952 resultados para Non-response model approach
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The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.
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The application of forced unsteady-state reactors in case of selective catalytic reduction of nitrogen oxides (NOx) with ammonia (NH3) is sustained by the fact that favorable temperature and composition distributions which cannot be achieved in any steady-state regime can be obtained by means of unsteady-state operations. In a normal way of operation the low exothermicity of the selective catalytic reduction (SCR) reaction (usually carried out in the range of 280-350°C) is not enough to maintain by itself the chemical reaction. A normal mode of operation usually requires supply of supplementary heat increasing in this way the overall process operation cost. Through forced unsteady-state operation, the main advantage that can be obtained when exothermic reactions take place is the possibility of trapping, beside the ammonia, the moving heat wave inside the catalytic bed. The unsteady state-operation enables the exploitation of the thermal storage capacity of the catalyticbed. The catalytic bed acts as a regenerative heat exchanger allowing auto-thermal behaviour when the adiabatic temperature rise is low. Finding the optimum reactor configuration, employing the most suitable operation model and identifying the reactor behavior are highly important steps in order to configure a proper device for industrial applications. The Reverse Flow Reactor (RFR) - a forced unsteady state reactor - corresponds to the above mentioned characteristics and may be employed as an efficient device for the treatment of dilute pollutant mixtures. As a main disadvantage, beside its advantages, the RFR presents the 'wash out' phenomena. This phenomenon represents emissions of unconverted reactants at every switch of the flow direction. As a consequence our attention was focused on finding an alternative reactor configuration for RFR which is not affected by the incontrollable emissions of unconverted reactants. In this respect the Reactor Network (RN) was investigated. Its configuration consists of several reactors connected in a closed sequence, simulating a moving bed by changing the reactants feeding position. In the RN the flow direction is maintained in the same way ensuring uniformcatalyst exploitation and in the same time the 'wash out' phenomena is annulated. The simulated moving bed (SMB) can operate in transient mode giving practically constant exit concentration and high conversion levels. The main advantage of the reactor network operation is emphasizedby the possibility to obtain auto-thermal behavior with nearly uniformcatalyst utilization. However, the reactor network presents only a small range of switching times which allow to reach and to maintain an ignited state. Even so a proper study of the complex behavior of the RN may give the necessary information to overcome all the difficulties that can appear in the RN operation. The unsteady-state reactors complexity arises from the fact that these reactor types are characterized by short contact times and complex interaction between heat and mass transportphenomena. Such complex interactions can give rise to a remarkable complex dynamic behavior characterized by a set of spatial-temporal patterns, chaotic changes in concentration and traveling waves of heat or chemical reactivity. The main efforts of the current research studies concern the improvement of contact modalities between reactants, the possibility of thermal wave storage inside the reactor and the improvement of the kinetic activity of the catalyst used. Paying attention to the above mentioned aspects is important when higher activity even at low feeding temperatures and low emissions of unconverted reactants are the main operation concerns. Also, the prediction of the reactor pseudo or steady-state performance (regarding the conversion, selectivity and thermal behavior) and the dynamicreactor response during exploitation are important aspects in finding the optimal control strategy for the forced unsteady state catalytic tubular reactors. The design of an adapted reactor requires knowledge about the influence of its operating conditions on the overall process performance and a precise evaluation of the operating parameters rage for which a sustained dynamic behavior is obtained. An apriori estimation of the system parameters result in diminution of the computational efforts. Usually the convergence of unsteady state reactor systems requires integration over hundreds of cycles depending on the initial guess of the parameter values. The investigation of various operation models and thermal transfer strategies give reliable means to obtain recuperative and regenerative devices which are capable to maintain an auto-thermal behavior in case of low exothermic reactions. In the present research work a gradual analysis of the SCR of NOx with ammonia process in forced unsteady-state reactors was realized. The investigation covers the presentationof the general problematic related to the effect of noxious emissions in the environment, the analysis of the suitable catalysts types for the process, the mathematical analysis approach for modeling and finding the system solutions and the experimental investigation of the device found to be more suitable for the present process. In order to gain information about the forced unsteady state reactor design, operation, important system parameters and their values, mathematical description, mathematicalmethod for solving systems of partial differential equations and other specific aspects, in a fast and easy way, and a case based reasoning (CBR) approach has been used. This approach, using the experience of past similarproblems and their adapted solutions, may provide a method for gaining informations and solutions for new problems related to the forced unsteady state reactors technology. As a consequence a CBR system was implemented and a corresponding tool was developed. Further on, grooving up the hypothesis of isothermal operation, the investigation by means of numerical simulation of the feasibility of the SCR of NOx with ammonia in the RFRand in the RN with variable feeding position was realized. The hypothesis of non-isothermal operation was taken into account because in our opinion ifa commercial catalyst is considered, is not possible to modify the chemical activity and its adsorptive capacity to improve the operation butis possible to change the operation regime. In order to identify the most suitable device for the unsteady state reduction of NOx with ammonia, considering the perspective of recuperative and regenerative devices, a comparative analysis of the above mentioned two devices performance was realized. The assumption of isothermal conditions in the beginningof the forced unsteadystate investigation allowed the simplification of the analysis enabling to focus on the impact of the conditions and mode of operation on the dynamic features caused by the trapping of one reactant in the reactor, without considering the impact of thermal effect on overall reactor performance. The non-isothermal system approach has been investigated in order to point out the important influence of the thermal effect on overall reactor performance, studying the possibility of RFR and RN utilization as recuperative and regenerative devices and the possibility of achieving a sustained auto-thermal behavior in case of lowexothermic reaction of SCR of NOx with ammonia and low temperature gasfeeding. Beside the influence of the thermal effect, the influence of the principal operating parameters, as switching time, inlet flow rate and initial catalyst temperature have been stressed. This analysis is important not only because it allows a comparison between the two devices and optimisation of the operation, but also the switching time is the main operating parameter. An appropriate choice of this parameter enables the fulfilment of the process constraints. The level of the conversions achieved, the more uniform temperature profiles, the uniformity ofcatalyst exploitation and the much simpler mode of operation imposed the RN as a much more suitable device for SCR of NOx with ammonia, in usual operation and also in the perspective of control strategy implementation. Theoretical simplified models have also been proposed in order to describe the forced unsteady state reactors performance and to estimate their internal temperature and concentration profiles. The general idea was to extend the study of catalytic reactor dynamics taking into account the perspectives that haven't been analyzed yet. The experimental investigation ofRN revealed a good agreement between the data obtained by model simulation and the ones obtained experimentally.
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Understanding the factors controlling fine root respiration (FRR) at different temporal scales will help to improve our knowledge about the spatial and temporal variability of soil respiration (SR) and to improve future predictions of CO2 effluxes to the atmosphere. Here we present a comparative study of how FRR respond to variability in soil temperature and moisture in two widely spread species, Scots pines (Pinus sylvestris L.) and Holm-oaks (HO; Quercus ilex L.). Those two species show contrasting water use strategies during the extreme summer-drought conditions that characterize the Mediterranean climate. The study was carried out on a mixed Mediterranean forest where Scots pines affected by drought induced die-back are slowly being replaced by the more drought resistant HO. FRR was measured in spring and early fall 2013 in excised roots freshly removed from the soil and collected under HO and under Scots pines at three different health stages: dead (D), defoliated (DP) and non-defoliated (NDP). Variations in soil temperature, soil water content and daily mean assimilation per tree were also recorded to evaluate FRR sensibility to abiotic and biotic environmental variations. Our results show that values of FRR were substantially lower under HO (1.26 ± 0.16 microgram CO2 /groot·min) than under living pines (1.89 ± 0.19 microgram CO2 /groot·min) which disagrees with the similar rates of soil respiration previously observed under both canopies and suggest that FRR contribution to total SR varies under different tree species. The similarity of FRR rates under HO and DP furthermore confirms other previous studies suggesting a recent Holm-oak root colonization of the gaps under dead trees. A linear mixed effect model approach indicated that seasonal variations in FRR were best explained by soil temperature (p<0.05) while soil moisture was not exerting any direct control over FRR, despite the low soil moisture values during the summer sampling. Plant assimilation rates were positively related to FRR explaining part of the observed variability (p<0.01). However the positive relations of FRR with plant assimilation occurred mainly during spring, when both soil moisture and plant assimilation rates were higher. Our results finally suggest that plants might be able to maintain relatively high rates of FRR during the sub-optimal abiotic and biotic summer conditions probably thanks to their capacity to re-mobilize carbon reserves and their capacity to passively move water from moister layers to upper layers with lower water potentials (where the FR were collected) by hydraulic lift.
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Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.
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This work deals with analysis of cracked structures using BEM. Two formulations to analyse the crack growth process in quasi-brittle materials are discussed. They are based on the dual formulation of BEM where two different integral equations are employed along the opposite sides of the crack surface. The first presented formulation uses the concept of constant operator, in which the corrections of the nonlinear process are made only by applying appropriate tractions along the crack surfaces. The second presented BEM formulation to analyse crack growth problems is an implicit technique based on the use of a consistent tangent operator. This formulation is accurate, stable and always requires much less iterations to reach the equilibrium within a given load increment in comparison with the classical approach. Comparison examples of classical problem of crack growth are shown to illustrate the performance of the two formulations. (C) 2009 Elsevier Ltd. All rights reserved.
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Introduction: Cognitive and attentional deficits in schizophrenia include impairment of the sensorimotor filter as measured by prepulse inhibition (PPI). In this way, the study of animals that naturally present low PPI responses could be a useful approach for screening new antipsychotic drugs. Several pieces of evidence suggest that dopamine and nitric oxide (NO) can modulate PPI but their role in those animals is unknown. Objectives: The aim of this study was to investigate the role of dopamine and NO in Wistar rats with naturally low PPI response. Methods: Male Wistar rats with low PPI responses received an i.p. injection of the antipsychotics haloperidol (0.1, 0.3 or 1 mg/kg) or clozapine (0.5, 1.5 or 5 mg/kg), the anxiolytic diazepam (1 or 3 mg/kg) or the NO synthase (NOS) inhibitors, N(G)- nitro-L-arginine (L-NOARG; 40 mg/kg, acutely or sub-chronically) or 7-Nitroindazole (7-NI; 3, 10 or 30 mg/kg). All animals were submitted to the PPI test 1 h after injection. Striatal and cortical dopamine, DOPAC, and noradrenaline levels of rats with low PPI responses were compared to rats with normal PPI responses. Results: We found increased levels of catecholamines on the striatum and prefrontal cortex of Wistar rats with low PPI. In these animals, both antipsychotics, typical and atypical, and NOS inhibitors significantly increased PPI. Conclusion: Taken together, our findings suggest that the low PPI phenotype may be driven by an over-active catecholamine system. Additionally, our results corroborate the hypothesis of dopamine and NO interaction on PPI modulation and suggest that Wistar rats with low PPI may represent an interesting non-pharmacological model to evaluate new potential antipsychotics. (C) 2010 Elsevier B.V. All rights reserved.
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This paper analyses the impact of using different correlation assumptions between lines of business when estimating the risk-based capital reserve, the Solvency Capital Requirement (SCR), under Solvency II regulations. A case study is presented and the SCR is calculated according to the Standard Model approach. Alternatively, the requirement is then calculated using an Internal Model based on a Monte Carlo simulation of the net underwriting result at a one-year horizon, with copulas being used to model the dependence between lines of business. To address the impact of these model assumptions on the SCR we conduct a sensitivity analysis. We examine changes in the correlation matrix between lines of business and address the choice of copulas. Drawing on aggregate historical data from the Spanish non-life insurance market between 2000 and 2009, we conclude that modifications of the correlation and dependence assumptions have a significant impact on SCR estimation.
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In terms of the treatment of illicit drug abuse, methadone maintenance is a well researched and widely applied systematic response. The approach to primary care methadone treatment in Ireland is based on the methadone protocol. Primary care plays a central role in the delivery of methadone treatment. Beginning with a view that a system evolves within the constraints and influencing factors of its context, the aim of this thesis is to model the process that has developed by which patients on primary care methadone treatment are referred to counselling. It investigates the role primary care practitioners perceive they have in relation to managing the psychosocial aspects of the methadone patient's treatment regime. It analyzes individual medical practitioner counselling referral mechanisms to determine what common processes operate across different practitioners. It identifies the factors that influence the use of counselling on primary care methadone programmes and structures these in a cause/effect model. This research used interviews and documentary analysis to acquire grounded data. The sample consisted primarily of medical practitioners involved in the delivery of methadone programmes. Others closely involved in the implementation of drug treatment in the primary care context made up the balance of interviewees. The study used a grounded theory methodology to induce the process that was latent in the grounded data. Concepts emerging were grouped under the headings of referral factors, decision making factors and factors related to the unique positioning of primary care at the interface between medicine and society. The core finding was that, in primary care in Ireland, there is no psychological model to complement the pharmacological intervention of methadone substitution. The findings from this study offer insight into the factors at work and their impacts, in the context of the use of counselling in primary care methadone treatment. The study suggests a possible direction for further evolution of opiate abuse treatment in Ireland which would transform it from a harm reduction to a holistic patient centric paradigm.This resource was contributed by The National Documentation Centre on Drug Use.
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Using data from the Spanish household budget survey, we investigate life- cycle effects on several product expenditures. A latent-variable model approach is adopted to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household life-cycle typologies. The analysis discloses significant life-cycle effects on the mean levels of expenditures; it also detects significant life-cycle effects on the way expenditures are affected by income and family size. Asymptotic robust methods are used to account for possible non-normality of the data.
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Using data from the Spanish household budget survey, we investigate life-cycle effects on several product expenditures. A latent-variable model approach is adopted to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household life-cycle typologies. The analysis discloses significant life-cycle effects on the mean levels of expenditures; it also detects significant life-cycle effects on the way expenditures are affected by income and family size. Asymptotic robust methods are used to account for possible non-normality of the data.
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Differences in efficacy and safety of drugs among patients are a recognized problem in pharmacotherapy. The reasons are multifactorial and, therefore, the choice of a drug and its dosage for a particular patient based on different clinical and genetic factors is suggested to improve the clinical outcome. Four drugs are currently used for the treatment of Alzheimer's disease: three acetylcholinesterase inhibitors (donepezil, galantamine, rivastigmine) and the N-methyl-D-aspartate-antagonist memantine. For these drugs, a high interindividual variability in plasma levels was observed, which might influence the response to treatment. The main objective of this thesis was to provide a better understanding of clinical and genetic factors affecting the plasma levels of antidementia drugs. Furthermore, the relationship between plasma levels, genetic variations and side effects was assessed. For this purpose, a pharmacogenetic study was conducted including 300 patients from a naturalistic clinical setting. Analytical methods for the simultaneous measurement of antidementia drugs in plasma have been developed and validated using liquid chromatography methods coupled with mass spectrometry detection. Presently, these methods are used in the therapeutic drug monitoring service of our laboratory. The routine use of therapeutic drug monitoring for antidementia drugs cannot yet be recommended with the available data, but it may be beneficial for some patients in special clinical cases such as insufficient treatment response, side effects or drug interactions. Donepezil and galantamine are extensively metabolized by the liver enzymes cytochromes P450 (CYP) 2D6 and 3A and are substrates of the drug transporter P-glycoprotein. The relationship of variations in genes affecting the activity of these metabolic enzymes and drug transporter (CYP2D6, CYP3A, POR, NR1I2, ABCB1) with donepezil and galantamine plasma levels was investigated. The CYP2D6 genotype appeared to be the major genetic factor involved in the pharmacokinetics of these two drugs. Thus, CYP2D6 poor metabolizers demonstrated significantly higher drug plasma levels than extensive metabolizers. Additionally, in the donepezil study population, the frequency of side effects was significantly increased in poor metabolizers. Lower donepezil plasma levels were observed in ultra rapid metabolizers, which might expose those patients to the risk of non-response. Memantine is mainly eliminated unchanged by the kidney, with implication of tubular secretion by renal transporters. A population pharmacokinetic model was developed to quantify the effects of clinical factors and genetic variations in renal cation transporters (SLC22A1/2/5, SLC47A1, ABCB1), and nuclear receptors (NR1I2, NR1I3, PPARG) involved in transporter expression, on memantine plasma levels. In addition to the renal function and gender, a genetic variation in the nuclear receptor Pregnane-X-Receptor (NR1I2) significantly affected memantine elimination. These findings suggest that an individualized therapy approach for antidementia drugs, taking into account clinical characteristics and genetic background of a patient, might increase efficacy and safety of the treatment. - Les différences interindividuelles dans l'efficacité et la tolérance des médicaments sont un problème connu en pharmacothérapie. Les raisons sont multiples, et le choix du médicament et de la dose, basé sur des facteurs cliniques et génétiques spécifiques au patient, peut contribuer à améliorer la réponse clinique. Quatre médicaments sont couramment utilisés dans le traitement de la maladie d'Alzheimer : trois inhibiteurs de l'acétylcholinestérase (donépézil, galantamine, rivastigmine) et un antagoniste du récepteur N-méthyl-D-aspartate, la mémantine. Une forte variabilité interindividuelle dans les taux plasmatiques de ces quatre composés a été observée, ce qui pourrait influencer la réponse au traitement. L'objectif principal de ce travail de thèse est de mieux comprendre les facteurs cliniques et génétiques influençant les taux des médicaments pro-cognitifs. En outre, des associations entre les taux, la variabilité génétique et les effets secondaires ont été recherchées. Dans ce but, 300 patients sous traitement avec un médicament pro-cognitif ont été recrutés pour une étude pharmacogénétique. Des méthodes de dosage simultané de médicaments pro-cognitifs par chromatographie liquide couplée à la spectrométrie de masse ont été développées et validées. Ces méthodes sont actuellement utilisées dans le service de suivi thérapeutique de notre unité. Malgré le fait qu'un suivi des taux sanguins des pro-cognitifs ne puisse pas encore être recommandé en routine, un dosage peut être utile dans des cas cliniques spécifiques, comme une réponse insuffisante, une intolérance ou une interaction médicamenteuse. Le donépézil et la galantamine sont fortement métabolisés par les cytochromes P450 (CYP) 2D6 et 3A, et sont également substrats du transporteur P-glycoprotéine. Les associations entre les polymorphismes génétiques de ces enzymes, cofacteur, récepteur nucléaire et transporteur (CYP2D6, CYP3A, POR, NR1I2, ABCB1) et les taux de donépézil et de galantamine ont été étudiées. Le génotype du CYP2D6 a été montré comme le facteur génétique majeur impliqué dans la pharmacocinétique de ces deux médicaments. Ainsi, les métaboliseurs déficients du CYP2D6 ont démontré des taux plasmatiques significativement plus élevés comparé aux bons métaboliseurs. De plus, dans la population traitée avec le donépézil, la fréquence des effets secondaires était plus élevée chez les métaboliseurs déficients. Des taux plasmatiques bas ont été mesurés chez les métaboliseurs ultra-rapides traités avec le donépézil, ce qui pourrait être un facteur de risque à une non-réponse au traitement. La mémantine est principalement éliminée sous forme inchangée par les reins, et partiellement par sécrétion tubulaire grâce à des transporteurs rénaux. Un modèle de cinétique de population a été développé pour quantifier les effets des différents facteurs cliniques et de la variabilité génétique des transporteurs rénaux (SLC22A1/2/5, SLC47A1, ABCB1) et des récepteurs nucléaires (NR1I2, NR1I3, PPARG, impliqués dans l'expression des transporteurs) sur les taux plasmatiques de mémantine. En plus de la fonction rénale et du genre, une variation génétique dans le récepteur nucléaire Pregnane-X-Receptor (NR1I2) a montré une influence significative sur l'élimination de la mémantine. Ces résultats suggèrent qu'une approche thérapeutique individualisée, prenant en compte des facteurs cliniques et génétiques du patient, pourrait améliorer l'efficacité et la sécurité du traitement pro-cognitif.
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In this paper we develop a new linear approach to identify the parameters of a moving average (MA) model from the statistics of the output. First, we show that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. Then, thisresult is used to obtain a new well-conditioned linear methodto estimate the MA parameters of a non-Gaussian process. Theproposed method presents several important differences withexisting linear approaches. The linear combination of slices usedto compute the MA parameters can be constructed from dif-ferent sets of cumulants of different orders, providing a generalframework where all the statistics can be combined. Further-more, it is not necessary to use second-order statistics (the autocorrelation slice), and therefore the proposed algorithm stillprovides consistent estimates in the presence of colored Gaussian noise. Another advantage of the method is that while mostlinear methods developed so far give totally erroneous estimates if the order is overestimated, the proposed approach doesnot require a previous estimation of the filter order. The simulation results confirm the good numerical conditioning of thealgorithm and the improvement in performance with respect to existing methods.
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Résumé: Le développement rapide de nouvelles technologies comme l'imagerie médicale a permis l'expansion des études sur les fonctions cérébrales. Le rôle principal des études fonctionnelles cérébrales est de comparer l'activation neuronale entre différents individus. Dans ce contexte, la variabilité anatomique de la taille et de la forme du cerveau pose un problème majeur. Les méthodes actuelles permettent les comparaisons interindividuelles par la normalisation des cerveaux en utilisant un cerveau standard. Les cerveaux standards les plus utilisés actuellement sont le cerveau de Talairach et le cerveau de l'Institut Neurologique de Montréal (MNI) (SPM99). Les méthodes de recalage qui utilisent le cerveau de Talairach, ou celui de MNI, ne sont pas suffisamment précises pour superposer les parties plus variables d'un cortex cérébral (p.ex., le néocortex ou la zone perisylvienne), ainsi que les régions qui ont une asymétrie très importante entre les deux hémisphères. Le but de ce projet est d'évaluer une nouvelle technique de traitement d'images basée sur le recalage non-rigide et utilisant les repères anatomiques. Tout d'abord, nous devons identifier et extraire les structures anatomiques (les repères anatomiques) dans le cerveau à déformer et celui de référence. La correspondance entre ces deux jeux de repères nous permet de déterminer en 3D la déformation appropriée. Pour les repères anatomiques, nous utilisons six points de contrôle qui sont situés : un sur le gyrus de Heschl, un sur la zone motrice de la main et le dernier sur la fissure sylvienne, bilatéralement. Evaluation de notre programme de recalage est accomplie sur les images d'IRM et d'IRMf de neuf sujets parmi dix-huit qui ont participés dans une étude précédente de Maeder et al. Le résultat sur les images anatomiques, IRM, montre le déplacement des repères anatomiques du cerveau à déformer à la position des repères anatomiques de cerveau de référence. La distance du cerveau à déformer par rapport au cerveau de référence diminue après le recalage. Le recalage des images fonctionnelles, IRMf, ne montre pas de variation significative. Le petit nombre de repères, six points de contrôle, n'est pas suffisant pour produire les modifications des cartes statistiques. Cette thèse ouvre la voie à une nouvelle technique de recalage du cortex cérébral dont la direction principale est le recalage de plusieurs points représentant un sillon cérébral. Abstract : The fast development of new technologies such as digital medical imaging brought to the expansion of brain functional studies. One of the methodolgical key issue in brain functional studies is to compare neuronal activation between individuals. In this context, the great variability of brain size and shape is a major problem. Current methods allow inter-individual comparisions by means of normalisation of subjects' brains in relation to a standard brain. A largerly used standard brains are the proportional grid of Talairach and Tournoux and the Montreal Neurological Insititute standard brain (SPM99). However, there is a lack of more precise methods for the superposition of more variable portions of the cerebral cortex (e.g, neocrotex and perisyvlian zone) and in brain regions highly asymmetric between the two cerebral hemipsheres (e.g. planum termporale). The aim of this thesis is to evaluate a new image processing technique based on non-linear model-based registration. Contrary to the intensity-based, model-based registration uses spatial and not intensitiy information to fit one image to another. We extract identifiable anatomical features (point landmarks) in both deforming and target images and by their correspondence we determine the appropriate deformation in 3D. As landmarks, we use six control points that are situated: one on the Heschl'y Gyrus, one on the motor hand area, and one on the sylvian fissure, bilaterally. The evaluation of this model-based approach is performed on MRI and fMRI images of nine of eighteen subjects participating in the Maeder et al. study. Results on anatomical, i.e. MRI, images, show the mouvement of the deforming brain control points to the location of the reference brain control points. The distance of the deforming brain to the reference brain is smallest after the registration compared to the distance before the registration. Registration of functional images, i.e fMRI, doesn't show a significant variation. The small number of registration landmarks, i.e. six, is obvious not sufficient to produce significant modification on the fMRI statistical maps. This thesis opens the way to a new computation technique for cortex registration in which the main directions will be improvement of the registation algorithm, using not only one point as landmark, but many points, representing one particular sulcus.
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The transport of macromolecules, such as low-density lipoprotein (LDL), and their accumulation in the layers of the arterial wall play a critical role in the creation and development of atherosclerosis. Atherosclerosis is a disease of large arteries e.g., the aorta, coronary, carotid, and other proximal arteries that involves a distinctive accumulation of LDL and other lipid-bearing materials in the arterial wall. Over time, plaque hardens and narrows the arteries. The flow of oxygen-rich blood to organs and other parts of the body is reduced. This can lead to serious problems, including heart attack, stroke, or even death. It has been proven that the accumulation of macromolecules in the arterial wall depends not only on the ease with which materials enter the wall, but also on the hindrance to the passage of materials out of the wall posed by underlying layers. Therefore, attention was drawn to the fact that the wall structure of large arteries is different than other vessels which are disease-resistant. Atherosclerosis tends to be localized in regions of curvature and branching in arteries where fluid shear stress (shear rate) and other fluid mechanical characteristics deviate from their normal spatial and temporal distribution patterns in straight vessels. On the other hand, the smooth muscle cells (SMCs) residing in the media layer of the arterial wall respond to mechanical stimuli, such as shear stress. Shear stress may affect SMC proliferation and migration from the media layer to intima. This occurs in atherosclerosis and intimal hyperplasia. The study of blood flow and other body fluids and of heat transport through the arterial wall is one of the advanced applications of porous media in recent years. The arterial wall may be modeled in both macroscopic (as a continuous porous medium) and microscopic scales (as a heterogeneous porous medium). In the present study, the governing equations of mass, heat and momentum transport have been solved for different species and interstitial fluid within the arterial wall by means of computational fluid dynamics (CFD). Simulation models are based on the finite element (FE) and finite volume (FV) methods. The wall structure has been modeled by assuming the wall layers as porous media with different properties. In order to study the heat transport through human tissues, the simulations have been carried out for a non-homogeneous model of porous media. The tissue is composed of blood vessels, cells, and an interstitium. The interstitium consists of interstitial fluid and extracellular fibers. Numerical simulations are performed in a two-dimensional (2D) model to realize the effect of the shape and configuration of the discrete phase on the convective and conductive features of heat transfer, e.g. the interstitium of biological tissues. On the other hand, the governing equations of momentum and mass transport have been solved in the heterogeneous porous media model of the media layer, which has a major role in the transport and accumulation of solutes across the arterial wall. The transport of Adenosine 5´-triphosphate (ATP) is simulated across the media layer as a benchmark to observe how SMCs affect on the species mass transport. In addition, the transport of interstitial fluid has been simulated while the deformation of the media layer (due to high blood pressure) and its constituents such as SMCs are also involved in the model. In this context, the effect of pressure variation on shear stress is investigated over SMCs induced by the interstitial flow both in 2D and three-dimensional (3D) geometries for the media layer. The influence of hypertension (high pressure) on the transport of lowdensity lipoprotein (LDL) through deformable arterial wall layers is also studied. This is due to the pressure-driven convective flow across the arterial wall. The intima and media layers are assumed as homogeneous porous media. The results of the present study reveal that ATP concentration over the surface of SMCs and within the bulk of the media layer is significantly dependent on the distribution of cells. Moreover, the shear stress magnitude and distribution over the SMC surface are affected by transmural pressure and the deformation of the media layer of the aorta wall. This work reflects the fact that the second or even subsequent layers of SMCs may bear shear stresses of the same order of magnitude as the first layer does if cells are arranged in an arbitrary manner. This study has brought new insights into the simulation of the arterial wall, as the previous simplifications have been ignored. The configurations of SMCs used here with elliptic cross sections of SMCs closely resemble the physiological conditions of cells. Moreover, the deformation of SMCs with high transmural pressure which follows the media layer compaction has been studied for the first time. On the other hand, results demonstrate that LDL concentration through the intima and media layers changes significantly as wall layers compress with transmural pressure. It was also noticed that the fraction of leaky junctions across the endothelial cells and the area fraction of fenestral pores over the internal elastic lamina affect the LDL distribution dramatically through the thoracic aorta wall. The simulation techniques introduced in this work can also trigger new ideas for simulating porous media involved in any biomedical, biomechanical, chemical, and environmental engineering applications.
Resumo:
This paper analyses the impact of using different correlation assumptions between lines of business when estimating the risk-based capital reserve, the Solvency Capital Requirement -SCR-, under Solvency II regulations. A case study is presented and the SCR is calculated according to the Standard Model approach. Alternatively, the requirement is then calculated using an Internal Model based on a Monte Carlo simulation of the net underwriting result at a one-year horizon, with copulas being used to model the dependence between lines of business. To address the impact of these model assumptions on the SCR we conduct a sensitivity analysis. We examine changes in the correlation matrix between lines of business and address the choice of copulas. Drawing on aggregate historical data from the Spanish non-life insurance market between 2000 and 2009, we conclude that modifications of the correlation and dependence assumptions have a significant impact on SCR estimation.