value (TLV) for HDI monomer and up to 60-mu-g/m3 (3 U.K. TLVs) for total -N = C = O groups.

Design and analysis of ChIP-Seq experiments for nuclear factor I DNA-binding proteins

SUMMARY : Eukaryotic DNA interacts with the nuclear proteins using non-covalent ionic interactions. Proteins can recognize specific nucleotide sequences based on the sterical interactions with the DNA and these specific protein-DNA interactions are the basis for many nuclear processes, e.g. gene transcription, chromosomal replication, and recombination. New technology termed ChIP-Seq has been recently developed for the analysis of protein-DNA interactions on a whole genome scale and it is based on immunoprecipitation of chromatin and high-throughput DNA sequencing procedure. ChIP-Seq is a novel technique with a great potential to replace older techniques for mapping of protein-DNA interactions. In this thesis, we bring some new insights into the ChIP-Seq data analysis. First, we point out to some common and so far unknown artifacts of the method. Sequence tag distribution in the genome does not follow uniform distribution and we have found extreme hot-spots of tag accumulation over specific loci in the human and mouse genomes. These artifactual sequence tags accumulations will create false peaks in every ChIP-Seq dataset and we propose different filtering methods to reduce the number of false positives. Next, we propose random sampling as a powerful analytical tool in the ChIP-Seq data analysis that could be used to infer biological knowledge from the massive ChIP-Seq datasets. We created unbiased random sampling algorithm and we used this methodology to reveal some of the important biological properties of Nuclear Factor I DNA binding proteins. Finally, by analyzing the ChIP-Seq data in detail, we revealed that Nuclear Factor I transcription factors mainly act as activators of transcription, and that they are associated with specific chromatin modifications that are markers of open chromatin. We speculate that NFI factors only interact with the DNA wrapped around the nucleosome. We also found multiple loci that indicate possible chromatin barrier activity of NFI proteins, which could suggest the use of NFI binding sequences as chromatin insulators in biotechnology applications. RESUME : L'ADN des eucaryotes interagit avec les protéines nucléaires par des interactions noncovalentes ioniques. Les protéines peuvent reconnaître les séquences nucléotidiques spécifiques basées sur l'interaction stérique avec l'ADN, et des interactions spécifiques contrôlent de nombreux processus nucléaire, p.ex. transcription du gène, la réplication chromosomique, et la recombinaison. Une nouvelle technologie appelée ChIP-Seq a été récemment développée pour l'analyse des interactions protéine-ADN à l'échelle du génome entier et cette approche est basée sur l'immuno-précipitation de la chromatine et sur la procédure de séquençage de l'ADN à haut débit. La nouvelle approche ChIP-Seq a donc un fort potentiel pour remplacer les anciennes techniques de cartographie des interactions protéine-ADN. Dans cette thèse, nous apportons de nouvelles perspectives dans l'analyse des données ChIP-Seq. Tout d'abord, nous avons identifié des artefacts très communs associés à cette méthode qui étaient jusqu'à présent insoupçonnés. La distribution des séquences dans le génome ne suit pas une distribution uniforme et nous avons constaté des positions extrêmes d'accumulation de séquence à des régions spécifiques, des génomes humains et de la souris. Ces accumulations des séquences artéfactuelles créera de faux pics dans toutes les données ChIP-Seq, et nous proposons différentes méthodes de filtrage pour réduire le nombre de faux positifs. Ensuite, nous proposons un nouvel échantillonnage aléatoire comme un outil puissant d'analyse des données ChIP-Seq, ce qui pourraient augmenter l'acquisition de connaissances biologiques à partir des données ChIP-Seq. Nous avons créé un algorithme d'échantillonnage aléatoire et nous avons utilisé cette méthode pour révéler certaines des propriétés biologiques importantes de protéines liant à l'ADN nommés Facteur Nucléaire I (NFI). Enfin, en analysant en détail les données de ChIP-Seq pour la famille de facteurs de transcription nommés Facteur Nucléaire I, nous avons révélé que ces protéines agissent principalement comme des activateurs de transcription, et qu'elles sont associées à des modifications de la chromatine spécifiques qui sont des marqueurs de la chromatine ouverte. Nous pensons que lés facteurs NFI interagir uniquement avec l'ADN enroulé autour du nucléosome. Nous avons également constaté plusieurs régions génomiques qui indiquent une éventuelle activité de barrière chromatinienne des protéines NFI, ce qui pourrait suggérer l'utilisation de séquences de liaison NFI comme séquences isolatrices dans des applications de la biotechnologie.

'Bio-nano interactions: new tools, insights and impacts': summary of the Royal Society discussion meeting

Bio-nano interactions can be defined as the study of interactions between nanoscale entities and biological systems such as, but not limited to, peptides, proteins, lipids, DNA and other biomolecules, cells and cellular receptors and organisms including humans. Studying bio-nano interactions is particularly useful for understanding engineered materials that have at least one dimension in the nanoscale. Such materials may consist of discrete particles or nanostructured surfaces. Much of biology functions at the nanoscale; therefore, our ability to manipulate materials such that they are taken up at the nanoscale, and engage biological machinery in a designed and purposeful manner, opens new vistas for more efficient diagnostics, therapeutics (treatments) and tissue regeneration, so-called nanomedicine. Additionally, this ability of nanomaterials to interact with and be taken up by cells allows nanomaterials to be used as probes and tools to advance our understanding of cellular functioning. Yet, as a new technology, assessment of the safety of nanomaterials, and the applicability of existing regulatory frameworks for nanomaterials must be investigated in parallel with development of novel applications. The Royal Society meeting 'Bio-nano interactions: new tools, insights and impacts' provided an important platform for open dialogue on the current state of knowledge on these issues, bringing together scientists, industry, regulatory and legal experts to concretize existing discourse in science law and policy. This paper summarizes these discussions and the insights that emerged.

Where microbiology meets microengineering: design and applications of reporter bacteria.

Bacteria have long been the targets for genetic manipulation, but more recently they have been synthetically designed to carry out specific tasks. Among the simplest of these tasks is chemical compound and toxicity detection coupled to the production of a quantifiable reporter signal. In this Review, we describe the current design of bacterial bioreporters and their use in a range of assays to measure the presence of harmful chemicals in water, air, soil, food or biological specimens. New trends for integrating synthetic biology and microengineering into the design of bacterial bioreporter platforms are also highlighted.

Development, design and validation of solid reference samples.

We developed a method of sample preparation using epoxy compound, which was validated in two steps. First, we studied the homogeneity within samples by scanning tubes filled with radioactive epoxy. We found within-sample homogeneity better than 2%. Then, we studied the homogeneity between samples during a 4.5 h dispensing time. The homogeneity between samples was found to be better than 2%. This study demonstrates that we have a validated method, which assures the traceability of epoxy samples.

Randomized controlled trial of interventions for young people at ultra-high risk of psychosis: study design and baseline characteristics.

OBJECTIVE: Intervention during the pre-psychotic period of illness holds the potential of delaying or even preventing the onset of a full-threshold disorder, or at least of reducing the impact of such a disorder if it does develop. The first step in realizing this aim was achieved more than 10 years ago with the development and validation of criteria for the identification of young people at ultra-high risk (UHR) of psychosis. Results of three clinical trials have been published that provide mixed support for the effectiveness of psychological and pharmacological interventions in preventing the onset of psychotic disorder. METHOD: The present paper describes a fourth study that has now been undertaken in which young people who met UHR criteria were randomized to one of three treatment groups: cognitive therapy plus risperidone (CogTher + Risp: n = 43); cognitive therapy plus placebo (CogTher + Placebo: n = 44); and supportive counselling + placebo (Supp + Placebo; n = 28). A fourth group of young people who did not agree to randomization were also followed up (monitoring: n = 78). Baseline characteristics of participants are provided. RESULTS AND CONCLUSION: The present study improves on the previous studies because treatment was provided for 12 months and the independent contributions of psychological and pharmacological treatments in preventing transition to psychosis in the UHR cohort and on levels of psychopathology and functioning can be directly compared. Issues associated with recruitment and randomization are discussed.

Bacterial sensors: synthetic design and application principles

Bacterial reporters are live, genetically engineered cells with promising application in bioanalytics. They contain genetic circuitry to produce a cellular sensing element, which detects the target compound and relays the detection to specific synthesis of so-called reporter proteins (the presence or activity of which is easy to quantify). Bioassays with bacterial reporters are a useful complement to chemical analytics because they measure biological responses rather than total chemical concentrations. Simple bacterial reporter assays may also replace more costly chemical methods as a first line sample analysis technique. Recent promising developments integrate bacterial reporter cells with microsystems to produce bacterial biosensors. This lecture presents an in-depth treatment of the synthetic biological design principles of bacterial reporters, the engineering of which started as simple recombinant DNA puzzles, but has now become a more rational approach of choosing and combining sensing, controlling and reporting DNA 'parts'. Several examples of existing bacterial reporter designs and their genetic circuitry will be illustrated. Besides the design principles, the lecture also focuses on the application principles of bacterial reporter assays. A variety of assay formats will be illustrated, and principles of quantification will be dealt with. In addition to this discussion, substantial reference material is supplied in various Annexes.

Machine learning analysis and modeling of interest rate curves

The present research deals with the review of the analysis and modeling of Swiss franc interest rate curves (IRC) by using unsupervised (SOM, Gaussian Mixtures) and supervised machine (MLP) learning algorithms. IRC are considered as objects embedded into different feature spaces: maturities; maturity-date, parameters of Nelson-Siegel model (NSM). Analysis of NSM parameters and their temporal and clustering structures helps to understand the relevance of model and its potential use for the forecasting. Mapping of IRC in a maturity-date feature space is presented and analyzed for the visualization and forecasting purposes.

The stomach cancer pooling (StoP) project: study design and presentation.

Gastric cancer affects about one million people per year worldwide, being the second leading cause of cancer mortality. The study of its etiology remains therefore a global issue as it may allow the identification of major targets, besides eradication of Helicobacter pylori infection, for primary prevention. It has however received little attention, given its comparatively low incidence in most high-income countries. We introduce a consortium of epidemiological investigations named the 'Stomach cancer Pooling (StoP) Project'. Twenty-two studies agreed to participate, for a total of over 9000 cases and 23 000 controls. Twenty studies have already shared the original data set. Of the patients, 40% are from Asia, 43% from Europe, and 17% from North America; 34% are women and 66% men; the median age is 61 years; 56% are from population-based case-control studies, 41% from hospital-based ones, and 3% from nested case-control studies derived from cohort investigations. Biological samples are available from 12 studies. The aim of the StoP Project is to analyze the role of lifestyle and genetic determinants in the etiology of gastric cancer through pooled analyses of individual-level data. The uniquely large data set will allow us to define and quantify the main effects of each risk factor of interest, including a number of infrequent habits, and to adequately address associations in subgroups of the population, as well as interaction within and between environmental and genetic factors. Further, we will carry out separate analyses according to different histotypes and subsites of gastric cancer, to identify potential different risk patterns and etiological characteristics.