A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

Protein interaction data curation: the International Molecular Exchange (IMEx) consortium.

The International Molecular Exchange (IMEx) consortium is an international collaboration between major public interaction data providers to share literature-curation efforts and make a nonredundant set of protein interactions available in a single search interface on a common website (http://www.imexconsortium.org/). Common curation rules have been developed, and a central registry is used to manage the selection of articles to enter into the dataset. We discuss the advantages of such a service to the user, our quality-control measures and our data-distribution practices.

The InterPro Database, 2003 brings increased coverage and new features.

InterPro, an integrated documentation resource of protein families, domains and functional sites, was created in 1999 as a means of amalgamating the major protein signature databases into one comprehensive resource. PROSITE, Pfam, PRINTS, ProDom, SMART and TIGRFAMs have been manually integrated and curated and are available in InterPro for text- and sequence-based searching. The results are provided in a single format that rationalises the results that would be obtained by searching the member databases individually. The latest release of InterPro contains 5629 entries describing 4280 families, 1239 domains, 95 repeats and 15 post-translational modifications. Currently, the combined signatures in InterPro cover more than 74% of all proteins in SWISS-PROT and TrEMBL, an increase of nearly 15% since the inception of InterPro. New features of the database include improved searching capabilities and enhanced graphical user interfaces for visualisation of the data. The database is available via a webserver (http://www.ebi.ac.uk/interpro) and anonymous FTP (ftp://ftp.ebi.ac.uk/pub/databases/interpro).

Epigenetic features of human mesenchymal stem cells determine their permissiveness for induction of relevant transcriptional changes by SYT-SSX1.

BACKGROUND: A characteristic SYT-SSX fusion gene resulting from the chromosomal translocation t(X;18)(p11;q11) is detectable in almost all synovial sarcomas, a malignant soft tissue tumor widely believed to originate from as yet unidentified pluripotent stem cells. The resulting fusion protein has no DNA binding motifs but possesses protein-protein interaction domains that are believed to mediate association with chromatin remodeling complexes. Despite recent advances in the identification of molecules that interact with SYT-SSX and with the corresponding wild type SYT and SSX proteins, the mechanisms whereby the SYT-SSX might contribute to neoplastic transformation remain unclear. Epigenetic deregulation has been suggested to be one possible mechanism. METHODOLOGY/PRINCIPAL FINDINGS: We addressed the effect of SYT/SSX expression on the transcriptome of four independent isolates of primary human bone marrow mesenchymal stem cells (hMSC). We observed transcriptional changes similar to the gene expression signature of synovial sarcoma, principally involving genes whose regulation is linked to epigenetic factors, including imprinted genes, genes with transcription start sites within a CpG island and chromatin related genes. Single population analysis revealed hMSC isolate-specific transcriptional changes involving genes that are important for biological functions of stem cells as well as genes that are considered to be molecular markers of synovial sarcoma including IGF2, EPHRINS, and BCL2. Methylation status analysis of sequences at the H19/IGF2 imprinted locus indicated that distinct epigenetic features characterize hMSC populations and condition the transcriptional effects of SYT-SSX expression. CONCLUSIONS/SIGNIFICANCE: Our observations suggest that epigenetic features may define the cellular microenvironment in which SYT-SSX displays its functional effects.

A fatal overdose of cocaine associated with coingestion of marijuana, buprenorphine, and fluoxetine. Body fluid and tissue distribution of cocaine and its metabolites determined by hydrophilic interaction chromatography-mass spectrometry(HILIC-MS).

Chromatographic separation of highly polar basic drugs with ideal ionspray mass spectrometry volatile mobile phases is a difficult challenge. A new quantification procedure was developed using hydrophilic interaction chromatography-mass spectrometry with turbo-ionspray ionization in the positive mode. After addition of deuterated internal standards and simple clean-up liquid extraction, the dried extracts were reconstituted in 500 microL pure acetonitrile and 5 microL was directly injected onto a Waters Atlantis HILIC 150- x 2.1-mm, 3-microm column. Chromatographic separations of cocaine, seven metabolites, and anhydroecgonine were obtained by linear gradient-elution with decreasing high concentrations of acetonitrile (80-56% in 18 min). This high proportion of organic solvent makes it easier to be coupled with MS. The eluent was buffered with 2 mM ammonium acetate at pH 4.5. Except for m-hydroxy-benzoylecgonine, the within-day and between-day precisions at 20, 100, and 500 ng/mL were below 7 and 19.1%, respectively. Accuracy was also below +/- 13.5% at all tested concentrations. The limit of quantification was 5 ng/mL (%Diff < 16.1, %RSD < 4.3) and the limit of detection below 0.5 ng/mL. This method was successfully applied to a fatal overdose. In Switzerland, cocaine abuse has dramatically increased in the last few years. A 45-year-old man, a known HIV-positive drug user, was found dead at home. According to relatives, cocaine was self-injected about 10 times during the evening before death. A low amount of cocaine (0.45 mg) was detected in the bloody fluid taken from a syringe discovered near the corpse. Besides injection marks, no significant lesions were detected during the forensic autopsy. Toxicological investigations showed high cocaine concentrations in all body fluids and tissues. The peripheral blood concentrations of cocaine, benzoylecgonine, and methylecgonine were 5.0, 10.4, and 4.1 mg/L, respectively. The brain concentrations of cocaine, benzoylecgonine, and methylecgonine were 21.2, 3.8, and 3.3 mg/kg, respectively. The highest concentrations of norcocaine (about 1 mg/L) were measured in bile and urine. Very high levels of cocaine were determined in hair (160 ng/mg), indicating chronic cocaine use. A low concentration of anhydroecgonine methylester was also found in urine (0.65 mg/L) suggesting recent cocaine inhalation. Therapeutic blood concentrations of fluoxetine (0.15 mg/L) and buprenorphine (0.1 microg/L) were also discovered. A relatively high concentration of Delta(9)-THC was measured both in peripheral blood (8.2 microg/L) and brain cortex (13.5 microg/kg), suggesting that the victim was under the influence of cannabis at the time of death. In addition, fluoxetine might have enhanced the toxic effects of cocaine because of its weak pro-arrhythmogenic properties. Likewise, combination of cannabinoids and cocaine might have increase detrimental cardiovascular effects. Altogether, these results indicate a lethal cocaine overdose with a minor contribution of fluoxetine and cannabinoids.

Animal dispersal modelling: handling landscape features and related animal choices

Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled. We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path.

An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

Segmenting ultrasound images is a challenging problemwhere standard unsupervised segmentation methods such asthe well-known Chan-Vese method fail. We propose in thispaper an efficient segmentation method for this class ofimages. Our proposed algorithm is based on asemi-supervised approach (user labels) and the use ofimage patches as data features. We also consider thePearson distance between patches, which has been shown tobe robust w.r.t speckle noise present in ultrasoundimages. Our results on phantom and clinical data show avery high similarity agreement with the ground truthprovided by a medical expert.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

The InterActive Choice Aid: A new approach to supporting online consumer decision making

Interactive Choice Aid (ICA) is a decision aid, introduced in this paper, that systematically assists consumers with online purchase decisions. ICA integrates aspects from prescriptive decision theory, insights from descriptive decision research, and practical considerations; thereby combining pre-existing best practices with novel features. Instead of imposing an objectively ideal but unnatural decision procedure on the user, ICA assists the natural process of human decision-making by providing explicit support for the execution of the user's decision strategies. The application contains an innovative feature for in-depth comparisons of alternatives through which users' importance ratings are elicited interactively and in a playful way. The usability and general acceptance of the choice aid was studied; results show that ICA is a promising contribution and provides insights that may further improve its usability.

Melt/peridotite interaction in the Southern Lanzo peridotite: Field, textural and geochemical evidence

This paper presents field, petrographic-structural and geochemical data on spinet and plagioclase peridotites from the southern domain of the Lanzo ophiolitic peridotite massif (Western Alps). Spinet lherzolites, harzburgites and dunites crop out at Mt. Arpone and Mt. Musine. Field evidence indicates that pristine porphyroclastic spinet lherzolites are transformed to coarse granular spinet harzburgites, which are in turn overprinted by plagioclase peridotites, while strongly depleted spinet harzburgite and dunite bands and bodies replace the plagioclase peridotites. On the northern flank of Mt. Arpone, deformed, porphyroclastic (lithospheric) lherzolites, with diffuse pyroxenite banding, represent the oldest spinel-facies rocks. They show microstructures of a composite subsolidus evolution, suggesting provenance from deeper (asthenospheric) mantle levels and accretion to the lithosphere. These protoliths are locally transformed to coarse granular (reactive) spinet harzburgites and dunites, which show textures reminiscent of melt/rock reaction and geochemical characteristics suggesting that they are products of peridotite interaction with reactively percolating melts. Geochemical data and modelling suggest that <1-5% fractional melting of spinel-facies DMM produced the injected melts. Plagioclase peridotites are hybrid rocks resulting from pre-existing spinet peridotites and variable enrichment of plagioclase and micro-gabbroic material by percolating melts. The impregnating melts attained silica-saturation, as testified by widespread orthopyroxene replacement of olivine, during open system migration in the lithosphere. At Mt. Musine, coarse granular spinet harzburgite and dunite bodies replace the plagioclase peridotites. Most of these replacive, refractory peridotites have interstitial magmatic clinopyroxene with trace element compositions in equilibrium with MORB, while some Cpx have REE-depleted patterns suggesting transient geochemical features of the migrating MORB-type melts, acquired by interaction with the ambient plagioclase peridotite. These replacive spinet harzburgite and dunite bodies are interpreted as channels exploited for focused and reactive migration of silica-undersaturated melts with aggregate MORB compositions. Such melts were unrelated to the silica-saturated melts that refertilized the pre-existing plagioclase peridotites. Finally, MORB melt migration occurred along open fractures, now recorded as gabbroic dikes. Our data document the complexity of rock-types and mantle processes in the South Lanzo peridotite massif and describe a composite tectonic and magmatic scenario that is not consistent with the ``asthenospheric scenario'' proposed by previous authors. We envisage a ``transitional scenario'' in which extending subcontinental lithospheric mantle was strongly modified (both depleted and refertilized) by early melts with MORB-affinity formed by decompression partial melting of the upwelling asthenosphere, during pre-oceanic rifting and lithospheric thinning in the Ligurian Tethys realm. (C) 2006 Elsevier B.V. All rights reserved.

Endothelial cells as key determinants of the tumor microenvironment: interaction with tumor cells, extracellular matrix and immune killer cells.

Besides tumor cells, the tumor microenvironment harbors a variety of host-derived cells, such as endothelial cells, fibroblasts, innate and adaptive immune cells. It is a complex and highly dynamic environment, providing very important cues to tumor development and progression. Tumor-associated endothelial cells play a key role in this process. On the one hand, they form tumor-associated (angiogenic) vessels through sprouting from locally preexisting vessels or recruitment of bone marrow-derived endothelial progenitor cells, to provide nutritional support to the growing tumor. On the other hand, they are the interface between circulating blood cells, tumor cells and the extracellular matrix, thereby playing a central role in controlling leukocyte recruitment, tumor cell behavior and metastasis formation. Hypoxia is a critical parameter modulating the tumor microenvironment and endothelial/tumor cell interactions. Under hypoxic stress, tumor cells produce factors that promote tumor angiogenesis, tumor cell motility and metastasis. Among these factors, VEGF, a main angiogenesis modulator, can also play a critical role in the control of immune tolerance. This review discusses some aspects of the role of endothelial cells within tumor microenvironment and emphasizes their interaction with tumor cells, the extracellular matrix and with immune killer cells. We will also address the role played by circulating endothelial progenitor cells and illustrate their features and mechanism of recruitment to the tumor microenvironment and their role in tumor angiogenesis.

Vessel centerline tracking and boundary sgementation in coronary MRA with minimal manual interaction.

Magnetic resonance angiography (MRA) provides a noninvasive means to detect the presence, location and severity of atherosclerosis throughout the vascular system. In such studies, and especially those in the coronary arteries, the vessel luminal area is typically measured at multiple cross-sectional locations along the course of the artery. The advent of fast volumetric imaging techniques covering proximal to mid segments of coronary arteries necessitates automatic analysis tools requiring minimal manual interactions to robustly measure cross-sectional area along the three-dimensional track of the arteries in under-sampled and non-isotropic datasets. In this work, we present a modular approach based on level set methods to track the vessel centerline, segment the vessel boundaries, and measure transversal area using two user-selected endpoints in each coronary of interest. Arterial area and vessel length are measured using our method and compared to the standard Soap-Bubble reformatting and analysis tool in in-vivo non-contrast enhanced coronary MRA images.

EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data.

The R package EasyStrata facilitates the evaluation and visualization of stratified genome-wide association meta-analyses (GWAMAs) results. It provides (i) statistical methods to test and account for between-strata difference as a means to tackle gene-strata interaction effects and (ii) extended graphical features tailored for stratified GWAMA results. The software provides further features also suitable for general GWAMAs including functions to annotate, exclude or highlight specific loci in plots or to extract independent subsets of loci from genome-wide datasets. It is freely available and includes a user-friendly scripting interface that simplifies data handling and allows for combining statistical and graphical functions in a flexible fashion. AVAILABILITY: EasyStrata is available for free (under the GNU General Public License v3) from our Web site www.genepi-regensburg.de/easystrata and from the CRAN R package repository cran.r-project.org/web/packages/EasyStrata/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The Hydrophobic interaction: modeling hydrophobic interactions and aggregation of non-polar particles in aqueous solutions

Malgré son importance dans notre vie de tous les jours, certaines propriétés de l?eau restent inexpliquées. L'étude des interactions entre l'eau et les particules organiques occupe des groupes de recherche dans le monde entier et est loin d'être finie. Dans mon travail j'ai essayé de comprendre, au niveau moléculaire, ces interactions importantes pour la vie. J'ai utilisé pour cela un modèle simple de l'eau pour décrire des solutions aqueuses de différentes particules. Récemment, l?eau liquide a été décrite comme une structure formée d?un réseau aléatoire de liaisons hydrogènes. En introduisant une particule hydrophobe dans cette structure à basse température, certaines liaisons hydrogènes sont détruites ce qui est énergétiquement défavorable. Les molécules d?eau s?arrangent alors autour de cette particule en formant une cage qui permet de récupérer des liaisons hydrogènes (entre molécules d?eau) encore plus fortes : les particules sont alors solubles dans l?eau. A des températures plus élevées, l?agitation thermique des molécules devient importante et brise les liaisons hydrogènes. Maintenant, la dissolution des particules devient énergétiquement défavorable, et les particules se séparent de l?eau en formant des agrégats qui minimisent leur surface exposée à l?eau. Pourtant, à très haute température, les effets entropiques deviennent tellement forts que les particules se mélangent de nouveau avec les molécules d?eau. En utilisant un modèle basé sur ces changements de structure formée par des liaisons hydrogènes j?ai pu reproduire les phénomènes principaux liés à l?hydrophobicité. J?ai trouvé une région de coexistence de deux phases entre les températures critiques inférieure et supérieure de solubilité, dans laquelle les particules hydrophobes s?agrègent. En dehors de cette région, les particules sont dissoutes dans l?eau. J?ai démontré que l?interaction hydrophobe est décrite par un modèle qui prend uniquement en compte les changements de structure de l?eau liquide en présence d?une particule hydrophobe, plutôt que les interactions directes entre les particules. Encouragée par ces résultats prometteurs, j?ai étudié des solutions aqueuses de particules hydrophobes en présence de co-solvants cosmotropiques et chaotropiques. Ce sont des substances qui stabilisent ou déstabilisent les agrégats de particules hydrophobes. La présence de ces substances peut être incluse dans le modèle en décrivant leur effet sur la structure de l?eau. J?ai pu reproduire la concentration élevée de co-solvants chaotropiques dans le voisinage immédiat de la particule, et l?effet inverse dans le cas de co-solvants cosmotropiques. Ce changement de concentration du co-solvant à proximité de particules hydrophobes est la cause principale de son effet sur la solubilité des particules hydrophobes. J?ai démontré que le modèle adapté prédit correctement les effets implicites des co-solvants sur les interactions de plusieurs corps entre les particules hydrophobes. En outre, j?ai étendu le modèle à la description de particules amphiphiles comme des lipides. J?ai trouvé la formation de différents types de micelles en fonction de la distribution des regions hydrophobes à la surface des particules. L?hydrophobicité reste également un sujet controversé en science des protéines. J?ai défini une nouvelle échelle d?hydrophobicité pour les acides aminés qui forment des protéines, basée sur leurs surfaces exposées à l?eau dans des protéines natives. Cette échelle permet une comparaison meilleure entre les expériences et les résultats théoriques. Ainsi, le modèle développé dans mon travail contribue à mieux comprendre les solutions aqueuses de particules hydrophobes. Je pense que les résultats analytiques et numériques obtenus éclaircissent en partie les processus physiques qui sont à la base de l?interaction hydrophobe.<br/><br/>Despite the importance of water in our daily lives, some of its properties remain unexplained. Indeed, the interactions of water with organic particles are investigated in research groups all over the world, but controversy still surrounds many aspects of their description. In my work I have tried to understand these interactions on a molecular level using both analytical and numerical methods. Recent investigations describe liquid water as random network formed by hydrogen bonds. The insertion of a hydrophobic particle at low temperature breaks some of the hydrogen bonds, which is energetically unfavorable. The water molecules, however, rearrange in a cage-like structure around the solute particle. Even stronger hydrogen bonds are formed between water molecules, and thus the solute particles are soluble. At higher temperatures, this strict ordering is disrupted by thermal movements, and the solution of particles becomes unfavorable. They minimize their exposed surface to water by aggregating. At even higher temperatures, entropy effects become dominant and water and solute particles mix again. Using a model based on these changes in water structure I have reproduced the essential phenomena connected to hydrophobicity. These include an upper and a lower critical solution temperature, which define temperature and density ranges in which aggregation occurs. Outside of this region the solute particles are soluble in water. Because I was able to demonstrate that the simple mixture model contains implicitly many-body interactions between the solute molecules, I feel that the study contributes to an important advance in the qualitative understanding of the hydrophobic effect. I have also studied the aggregation of hydrophobic particles in aqueous solutions in the presence of cosolvents. Here I have demonstrated that the important features of the destabilizing effect of chaotropic cosolvents on hydrophobic aggregates may be described within the same two-state model, with adaptations to focus on the ability of such substances to alter the structure of water. The relevant phenomena include a significant enhancement of the solubility of non-polar solute particles and preferential binding of chaotropic substances to solute molecules. In a similar fashion, I have analyzed the stabilizing effect of kosmotropic cosolvents in these solutions. Including the ability of kosmotropic substances to enhance the structure of liquid water, leads to reduced solubility, larger aggregation regime and the preferential exclusion of the cosolvent from the hydration shell of hydrophobic solute particles. I have further adapted the MLG model to include the solvation of amphiphilic solute particles in water, by allowing different distributions of hydrophobic regions at the molecular surface, I have found aggregation of the amphiphiles, and formation of various types of micelle as a function of the hydrophobicity pattern. I have demonstrated that certain features of micelle formation may be reproduced by the adapted model to describe alterations of water structure near different surface regions of the dissolved amphiphiles. Hydrophobicity remains a controversial quantity also in protein science. Based on the surface exposure of the 20 amino-acids in native proteins I have defined the a new hydrophobicity scale, which may lead to an improvement in the comparison of experimental data with the results from theoretical HP models. Overall, I have shown that the primary features of the hydrophobic interaction in aqueous solutions may be captured within a model which focuses on alterations in water structure around non-polar solute particles. The results obtained within this model may illuminate the processes underlying the hydrophobic interaction.<br/><br/>La vie sur notre planète a commencé dans l'eau et ne pourrait pas exister en son absence : les cellules des animaux et des plantes contiennent jusqu'à 95% d'eau. Malgré son importance dans notre vie de tous les jours, certaines propriétés de l?eau restent inexpliquées. En particulier, l'étude des interactions entre l'eau et les particules organiques occupe des groupes de recherche dans le monde entier et est loin d'être finie. Dans mon travail j'ai essayé de comprendre, au niveau moléculaire, ces interactions importantes pour la vie. J'ai utilisé pour cela un modèle simple de l'eau pour décrire des solutions aqueuses de différentes particules. Bien que l?eau soit généralement un bon solvant, un grand groupe de molécules, appelées molécules hydrophobes (du grecque "hydro"="eau" et "phobia"="peur"), n'est pas facilement soluble dans l'eau. Ces particules hydrophobes essayent d'éviter le contact avec l'eau, et forment donc un agrégat pour minimiser leur surface exposée à l'eau. Cette force entre les particules est appelée interaction hydrophobe, et les mécanismes physiques qui conduisent à ces interactions ne sont pas bien compris à l'heure actuelle. Dans mon étude j'ai décrit l'effet des particules hydrophobes sur l'eau liquide. L'objectif était d'éclaircir le mécanisme de l'interaction hydrophobe qui est fondamentale pour la formation des membranes et le fonctionnement des processus biologiques dans notre corps. Récemment, l'eau liquide a été décrite comme un réseau aléatoire formé par des liaisons hydrogènes. En introduisant une particule hydrophobe dans cette structure, certaines liaisons hydrogènes sont détruites tandis que les molécules d'eau s'arrangent autour de cette particule en formant une cage qui permet de récupérer des liaisons hydrogènes (entre molécules d?eau) encore plus fortes : les particules sont alors solubles dans l'eau. A des températures plus élevées, l?agitation thermique des molécules devient importante et brise la structure de cage autour des particules hydrophobes. Maintenant, la dissolution des particules devient défavorable, et les particules se séparent de l'eau en formant deux phases. A très haute température, les mouvements thermiques dans le système deviennent tellement forts que les particules se mélangent de nouveau avec les molécules d'eau. A l'aide d'un modèle qui décrit le système en termes de restructuration dans l'eau liquide, j'ai réussi à reproduire les phénomènes physiques liés à l?hydrophobicité. J'ai démontré que les interactions hydrophobes entre plusieurs particules peuvent être exprimées dans un modèle qui prend uniquement en compte les liaisons hydrogènes entre les molécules d'eau. Encouragée par ces résultats prometteurs, j'ai inclus dans mon modèle des substances fréquemment utilisées pour stabiliser ou déstabiliser des solutions aqueuses de particules hydrophobes. J'ai réussi à reproduire les effets dûs à la présence de ces substances. De plus, j'ai pu décrire la formation de micelles par des particules amphiphiles comme des lipides dont la surface est partiellement hydrophobe et partiellement hydrophile ("hydro-phile"="aime l'eau"), ainsi que le repliement des protéines dû à l'hydrophobicité, qui garantit le fonctionnement correct des processus biologiques de notre corps. Dans mes études futures je poursuivrai l'étude des solutions aqueuses de différentes particules en utilisant les techniques acquises pendant mon travail de thèse, et en essayant de comprendre les propriétés physiques du liquide le plus important pour notre vie : l'eau.

Asymmetrical nature of the Trollius-Chiastocheta interaction: insights into the evolution of nursery pollination systems

The mutualistic versus antagonistic nature of an interaction is defined by costs and benefits of each partner, which may vary depending on the environment. Contrasting with this dynamic view, several pollination interactions are considered as strictly obligate and mutualistic. Here, we focus on the interaction between Trollius europaeus and Chiastocheta flies, considered as a specialized and obligate nursery pollination system - the flies are thought to be exclusive pollinators of the plant and their larvae develop only in T.europaeus fruits. In this system, features such as the globelike flower shape are claimed to have evolved in a coevolutionary context. We examine the specificity of this pollination system and measure traits related to offspring fitness in isolated T.europaeus populations, in some of which Chiastocheta flies have gone extinct. We hypothesize that if this interaction is specific and obligate, the plant should experience dramatic drop in its relative fitness in the absence of Chiastocheta. Contrasting with this hypothesis, T.europaeus populations without flies demonstrate a similar relative fitness to those with the flies present, contradicting the putative obligatory nature of this pollination system. It also agrees with our observation that many other insects also visit and carry pollen among T.europaeus flowers. We propose that the interaction could have evolved through maximization of by-product benefits of the Chiastocheta visits, through the male flower function, and selection on floral traits by the most effective pollinator. We argue this mechanism is also central in the evolution of other nursery pollination systems.