Crossed ataxia: a case report and a diffusion tensor imaging tractography study.

Background and Purpose-Ever since the seminal description of ataxic hemiparesis contralateral to a pontine lesion by Miller-Fisher, the question of why contralesional crossing pontocerebellar fibers do not more frequently produce ipsilesional hemiataxia was raised. The few cases of "quadrataxic hemiparesis" or bilateral leg ataxia remain exceptions.Summary of Case-We report an even more unusual variant, namely "crossed ataxia" of the contralesional arm and the ipsilesional leg subsequent to an anteromedial pontine ischemic stroke.Conclusions-MRI diffusion tensor imaging tractography shows that caudal contralesional crossing pontocerebellar fibers (those for the leg) travel trough the lesion, whereas more rostral fibers (those for the arm) are spared. (Stroke. 2011; 42:e571-e573.)

Pore-scale modeling of two-phase flow instabilities in porous media

Les problèmes d'écoulements multiphasiques en média poreux sont d'un grand intérêt pour de nombreuses applications scientifiques et techniques ; comme la séquestration de C02, l'extraction de pétrole et la dépollution des aquifères. La complexité intrinsèque des systèmes multiphasiques et l'hétérogénéité des formations géologiques sur des échelles multiples représentent un challenge majeur pour comprendre et modéliser les déplacements immiscibles dans les milieux poreux. Les descriptions à l'échelle supérieure basées sur la généralisation de l'équation de Darcy sont largement utilisées, mais ces méthodes sont sujettes à limitations pour les écoulements présentant de l'hystérèse. Les avancées récentes en terme de performances computationnelles et le développement de méthodes précises pour caractériser l'espace interstitiel ainsi que la distribution des phases ont favorisé l'utilisation de modèles qui permettent une résolution fine à l'échelle du pore. Ces modèles offrent un aperçu des caractéristiques de l'écoulement qui ne peuvent pas être facilement observées en laboratoire et peuvent être utilisé pour expliquer la différence entre les processus physiques et les modèles à l'échelle macroscopique existants. L'objet premier de la thèse se porte sur la simulation numérique directe : les équations de Navier-Stokes sont résolues dans l'espace interstitiel et la méthode du volume de fluide (VOF) est employée pour suivre l'évolution de l'interface. Dans VOF, la distribution des phases est décrite par une fonction fluide pour l'ensemble du domaine et des conditions aux bords particulières permettent la prise en compte des propriétés de mouillage du milieu poreux. Dans la première partie de la thèse, nous simulons le drainage dans une cellule Hele-Shaw 2D avec des obstacles cylindriques. Nous montrons que l'approche proposée est applicable même pour des ratios de densité et de viscosité très importants et permet de modéliser la transition entre déplacement stable et digitation visqueuse. Nous intéressons ensuite à l'interprétation de la pression capillaire à l'échelle macroscopique. Nous montrons que les techniques basées sur la moyenne spatiale de la pression présentent plusieurs limitations et sont imprécises en présence d'effets visqueux et de piégeage. Au contraire, une définition basée sur l'énergie permet de séparer les contributions capillaires des effets visqueux. La seconde partie de la thèse est consacrée à l'investigation des effets d'inertie associés aux reconfigurations irréversibles du ménisque causé par l'interface des instabilités. Comme prototype pour ces phénomènes, nous étudions d'abord la dynamique d'un ménisque dans un pore angulaire. Nous montrons que, dans un réseau de pores cubiques, les sauts et reconfigurations sont si fréquents que les effets d'inertie mènent à différentes configurations des fluides. A cause de la non-linéarité du problème, la distribution des fluides influence le travail des forces de pression, qui, à son tour, provoque une chute de pression dans la loi de Darcy. Cela suggère que ces phénomènes devraient être pris en compte lorsque que l'on décrit l'écoulement multiphasique en média poreux à l'échelle macroscopique. La dernière partie de la thèse s'attache à démontrer la validité de notre approche par une comparaison avec des expériences en laboratoire : un drainage instable dans un milieu poreux quasi 2D (une cellule Hele-Shaw avec des obstacles cylindriques). Plusieurs simulations sont tournées sous différentes conditions aux bords et en utilisant différents modèles (modèle intégré 2D et modèle 3D) afin de comparer certaines quantités macroscopiques avec les observations au laboratoire correspondantes. Malgré le challenge de modéliser des déplacements instables, où, par définition, de petites perturbations peuvent grandir sans fin, notre approche numérique apporte de résultats satisfaisants pour tous les cas étudiés. - Problems involving multiphase flow in porous media are of great interest in many scientific and engineering applications including Carbon Capture and Storage, oil recovery and groundwater remediation. The intrinsic complexity of multiphase systems and the multi scale heterogeneity of geological formations represent the major challenges to understand and model immiscible displacement in porous media. Upscaled descriptions based on generalization of Darcy's law are widely used, but they are subject to several limitations for flow that exhibit hysteric and history- dependent behaviors. Recent advances in high performance computing and the development of accurate methods to characterize pore space and phase distribution have fostered the use of models that allow sub-pore resolution. These models provide an insight on flow characteristics that cannot be easily achieved by laboratory experiments and can be used to explain the gap between physical processes and existing macro-scale models. We focus on direct numerical simulations: we solve the Navier-Stokes equations for mass and momentum conservation in the pore space and employ the Volume Of Fluid (VOF) method to track the evolution of the interface. In the VOF the distribution of the phases is described by a fluid function (whole-domain formulation) and special boundary conditions account for the wetting properties of the porous medium. In the first part of this thesis we simulate drainage in a 2-D Hele-Shaw cell filled with cylindrical obstacles. We show that the proposed approach can handle very large density and viscosity ratios and it is able to model the transition from stable displacement to viscous fingering. We then focus on the interpretation of the macroscopic capillary pressure showing that pressure average techniques are subject to several limitations and they are not accurate in presence of viscous effects and trapping. On the contrary an energy-based definition allows separating viscous and capillary contributions. In the second part of the thesis we investigate inertia effects associated with abrupt and irreversible reconfigurations of the menisci caused by interface instabilities. As a prototype of these phenomena we first consider the dynamics of a meniscus in an angular pore. We show that in a network of cubic pores, jumps and reconfigurations are so frequent that inertia effects lead to different fluid configurations. Due to the non-linearity of the problem, the distribution of the fluids influences the work done by pressure forces, which is in turn related to the pressure drop in Darcy's law. This suggests that these phenomena should be taken into account when upscaling multiphase flow in porous media. The last part of the thesis is devoted to proving the accuracy of the numerical approach by validation with experiments of unstable primary drainage in a quasi-2D porous medium (i.e., Hele-Shaw cell filled with cylindrical obstacles). We perform simulations under different boundary conditions and using different models (2-D integrated and full 3-D) and we compare several macroscopic quantities with the corresponding experiment. Despite the intrinsic challenges of modeling unstable displacement, where by definition small perturbations can grow without bounds, the numerical method gives satisfactory results for all the cases studied.

Mapping the human connectome at multiple scales with diffusion spectrum MRI.

The global structural connectivity of the brain, the human connectome, is now accessible at millimeter scale with the use of MRI. In this paper, we describe an approach to map the connectome by constructing normalized whole-brain structural connection matrices derived from diffusion MRI tractography at 5 different scales. Using a template-based approach to match cortical landmarks of different subjects, we propose a robust method that allows (a) the selection of identical cortical regions of interest of desired size and location in different subjects with identification of the associated fiber tracts (b) straightforward construction and interpretation of anatomically organized whole-brain connection matrices and (c) statistical inter-subject comparison of brain connectivity at various scales. The fully automated post-processing steps necessary to build such matrices are detailed in this paper. Extensive validation tests are performed to assess the reproducibility of the method in a group of 5 healthy subjects and its reliability is as well considerably discussed in a group of 20 healthy subjects.

Towards a diffusion image processing validation and accuracy prediction framework

Validation is the main bottleneck preventing theadoption of many medical image processing algorithms inthe clinical practice. In the classical approach,a-posteriori analysis is performed based on someobjective metrics. In this work, a different approachbased on Petri Nets (PN) is proposed. The basic ideaconsists in predicting the accuracy that will result froma given processing based on the characterization of thesources of inaccuracy of the system. Here we propose aproof of concept in the scenario of a diffusion imaginganalysis pipeline. A PN is built after the detection ofthe possible sources of inaccuracy. By integrating thefirst qualitative insights based on the PN withquantitative measures, it is possible to optimize the PNitself, to predict the inaccuracy of the system in adifferent setting. Results show that the proposed modelprovides a good prediction performance and suggests theoptimal processing approach.

Toxicokinetic modeling of folpet fungicide and its ring-biomarkers of exposure in humans.

A human in vivo toxicokinetic model was built to allow a better understanding of the toxicokinetics of folpet fungicide and its key ring biomarkers of exposure: phthalimide (PI), phthalamic acid (PAA) and phthalic acid (PA). Both PI and the sum of ring metabolites, expressed as PA equivalents (PAeq), may be used as biomarkers of exposure. The conceptual representation of the model was based on the analysis of the time course of these biomarkers in volunteers orally and dermally exposed to folpet. In the model, compartments were also used to represent the body burden of folpet and experimentally relevant PI, PAA and PA ring metabolites in blood and in key tissues as well as in excreta, hence urinary and feces. The time evolution of these biomarkers in each compartment of the model was then mathematically described by a system of coupled differential equations. The mathematical parameters of the model were then determined from best fits to the time courses of PI and PAeq in blood and urine of five volunteers administered orally 1 mg kg(-1) and dermally 10 mg kg(-1) of folpet. In the case of oral administration, the mean elimination half-life of PI from blood (through feces, urine or metabolism) was found to be 39.9 h as compared with 28.0 h for PAeq. In the case of a dermal application, mean elimination half-life of PI and PAeq was estimated to be 34.3 and 29.3 h, respectively. The average final fractions of administered dose recovered in urine as PI over the 0-96 h period were 0.030 and 0.002%, for oral and dermal exposure, respectively. Corresponding values for PAeq were 24.5 and 1.83%, respectively. Finally, the average clearance rate of PI from blood calculated from the oral and dermal data was 0.09 ± 0.03 and 0.13 ± 0.05 ml h(-1) while the volume of distribution was 4.30 ± 1.12 and 6.05 ± 2.22 l, respectively. It was not possible to obtain the corresponding values from PAeq data owing to the lack of blood time course data.

Combining digital elevation model analysis and run-out modeling to characterize hazard posed by a potentially unstable rock slope at Turtle Mountain, Alberta, Canada

Turtle Mountain in Alberta, Canada has become an important field laboratory for testing different techniques related to the characterization and monitoring of large slope mass movements as the stability of large portions of the eastern face of the mountain is still questionable. In order to better quantify the volumes potentially unstable and the most probable failure mechanisms and potential consequences, structural analysis and runout modeling were preformed. The structural features of the eastern face were investigated using a high resolution digital elevation model (HRDEM). According to displacement datasets and structural observations, potential failure mechanisms affecting different portions of the mountain have been assessed. The volumes of the different potentially unstable blocks have been calculated using the Sloping Local Base Level (SLBL) method. Based on the volume estimation, two and three dimensional dynamic runout analyses have been performed. Calibration of this analysis is based on the experience from the adjacent Frank Slide and other similar rock avalanches. The results will be used to improve the contingency plans within the hazard area.

Public health impact of statin prescribing strategies based on JUPITER Modeling study from a population-based study.

OBJECTIVE: To evaluate the public health impact of statin prescribing strategies based on the Justification for the Use of Statins in Primary Prevention: An Intervention Trial Evaluating Rosuvastatin Study (JUPITER). METHODS: We studied 2268 adults aged 35-75 without cardiovascular disease in a population-based study in Switzerland in 2003-2006. We assessed the eligibility for statins according to the Adult Treatment Panel III (ATPIII) guidelines, and by adding "strict" (hs-CRP≥2.0mg/L and LDL-cholesterol <3.4mmol/L), and "extended" (hs-CRP≥2.0mg/L alone) JUPITER-like criteria. We estimated the proportion of CHD deaths potentially prevented over 10years in the Swiss population. RESULTS: Fifteen % were already taking statins, 42% were eligible by ATPIII guidelines, 53% by adding "strict", and 62% by adding "extended" criteria, with a total of 19% newly eligible. The number needed to treat with statins to avoid one CHD death over 10years was 38 for ATPIII, 84 for "strict" and 92 for "extended" JUPITER-like criteria. ATPIII would prevent 17% of CHD deaths, compared with 20% for ATPIII+"strict" and 23% for ATPIII + "extended" criteria (+6%). CONCLUSION: Implementing JUPITER-like strategies would make statin prescribing for primary prevention more common and less efficient than it is with current guidelines.

Long-term monitoring of post-stroke plasticity after transient cerebral ischemia in mice using in vivo and ex vivo diffusion tensor MRI.

WE USED A MURINE MODEL OF TRANSIENT FOCAL CEREBRAL ISCHEMIA TO STUDY: 1) in vivo DTI long-term temporal evolution of the apparent diffusion coefficient (ADC) and diffusion fractional anisotropy (FA) at days 4, 10, 15 and 21 after stroke 2) ex vivo distribution of a plasticity-related protein (GAP-43) and its relationship with the ex vivo DTI characteristics of the striato-thalamic pathway (21 days). All animals recovered motor function. In vivo ADC within the infarct was significantly increased after stroke. In the stroke group, GAP-43 expression and FA values were significantly higher in the ipsilateral (IL) striatum and contralateral (CL) hippocampus compared to the shams. DTI tractography showed fiber trajectories connecting the CL striatum to the stroke region, where increased GAP43 and FA were observed and fiber tracts from the CL striatum terminating in the IL hippocampus.Our data demonstrate that DTI changes parallel histological remodeling and recovery of function.

Mechanisms underlying functional recovery after in vivo focal cerebral ischemia : from preconditioning to diffusion MRI

Version abregée L'ischémie cérébrale est la troisième cause de mort dans les pays développés, et la maladie responsable des plus sérieux handicaps neurologiques. La compréhension des bases moléculaires et anatomiques de la récupération fonctionnelle après l'ischémie cérébrale est donc extrêmement importante et représente un domaine d'intérêt crucial pour la recherche fondamentale et clinique. Durant les deux dernières décennies, les chercheurs ont tenté de combattre les effets nocifs de l'ischémie cérébrale à l'aide de substances exogènes qui, bien que testées avec succès dans le domaine expérimental, ont montré un effet contradictoire dans l'application clinique. Une approche différente mais complémentaire est de stimuler des mécanismes intrinsèques de neuroprotection en utilisant le «modèle de préconditionnement» : une brève insulte protège contre des épisodes d'ischémie plus sévères à travers la stimulation de voies de signalisation endogènes qui augmentent la résistance à l'ischémie. Cette approche peut offrir des éléments importants pour clarifier les mécanismes endogènes de neuroprotection et fournir de nouvelles stratégies pour rendre les neurones et la glie plus résistants à l'attaque ischémique cérébrale. Dans un premier temps, nous avons donc étudié les mécanismes de neuroprotection intrinsèques stimulés par la thrombine, un neuroprotecteur «préconditionnant» dont on a montré, à l'aide de modèles expérimentaux in vitro et in vivo, qu'il réduit la mort neuronale. En appliquant une technique de microchirurgie pour induire une ischémie cérébrale transitoire chez la souris, nous avons montré que la thrombine peut stimuler les voies de signalisation intracellulaire médiées par MAPK et JNK par une approche moléculaire et l'analyse in vivo d'un inhibiteur spécifique de JNK (L JNK) .Nous avons également étudié l'impact de la thrombine sur la récupération fonctionnelle après une attaque et avons pu démontrer que ces mécanismes moléculaires peuvent améliorer la récupération motrice. La deuxième partie de cette étude des mécanismes de récupération après ischémie cérébrale est basée sur l'investigation des bases anatomiques de la plasticité des connections cérébrales, soit dans le modèle animal d'ischémie transitoire, soit chez l'homme. Selon des résultats précédemment publiés par divers groupes ,nous savons que des mécanismes de plasticité aboutissant à des degrés divers de récupération fonctionnelle sont mis enjeu après une lésion ischémique. Le résultat de cette réorganisation est une nouvelle architecture fonctionnelle et structurelle, qui varie individuellement selon l'anatomie de la lésion, l'âge du sujet et la chronicité de la lésion. Le succès de toute intervention thérapeutique dépendra donc de son interaction avec la nouvelle architecture anatomique. Pour cette raison, nous avons appliqué deux techniques de diffusion en résonance magnétique qui permettent de détecter les changements de microstructure cérébrale et de connexions anatomiques suite à une attaque : IRM par tenseur de diffusion (DT-IR1V) et IRM par spectre de diffusion (DSIRM). Grâce à la DT-IRM hautement sophistiquée, nous avons pu effectuer une étude de follow-up à long terme chez des souris ayant subi une ischémie cérébrale transitoire, qui a mis en évidence que les changements microstructurels dans l'infarctus ainsi que la modification des voies anatomiques sont corrélés à la récupération fonctionnelle. De plus, nous avons observé une réorganisation axonale dans des aires où l'on détecte une augmentation d'expression d'une protéine de plasticité exprimée dans le cône de croissance des axones (GAP-43). En appliquant la même technique, nous avons également effectué deux études, rétrospective et prospective, qui ont montré comment des paramètres obtenus avec DT-IRM peuvent monitorer la rapidité de récupération et mettre en évidence un changement structurel dans les voies impliquées dans les manifestations cliniques. Dans la dernière partie de ce travail, nous avons décrit la manière dont la DS-IRM peut être appliquée dans le domaine expérimental et clinique pour étudier la plasticité cérébrale après ischémie. Abstract Ischemic stroke is the third leading cause of death in developed countries and the disease responsible for the most serious long-term neurological disability. Understanding molecular and anatomical basis of stroke recovery is, therefore, extremely important and represents a major field of interest for basic and clinical research. Over the past 2 decades, much attention has focused on counteracting noxious effect of the ischemic insult with exogenous substances (oxygen radical scavengers, AMPA and NMDA receptor antagonists, MMP inhibitors etc) which were successfully tested in the experimental field -but which turned out to have controversial effects in clinical trials. A different but complementary approach to address ischemia pathophysiology and treatment options is to stimulate and investigate intrinsic mechanisms of neuroprotection using the "preconditioning effect": applying a brief insult protects against subsequent prolonged and detrimental ischemic episodes, by up-regulating powerful endogenous pathways that increase resistance to injury. We believe that this approach might offer an important insight into the molecular mechanisms responsible for endogenous neuroprotection. In addition, results from preconditioning model experiment may provide new strategies for making brain cells "naturally" more resistant to ischemic injury and accelerate their rate of functional recovery. In the first part of this work, we investigated down-stream mechanisms of neuroprotection induced by thrombin, a well known neuroprotectant which has been demonstrated to reduce stroke-induced cell death in vitro and in vivo experimental models. Using microsurgery to induce transient brain ischemia in mice, we showed that thrombin can stimulate both MAPK and JNK intracellular pathways through a molecular biology approach and an in vivo analysis of a specific kinase inhibitor (L JNK1). We also studied thrombin's impact on functional recovery demonstrating that these molecular mechanisms could enhance post-stroke motor outcome. The second part of this study is based on investigating the anatomical basis underlying connectivity remodeling, leading to functional improvement after stroke. To do this, we used both a mouse model of experimental ischemia and human subjects with stroke. It is known from previous data published in literature, that the brain adapts to damage in a way that attempts to preserve motor function. The result of this reorganization is a new functional and structural architecture, which will vary from patient to patient depending on the anatomy of the damage, the biological age of the patient and the chronicity of the lesion. The success of any given therapeutic intervention will depend on how well it interacts with this new architecture. For this reason, we applied diffusion magnetic resonance techniques able to detect micro-structural and connectivity changes following an ischemic lesion: diffusion tensor MRI (DT-MRI) and diffusion spectrum MRI (DS-MRI). Using DT-MRI, we performed along-term follow up study of stroke mice which showed how diffusion changes in the stroke region and fiber tract remodeling is correlating with stroke recovery. In addition, axonal reorganization is shown in areas of increased plasticity related protein expression (GAP 43, growth axonal cone related protein). Applying the same technique, we then performed a retrospective and a prospective study in humans demonstrating how specific DTI parameters could help to monitor the speed of recovery and show longitudinal changes in damaged tracts involved in clinical symptoms. Finally, in the last part of this study we showed how DS-MRI could be applied both to experimental and human stroke and which perspectives it can open to further investigate post stroke plasticity.

Implicit methods for qualitative modeling of gene regulatory networks.

Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from the single-gene single-protein experimental approach to studying the behavior of a gene in the context of the entire genome (and proteome). This shift in research methodologies has resulted in a new field of network biology that deals with modeling cellular behavior in terms of network structures such as signaling pathways and gene regulatory networks. In these networks, different biological entities such as genes, proteins, and metabolites interact with each other, giving rise to a dynamical system. Even though there exists a mature field of dynamical systems theory to model such network structures, some technical challenges are unique to biology such as the inability to measure precise kinetic information on gene-gene or gene-protein interactions and the need to model increasingly large networks comprising thousands of nodes. These challenges have renewed interest in developing new computational techniques for modeling complex biological systems. This chapter presents a modeling framework based on Boolean algebra and finite-state machines that are reminiscent of the approach used for digital circuit synthesis and simulation in the field of very-large-scale integration (VLSI). The proposed formalism enables a common mathematical framework to develop computational techniques for modeling different aspects of the regulatory networks such as steady-state behavior, stochasticity, and gene perturbation experiments.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.