Challenges in lung transplantation.

Lung transplantation is an established therapy for end-stage pulmonary disorders in selected patients without significant comorbidities. The particular constraints associated with organ transplantation from deceased donors involve specific allocation rules in order to optimise the medical efficacy of the procedure. Comparison of different policies adopted by national transplant agencies reveals that an optimal and unique allocation system is an elusive goal, and that practical, geographical and logistic parameters must be taken into account. A solution to attenuate the imbalance between the number of lung transplant candidates and the limited availability of organs is to consider marginal donors. In particular, assessment and restoration of gas exchange capacity ex vivo in explanted lungs is a new and promising approach that some lung transplant programmes have started to apply in clinical practice. Chronic lung allograft dysfunction, and especially bronchiolitis obliterans, remains the major medium- and long-term problem in lung transplantation with a major impact on survival. Although there is to date no cure for established bronchiolitis obliterans, new preventive strategies have the potential to limit the burden of this feared complication. Unfortunately, randomised prospective studies are infrequent in the field of lung transplantation, and data obtained from larger studies involving kidney or liver recipients are not always relevant for this purpose.

Formule sanguine: intérêt des nouveaux paramètres [Complete blood counts: new parameters].

Performing a complete blood count analysis is a daily routine necessary for a good care of patients. Nowadays, modern blood analyzers provide on top of classical blood values, several additional parameters. In this paper, using short case presentations, we discuss how to interpret these results and integrate them in the clinical context.

When "enough" is not enough: new perspectives on optimal methadone maintenance dose.

Some methadone maintenance treatment (MMT) programs prescribe inadequate daily methadone doses. Patients complain of withdrawal symptoms and continue illicit opioid use, yet practitioners are reluctant to increase doses above certain arbitrary thresholds. Serum methadone levels (SMLs) may guide practitioners dosing decisions, especially for those patients who have low SMLs despite higher methadone doses. Such variation is due in part to the complexities of methadone metabolism. The medication itself is a racemic (50:50) mixture of 2 enantiomers: an active "R" form and an essentially inactive "S" form. Methadone is metabolized primarily in the liver, by up to five cytochrome P450 isoforms, and individual differences in enzyme activity help explain wide ranges of active R-enantiomer concentrations in patients given identical doses of racemic methadone. Most clinical research studies have used methadone doses of less than 100 mg/day [d] and have not reported corresponding SMLs. New research suggests that doses ranging from 120 mg/d to more than 700 mg/d, with correspondingly higher SMLs, may be optimal for many patients. Each patient presents a unique clinical challenge, and there is no way of prescribing a single best methadone dose to achieve a specific blood level as a "gold standard" for all patients. Clinical signs and patient-reported symptoms of abstinence syndrome, and continuing illicit opioid use, are effective indicators of dose inadequacy. There does not appear to be a maximum daily dose limit when determining what is adequately "enough" methadone in MMT.

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

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

Population density and optimal body size.

The population density of an organism is one of the main aspects of its environment, and shoud therefore strongly influence its adaptive strategy. The r/K theory, based on the logistic model, was developed to formalize this influence. K-selectioon is classically thought to favour large body sizes. This prediction, however, cannot be directly derived from the logistic model: some auxiliary hypotheses are therefor implicit. These are to be made explicit if the theory is to be tested. An alternative approach, based on the Euler-Lotka equation, shows that density itself is irrelevant, but that the relative effect of density on adult and juvenile features is crucial. For instance, increasing population will select for a smaller body size if the density affects mainly juvenile growth and/or survival. In this case, density shoud indeed favour large body sizes. The theory appears nevertheless inconsistent, since a probable consequence of increasing body size will be a decrease in the carrying capacity

Correlations between trabecular bone score, measured using anteroposterior dual-energy x-ray absorptiometry acquisition, and 3-dimensional parameters of bone microarchitecture: an experimental study on human cadaver vertebrae.

Developing a novel technique for the efficient, noninvasive clinical evaluation of bone microarchitecture remains both crucial and challenging. The trabecular bone score (TBS) is a new gray-level texture measurement that is applicable to dual-energy X-ray absorptiometry (DXA) images. Significant correlations between TBS and standard 3-dimensional (3D) parameters of bone microarchitecture have been obtained using a numerical simulation approach. The main objective of this study was to empirically evaluate such correlations in anteroposterior spine DXA images. Thirty dried human cadaver vertebrae were evaluated. Micro-computed tomography acquisitions of the bone pieces were obtained at an isotropic resolution of 93μm. Standard parameters of bone microarchitecture were evaluated in a defined region within the vertebral body, excluding cortical bone. The bone pieces were measured on a Prodigy DXA system (GE Medical-Lunar, Madison, WI), using a custom-made positioning device and experimental setup. Significant correlations were detected between TBS and 3D parameters of bone microarchitecture, mostly independent of any correlation between TBS and bone mineral density (BMD). The greatest correlation was between TBS and connectivity density, with TBS explaining roughly 67.2% of the variance. Based on multivariate linear regression modeling, we have established a model to allow for the interpretation of the relationship between TBS and 3D bone microarchitecture parameters. This model indicates that TBS adds greater value and power of differentiation between samples with similar BMDs but different bone microarchitectures. It has been shown that it is possible to estimate bone microarchitecture status derived from DXA imaging using TBS.

Erste Resultate der HOT-Studie in der Schweiz. [Initial results of the HOT-study in Switzerland (hypertension optimal treatment)]

The HOT study (hypertension-optimal treatment) is an international clinical study on primary prevention of cardiovascular events in 19,193 hypertensive patients worldwide. It aims at the recognition of the optimal diastolic blood pressure value (< 90, < 85 or < 80 mmHg?) in order to maximize the possible benefit of an antihypertensive therapy. In addition, the HOT study investigates whether low doses of aspirin (75 mg/day) are able to reduce the occurrence of severe cardiovascular events. In Switzerland a total of 797 patients have been enrolled in the study. Antihypertensive therapy was initiated with felodipine = Plendil (5 mg/day). This vasoelective calcium antagonist could reduce diastolic blood pressure values to < 90 or < 80 mg/Hg, respectively, in one of two or one of three patients within the first three months. In nine or six patients, respectively out of ten a reduction of diastolic blood pressure values to < 90 or < 80 mmHg was reached within one year by combination of felodipine with other antihypertensive drugs (ACE inhibitors, beta blockers and diuretics).

Ispol'zovanie metodov teorii vosstanovleniia v modeliakh optimal'nogo dobyvaniia pishchi [Restoration theory in models of optimal feeding behavior]

The method of stochastic dynamic programming is widely used in ecology of behavior, but has some imperfections because of use of temporal limits. The authors presented an alternative approach based on the methods of the theory of restoration. Suggested method uses cumulative energy reserves per time unit as a criterium, that leads to stationary cycles in the area of states. This approach allows to study the optimal feeding by analytic methods.

Optimal activation of tumor-reactive T cells by selected antigenic peptide analogues.

Many mechanisms have been proposed to explain why immune responses against human tumor antigens are generally ineffective. For example, tumor cells have been shown to develop active immune evasion mechanisms. Another possibility is that tumor antigens are unable to optimally stimulate tumor-specific T cells. In this study we have used HLA-A2/Melan-A peptide tetramers to directly isolate antigen-specific CD8(+) T cells from tumor-infiltrated lymph nodes. This allowed us to quantify the activation requirements of a representative polyclonal yet monospecific tumor-reactive T cell population. The results obtained from quantitative assays of intracellular Ca(2+) mobilization, TCR down-regulation, cytokine production and induction of effector cell differentiation indicate that the naturally produced Melan-A peptides are weak agonists and are clearly suboptimal for T cell activation. In contrast, optimal T cell activation was obtained by stimulation with recently defined peptide analogues. These findings provide a molecular basis for the low immunogenicity of tumor cells and suggest that patient immunization with full agonist peptide analogues may be essential for stimulation and maintenance of anti-tumor T cell responses in vivo.

Deciding the sale of a life policy in the viatical market: Implications on individual welfare

[cat] En aquest article, es presenta un model econòmic que permet determinar la venda o no d'una pòlissa de vida (total o en part) per part d'un assegurat malalt terminal en el mercat dels viatical settlements. Aquest mercat va aparèixer a finals de la dècada dels 80 a conseqüència de l'epidèmia de la SIDA. Actualment, representa una part del mercat dels life settlements. Les pòlisses que es comercialitzen en el mercat dels viaticals són aquelles on l'assegurat és malalt terminal amb una esperança de vida de dos anys o menys. El model és discret i considera només dos períodes (anys), ja que aquesta és la vida residual màxima que contempla el mercat. L'agent posseix una riquesa inicial que ha de repartir entre consum i herència. S'introdueix en primer lloc la funció d'utilitat esperada del decisor i, utilitzant programació dinàmica, es dedueix l'estratègia que reporta una utilitat més gran (no vendre/vendre (en part) la pòlissa en el moment zero/vendre (en part) la pòlissa en el moment ú). L'òptim depèn del preu de la pòlissa venuda i de paràmetres personals de l'individu. Es troba una expressió analítica per l'estratègia òptima i es realitza un anàlisi de sensibilitat.

Optimal fiscal policy in overlapping generations models

[eng] This paper provides, from a theoretical and quantitative point of view, an explanation of why taxes on capital returns are high (around 35%) by analyzing the optimal fiscal policy in an economy with intergenerational redistribution. For this purpose, the government is modeled explicitly and can choose (and commit to) an optimal tax policy in order to maximize society's welfare. In an infinitely lived economy with heterogeneous agents, the long run optimal capital tax is zero. If heterogeneity is due to the existence of overlapping generations, this result in general is no longer true. I provide sufficient conditions for zero capital and labor taxes, and show that a general class of preferences, commonly used on the macro and public finance literature, violate these conditions. For a version of the model, calibrated to the US economy, the main results are: first, if the government is restricted to a set of instruments, the observed fiscal policy cannot be disregarded as sub optimal and capital taxes are positive and quantitatively relevant. Second, if the government can use age specific taxes for each generation, then the age profile capital tax pattern implies subsidizing asset returns of the younger generations and taxing at higher rates the asset returns of the older ones.

Measuring conduct and cost parameters in the Spanish air transport market

This paper estimates a model of airline competition for the Spanish air transport market. I test the explanatory power of alternative oligopoly models with capacity constraints. In addition, I analyse the degree of density economies. Results show that Spanish airlines conduct follows a price-leadership scheme so that it is less competitive than the Cournot solution. I also find evidence that thin routes can be considered as natural monopolies

Interiority of the optimal population growth rate with endogenous fertility

This paper analyzes the issue of the interiority of the optimal population growth rate in a two-period overlapping generations model with endogenous fertility. Using Cobb-Douglas utility and production functions, we show that the introduction of a cost of raising children allows for the possibility of the existence of an interior global maximum in the planner¿s problem, contrary to the exogenous fertility case