Baseline data of a population-based cohort of patients with diabetes in Switzerland (CoDiab-VD)

QUESTIONS UNDER STUDY: To describe a population-based sample of patients with diabetes and the quality of their care in the canton of Vaud, Switzerland, as a baseline measure for the evaluation of the "Programme cantonal Diabète". METHODS: We conducted a self-administered paper-based questionnaire survey. Non-institutionalised adult (aged ≥18 years) patients with diabetes diagnosed for at least 1 year and residing in the canton of Vaud were recruited by community pharmacies. Women with gestational diabetes, people with obvious cognitive impairment or people not sufficiently fluent in French were excluded. Primary outcomes were recommended processes-of-care and outcomes of care (glycosylated haemoglobin [HbA1c], generic and disease-specific health-related quality of life (HRQoL), overall care score in relation to the Chronic Care Model). Other measures included diabetes education, self-management support and self-efficacy, health status, health behaviour and demographics. RESULTS: A total of 519 patients with diabetes were included. Whereas the mean HbA1c level was 7.3% (n = 177, 95% confidence interval 7.1-7.5), diabetes-specific processes-of-care and influenza vaccination were reported by less than two-thirds of the patients. Physical activity and diet recommendations results mirrored patients' difficulties with their management in daily life and diabetes-specific HRQoL was worst in the dimensions relative to diet (eating and drinking) and sex life. A minority of patients reported ever having participated in diabetes education courses (32.8%). Overall, patients were satisfied with their care and the support they received. CONCLUSIONS: This study provides a broad picture of the experiences of people living with diabetes in the canton of Vaud. It shall guide the development of targeted interventions within the "Programme cantonal Diabète".

Cape Verdean Creole of São Vicente: Its genesis and Structure

Although the Santiago variety of Cape Verdean Creole (CVC) has been the subject of numerous linguistic works, the second major variety of the language, i.e. the São Vicente variety of CVC (CVSV), has hardly been described. Nevertheless this lack of studies and given its striking differences, on all linguistic levels, from the variety of Santiago (CVST), the implicit explanation for such divergences, echoed for decades in the literature on CVC, has been the presumably decreolized character of CVSV. First, this study provides a comprehensive fieldwork-based synchronic description of CVSV major morpho-syntactic categories in the intent to document the variety. Second, it aims to place the study of CVSV within a broader scope of contact linguistics in the quest to explain its structure. Based on analyses of historical documents and studies, it reconstructs the sociohistorical scenario of the emergence and development of CVSV in the period of 1797- 1975. From the comparison of the current structures of CVSV and CVST, the examination of linguistic data in historical texts and the analysis of sociohistorical facts it becomes clear that the contemporary structure of CVSV stems from the contact-induced changes that occurred during the intensive language and dialect contact on the island of São Vicente in the early days of its settlement in the late 18th and ensuing early 19th century development, rather than from modern day pressure of Portuguese. Although this dissertation argues for multiple explanations rather than a single theory, by showing that processes such as languages shift among the first Portuguese settlers, L2 acquisition, migration of the Barlavento speakers and subsequent dialect leveling as well as language borrowing at a later stage were at stake, it demonstrates the usefulness of partial-restructuring model proposed by Holm (2004).

Female-biased dispersal in the monogamous mammal Crocidura russula: evidence from field data and microsatellite patterns.

We investigated dispersal patterns in the monogamous Crocidura russula, based both on direct field observations (mark-recapture data) and on genetic analyses (microsatellite loci). Natal dispersal was found to be low. Most juveniles settled within their natal territory or one immediately adjacent. Migration rate was estimated to two individuals per year and per population. The correlation between genetic and geographical distances over a 16 km transect implies that migration occurs over short ranges. Natal dispersal was restricted to first-litter juveniles weaned in early May; this result suggests a direct dependence of dispersal on reproductive opportunities. Natal dispersal was highly female biased, a pattern unusual among mammals. Its association with monogamy provides support for the resource-competition model of dispersal. Our results demonstrate that a state-biased dispersal can be directly inferred from microsatellite genotype distributions, which opens new perspectives for empirical studies in this area.

Identification of optimal structural connectivity using functional connectivity and neural modeling.

The complex network dynamics that arise from the interaction of the brain's structural and functional architectures give rise to mental function. Theoretical models demonstrate that the structure-function relation is maximal when the global network dynamics operate at a critical point of state transition. In the present work, we used a dynamic mean-field neural model to fit empirical structural connectivity (SC) and functional connectivity (FC) data acquired in humans and macaques and developed a new iterative-fitting algorithm to optimize the SC matrix based on the FC matrix. A dramatic improvement of the fitting of the matrices was obtained with the addition of a small number of anatomical links, particularly cross-hemispheric connections, and reweighting of existing connections. We suggest that the notion of a critical working point, where the structure-function interplay is maximal, may provide a new way to link behavior and cognition, and a new perspective to understand recovery of function in clinical conditions.

Physiologically based pharmacokinetic modeling of arsenic in the mouse

A remarkable feature of the carcinogenicity of inorganic arsenic is that while human exposures to high concentrations of inorganic arsenic in drinking water are associated with increases in skin, lung, and bladder cancer, inorganic arsenic has not typically caused tumors in standard laboratory animal test protocols. Inorganic arsenic administered for periods of up to 2 yr to various strains of laboratory mice, including the Swiss CD-1, Swiss CR:NIH(S), C57Bl/6p53(+/-), and C57Bl/6p53(+/+), has not resulted in significant increases in tumor incidence. However, Ng et al. (1999) have reported a 40% tumor incidence in C57Bl/6J mice exposed to arsenic in their drinking water throughout their lifetime, with no tumors reported in controls. In order to investigate the potential role of tissue dosimetry in differential susceptibility to arsenic carcinogenicity, a physiologically based pharmacokinetic (PBPK) model for inorganic arsenic in the rat, hamster, monkey, and human (Mann et al., 1996a, 1996b) was extended to describe the kinetics in the mouse. The PBPK model was parameterized in the mouse using published data from acute exposures of B6C3F1 mice to arsenate, arsenite, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) and validated using data from acute exposures of C57Black mice. Predictions of the acute model were then compared with data from chronic exposures. There was no evidence of changes in the apparent volume of distribution or in the tissue-plasma concentration ratios between acute and chronic exposure that might support the possibility of inducible arsenite efflux. The PBPK model was also used to project tissue dosimetry in the C57Bl/6J study, in comparison with tissue levels in studies having shorter duration but higher arsenic treatment concentrations. The model evaluation indicates that pharmacokinetic factors do not provide an explanation for the difference in outcomes across the various mouse bioassays. Other possible explanations may relate to strain-specific differences, or to the different durations of dosing in each of the mouse studies, given the evidence that inorganic arsenic is likely to be active in the later stages of the carcinogenic process. [Authors]

Positional information by differential endocytosis splits auxin response to drive Arabidopsis root meristem growth.

In the Arabidopsis root meristem, polar auxin transport creates a transcriptional auxin response gradient that peaks at the stem cell niche and gradually decreases as stem cell daughters divide and differentiate [1-3]. The amplitude and extent of this gradient are essential for both stem cell maintenance and root meristem growth [4, 5]. To investigate why expression of some auxin-responsive genes, such as the essential root meristem growth regulator BREVIS RADIX (BRX) [6], deviates from this gradient, we combined experimental and computational approaches. We created cellular-level root meristem models that accurately reproduce distribution of nuclear auxin activity and allow dynamic modeling of regulatory processes to guide experimentation. Expression profiles deviating from the auxin gradient could only be modeled after intersection of auxin activity with the observed differential endocytosis pattern and positive autoregulatory feedback through plasma-membrane-to-nucleus transfer of BRX. Because BRX is required for expression of certain auxin response factor targets, our data suggest a cell-type-specific endocytosis-dependent input into transcriptional auxin perception. This input sustains expression of a subset of auxin-responsive genes across the root meristem's division and transition zones and is essential for meristem growth. Thus, the endocytosis pattern provides specific positional information to modulate auxin response.

The role of matrix metalloproteinase mmp-9 in peripheral neural system regeneration

Multiple lines of evidence show that matrix metalloproteinases (MMPs) are involved in the peripheral neural system degenerative and regenerative processes. MMP-9 was suggested in particular to play a role in the peripheral nerve after injury or during Wallerian degeneration. Interestingly, our previous analysis of Lpin1 mutant mice (which present morphological signs of active demyelination and acute inflammatory cell migration, similar to processes present in the PNS undergoing Wallerian degeneration) revealed an accumulation of MMP-9 in the endoneurium of affected animals. We therefore generated a mouse line lacking both the Lpin1 and the MMP-9 genes in order to determine if MMP-9 plays a role in either inhibition or potentiation of the demyelinating phenotype present in Lpin1 knockout mice. The inactivation of MMP-9 alone did not lead to defects in PNS structure or function. Interestingly we observed that the double mutant animals showed reduced nerve conduction velocity, lower myelin protein mRNA expressions, and had more histological abnormalities as compared to the Lpin1 single mutants. In addition, based on immunohistochemical analysis and macrophage markers mRNA expression, we found a lower macrophage content in the sciatic nerve of the double mutant animals. Together our data indicate that MMP-9 plays a role in macrophage recruitment during postinjury PNS regeneration processes and suggest that slower macrophage infiltration delays regenerative processes in PNS.

The role of migration and domestic transmission in the spread of HIV-1 non-B subtypes in Switzerland.

BACKGROUND: By analyzing human immunodeficiency virus type 1 (HIV-1) pol sequences from the Swiss HIV Cohort Study (SHCS), we explored whether the prevalence of non-B subtypes reflects domestic transmission or migration patterns. METHODS: Swiss non-B sequences and sequences collected abroad were pooled to construct maximum likelihood trees, which were analyzed for Swiss-specific subepidemics, (subtrees including ≥80% Swiss sequences, bootstrap >70%; macroscale analysis) or evidence for domestic transmission (sequence pairs with genetic distance <1.5%, bootstrap ≥98%; microscale analysis). RESULTS: Of 8287 SHCS participants, 1732 (21%) were infected with non-B subtypes, of which A (n = 328), C (n = 272), CRF01_AE (n = 258), and CRF02_AG (n = 285) were studied further. The macroscale analysis revealed that 21% (A), 16% (C), 24% (CRF01_AE), and 28% (CRF02_AG) belonged to Swiss-specific subepidemics. The microscale analysis identified 26 possible transmission pairs: 3 (12%) including only homosexual Swiss men of white ethnicity; 3 (12%) including homosexual white men from Switzerland and partners from foreign countries; and 10 (38%) involving heterosexual white Swiss men and females of different nationality and predominantly nonwhite ethnicity. CONCLUSIONS: Of all non-B infections diagnosed in Switzerland, <25% could be prevented by domestic interventions. Awareness should be raised among immigrants and Swiss individuals with partners from high prevalence countries to contain the spread of non-B subtypes.

No consistent association between processes-of-care and health-related quality of life among patients with diabetes : a missing link?

PURPOSE: Health-related quality of life (HRQoL) is considered a representative outcome in the evaluation of chronic disease management initiatives emphasizing patient-centered care. We evaluated the association between receipt of processes-of-care (PoC) for diabetes and HRQoL. METHODS: This cross-sectional study used self-reported data from non-institutionalized adults with diabetes in a Swiss canton. Outcomes were the physical/mental composites of the short form health survey 12 (SF-12) physical composite score, mental composite score (PCS, MCS) and the Audit of Diabetes-Dependent Quality of Life (ADDQoL). Main exposure variables were receipt of six PoC for diabetes in the past 12 months, and the Patient Assessment of Chronic Illness Care (PACIC) score. We performed linear regressions to examine the association between PoC, PACIC and the three composites of HRQoL. RESULTS: Mean age of the 519 patients was 64.5 years (SD 11.3); 60% were male, 87% reported type 2 or undetermined diabetes and 48% had diabetes for over 10 years. Mean HRQoL scores were SF-12 PCS: 43.4 (SD 10.5), SF-12 MCS: 47.0 (SD 11.2) and ADDQoL: -1.6 (SD 1.6). In adjusted models including all six PoC simultaneously, receipt of influenza vaccine was associated with lower ADDQoL (β=-0.4, p≤0.01) and foot examination was negatively associated with SF-12 PCS (β=-1.8, p≤0.05). There was no association or trend towards a negative association when these PoC were reported as combined measures. PACIC score was associated only with the SF-12 MCS (β=1.6, p≤0.05). CONCLUSIONS: PoC for diabetes did not show a consistent association with HRQoL in a cross-sectional analysis. This may represent an effect lag time between time of process received and health-related quality of life. Further research is needed to study this complex phenomenon.

Evaluation of occupational exposure: comparison of biological and environmental variabilities using physiologically based toxicokinetic modeling

PURPOSE: Few studies compare the variabilities that characterize environmental (EM) and biological monitoring (BM) data. Indeed, comparing their respective variabilities can help to identify the best strategy for evaluating occupational exposure. The objective of this study is to quantify the biological variability associated with 18 bio-indicators currently used in work environments. METHOD: Intra-individual (BV(intra)), inter-individual (BV(inter)), and total biological variability (BV(total)) were quantified using validated physiologically based toxicokinetic (PBTK) models coupled with Monte Carlo simulations. Two environmental exposure profiles with different levels of variability were considered (GSD of 1.5 and 2.0). RESULTS: PBTK models coupled with Monte Carlo simulations were successfully used to predict the biological variability of biological exposure indicators. The predicted values follow a lognormal distribution, characterized by GSD ranging from 1.1 to 2.3. Our results show that there is a link between biological variability and the half-life of bio-indicators, since BV(intra) and BV(total) both decrease as the biological indicator half-lives increase. BV(intra) is always lower than the variability in the air concentrations. On an individual basis, this means that the variability associated with the measurement of biological indicators is always lower than the variability characterizing airborne levels of contaminants. For a group of workers, BM is less variable than EM for bio-indicators with half-lives longer than 10-15 h. CONCLUSION: The variability data obtained in the present study can be useful in the development of BM strategies for exposure assessment and can be used to calculate the number of samples required for guiding industrial hygienists or medical doctors in decision-making.

Macrophage migration inhibitory factor is involved in a positive feedback loop increasing aromatase expression in endometriosis.

Immune-endocrine interplay may play a major role in the pathogenesis of endometriosis. In the present study, we have investigated the interaction between macrophage migration inhibitory factor (MIF), a major pro-inflammatory and growth-promoting factor markedly expressed in active endometriotic lesions, and estradiol (E(2)) in ectopic endometrial cells. Our data showed a significant increase of MIF protein secretion and mRNA expression in endometriotic cells in response to E(2). MIF production was blocked by Fulvestrant, an estrogen receptor (ER) antagonist, and induced by ERα and ERβ selective agonists propyl-pyrazole-triol (PPT) and diarylpropionrile (DPN), respectively, thus demonstrating a specific receptor-mediated effect. Cell transfection with MIF promoter construct showed that E(2) significantly stimulates MIF promoter activity. Interestingly, our data further revealed that MIF reciprocally stimulates aromatase protein and mRNA expression via a posttranscriptional mRNA stabilization mechanism, that E(2) itself can upregulate aromatase expression, and that inhibition of endogenous MIF, using MIF specific siRNA, significantly inhibits E(2)-induced aromatase. Thus, the present study revealed the existence of a local positive feedback loop by which estrogen acts directly on ectopic endometrial cells to upregulate the expression of MIF, which, in turn, displays the capability of inducing the expression of aromatase, the key and rate-limiting enzyme for estrogen synthesis. Such interplay may have a considerable impact on the development of endometriosis.

Inferring transport characteristics in a fractured rock aquifer by combining single-hole ground-penetrating radar reflection monitoring and tracer test data

Investigations of solute transport in fractured rock aquifers often rely on tracer test data acquired at a limited number of observation points. Such data do not, by themselves, allow detailed assessments of the spreading of the injected tracer plume. To better understand the transport behavior in a granitic aquifer, we combine tracer test data with single-hole ground-penetrating radar (GPR) reflection monitoring data. Five successful tracer tests were performed under various experimental conditions between two boreholes 6 m apart. For each experiment, saline tracer was injected into a previously identified packed-off transmissive fracture while repeatedly acquiring single-hole GPR reflection profiles together with electrical conductivity logs in the pumping borehole. By analyzing depth-migrated GPR difference images together with tracer breakthrough curves and associated simplified flow and transport modeling, we estimate (1) the number, the connectivity, and the geometry of fractures that contribute to tracer transport, (2) the velocity and the mass of tracer that was carried along each flow path, and (3) the effective transport parameters of the identified flow paths. We find a qualitative agreement when comparing the time evolution of GPR reflectivity strengths at strategic locations in the formation with those arising from simulated transport. The discrepancies are on the same order as those between observed and simulated breakthrough curves at the outflow locations. The rather subtle and repeatable GPR signals provide useful and complementary information to tracer test data acquired at the outflow locations and may help us to characterize transport phenomena in fractured rock aquifers.

Ecological assembly rules in plant communities--approaches, patterns and prospects.

Understanding how communities of living organisms assemble has been a central question in ecology since the early days of the discipline. Disentangling the different processes involved in community assembly is not only interesting in itself but also crucial for an understanding of how communities will behave under future environmental scenarios. The traditional concept of assembly rules reflects the notion that species do not co-occur randomly but are restricted in their co-occurrence by interspecific competition. This concept can be redefined in a more general framework where the co-occurrence of species is a product of chance, historical patterns of speciation and migration, dispersal, abiotic environmental factors, and biotic interactions, with none of these processes being mutually exclusive. Here we present a survey and meta-analyses of 59 papers that compare observed patterns in plant communities with null models simulating random patterns of species assembly. According to the type of data under study and the different methods that are applied to detect community assembly, we distinguish four main types of approach in the published literature: species co-occurrence, niche limitation, guild proportionality and limiting similarity. Results from our meta-analyses suggest that non-random co-occurrence of plant species is not a widespread phenomenon. However, whether this finding reflects the individualistic nature of plant communities or is caused by methodological shortcomings associated with the studies considered cannot be discerned from the available metadata. We advocate that more thorough surveys be conducted using a set of standardized methods to test for the existence of assembly rules in data sets spanning larger biological and geographical scales than have been considered until now. We underpin this general advice with guidelines that should be considered in future assembly rules research. This will enable us to draw more accurate and general conclusions about the non-random aspect of assembly in plant communities.

Targeting the PI3K p110alpha isoform inhibits medulloblastoma proliferation, chemoresistance, and migration.

PURPOSE: The phosphoinositide 3-kinase (PI3K)/Akt pathway is frequently activated in human cancer and plays a crucial role in medulloblastoma biology. We were interested in gaining further insight into the potential of targeting PI3K/Akt signaling as a novel antiproliferative approach in medulloblastoma. EXPERIMENTAL DESIGN: The expression pattern and functions of class I(A) PI3K isoforms were investigated in medulloblastoma tumour samples and cell lines. Effects on cell survival and downstream signaling were analyzed following down-regulation of p110alpha, p110beta, or p110delta by means of RNA interference or inhibition with isoform-specific PI3K inhibitors. RESULTS: Overexpression of the catalytic p110alpha isoform was detected in a panel of primary medulloblastoma samples and cell lines compared with normal brain tissue. Down-regulation of p110alpha expression by RNA interference impaired the growth of medulloblastoma cells, induced apoptosis, and led to decreased migratory capacity of the cells. This effect was selective, because RNA interference targeting of p110beta or p110delta did not result in a comparable impairment of DAOY cell survival. Isoform-specific p110alpha inhibitors also impaired medulloblastoma cell proliferation and sensitized the cells to chemotherapy. Medulloblastoma cells treated with p110alpha inhibitors further displayed reduced activation of Akt and the ribosomal protein S6 kinase in response to stimulation with hepatocyte growth factor and insulin-like growth factor-I. CONCLUSIONS: Together, our data reveal a novel function of p110alpha in medulloblastoma growth and survival.

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.