Design, data management, and population baseline characteristics of the PERFORM magnetic resonance imaging project.

Quantitative information from magnetic resonance imaging (MRI) may substantiate clinical findings and provide additional insight into the mechanism of clinical interventions in therapeutic stroke trials. The PERFORM study is exploring the efficacy of terutroban versus aspirin for secondary prevention in patients with a history of ischemic stroke. We report on the design of an exploratory longitudinal MRI follow-up study that was performed in a subgroup of the PERFORM trial. An international multi-centre longitudinal follow-up MRI study was designed for different MR systems employing safety and efficacy readouts: new T2 lesions, new DWI lesions, whole brain volume change, hippocampal volume change, changes in tissue microstructure as depicted by mean diffusivity and fractional anisotropy, vessel patency on MR angiography, and the presence of and development of new microbleeds. A total of 1,056 patients (men and women ≥ 55 years) were included. The data analysis included 3D reformation, image registration of different contrasts, tissue segmentation, and automated lesion detection. This large international multi-centre study demonstrates how new MRI readouts can be used to provide key information on the evolution of cerebral tissue lesions and within the macrovasculature after atherothrombotic stroke in a large sample of patients.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

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.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Structural components in functional data

Analyzing functional data often leads to finding common factors, for which functional principal component analysis proves to be a useful tool to summarize and characterize the random variation in a function space. The representation in terms of eigenfunctions is optimal in the sense of L-2 approximation. However, the eigenfunctions are not always directed towards an interesting and interpretable direction in the context of functional data and thus could obscure the underlying structure. To overcome such difficulty, an alternative to functional principal component analysis is proposed that produces directed components which may be more informative and easier to interpret. These structural components are similar to principal components, but are adapted to situations in which the domain of the function may be decomposed into disjoint intervals such that there is effectively independence between intervals and positive correlation within intervals. The approach is demonstrated with synthetic examples as well as real data. Properties for special cases are also studied.

Rules of origin : from analysis to reform

General Introduction This thesis can be divided into two main parts :the first one, corresponding to the first three chapters, studies Rules of Origin (RoOs) in Preferential Trade Agreements (PTAs); the second part -the fourth chapter- is concerned with Anti-Dumping (AD) measures. Despite wide-ranging preferential access granted to developing countries by industrial ones under North-South Trade Agreements -whether reciprocal, like the Europe Agreements (EAs) or NAFTA, or not, such as the GSP, AGOA, or EBA-, it has been claimed that the benefits from improved market access keep falling short of the full potential benefits. RoOs are largely regarded as a primary cause of the under-utilization of improved market access of PTAs. RoOs are the rules that determine the eligibility of goods to preferential treatment. Their economic justification is to prevent trade deflection, i.e. to prevent non-preferred exporters from using the tariff preferences. However, they are complex, cost raising and cumbersome, and can be manipulated by organised special interest groups. As a result, RoOs can restrain trade beyond what it is needed to prevent trade deflection and hence restrict market access in a statistically significant and quantitatively large proportion. Part l In order to further our understanding of the effects of RoOs in PTAs, the first chapter, written with Pr. Olivier Cadot, Celine Carrère and Pr. Jaime de Melo, describes and evaluates the RoOs governing EU and US PTAs. It draws on utilization-rate data for Mexican exports to the US in 2001 and on similar data for ACP exports to the EU in 2002. The paper makes two contributions. First, we construct an R-index of restrictiveness of RoOs along the lines first proposed by Estevadeordal (2000) for NAFTA, modifying it and extending it for the EU's single-list (SL). This synthetic R-index is then used to compare Roos under NAFTA and PANEURO. The two main findings of the chapter are as follows. First, it shows, in the case of PANEURO, that the R-index is useful to summarize how countries are differently affected by the same set of RoOs because of their different export baskets to the EU. Second, it is shown that the Rindex is a relatively reliable statistic in the sense that, subject to caveats, after controlling for the extent of tariff preference at the tariff-line level, it accounts for differences in utilization rates at the tariff line level. Finally, together with utilization rates, the index can be used to estimate total compliance costs of RoOs. The second chapter proposes a reform of preferential Roos with the aim of making them more transparent and less discriminatory. Such a reform would make preferential blocs more "cross-compatible" and would therefore facilitate cumulation. It would also contribute to move regionalism toward more openness and hence to make it more compatible with the multilateral trading system. It focuses on NAFTA, one of the most restrictive FTAs (see Estevadeordal and Suominen 2006), and proposes a way forward that is close in spirit to what the EU Commission is considering for the PANEURO system. In a nutshell, the idea is to replace the current array of RoOs by a single instrument- Maximum Foreign Content (MFC). An MFC is a conceptually clear and transparent instrument, like a tariff. Therefore changing all instruments into an MFC would bring improved transparency pretty much like the "tariffication" of NTBs. The methodology for this exercise is as follows: In step 1, I estimate the relationship between utilization rates, tariff preferences and RoOs. In step 2, I retrieve the estimates and invert the relationship to get a simulated MFC that gives, line by line, the same utilization rate as the old array of Roos. In step 3, I calculate the trade-weighted average of the simulated MFC across all lines to get an overall equivalent of the current system and explore the possibility of setting this unique instrument at a uniform rate across lines. This would have two advantages. First, like a uniform tariff, a uniform MFC would make it difficult for lobbies to manipulate the instrument at the margin. This argument is standard in the political-economy literature and has been used time and again in support of reductions in the variance of tariffs (together with standard welfare considerations). Second, uniformity across lines is the only way to eliminate the indirect source of discrimination alluded to earlier. Only if two countries face uniform RoOs and tariff preference will they face uniform incentives irrespective of their initial export structure. The result of this exercise is striking: the average simulated MFC is 25% of good value, a very low (i.e. restrictive) level, confirming Estevadeordal and Suominen's critical assessment of NAFTA's RoOs. Adopting a uniform MFC would imply a relaxation from the benchmark level for sectors like chemicals or textiles & apparel, and a stiffening for wood products, papers and base metals. Overall, however, the changes are not drastic, suggesting perhaps only moderate resistance to change from special interests. The third chapter of the thesis considers whether Europe Agreements of the EU, with the current sets of RoOs, could be the potential model for future EU-centered PTAs. First, I have studied and coded at the six-digit level of the Harmonised System (HS) .both the old RoOs -used before 1997- and the "Single list" Roos -used since 1997. Second, using a Constant Elasticity Transformation function where CEEC exporters smoothly mix sales between the EU and the rest of the world by comparing producer prices on each market, I have estimated the trade effects of the EU RoOs. The estimates suggest that much of the market access conferred by the EAs -outside sensitive sectors- was undone by the cost-raising effects of RoOs. The chapter also contains an analysis of the evolution of the CEECs' trade with the EU from post-communism to accession. Part II The last chapter of the thesis is concerned with anti-dumping, another trade-policy instrument having the effect of reducing market access. In 1995, the Uruguay Round introduced in the Anti-Dumping Agreement (ADA) a mandatory "sunset-review" clause (Article 11.3 ADA) under which anti-dumping measures should be reviewed no later than five years from their imposition and terminated unless there was a serious risk of resumption of injurious dumping. The last chapter, written with Pr. Olivier Cadot and Pr. Jaime de Melo, uses a new database on Anti-Dumping (AD) measures worldwide to assess whether the sunset-review agreement had any effect. The question we address is whether the WTO Agreement succeeded in imposing the discipline of a five-year cycle on AD measures and, ultimately, in curbing their length. Two methods are used; count data analysis and survival analysis. First, using Poisson and Negative Binomial regressions, the count of AD measures' revocations is regressed on (inter alia) the count of "initiations" lagged five years. The analysis yields a coefficient on measures' initiations lagged five years that is larger and more precisely estimated after the agreement than before, suggesting some effect. However the coefficient estimate is nowhere near the value that would give a one-for-one relationship between initiations and revocations after five years. We also find that (i) if the agreement affected EU AD practices, the effect went the wrong way, the five-year cycle being quantitatively weaker after the agreement than before; (ii) the agreement had no visible effect on the United States except for aone-time peak in 2000, suggesting a mopping-up of old cases. Second, the survival analysis of AD measures around the world suggests a shortening of their expected lifetime after the agreement, and this shortening effect (a downward shift in the survival function postagreement) was larger and more significant for measures targeted at WTO members than for those targeted at non-members (for which WTO disciplines do not bind), suggesting that compliance was de jure. A difference-in-differences Cox regression confirms this diagnosis: controlling for the countries imposing the measures, for the investigated countries and for the products' sector, we find a larger increase in the hazard rate of AD measures covered by the Agreement than for other measures.

Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

Hazardous substances in frequently used professional cleaning products.

A growing number of studies have identified cleaners as a group at risk for adverse health effects of the skin and the respiratory tract. Chemical substances present in cleaning products could be responsible for these effects. Currently, only limited information is available about irritant and health hazardous chemical substances found in cleaning products. We hypothesized that chemical substances present in cleaning products are known health hazardous substances that might be involved in adverse health effects of the skin and the respiratory tract. We performed a systematic review of cleaning products used in the Swiss cleaning sector. We surveyed Swiss professional cleaning companies (n = 1476) to identify the most used products (n = 105) for inclusion. Safety data sheets (SDSs) were reviewed and hazardous substances present in cleaning products were tabulated with current European and global harmonized system hazard labels. Professional cleaning products are mixtures of substances (arithmetic mean 3.5 +/- 2.8), and more than 132 different chemical substances were identified in 105 products. The main groups of chemicals were fragrances, glycol ethers, surfactants, solvents; and to a lesser extent, phosphates, salts, detergents, pH-stabilizers, acids, and bases. Up to 75% of products contained irritant (Xi), 64% harmful (Xn) and 28% corrosive (C) labeled substances. Hazards for eyes (59%) and skin (50%), and hazards by ingestion (60%) were the most reported. Cleaning products potentially give rise to simultaneous exposures to different chemical substances. As professional cleaners represent a large workforce, and cleaning products are widely used, it is a major public health issue to better understand these exposures. The list of substances provided in this study contains important information for future occupational exposure assessment studies.

Post-detection analysis for grating-based ultra-small angle X-ray scattering.

Until recently, the hard X-ray, phase-sensitive imaging technique called grating interferometry was thought to provide information only in real space. However, by utilizing an alternative approach to data analysis we demonstrated that the angular resolved ultra-small angle X-ray scattering distribution can be retrieved from experimental data. Thus, reciprocal space information is accessible by grating interferometry in addition to real space. Naturally, the quality of the retrieved data strongly depends on the performance of the employed analysis procedure, which involves deconvolution of periodic and noisy data in this context. The aim of this article is to compare several deconvolution algorithms to retrieve the ultra-small angle X-ray scattering distribution in grating interferometry. We quantitatively compare the performance of three deconvolution procedures (i.e., Wiener, iterative Wiener and Lucy-Richardson) in case of realistically modeled, noisy and periodic input data. The simulations showed that the algorithm of Lucy-Richardson is the more reliable and more efficient as a function of the characteristics of the signals in the given context. The availability of a reliable data analysis procedure is essential for future developments in grating interferometry.

Bortezomib(Velcade (R))-Thalidomide-Dexamethasone (VTD) Is Superior to Thalidomide-Dexamethasone (TD) In Patients with Multiple Myeloma (MM) Progressing or Relapsing After Autologous Transplantation.

Introduction: The Thalidomide-Dexamethasone (TD) regimen has provided encouraging results in relapsed MM. To improve results, bortezomib (Velcade) has been added to the combination in previous phase II studies, the so called VTD regimen. In January 2006, the European Group for Blood and Marrow Transplantation (EBMT) and the Intergroupe Francophone du Myélome (IFM) initiated a prospective, randomized, parallel-group, open-label phase III, multicenter study, comparing VTD (arm A) with TD (arm B) for MM patients progressing or relapsing after autologous transplantation. Patients and Methods: Inclusion criteria: patients in first progression or relapse after at least one autologous transplantation, including those who had received bortezomib or thalidomide before transplant. Exclusion criteria: subjects with neuropathy above grade 1 or non secretory MM. Primary study end point was time to progression (TTP). Secondary end points included safety, response rate, progression-free survival (PFS) and overall survival (OS). Treatment was scheduled as follows: bortezomib 1.3 mg/m2 was given as an i.v bolus on Days 1, 4, 8 and 11 followed by a 10-Day rest period (days 12 to 21) for 8 cycles (6 months) and then on Days 1, 8, 15, 22 followed by a 20-Day rest period (days 23 to 42) for 4 cycles (6 months). In both arms, thalidomide was scheduled at 200 mg/Day orally for one year and dexamethasone 40 mg/Day orally four days every three weeks for one year. Patients reaching remission could proceed to a new stem cell harvest. However, transplantation, either autologous or allogeneic, could only be performed in patients who completed the planned one year treatment period. Response was assessed by EBMT criteria, with additional category of near complete remission (nCR). Adverse events were graded by the NCI-CTCAE, Version 3.0.The trial was based on a group sequential design, with 4 planned interim analyses and one final analysis that allowed stopping for efficacy as well as futility. The overall alpha and power were set equal to 0.025 and 0.90 respectively. The test for decision making was based on the comparison in terms of the ratio of the cause-specific hazards of relapse/progression, estimated in a Cox model stratified on the number of previous autologous transplantations. Relapse/progression cumulative incidence was estimated using the proper nonparametric estimator, the comparison was done by the Gray test. PFS and OS probabilities were estimated by the Kaplan-Meier curves, the comparison was performed by the Log-Rank test. An interim safety analysis was performed when the first hundred patients had been included. The safety committee recommended to continue the trial. Results: As of 1st July 2010, 269 patients had been enrolled in the study, 139 in France (IFM 2005-04 study), 21 in Italy, 38 in Germany, 19 in Switzerland (a SAKK study), 23 in Belgium, 8 in Austria, 8 in the Czech republic, 11 in Hungary, 1 in the UK and 1 in Israel. One hundred and sixty nine patients were males and 100 females; the median age was 61 yrs (range 29-76). One hundred and thirty six patients were randomized to receive VTD and 133 to receive TD. The current analysis is based on 246 patients (124 in arm A, 122 in arm B) included in the second interim analysis, carried out when 134 events were observed. Following this analysis, the trial was stopped because of significant superiority of VTD over TD. The remaining patients were too premature to contribute to the analysis. The number of previous autologous transplants was one in 63 vs 60 and two or more in 61 vs 62 patients in arm A vs B respectively. The median follow-up was 25 months. The median TTP was 20 months vs 15 months respectively in arm A and B, with cumulative incidence of relapse/progression at 2 years equal to 52% (95% CI: 42%-64%) vs 70% (95% CI: 61%-81%) (p=0.0004, Gray test). The same superiority of arm A was also observed when stratifying on the number of previous autologous transplantations. At 2 years, PFS was 39% (95% CI: 30%-51%) vs 23% (95% CI: 16%-34%) (A vs B, p=0.0006, Log-Rank test). OS in the first two years was comparable in the two groups. Conclusion: VTD resulted in significantly longer TTP and PFS in patients relapsing after ASCT. Analysis of response and safety data are on going and results will be presented at the meeting. Protocol EU-DRACT number: 2005-001628-35.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

Occupational respiratory exposures to irritating and sensitizing volatile compounds deriving from cleaning products

Recent findings suggest an association between exposure to cleaning products and respiratory dysfunctions including asthma. However, little information is available about quantitative airborne exposures of professional cleaners to volatile organic compounds deriving from cleaning products. During the first phases of the study, a systematic review of cleaning products was performed. Safety data sheets were reviewed to assess the most frequently added volatile organic compounds. It was found that professional cleaning products are complex mixtures of different components (compounds in cleaning products: 3.5 ± 2.8), and more than 130 chemical substances listed in the safety data sheets were identified in 105 products. The main groups of chemicals were fragrances, glycol ethers, surfactants, solvents; and to a lesser extent phosphates, salts, detergents, pH-stabilizers, acids, and bases. Up to 75% of products contained irritant (Xi), 64% harmful (Xn) and 28% corrosive (C) labeled substances. Hazards for eyes (59%), skin (50%) and by ingestion (60%) were the most reported. Monoethanolamine, a strong irritant and known to be involved in sensitizing mechanisms as well as allergic reactions, is frequently added to cleaning products. Monoethanolamine determination in air has traditionally been difficult and air sampling and analysis methods available were little adapted for personal occupational air concentration assessments. A convenient method was developed with air sampling on impregnated glass fiber filters followed by one step desorption, gas chromatography and nitrogen phosphorous selective detection. An exposure assessment was conducted in the cleaning sector, to determine airborne concentrations of monoethanolamine, glycol ethers, and benzyl alcohol during different cleaning tasks performed by professional cleaning workers in different companies, and to determine background air concentrations of formaldehyde, a known indoor air contaminant. The occupational exposure study was carried out in 12 cleaning companies, and personal air samples were collected for monoethanolamine (n=68), glycol ethers (n=79), benzyl alcohol (n=15) and formaldehyde (n=45). All but ethylene glycol mono-n-butyl ether air concentrations measured were far below (<1/10) of the Swiss eight hours occupational exposure limits, except for butoxypropanol and benzyl alcohol, where no occupational exposure limits were available. Although only detected once, ethylene glycol mono-n-butyl ether air concentrations (n=4) were high (49.5 mg/m3 to 58.7 mg/m3), hovering at the Swiss occupational exposure limit (49 mg/m3). Background air concentrations showed no presence of monoethanolamine, while the glycol ethers were often present, and formaldehyde was universally detected. Exposures were influenced by the amount of monoethanolamine in the cleaning product, cross ventilation and spraying. The collected data was used to test an already existing exposure modeling tool during the last phases of the study. The exposure estimation of the so called Bayesian tool converged with the measured range of exposure the more air concentrations of measured exposure were added. This was best described by an inverse 2nd order equation. The results suggest that the Bayesian tool is not adapted to predict low exposures. The Bayesian tool should be tested also with other datasets describing higher exposures. Low exposures to different chemical sensitizers and irritants should be further investigated to better understand the development of respiratory disorders in cleaning workers. Prevention measures should especially focus on incorrect use of cleaning products, to avoid high air concentrations at the exposure limits. - De récentes études montrent l'existence d'un lien entre l'exposition aux produits de nettoyages et les maladies respiratoires telles que l'asthme. En revanche, encore peu d'informations sont disponibles concernant la quantité d'exposition des professionnels du secteur du nettoyage aux composants organiques volatiles provenant des produits qu'ils utilisent. Pendant la première phase de cette étude, un recueil systématique des produits professionnels utilisés dans le secteur du nettoyage a été effectué. Les fiches de données de sécurité de ces produits ont ensuite été analysées, afin de répertorier les composés organiques volatiles les plus souvent utilisés. Il a été mis en évidence que les produits de nettoyage professionnels sont des mélanges complexes de composants chimiques (composants chimiques dans les produits de nettoyage : 3.5 ± 2.8). Ainsi, plus de 130 substances listées dans les fiches de données de sécurité ont été retrouvées dans les 105 produits répertoriés. Les principales classes de substances chimiques identifiées étaient les parfums, les éthers de glycol, les agents de surface et les solvants; dans une moindre mesure, les phosphates, les sels, les détergents, les régulateurs de pH, les acides et les bases ont été identifiés. Plus de 75% des produits répertoriés contenaient des substances décrites comme irritantes (Xi), 64% nuisibles (Xn) et 28% corrosives (C). Les risques pour les yeux (59%), la peau (50%) et par ingestion (60%) était les plus mentionnés. La monoéthanolamine, un fort irritant connu pour être impliqué dans les mécanismes de sensibilisation tels que les réactions allergiques, est fréquemment ajouté aux produits de nettoyage. L'analyse de la monoéthanolamine dans l'air a été habituellement difficile et les échantillons d'air ainsi que les méthodes d'analyse déjà disponibles étaient peu adaptées à l'évaluation de la concentration individuelle d'air aux postes de travail. Une nouvelle méthode plus efficace a donc été développée en captant les échantillons d'air sur des filtres de fibre de verre imprégnés, suivi par une étape de désorption, puis une Chromatographie des gaz et enfin une détection sélective des composants d'azote. Une évaluation de l'exposition des professionnels a été réalisée dans le secteur du nettoyage afin de déterminer la concentration atmosphérique en monoéthanolamine, en éthers de glycol et en alcool benzylique au cours des différentes tâches de nettoyage effectuées par les professionnels du nettoyage dans différentes entreprises, ainsi que pour déterminer les concentrations atmosphériques de fond en formaldéhyde, un polluant de l'air intérieur bien connu. L'étude de l'exposition professionnelle a été effectuée dans 12 compagnies de nettoyage et les échantillons d'air individuels ont été collectés pour l'éthanolamine (n=68), les éthers de glycol (n=79), l'alcool benzylique (n=15) et le formaldéhyde (n=45). Toutes les substances mesurées dans l'air, excepté le 2-butoxyéthanol, étaient en-dessous (<1/10) de la valeur moyenne d'exposition aux postes de travail en Suisse (8 heures), excepté pour le butoxypropanol et l'alcool benzylique, pour lesquels aucune valeur limite d'exposition n'était disponible. Bien que détecté qu'une seule fois, les concentrations d'air de 2-butoxyéthanol (n=4) étaient élevées (49,5 mg/m3 à 58,7 mg/m3), se situant au-dessus de la frontière des valeurs limites d'exposition aux postes de travail en Suisse (49 mg/m3). Les concentrations d'air de fond n'ont montré aucune présence de monoéthanolamine, alors que les éthers de glycol étaient souvent présents et les formaldéhydes quasiment toujours détectés. L'exposition des professionnels a été influencée par la quantité de monoéthanolamine présente dans les produits de nettoyage utilisés, par la ventilation extérieure et par l'emploie de sprays. Durant la dernière phase de l'étude, les informations collectées ont été utilisées pour tester un outil de modélisation de l'exposition déjà existant, l'outil de Bayesian. L'estimation de l'exposition de cet outil convergeait avec l'exposition mesurée. Cela a été le mieux décrit par une équation du second degré inversée. Les résultats suggèrent que l'outil de Bayesian n'est pas adapté pour mettre en évidence les taux d'expositions faibles. Cet outil devrait également être testé avec d'autres ensembles de données décrivant des taux d'expositions plus élevés. L'exposition répétée à des substances chimiques ayant des propriétés irritatives et sensibilisantes devrait être investiguée d'avantage, afin de mieux comprendre l'apparition de maladies respiratoires chez les professionnels du nettoyage. Des mesures de prévention devraient tout particulièrement être orientées sur l'utilisation correcte des produits de nettoyage, afin d'éviter les concentrations d'air élevées se situant à la valeur limite d'exposition acceptée.

Toward synthetic combinatorial peptide libraries in positional scanning format (PS-SCL)-based identification of CD8+ Tumor-reactive T-Cell Ligands: a comparative analysis of PS-SCL recognition by a single tumor-reactive CD8+ cytolytic T-lymphocyte clone.

The use of synthetic combinatorial peptide libraries in positional scanning format (PS-SCL) has emerged recently as an alternative approach for the identification of peptides recognized by T lymphocytes. The choice of both the PS-SCL used for screening experiments and the method used for data analysis are crucial for implementing this approach. With this aim, we tested the recognition of different PS-SCL by a tyrosinase 368-376-specific CTL clone and analyzed the data obtained with a recently developed biometric data analysis based on a model of independent and additive contribution of individual amino acids to peptide antigen recognition. Mixtures defined with amino acids present at the corresponding positions in the native sequence were among the most active for all of the libraries. Somewhat surprisingly, a higher number of native amino acids were identifiable by using amidated COOH-terminal rather than free COOH-terminal PS-SCL. Also, our data clearly indicate that when using PS-SCL longer than optimal, frame shifts occur frequently and should be taken into account. Biometric analysis of the data obtained with the amidated COOH-terminal nonapeptide library allowed the identification of the native ligand as the sequence with the highest score in a public human protein database. However, the adequacy of the PS-SCL data for the identification for the peptide ligand varied depending on the PS-SCL used. Altogether these results provide insight into the potential of PS-SCL for the identification of CTL-defined tumor-derived antigenic sequences and may significantly implement our ability to interpret the results of these analyses.

Long-Term Safety of Canakinumab in Patients with Gouty Arthritis.

Background/Purpose: Gouty arthritis (GA) is a chronic inflammatory disease. Targeting the inflammatory pathway through IL-1_ inhibition with canakinumab (CAN) may provide significant long-term benefits. CAN safety versus triamcinolone acetonide (TA) over initial 24 weeks (blinded study) for patients (pts) with history of frequent attacks (_3 in year before baseline) was reported earlier from core (_-RELIEVED [_-REL] and _-REL-II) and first extension (E1) studies1. Herein we present full 18-month long-term CAN safety data, including open-label second extension (E2) studies. Methods: GA pts completing _-REL E1 and _-REL-II E1 studies1 were enrolled in these 1-year, open-label, E2 studies. All pts entering E2, whether randomized to CAN or TA, received CAN 150 mg sc on demand upon new attack. Data are presented only for pts randomized to CAN, and are reported cumulatively, i.e. including corresponding data from previously reported core and E1 studies. Long-term safety outcomes and safety upon re-treatment are presented as incidence rate per 100 patient-years (pyr) of study participation for AEs and SAEs. Deaths are reported for all pts (randomized to CAN or TA). Selected predefined notable laboratory abnormalities are shown (neutrophils, platelets, liver and renal function tests). Long-term attack rate per year is also provided. Results: In total, 69/115 (60%) and 72/112 (64.3%) of the pts randomized to CAN in the two core studies entered the two E2 studies, of which 68 and 64 pts, respectively completed the E2 studies. The 2 study populations had differing baseline comorbidity and geographic origin. Lab data (not time adjusted) for neutropenia appears worse after retreatment in _-REL E2, and deterioration of creatinine clearance appears worse after retreatment (Table 1). The time-adjusted incidence rates for AEs were 302.4/100 pyr and 360/100 pyr, and for SAEs were 27.9/100 pyr and 13.9/100 pyr in _-REL E2 and _-REL-II E2 respectively (Table 1). The time-adjusted incidence rates of any AEs, infection AEs, any SAEs, and selected SAEs before and after re-treatment are presented in Table 1. Incidence rates for AEs and SAEs declined after re-treatment, with the exception of SAEs in _-REL-II E2, which increased from 2.9/100 pyr to 10.9/100 pyr (no infection SAEs after retreatment in _-REL-II E2, and other SAEs fit no special pattern). In the total safety population (N_454, core and all extensions), there were 4 deaths, 2 in the core studies previously reported1 and 2 during the _-REL E2 study (one patient in the CAN group died from pneumonia; one patient in the TA group who never received CAN died of pneumococcal sepsis). None of the deaths was suspected by investigators to be study drug related. The mean rates of new attacks per year on CAN were 1.21 and 1.18 in _-REL E2 and in _-REL-II E2. Conclusion: The clinical safety profile of CAN upon re-treatment was maintained long-term with no new infection concerns

Comparative modular analysis of gene expression in vertebrate development

The focus of my PhD research was the concept of modularity. In the last 15 years, modularity has become a classic term in different fields of biology. On the conceptual level, a module is a set of interacting elements that remain mostly independent from the elements outside of the module. I used modular analysis techniques to study gene expression evolution in vertebrates. In particular, I identified ``natural'' modules of gene expression in mouse and human, and I showed that expression of organ-specific and system-specific genes tends to be conserved between such distance vertebrates as mammals and fishes. Also with a modular approach, I studied patterns of developmental constraints on transcriptome evolution. I showed that none of the two commonly accepted models of the evolution of embryonic development (``evo-devo'') are exclusively valid. In particular, I found that the conservation of the sequences of regulatory regions is highest during mid-development of zebrafish, and thus it supports the ``hourglass model''. In contrast, events of gene duplication and new gene introduction are most rare in early development, which supports the ``early conservation model''. In addition to the biological insights on transcriptome evolution, I have also discussed in detail the advantages of modular approaches in large-scale data analysis. Moreover, I re-analyzed several studies (published in high-ranking journals), and showed that their conclusions do not hold out under a detailed analysis. This demonstrates that complex analysis of high-throughput data requires a co-operation between biologists, bioinformaticians, and statisticians.