Non conventional species as monitor of environmental pollution

This thesis collects several ecotoxicological studies focused on the quali- quantitative analysis of several classes of chemical compounds. Our studies have been conducted on different aquatic species occupying different food chain trophic levels and characterized by differences in biology, ethology, and nutrition, but all considered excellent bioindicators. This choice allowed us to have a broad overview of the contamination of aquatic environments. Detrimental effects of several chemical compounds on the species investigated have been discussed, considering the economic and public health implications linked to the pollution of the environment and the exposure to old and emerging xenobiotics. Our studies underline the importance of a multidisciplinary and integrated approach that includes the application of the one health concept to ensure the protection of public health and respect for natural environments. Studies collected in this thesis also aim to overcome some critical limitations of the branch of ecotoxicology, such as the lack of standardization in laboratory methods. Our data also underline the importance of expanding research to a greater number of various biological matrices than those indicated by the literature as target tissues for specific pollutants. This condition enables more detailed information on the kinetics of xenobiotics in animal organisms. Our studies also allow us to expand the knowledge related to the mechanisms of synergy and antagonism of mixtures of pollutants that can simultaneously accumulate in wildlife.

Data driven regularization models of non-linear ill-posed inverse problems in imaging

Imaging technologies are widely used in application fields such as natural sciences, engineering, medicine, and life sciences. A broad class of imaging problems reduces to solve ill-posed inverse problems (IPs). Traditional strategies to solve these ill-posed IPs rely on variational regularization methods, which are based on minimization of suitable energies, and make use of knowledge about the image formation model (forward operator) and prior knowledge on the solution, but lack in incorporating knowledge directly from data. On the other hand, the more recent learned approaches can easily learn the intricate statistics of images depending on a large set of data, but do not have a systematic method for incorporating prior knowledge about the image formation model. The main purpose of this thesis is to discuss data-driven image reconstruction methods which combine the benefits of these two different reconstruction strategies for the solution of highly nonlinear ill-posed inverse problems. Mathematical formulation and numerical approaches for image IPs, including linear as well as strongly nonlinear problems are described. More specifically we address the Electrical impedance Tomography (EIT) reconstruction problem by unrolling the regularized Gauss-Newton method and integrating the regularization learned by a data-adaptive neural network. Furthermore we investigate the solution of non-linear ill-posed IPs introducing a deep-PnP framework that integrates the graph convolutional denoiser into the proximal Gauss-Newton method with a practical application to the EIT, a recently introduced promising imaging technique. Efficient algorithms are then applied to the solution of the limited electrods problem in EIT, combining compressive sensing techniques and deep learning strategies. Finally, a transformer-based neural network architecture is adapted to restore the noisy solution of the Computed Tomography problem recovered using the filtered back-projection method.

A FEM procedure based on positions and unconstrained vectors applied to non-linear dynamic of 3D frames

This study presents an alternative three-dimensional geometric non-linear frame formulation based on generalized unconstrained vector and positions to solve structures and mechanisms subjected to dynamic loading. The formulation is classified as total Lagrangian with exact kinematics description. The resulting element presents warping and non-constant transverse strain modes, which guarantees locking-free behavior for the adopted three-dimensional constitutive relation, Saint-Venant-Kirchhoff, for instance. The application of generalized vectors is an alternative to the use of finite rotations and rigid triad`s formulae. Spherical and revolute joints are considered and selected dynamic and static examples are presented to demonstrate the accuracy and generality of the proposed technique. (C) 2010 Elsevier B.V. All rights reserved.

Defining a role for the subthalamic nucleus within operative theoretical models of subcortical participation in language

Objective:To investigate the effects of bilateral, surgically induced functional inhibition of the subthalamic nucleus (STN) on general language, high level linguistic abilities, and semantic processing skills in a group of patients with Parkinson’s disease. Methods:Comprehensive linguistic profiles were obtained up to one month before and three months after bilateral implantation of electrodes in the STN during active deep brain stimulation (DBS) in five subjects with Parkinson’s disease (mean age, 63.2 years). Equivalent linguistic profiles were generated over a three month period for a non-surgical control cohort of 16 subjects with Parkinson’s disease (NSPD) (mean age, 64.4 years). Education and disease duration were similar in the two groups. Initial assessment and three month follow up performance profiles were compared within subjects by paired t tests. Reliability change indices (RCI), representing clinically significant alterations in performance over time, were calculated for each of the assessment scores achieved by the five STN-DBS cases and the 16 NSPD controls, relative to performance variability within a group of 16 non-neurologically impaired adults (mean age, 61.9 years). Proportions of reliable change were then compared between the STN-DBS and NSPD groups. Results:Paired comparisons within the STN-DBS group showed prolonged postoperative semantic processing reaction times for a range of word types coded for meanings and meaning relatedness. Case by case analyses of reliable change across language assessments and groups revealed differences in proportions of change over time within the STN-DBS and NSPD groups in the domains of high level linguistics and semantic processing. Specifically, when compared with the NSPD group, the STN-DBS group showed a proportionally significant (p

Redefining functional models of basal ganglia organisation: Role for the posteroventral pallidum in linguistic processing?

Traditionally the basal ganglia have been implicated in motor behavior, as they are involved in both the execution of automatic actions and the modification of ongoing actions in novel contexts. Corresponding to cognition, the role of the basal ganglia has not been defined as explicitly. Relative to linguistic processes, contemporary theories of subcortical participation in language have endorsed a role for the globus pallidus internus (GPi) in the control of lexical-semantic operations. However, attempts to empirically validate these postulates have been largely limited to neuropsychological investigations of verbal fluency abilities subsequent to pallidotomy. We evaluated the impact of bilateral posteroventral pallidotomy (BPVP) on language function across a range of general and high-level linguistic abilities, and validated/extended working theories of pallidal participation in language. Comprehensive linguistic profiles were compiled up to 1 month before and 3 months after BPVP in 6 subjects with Parkinson's disease (PD). Commensurate linguistic profiles were also gathered over a 3-month period for a nonsurgical control cohort of 16 subjects with PD and a group of 16 non-neurologically impaired controls (NC). Nonparametric between-groups comparisons were conducted and reliable change indices calculated, relative to baseline/3-month follow-up difference scores. Group-wise statistical comparisons between the three groups failed to reveal significant postoperative changes in language performance. Case-by-case data analysis relative to clinically consequential change indices revealed reliable alterations in performance across several language variables as a consequence of BPVP. These findings lend support to models of subcortical participation in language, which promote a role for the GPi in lexical-semantic manipulation mechanisms. Concomitant improvements and decrements in postoperative performance were interpreted within the context of additive and subtractive postlesional effects. Relative to parkinsonian cohorts, clinically reliable versus statistically significant changes on a case by case basis may provide the most accurate method of characterizing the way in which pathophysiologically divergent basal ganglia linguistic circuits respond to BPVP.

Non-diagonal solutions of the reflection equation for the trigonometric A((1)) (n-1) vertex model

We obtain a class of non-diagonal solutions of the reflection equation for the trigonometric A(n-1)((1)) vertex model. The solutions can be expressed in terms of intertwinner matrix and its inverse, which intertwine two trigonometric R-matrices. In addition to a discrete (positive integer) parameter l, 1 less than or equal to l less than or equal to n, the solution contains n + 2 continuous boundary parameters.

Microscopic origin of non-Gaussian distributions of financial returns

In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumption, akin to the Born-Oppenheimer approximation, in which the volatility has already relaxed to its equilibrium distribution and acts as a background to the evolution of the price process. In this approximation, we show that all models of stochastic volatility should exhibit a scaling relation in the time lag of zero-drift modified log-returns. We verify that the Dow-Jones Industrial Average index indeed follows this scaling. We then focus on two popular stochastic volatility models, the Heston and Hull-White models. In particular, we show that in the Hull-White model the resulting probability distribution of log-returns in this approximation corresponds to the Tsallis (t-Student) distribution. The Tsallis parameters are given in terms of the microscopic stochastic volatility model. Finally, we show that the log-returns for 30 years Dow Jones index data is well fitted by a Tsallis distribution, obtaining the relevant parameters. (c) 2007 Elsevier B.V. All rights reserved.

Limitations and biases of conventional analysis of climate change. Towards an analysis coherent with sustainable development

This paper shows the numerous problems of conventional economic analysis in the evaluation of climate change mitigation policies. The article points out the many limitations, omissions, and the arbitrariness that have characterized most evaluation models applied up until now. These shortcomings, in an almost overwhelming way, have biased the result towards the recommendation of a lower aggressiveness of emission mitigation policies. Consequently, this paper questions whether these results provide an appropriate answer to the problem. Finally, various points that an analysis coherent with sustainable development should take into account are presented.

An Introduction to parametric and non-parametric models for bivariate positive insurance claim severity distributions

We present a real data set of claims amounts where costs related to damage are recorded separately from those related to medical expenses. Only claims with positive costs are considered here. Two approaches to density estimation are presented: a classical parametric and a semi-parametric method, based on transformation kernel density estimation. We explore the data set with standard univariate methods. We also propose ways to select the bandwidth and transformation parameters in the univariate case based on Bayesian methods. We indicate how to compare the results of alternative methods both looking at the shape of the overall density domain and exploring the density estimates in the right tail.

Predictive models of syncope causes in an outpatient clinic

The investigation of unexplained syncope remains a challenging clinical problem. In the present study we sought to evaluate the diagnostic value of a standardized work-up focusing on non invasive tests in patients with unexplained syncope referred to a syncope clinic, and whether certain combinations of clinical parameters are characteristic of rhythmic and reflex causes of syncope. METHODS AND RESULTS: 317 consecutive patients underwent a standardized work-up including a 12-lead ECG, physical examination, detailed history with screening for syncope-related symptoms using a structured questionnaire followed by carotid sinus massage (CSM), and head-up tilt test. Invasive testings including an electrophysiological study and implantation of a loop recorder were only performed in those with structural heart disease or traumatic syncope. Our work-up identified an etiology in 81% of the patients. Importantly, three quarters of the causes were established non invasively combining head-up tilt test, CSM and hyperventilation testing. Invasive tests yielded an additional 7% of diagnoses. Logistic analysis identified age and number of significant prodromes as the only predictive factors of rhythmic syncope. The same two factors, in addition to the duration of the ECG P-wave, were also predictive of vasovagal and psychogenic syncope. These factors, optimally combined in predictive models, showed a high negative and a modest positive predictive value. CONCLUSION: A standardized work-up focusing on non invasive tests allows to establish more than three quarters of syncope causes. Predictive models based on simple clinical parameters may help to distinguish between rhythmic and other causes of syncope

From SNPs to pathways: integration of functional effect of sequence variations on models of cell signalling pathways

Background: Single nucleotide polymorphisms (SNPs) are the most frequent type of sequence variation between individuals, and represent a promising tool for finding genetic determinants of complex diseases and understanding the differences in drug response. In this regard, it is of particular interest to study the effect of non-synonymous SNPs in the context of biological networks such as cell signalling pathways. UniProt provides curated information about the functional and phenotypic effects of sequence variation, including SNPs, as well as on mutations of protein sequences. However, no strategy has been developed to integrate this information with biological networks, with the ultimate goal of studying the impact of the functional effect of SNPs in the structure and dynamics of biological networks. Results: First, we identified the different challenges posed by the integration of the phenotypic effect of sequence variants and mutations with biological networks. Second, we developed a strategy for the combination of data extracted from public resources, such as UniProt, NCBI dbSNP, Reactome and BioModels. We generated attribute files containing phenotypic and genotypic annotations to the nodes of biological networks, which can be imported into network visualization tools such as Cytoscape. These resources allow the mapping and visualization of mutations and natural variations of human proteins and their phenotypic effect on biological networks (e.g. signalling pathways, protein-protein interaction networks, dynamic models). Finally, an example on the use of the sequence variation data in the dynamics of a network model is presented. Conclusion: In this paper we present a general strategy for the integration of pathway and sequence variation data for visualization, analysis and modelling purposes, including the study of the functional impact of protein sequence variations on the dynamics of signalling pathways. This is of particular interest when the SNP or mutation is known to be associated to disease. We expect that this approach will help in the study of the functional impact of disease-associated SNPs on the behaviour of cell signalling pathways, which ultimately will lead to a better understanding of the mechanisms underlying complex diseases.

Effectiveness of career counseling: A one-year follow-up

The aim of this study was to analyze the psychometric properties of the Career Adapt-Abilities Scale (CAAS) in a French-speaking Swiss sample and its relationship with personality dimensions and work engagement. The heterogeneous sample of 391 participants (Mage = 39.59, SD = 12.30) completed the CAAS-International and a short version of the Utrecht Work Engagement Scale. To assess personality dimensions, participants completed either the Zuckerman-Kuhlman-Aluja Personality Questionnaire (n=283) or the NEO-FFI-R (n=108). The internal consistencies for the four subscales and total scores of the CAAS ranged from good to excellent, and skewness and kurtosis values indicated that scores were normally distributed. Gender differences and cor- relations with age were small or negligible. Several CFA models confirmed the factor structure of the French version of the CAAS-International, with loadings very similar to the ones observed for the international form. Adaptability was related to different personality dimensions, particularly neuroticism and conscientiousness, and also to work engagement. When predicting work engage- ment, career adaptability had a significant incremental validity over personality dimensions. Fi- nally, career adaptability partially moderated the relationship between personality and work engagement, suggesting that career adaptability also contributes to regulating the expression of personality dispositions.

Integrating detection probabilities in species distribution models of amphibians breeding in Mediterranean temporary ponds

Aim  The imperfect detection of species may lead to erroneous conclusions about species-environment relationships. Accuracy in species detection usually requires temporal replication at sampling sites, a time-consuming and costly monitoring scheme. Here, we applied a lower-cost alternative based on a double-sampling approach to incorporate the reliability of species detection into regression-based species distribution modelling.Location  Doñana National Park (south-western Spain).Methods  Using species-specific monthly detection probabilities, we estimated the detection reliability as the probability of having detected the species given the species-specific survey time. Such reliability estimates were used to account explicitly for data uncertainty by weighting each absence. We illustrated how this novel framework can be used to evaluate four competing hypotheses as to what constitutes primary environmental control of amphibian distribution: breeding habitat, aestivating habitat, spatial distribution of surrounding habitats and/or major ecosystems zonation. The study was conducted on six pond-breeding amphibian species during a 4-year period.Results  Non-detections should not be considered equivalent to real absences, as their reliability varied considerably. The occurrence of Hyla meridionalis and Triturus pygmaeus was related to a particular major ecosystem of the study area, where suitable habitat for these species seemed to be widely available. Characteristics of the breeding habitat (area and hydroperiod) were of high importance for the occurrence of Pelobates cultripes and Pleurodeles waltl. Terrestrial characteristics were the most important predictors of the occurrence of Discoglossus galganoi and Lissotriton boscai, along with spatial distribution of breeding habitats for the last species.Main conclusions  We did not find a single best supported hypothesis valid for all species, which stresses the importance of multiscale and multifactor approaches. More importantly, this study shows that estimating the reliability of non-detection records, an exercise that had been previously seen as a naïve goal in species distribution modelling, is feasible and could be promoted in future studies, at least in comparable systems.

Role of the inflammasome in murine experimental models of arthritis

Summary : The purpose of this study was to investigate the role of the inflammasome in human and experimental murine models (such as ΑΙΑ and K/BxN) of rheumatoid arthritis (RA)RA, affecting 1% of the population is the most frequent inflammatory disease characterized by synovial hyperplasia and cartilage and bone erosion, leading to joint destruction. In general, women are 3 times more affected by RA suggesting a role of estrogen in this disease. The inflammasome is a multiproteic complex triggering the activation of caspase-1 leading to the activation of IL-1 β, an important pro-inflammatory cytokine implicated in arthritis. The inflammasome has been implicated in several inflammatory diseases and particularly in gout. To highlight a possible role of the inflammasome in murine arthritis, we obtained ASC, caspase-1 and NALP3 +/+ and -/- littermate mice to perform ΑΙΑ and K/BxN arthritis. NALP3 -/- and caspase-1 -/- mice were as arthritic as wild type littermate mice in both ΑΙΑ and K/BxN models implicating that the NALP3 inflammasome is not involved in experimental arthritis. By contrast, ΑΙΑ severity was significantly diminished in ASC- deficient male and female mice, and in the K/BxN model, in ASC-deficient female mice. These results were supported by histological scoring and acute phase protein serum amyloid A (SAA) levels that were equivalent between NALP+/+ and NALP3-/- mice and diminished in ASC -/- mice. In ΑΙΑ and K/BxN murine experimental models, we observed a sexdependent phenotype. We studied the role of estradiol in both the ALA and the K/BxN models. Castrated female or male ASC -/- mice that received estradiol had a decreased arthritis severity. This implies a protective role of estrogen in the absence of ASC. In the ΑΙΑ model, proliferation assay were performed using splenocytes from mBSA- immunized ASC +/+ and -/- mice. The mBSA-induced proliferation was significantly lower in ASC-/- splenocytes. Moreover the CD3-specific proliferation of purified splenic Τ cells was significantly lower in ASC-/- cells. Finally, Τ cells from ASC-/- mice produced significantly decreased levels of IFN-gamma associated with increased levels of IL-10. These results imply a possible role of ASC in the TCR-signaling pathway and Τ cell cytokine production. In parallel the expression of the different inflammasome components were analyzed in biopsies from rheumatoid arthritis (RA) and osteoarthritis (OA) patiens. The expression of the 14 different NALPs, their effector protein ASC, and caspase-1 and -5 was readily measurable by RT-PCR in a similar proportion in RA and OA synovial samples, with the exception of NALP-5 and NALP-13, which weren't found in samples from either disease. The corresponding NALP1, -3, -12 and ASC proteins were expressed at similar levels in both OA and RA biopsies, as determined by immunohistochemistry and Western-blot analysis. By contrast, caspase-1 levels were significantly enhanced in RA synovial tissues compared to those from OA patients. NALP-1, -2, -3, -10, -12 and -14, as well as ASC, caspase-1, and -5 were detected in RNA from unstimulated and stimulated RA synoviocytes. In FLS, only ASC and caspase-1 were expressed at the protein level. NALP1, 3 and 12 were not detected. However, upon stimulation, no secreted IL-Ιβ was detectable in either RA or in OA synoviocytes culture medium. Résumé : Le but de ce projet était d'étudier le rôle de l'inflammasome dans des modèles expérimentaux d'arthrite tels que les modèles ΑΙΑ et K/BxN ainsi que dans la polyarthrite humaine (RA). La polyarthrite est une maladie inflammatoire très fréquente avec 1 % de la population affectée et touche 3 fois plus les femmes que les hommes, suggérant un rôle des hormones sexuelles dans cette pathologie. L'inflammasome est un complexe multiprotéique qui permet l'activation de la caspase-1, une cystéine protéase qui va ensuite cliver et activer rinterleukine-ΐβ (IL-Ιβ). L'inflammasome a été impliqué ces dernières années dans de nombreuses maladies inflammatoires notamment dans la goutte. Pour mettre en évidence un éventuel rôle de l'inflammasome dans l'arthrite expérimentale nous avons obtenu des souris déficientes pour certains des composants de l'inflammasome tels que ASC, NALP3 et caspase-1. Les souris NALP3 déficientes et caspase-1 déficientes sont aussi arthritiques que les souris wild type correspondantes que ce soit dans le modèle ΑΙΑ ou K/BxN. Par contre les souris mâles et femelles ASC-déficientes sont moins arthritiques que les souris +/+ correspondantes dans le modèle ΑΙΑ. Dans le modèle KRN, le même phénotype (diminution de la sévérité de l'arthrite) est observé uniquement chez les femelles ASC-/- Ce phénotype est corrélé avec l'histologie ainsi qu'avec le dosage du serum amyloid A (SAA) qui reflète l'inflammation systémique et qui est diminué chez les souris ASC-déficientes. Nous avons ensuite étudié le rôle de Γ estradiol (une des formes active des estrogènes) dans les modèles K/BxN et ΑΙΑ. Les souris castrées maies ou femelles déficientes pour ASC ayant reçu de l'estradiol ont une arthrite moins sévère ce qui implique que les estradiol ont un effet protecteur en l'absence de ASC. Dans le modèle ΑΙΑ, nous nous sommes aussi intéressés à la réponse immune. Des tests de prolifération ont été effectués sur des splénocytes en présence de mBSA (qui est l'antigène utilisé dans le modèle ΑΙΑ). Les splénocytes ASC -/- ont une proliferation qui est diminuée en présence de l'antigène. De plus la proliferation de cellules Τ spléniques purifiées en présence d'anti-CD3 est diminuée chez les cellules Τ ASC-/-. Ces résultats nous indiquent une éventuelle implication de ASC dans la signalisation par le récépteur des cellules T. En parallèle l'expression des différents composants de l'inflammasome a été analysée dans des biopsies de patients atteints de polyarthrite rhumatoide (RA) et d'arthrose (OA). L'expression des 14 différents NALPs, de l'adaptateur ASC, ainsi que des caspase-1 et -5 était similaires dans les échantillons RA et OA, à l'exception de NALP5 et 13 qui n'étaient pas détéctables. L'expression protéique de NALP1, 3, 12 et ASC effectuée par Western blot et immunohistochimie était similaire dans les biopsies RA et OA. Par contre la quantité de la caspase-1 mesurée par ELISA était augmentée de façon significative dans les extraits protéiques de biopsies RA. NALP-1, -2. -3, -10, -12, and -14 ainsi que ASC, caspase-1 et -5 étaient exprimés de façon similaire par les synoviocytes RA non stimulés et stimulés. Dans les synoviocytes seuls ASC et caspase-1 étaient détéctable au niveau protéique. NALP-1, -3 et -12 n'était pas détéctables. Cependant après stimulation il n'y avait d'IL-Ιβ sécrété que ce soit dans les surnageants de cultures de synoviocytes RA ou OA.

Building predictive models of soil particle-size distribution

Is it possible to build predictive models (PMs) of soil particle-size distribution (psd) in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index). The PMs explained more than half of the data variance. This performance is similar to (or even better than) that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas. Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available. Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd) of soils in regions of complex geology.