Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

How can a dual oriT system contribute to efficient transfer of an integrative and conjugative element?

Integrative and conjugative elements (ICEs) are particularly interesting model systems for horizontal gene transfer, because they normally reside in an integrated state in the host chromosome but can excise and self-transfer under particular conditions, typically requiring exquisite regulatory cascades. Despite important advances in our understanding of the transfer mechanisms of a number of ICE, many essential details are lacking. Recently we reported that ICEclc, a 103 kb ICE of Pseudomonas knackmussii B13, has two active origins of transfer (oriTs), which is very much unlike conjugative plasmids that usually employ a single oriT. We discuss here how this dual oriT system could function and how it actually could have presented an evolutionary advantage for ICEclc distribution.

MMPBSA decomposition of the binding energy throughout a molecular dynamics simulation of Amyloid-Beta (Aß10-35) aggregation

Recent experiments with amyloid-beta (Aß) peptides indicate that the formation of toxic oligomers may be an important contribution to the onset of Alzheimer's disease. The toxicity of Aß oligomers depend on their structure, which is governed by assembly dynamics. However, a detailed knowledge of the structure of at the atomic level has not been achieved yet due to limitations of current experimental techniques. In this study, replica exchange molecular dynamics simulations are used to identify the expected diversity of dimer conformations of Aß10-35 monomers. The most representative dimer conformation has been used to track the dimer formation process between both monomers. The process has been characterized by means of the evolution of the decomposition of the binding free energy, which provides an energetic profile of the interaction. Dimers undergo a process of reorganization driven basically by inter-chain hydrophobic and hydrophilic interactions and also solvation/desolvation processes.

Test result-based sampling: an efficient design for estimating the accuracy of patient safety indicators.

OBJECTIVE: Accuracy studies of Patient Safety Indicators (PSIs) are critical but limited by the large samples required due to low occurrence of most events. We tested a sampling design based on test results (verification-biased sampling [VBS]) that minimizes the number of subjects to be verified. METHODS: We considered 3 real PSIs, whose rates were calculated using 3 years of discharge data from a university hospital and a hypothetical screen of very rare events. Sample size estimates, based on the expected sensitivity and precision, were compared across 4 study designs: random and VBS, with and without constraints on the size of the population to be screened. RESULTS: Over sensitivities ranging from 0.3 to 0.7 and PSI prevalence levels ranging from 0.02 to 0.2, the optimal VBS strategy makes it possible to reduce sample size by up to 60% in comparison with simple random sampling. For PSI prevalence levels below 1%, the minimal sample size required was still over 5000. CONCLUSIONS: Verification-biased sampling permits substantial savings in the required sample size for PSI validation studies. However, sample sizes still need to be very large for many of the rarer PSIs.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

Invasion and eradication of a competitively superior species in heterogeneous landscapes

The effect of heterogeneous environments upon the dynamics of invasion and the eradication or control of invasive species is poorly understood, although it is a major challenge for biodiversity conservation. Here, we first investigate how the probability and time for invasion are affected by spatial heterogeneity. Then, we study the effect of control program strategies (e.g. species specificity, spatial scale of action, detection and eradication efficiency) on the success and time of eradication. We find that heterogeneity increases both the invasion probability and the time to invasion. Heterogeneity also reduces the probability of eradication but does not change the time taken for successful eradication. We confirm that early detection of invasive species reduces the time until eradication, but we also demonstrate that this is true only if the local control action is sufficiently efficient. The criterion of removal efficiency is even more important for an eradication program than simply ensuring control effort when the invasive species is not abundant.

Dosage optimization of treatments using population pharmacokinetic modeling and simulation.

Pharmacokinetic variability in drug levels represent for some drugs a major determinant of treatment success, since sub-therapeutic concentrations might lead to toxic reactions, treatment discontinuation or inefficacy. This is true for most antiretroviral drugs, which exhibit high inter-patient variability in their pharmacokinetics that has been partially explained by some genetic and non-genetic factors. The population pharmacokinetic approach represents a very useful tool for the description of the dose-concentration relationship, the quantification of variability in the target population of patients and the identification of influencing factors. It can thus be used to make predictions and dosage adjustment optimization based on Bayesian therapeutic drug monitoring (TDM). This approach has been used to characterize the pharmacokinetics of nevirapine (NVP) in 137 HIV-positive patients followed within the frame of a TDM program. Among tested covariates, body weight, co-administration of a cytochrome (CYP) 3A4 inducer or boosted atazanavir as well as elevated aspartate transaminases showed an effect on NVP elimination. In addition, genetic polymorphism in the CYP2B6 was associated with reduced NVP clearance. Altogether, these factors could explain 26% in NVP variability. Model-based simulations were used to compare the adequacy of different dosage regimens in relation to the therapeutic target associated with treatment efficacy. In conclusion, the population approach is very useful to characterize the pharmacokinetic profile of drugs in a population of interest. The quantification and the identification of the sources of variability is a rational approach to making optimal dosage decision for certain drugs administered chronically.

Comparing simulation methods for modelling the errors of stand inventory data

Abstract

Réplication cérébrale du VIH malgré une thérapie antirétrovirale efficace: impact clinique et prise en charge [Intracerebral HIV replication despite an efficient antiretroviral treatment: clinical impact and management].

Various neurological and neuropsychological manifestations are still relatively frequently reported in HIV infected patients in the highly active antiretroviral therapy era. A fraction of them could be related to HIV replication in the central nervous system (CNS) despite adequate peripheral viral suppression. This hypothesis is supported by numerous reports of detectable HIV RNA in the cerebrospinal fluid in the context of a low or undetectable viremia in association with neurological or neuropsychological complaints. In addition, some antiviral molecules may not achieve adequate levels in the CNS, thus potentially favoring intracerebral HIV replication and even antiretroviral resistance. Neurologic manifestations in the presence of CNS HIV replication often decrease after antiretroviral treatment CNS penetration optimization.

Efficient total variation algorithm for fetal brain MRI reconstruction.

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy, Total Variation (TV)- based energies and more recently non-local means. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm or fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n2) and O(1/√ε), while existing techniques are in O(1/n2) and O(1/√ε). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

Simulation of spring wheat responses to elevated CO‚́‚ and temperature by using CERES-wheat crop model

Selostus: Kohotettujen CO‚́‚:n ja lämpötilan vaikutukset kevätvehnän fenologiseen kehitykseen ja sadontuottomahdollisuuksiin

Immediate hip spica is as effective as but more efficient than flexible intramedullary nailing for femoral shaft fractures in preschool children

Résumé¦L'Embrochage Centro-Médullaire Elastique Stable (ECMES) est le traitement de choix des fractures du fémur chez l'enfant en âge scolaire. Il est pratiqué avec succès chez le jeune enfant, alors que l'Immobilisation par Plâtre (IP) était la technique la plus largement utilisée jusque-là.¦Méthode : Une analyse rétrospective comparant deux groupes d'enfants âgés de 1 à 4 ans avec des fractures diaphysaires du fémur a été effectuée. Deux hôpitaux universitaires, utilisant chacun une méthode de traitement spécifique, ont participé à cette étude : l'IP dans le groupe I (Bâle, Suisse) et l'ECMES dans le groupe II (Lausanne, Suisse).¦Résultats : Le groupe I inclue 19 enfants avec un âge médian de 26 mois (12-46 mois). La médiane du séjour hospitalier est de 1 jour (0-5 jours) et le plâtre est laissé en place pour une durée médiane de 21 jours (12-29 jours). Une anesthésie générale a été nécessaire chez 6 enfants et une sédation chez 4. Des lésions cutanées secondaires au plâtre sont apparues chez 2 enfants (10.5%). La médiane de la durée du suivi est de 114 mois (37-171 mois). Aucun défaut de consolidation n'est à déplorer. Le groupe II inclue 27 enfants avec un âge médian de 38.4 mois (18.7-46.7 mois). La médiane du séjour hospitalier est de 4 jours (1-13 jours). Tous les enfants ont nécessité une anesthésie générale pour la mise en place et pour le retrait des broches. La mobilisation et la mise en charge complète du membre ont été permises respectivement à une médiane de 2 jours (1-10 jours) et 7 jours (1-30 jours) postopératoires. Une complication sous la forme d'une extériorisation à la peau d'une broche a été notée chez 3 enfants (11%). La médiane de la durée du suivi et de 16.5 mois (8-172 mois). Aucun défaut de consolidation n'est à déplorer.¦Conclusion : Les jeunes enfants présentant une fracture diaphysaire du fémur, traité pas IP ou ECMES, ont des résultats favorables et des taux de complications similaires. L'ECMES permet une mobilisation et une charge complète sur le membre fracturé plus rapide. Mais comparé à l'IP, l'ECMES requiert un plus grand nombre d'anesthésies générales. Chez un enfant d'âge préscolaire présentant une fracture diaphysaire du fémur, l'application immédiate d'un plâtre par une équipe orthopédique pédiatrique entraînée à la mise en place de plâtre chez l'enfant, permet un retour à domicile rapide et un taux de complication bas.