Examining chemical compound biodegradation at low concentrations through bacterial cell proliferation.

We show proof of principle for assessing compound biodegradation at 1-2 mg C per L by measuring microbial community growth over time with direct cell counting by flow cytometry. The concept is based on the assumption that the microbial community will increase in cell number through incorporation of carbon from the added test compound into new cells in the absence of (as much as possible) other assimilable carbon. We show on pure cultures of the bacterium Pseudomonas azelaica that specific population growth can be measured with as low as 0.1 mg 2-hydroxybiphenyl per L, whereas in mixed community 1 mg 2-hydroxybiphenyl per L still supported growth. Growth was also detected with a set of fragrance compounds dosed at 1-2 mg C per L into diluted activated sludge and freshwater lake communities at starting densities of 10(4) cells per ml. Yield approximations from the observed community growth was to some extent in agreement with standard OECD biodegradation test results for all, except one of the examined compounds.

Acid-sensing channels in human bladder: expression, function and alterations during bladder pain syndrome.

Purpose: To examine the possible role of H+-activated acid-sensing ion channels (ASICs) in pain perception we characterized their expression in bladder dome biopsies of Bladder Pain Syndrome (BPS) patients and controls, in cultured human urothelium and in urothelial TEU-2 cells.Materials and Methods: Cold cut biopsies from the bladder dome were obtained in 8 asymptomatic controls and 28 patients with symptoms of BPS. ASIC expression was analyzed by QPCR and immunofluorescence. The channel function was measured by electrophysiology.Results: ASIC1a, ASIC2a and ASIC3 mRNAs were detected in human bladder. Similar amounts of ASIC1a and -3 were detected in detrusor smooth muscle, whereas in urothelium ASIC3 levels were higher than -1a. ASIC2a mRNA levels were lower than either -1a or -3 in both layers. ASIC currents were measured in TEU-2 cells and in primary cultures of human urothelium, and ASIC expression was confirmed by QPCR. Differentiation of TEU-2 cells caused an up-regulation of ASIC2a and ASIC3, and a down-regulation of ASIC1a mRNAs. BPS patients showed an up-regulation of ASIC2a and -3 mRNA, whereas ASIC1a remained unchanged. In contrast, the mRNA levels of TRPV1 were down-regulated during BPS. All differences were statistically significant (p<0.05)Conclusions: Several different ASIC subunits are expressed in human bladder and TEU-2 cells, where their levels are regulated during urothelial differentiation. An up-regulation of ASIC2a and -3 in BPS suggests their involvement in increased pain and hyperalgesia. A down-regulation of TRPV1 mRNA levels might indicate a different regulatory mechanism, controlling its expression in human bladder.

Glucose sensing and the pathogenesis of obesity and type 2 diabetes.

The control of body weight and of blood glucose concentrations depends on the exquisite coordination of the function of several organs and tissues, in particular the liver, muscle and fat. These organs and tissues have major roles in the use and storage of nutrients in the form of glycogen or triglycerides and in the release of glucose or free fatty acids into the blood, in periods of metabolic needs. These mechanisms are tightly regulated by hormonal and nervous signals, which are generated by specialized cells that detect variations in blood glucose or lipid concentrations. The hormones insulin and glucagon not only regulate glycemic levels through their action on these organs and the sympathetic and parasympathetic branches of the autonomic nervous system, which are activated by glucose or lipid sensors, but also modulate pancreatic hormone secretion and liver, muscle and fat glucose and lipid metabolism. Other signaling molecules, such as the adipocyte hormones leptin and adiponectin, have circulating plasma concentrations that reflect the level of fat stored in adipocytes. These signals are integrated at the level of the hypothalamus by the melanocortin pathway, which produces orexigenic and anorexigenic neuropeptides to control feeding behavior, energy expenditure and glucose homeostasis. Work from several laboratories, including ours, has explored the physiological role of glucose as a signal that regulates these homeostatic processes and has tested the hypothesis that the mechanism of glucose sensing that controls insulin secretion by the pancreatic beta-cells is also used by other cell types. I discuss here evidence for these mechanisms, how they integrate signals from other nutrients such as lipids and how their deregulation may initiate metabolic diseases.

Semi-supervised remote sensing image classification with cluster kernels

A semisupervised support vector machine is presented for the classification of remote sensing images. The method exploits the wealth of unlabeled samples for regularizing the training kernel representation locally by means of cluster kernels. The method learns a suitable kernel directly from the image and thus avoids assuming a priori signal relations by using a predefined kernel structure. Good results are obtained in image classification examples when few labeled samples are available. The method scales almost linearly with the number of unlabeled samples and provides out-of-sample predictions.

Variation in the level of aggression, chemical and genetic distance among three supercolonies of the Argentine ant in Europe.

In their invasive ranges, Argentine ant populations often form one geographically vast supercolony, genetically and chemically uniform within which there is no intraspecific aggression. Here we present regional patterns of intraspecific aggression, cuticular hydrocarbons (CHCs) and population genetics of 18 nesting sites across Corsica and the French mainland. Aggression tests confirm the presence of a third European supercolony, the Corsican supercolony, which exhibits moderate to high levels of aggression, depending on nesting sites, with the Main supercolony, and invariably high levels of aggression with the Catalonian supercolony. The chemical analyses corroborated the behavioural data, with workers of the Corsican supercolony showing moderate differences in CHCs compared to workers of the European Main supercolony and strong differences compared to workers of the Catalonian supercolony. Interestingly, there were also clear genetic differences between workers of the Catalonian supercolony and the two other supercolonies at both nuclear and mitochondrial markers, but only very weak genetic differentiation between nesting sites of the Corsican and Main supercolonies (F(ST) = 0.06). A detailed comparison of the genetic composition of supercolonies also revealed that, if one of the last two supercolonies derived from the other, it is the Main supercolony that derived from the Corsican supercolony rather than the reverse. Overall, these findings highlight the importance of conducting more qualitative and quantitative analyses of the level of aggression between supercolonies, which has to be correlated with genetic and chemical data.

The bZIP transcription factor Rca1p is a central regulator of a novel CO₂ sensing pathway in yeast.

Like many organisms the fungal pathogen Candida albicans senses changes in the environmental CO(2) concentration. This response involves two major proteins: adenylyl cyclase and carbonic anhydrase (CA). Here, we demonstrate that CA expression is tightly controlled by the availability of CO(2) and identify the bZIP transcription factor Rca1p as the first CO(2) regulator of CA expression in yeast. We show that Rca1p upregulates CA expression during contact with mammalian phagocytes and demonstrate that serine 124 is critical for Rca1p signaling, which occurs independently of adenylyl cyclase. ChIP-chip analysis and the identification of Rca1p orthologs in the model yeast Saccharomyces cerevisiae (Cst6p) point to the broad significance of this novel pathway in fungi. By using advanced microscopy we visualize for the first time the impact of CO(2) build-up on gene expression in entire fungal populations with an exceptional level of detail. Our results present the bZIP protein Rca1p as the first fungal regulator of carbonic anhydrase, and reveal the existence of an adenylyl cyclase independent CO(2) sensing pathway in yeast. Rca1p appears to regulate cellular metabolism in response to CO(2) availability in environments as diverse as the phagosome, yeast communities or liquid culture.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Distribution and anatomical localization of the glucose transporter 2 (GLUT2) in the adult rat brain--an immunohistochemical study.

The aim of this work was to study the distribution and cellular localization of GLUT2 in the rat brain by light and electron microscopic immunohistochemistry, whereas our ultrastructural observations will be reported in a second paper. Confirming previous results, we show that GLUT2-immunoreactive profiles are present throughout the brain, especially in the limbic areas and related nuclei, whereas they appear most concentrated in the ventral and medial regions close to the midline. Using cresyl violet counterstaining and double immunohistochemical staining for glial or neuronal markers (GFAp, CAII and NeuN), we show that two limited populations of oligodendrocytes and astrocytes cell bodies and processes are immunoreactive for GLUT2, whereas a cross-reaction with GLUT1 cannot be ruled out. In addition, we report that the nerve cell bodies clearly immunostained for GLUT2 were scarce (although numerous in the dentate gyrus granular layer in particular), whereas the periphery of numerous nerve cells appeared labeled for this transporter. The latter were clustered in the dorsal endopiriform nucleus and neighboring temporal and perirhinal cortex, in the dorsal amygdaloid region, and in the paraventricular and reuniens thalamic nuclei, whereas they were only a few in the hypothalamus. Moreover, a group of GLUT2-immunoreactive nerve cell bodies was localized in the dorsal medulla oblongata while some large multipolar nerve cell bodies peripherally labeled for GLUT2 were scattered in the caudal ventral reticular formation. This anatomical localization of GLUT2 appears characteristic and different from that reported for the neuronal transporter GLUT3 and GLUT4. Indeed, the possibility that GLUT2 may be localized in the sub-plasmalemnal region of neurones and/or in afferent nerve fibres remains to be confirmed by ultrastructural observations. Because of the neuronal localization of GLUT2, and of its distribution relatively similar to glucokinase, it may be hypothesized that this transporter is, at least partially, involved in cerebral glucose sensing.

Characterization of gravitational rock slope deformations at different spatial scales based on field, remote sensing and numerical approaches

Rock slope instabilities such as rock slides, rock avalanche or deep-seated gravitational slope deformations are widespread in Alpine valleys. These phenomena represent at the same time a main factor that control the mountain belts erosion and also a significant natural hazard that creates important losses to the mountain communities. However, the potential geometrical and dynamic connections linking outcrop and slope-scale instabilities are often unknown. A more detailed definition of the potential links will be essential to improve the comprehension of the destabilization processes and to dispose of a more complete hazard characterization of the rock instabilities at different spatial scales. In order to propose an integrated approach in the study of the rock slope instabilities, three main themes were analysed in this PhD thesis: (1) the inventory and the spatial distribution of rock slope deformations at regional scale and their influence on the landscape evolution, (2) the influence of brittle and ductile tectonic structures on rock slope instabilities development and (3) the characterization of hazard posed by potential rock slope instabilities through the development of conceptual instability models. To prose and integrated approach for the analyses of these topics, several techniques were adopted. In particular, high resolution digital elevation models revealed to be fundamental tools that were employed during the different stages of the rock slope instability assessment. A special attention was spent in the application of digital elevation model for detailed geometrical modelling of past and potential instabilities and for the rock slope monitoring at different spatial scales. Detailed field analyses and numerical models were performed to complete and verify the remote sensing approach. In the first part of this thesis, large slope instabilities in Rhone valley (Switzerland) were mapped in order to dispose of a first overview of tectonic and climatic factors influencing their distribution and their characteristics. Our analyses demonstrate the key influence of neotectonic activity and the glacial conditioning on the spatial distribution of the rock slope deformations. Besides, the volumes of rock instabilities identified along the main Rhone valley, were then used to propose the first estimate of the postglacial denudation and filling of the Rhone valley associated to large gravitational movements. In the second part of the thesis, detailed structural analyses of the Frank slide and the Sierre rock avalanche were performed to characterize the influence of brittle and ductile tectonic structures on the geometry and on the failure mechanism of large instabilities. Our observations indicated that the geometric characteristics and the variation of the rock mass quality associated to ductile tectonic structures, that are often ignored landslide study, represent important factors that can drastically influence the extension and the failure mechanism of rock slope instabilities. In the last part of the thesis, the failure mechanisms and the hazard associated to five potential instabilities were analysed in detail. These case studies clearly highlighted the importance to incorporate different analyses and monitoring techniques to dispose of reliable and hazard scenarios. This information associated to the development of a conceptual instability model represents the primary data for an integrated risk management of rock slope instabilities. - Les mouvements de versant tels que les chutes de blocs, les éboulements ou encore les phénomènes plus lents comme les déformations gravitaires profondes de versant représentent des manifestations courantes en régions montagneuses. Les mouvements de versant sont à la fois un des facteurs principaux contrôlant la destruction progressive des chaines orogéniques mais aussi un danger naturel concret qui peut provoquer des dommages importants. Pourtant, les phénomènes gravitaires sont rarement analysés dans leur globalité et les rapports géométriques et mécaniques qui lient les instabilités à l'échelle du versant aux instabilités locales restent encore mal définis. Une meilleure caractérisation de ces liens pourrait pourtant représenter un apport substantiel dans la compréhension des processus de déstabilisation des versants et améliorer la caractérisation des dangers gravitaires à toutes les échelles spatiales. Dans le but de proposer un approche plus globale à la problématique des mouvements gravitaires, ce travail de thèse propose trois axes de recherche principaux: (1) l'inventaire et l'analyse de la distribution spatiale des grandes instabilités rocheuses à l'échelle régionale, (2) l'analyse des structures tectoniques cassantes et ductiles en relation avec les mécanismes de rupture des grandes instabilités rocheuses et (3) la caractérisation des aléas rocheux par une approche multidisciplinaire visant à développer un modèle conceptuel de l'instabilité et une meilleure appréciation du danger . Pour analyser les différentes problématiques traitées dans cette thèse, différentes techniques ont été utilisées. En particulier, le modèle numérique de terrain s'est révélé être un outil indispensable pour la majorité des analyses effectuées, en partant de l'identification de l'instabilité jusqu'au suivi des mouvements. Les analyses de terrain et des modélisations numériques ont ensuite permis de compléter les informations issues du modèle numérique de terrain. Dans la première partie de cette thèse, les mouvements gravitaires rocheux dans la vallée du Rhône (Suisse) ont été cartographiés pour étudier leur répartition en fonction des variables géologiques et morphologiques régionales. En particulier, les analyses ont mis en évidence l'influence de l'activité néotectonique et des phases glaciaires sur la distribution des zones à forte densité d'instabilités rocheuses. Les volumes des instabilités rocheuses identifiées le long de la vallée principale ont été ensuite utilisés pour estimer le taux de dénudations postglaciaire et le remplissage de la vallée du Rhône lié aux grands mouvements gravitaires. Dans la deuxième partie, l'étude de l'agencement structural des avalanches rocheuses de Sierre (Suisse) et de Frank (Canada) a permis de mieux caractériser l'influence passive des structures tectoniques sur la géométrie des instabilités. En particulier, les structures issues d'une tectonique ductile, souvent ignorées dans l'étude des instabilités gravitaires, ont été identifiées comme des structures très importantes qui contrôlent les mécanismes de rupture des instabilités à différentes échelles. Dans la dernière partie de la thèse, cinq instabilités rocheuses différentes ont été étudiées par une approche multidisciplinaire visant à mieux caractériser l'aléa et à développer un modèle conceptuel trois dimensionnel de ces instabilités. A l'aide de ces analyses on a pu mettre en évidence la nécessité d'incorporer différentes techniques d'analyses et de surveillance pour une gestion plus objective du risque associée aux grandes instabilités rocheuses.

Quorum-sensing-negative (lasR) mutants of Pseudomonas aeruginosa avoid cell lysis and death.

In Pseudomonas aeruginosa, N-acylhomoserine lactone signals regulate the expression of several hundreds of genes, via the transcriptional regulator LasR and, in part, also via the subordinate regulator RhlR. This regulatory network termed quorum sensing contributes to the virulence of P. aeruginosa as a pathogen. The fact that two supposed PAO1 wild-type strains from strain collections were found to be defective for LasR function because of independent point mutations in the lasR gene led to the hypothesis that loss of quorum sensing might confer a selective advantage on P. aeruginosa under certain environmental conditions. A convenient plate assay for LasR function was devised, based on the observation that lasR mutants did not grow on adenosine as the sole carbon source because a key degradative enzyme, nucleoside hydrolase (Nuh), is positively controlled by LasR. The wild-type PAO1 and lasR mutants showed similar growth rates when incubated in nutrient yeast broth at pH 6.8 and 37 degrees C with good aeration. However, after termination of growth during 30 to 54 h of incubation, when the pH rose to > or = 9, the lasR mutants were significantly more resistant to cell lysis and death than was the wild type. As a consequence, the lasR mutant-to-wild-type ratio increased about 10-fold in mixed cultures incubated for 54 h. In a PAO1 culture, five consecutive cycles of 48 h of incubation sufficed to enrich for about 10% of spontaneous mutants with a Nuh(-) phenotype, and five of these mutants, which were functionally complemented by lasR(+), had mutations in lasR. The observation that, in buffered nutrient yeast broth, the wild type and lasR mutants exhibited similar low tendencies to undergo cell lysis and death suggests that alkaline stress may be a critical factor providing a selective survival advantage to lasR mutants.

Genome-wide meta-analysis for serum calcium identifies significantly associated SNPs near the calcium-sensing receptor (CASR) gene.

Calcium has a pivotal role in biological functions, and serum calcium levels have been associated with numerous disorders of bone and mineral metabolism, as well as with cardiovascular mortality. Here we report results from a genome-wide association study of serum calcium, integrating data from four independent cohorts including a total of 12,865 individuals of European and Indian Asian descent. Our meta-analysis shows that serum calcium is associated with SNPs in or near the calcium-sensing receptor (CASR) gene on 3q13. The top hit with a p-value of 6.3 x 10(-37) is rs1801725, a missense variant, explaining 1.26% of the variance in serum calcium. This SNP had the strongest association in individuals of European descent, while for individuals of Indian Asian descent the top hit was rs17251221 (p = 1.1 x 10(-21)), a SNP in strong linkage disequilibrium with rs1801725. The strongest locus in CASR was shown to replicate in an independent Icelandic cohort of 4,126 individuals (p = 1.02 x 10(-4)). This genome-wide meta-analysis shows that common CASR variants modulate serum calcium levels in the adult general population, which confirms previous results in some candidate gene studies of the CASR locus. This study highlights the key role of CASR in calcium regulation.

Concomitant administration of intravenous drugs in the ICU: evaluation of physico-chemical compatibilities

Background and objective: Patients in the ICU often get many intravenous (iv) drugs at the same time. Even with three-lumen central venous catheters, the administration of more than one drug in the same iv line (IVL) is frequently necessary. The objective of this study was to observe how nurses managed to administer these many medications and to evaluate the proportion of two-drugs associations (TDA) that are compatible or not, based on known compatibility data. Design: Observational prospective study over 4 consecutive months. All patients receiving simultaneously more than one drugs in the same IVL (Y-site injection or mixed in the same container) were included. For each patient, all iv drugs were recorded, as well as concentration, infusion solution, location on the IVL system, time, rate and duration of administration. For each association of two or more drugs, compatibility of each drug was checked with each other. Compatibilities between these pairs of drugs were assessed using published data (mainly Trissel LA. Handbook on Injectable Drugs and Trissel's Tables of Physical Compatibility) and visual tests performed in our quality control laboratory. Setting: 34 beds university hospital adult ICU. Main outcome measures: Percentage of compatibilities and incompatibilities between drugs administered in the same IVL. Results: We observed 1,913 associations of drugs administered together in the same IVL, 783 implying only two drugs. The average number of drugs per IVL was 3.1 ± 0.8 (range: 2-9). 83.2% of the drugs were given by continuous infusion, 14.3% by intermittent infusion and 2.5% in bolus. The associations observed allowed to form 8,421 pairs of drugs (71.7% drug-drug and 28.3% drug-solute). According to literature data, 80.2% of the association were considered as compatible and 4.4% incompatible. 15.4% were not interpretable because of different conditions between local practices and those described in the literature (drug concentration, solute, etc.) or because of a lack of data. After laboratory tests performed on the most used drugs (furosemide, KH2PO4, morphine HCl, etc.), the proportion of compatible TDA raised to 85.7%, the incompatible stayed at 4.6% and only 9.7% remain unknown or not interpretable. Conclusions: Nurses managed the administration of iv medications quite well, as only less than 5% of observed TDA were considered as incompatible. But the 10% of TDA with unavailable compatibility data should have been avoided too, since the consequences of their concomitant administration cannot be predictable. For practical reasons, drugs were analysed only by pairs, which constitutes the main limit of this work. The average number of drugs in the same association being three, laboratory tests are currently performed to evaluate some of the most observed three-drugs associations.

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.