Le traitement de l'échinococcose alvéolaire humaine: une approche multidisciplinaire [Treatment of alveolar echinococcosis: a multidisciplinary task]

Alveolar echinococcosis is characterized by a long asymptomatic period but, without treatment, up to 80% of patients may die within ten years of diagnosis. Owing to a lack of fast-acting and fully effective chemotherapy, partial radical hepatic resection is the only chance of cure. One-third of patients are now treated in this way, and complex vascular and biliary reconstruction procedures are sometimes necessary. Liver transplantation may also be indicated for highly selected patients (about 5%) with life-threatening complications after failure of other treatments. Interventional radiology and endoscopy can be used to drain liver abscesses and/or infected and obstructed bile ducts, either as palliative procedures or as a bridge to radical resection. Parasitostatic benzimidazole therapy, especially based on continuous albendazole administration, is mandatory for at least two years after radical resection, and for life in inoperable patients.

Task force IV: Clinical use of ambulatory blood pressure monitoring. Participants of the 1999 Consensus Conference on Ambulatory Blood Pressure Monitoring

OBJECTIVE: To reach a consensus on the clinical use of ambulatory blood pressure monitoring (ABPM). METHODS: A task force on the clinical use of ABPM wrote this overview in preparation for the Seventh International Consensus Conference (23-25 September 1999, Leuven, Belgium). This article was amended to account for opinions aired at the conference and to reflect the common ground reached in the discussions. POINTS OF CONSENSUS: The Riva Rocci/Korotkoff technique, although it is prone to error, is easy and cheap to perform and remains worldwide the standard procedure for measuring blood pressure. ABPM should be performed only with properly validated devices as an accessory to conventional measurement of blood pressure. Ambulatory recording of blood pressure requires considerable investment in equipment and training and its use for screening purposes cannot be recommended. ABPM is most useful for identifying patients with white-coat hypertension (WCH), also known as isolated clinic hypertension, which is arbitrarily defined as a clinic blood pressure of more than 140 mmHg systolic or 90 mmHg diastolic in a patient with daytime ambulatory blood pressure below 135 mmHg systolic and 85 mmHg diastolic. Some experts consider a daytime blood pressure below 130 mmHg systolic and 80 mmHg diastolic optimal. Whether WCH predisposes subjects to sustained hypertension remains debated. However, outcome is better correlated to the ambulatory blood pressure than it is to the conventional blood pressure. Antihypertensive drugs lower the clinic blood pressure in patients with WCH but not the ambulatory blood pressure, and also do not improve prognosis. Nevertheless, WCH should not be left unattended. If no previous cardiovascular complications are present, treatment could be limited to follow-up and hygienic measures, which should also account for risk factors other than hypertension. ABPM is superior to conventional measurement of blood pressure not only for selecting patients for antihypertensive drug treatment but also for assessing the effects both of non-pharmacological and of pharmacological therapy. The ambulatory blood pressure should be reduced by treatment to below the thresholds applied for diagnosing sustained hypertension. ABPM makes the diagnosis and treatment of nocturnal hypertension possible and is especially indicated for patients with borderline hypertension, the elderly, pregnant women, patients with treatment-resistant hypertension and patients with symptoms suggestive of hypotension. In centres with sufficient financial resources, ABPM could become part of the routine assessment of patients with clinic hypertension. For patients with WCH, it should be repeated at annual or 6-monthly intervals. Variation of blood pressure throughout the day can be monitored only by ABPM, but several advantages of the latter technique can also be obtained by self-measurement of blood pressure, a less expensive method that is probably better suited to primary practice and use in developing countries. CONCLUSIONS: ABPM or equivalent methods for tracing the white-coat effect should become part of the routine diagnostic and therapeutic procedures applied to treated and untreated patients with elevated clinic blood pressures. Results of long-term outcome trials should better establish the advantage of further integrating ABPM as an accessory to conventional sphygmomanometry into the routine care of hypertensive patients and should provide more definite information on the long-term cost-effectiveness. Because such trials are not likely to be funded by the pharmaceutical industry, governments and health insurance companies should take responsibility in this regard.

Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

Dynamical modeling and analysis of large cellular regulatory networks.

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

Screening for elevated blood pressure in children and adolescents: a critical appraisal.

Although screening for elevated blood pressure (BP) in adults is beneficial, evidence of its beneficial effects in children is not clear. Elevated BP in children is associated with atherosclerosis early in life and tracks across the life course. However, because of the high variability in BP, tracking is weak, and having an elevated BP in childhood has a low predictive value for having elevated BP later in life. The absolute risk of cardiovascular diseases associated with a given level of BP in childhood and the long-term effect of treatment beginning in childhood are not known. No study has experimentally evaluated the benefits and harm of BP screening in children. One modeling study indicates that BP screen-and-treat strategies in adolescents are moderately cost-effective but less cost-effective than population-wide interventions to decrease BP for the reduction of coronary heart diseases. The US National Heart, Lung, and Blood Institute and the European Society of Hypertension recommend that children 3 years of age and older have their BP measured during every health care visit. According to the US Preventive Services Task Force, there is no sufficient evidence to recommend for or against screening, but their recommendations have to be updated. Whether the benefits of universal BP screening in children outweigh the harm has to be determined. Studies are needed to assess the absolute risk of cardiovascular diseases associated with elevated BP in childhood, to evaluate how to simplify the identification of elevated BP, to evaluate the long-term benefits and harm of treatment beginning in childhood, and to compare universal and targeted screening strategies.

Multimodel inference and multimodel averaging in empirical modeling of occupational exposure levels.

Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice.

Evolution of decision-making and learning under fluctuating social environments

The capacity to learn to associate sensory perceptions with appropriate motor actions underlies the success of many animal species, from insects to humans. The evolutionary significance of learning has long been a subject of interest for evolutionary biologists who emphasize the bene¬fit yielded by learning under changing environmental conditions, where it is required to flexibly switch from one behavior to another. However, two unsolved questions are particularly impor¬tant for improving our knowledge of the evolutionary advantages provided by learning, and are addressed in the present work. First, because it is possible to learn the wrong behavior when a task is too complex, the learning rules and their underlying psychological characteristics that generate truly adaptive behavior must be identified with greater precision, and must be linked to the specific ecological problems faced by each species. A framework for predicting behavior from the definition of a learning rule is developed here. Learning rules capture cognitive features such as the tendency to explore, or the ability to infer rewards associated to unchosen actions. It is shown that these features interact in a non-intuitive way to generate adaptive behavior in social interactions where individuals affect each other's fitness. Such behavioral predictions are used in an evolutionary model to demonstrate that, surprisingly, simple trial-and-error learn¬ing is not always outcompeted by more computationally demanding inference-based learning, when population members interact in pairwise social interactions. A second question in the evolution of learning is its link with and relative advantage compared to other simpler forms of phenotypic plasticity. After providing a conceptual clarification on the distinction between genetically determined vs. learned responses to environmental stimuli, a new factor in the evo¬lution of learning is proposed: environmental complexity. A simple mathematical model shows that a measure of environmental complexity, the number of possible stimuli in one's environ¬ment, is critical for the evolution of learning. In conclusion, this work opens roads for modeling interactions between evolving species and their environment in order to predict how natural se¬lection shapes animals' cognitive abilities. - La capacité d'apprendre à associer des sensations perceptives à des actions motrices appropriées est sous-jacente au succès évolutif de nombreuses espèces, depuis les insectes jusqu'aux êtres hu¬mains. L'importance évolutive de l'apprentissage est depuis longtemps un sujet d'intérêt pour les biologistes de l'évolution, et ces derniers mettent l'accent sur le bénéfice de l'apprentissage lorsque les conditions environnementales sont changeantes, car dans ce cas il est nécessaire de passer de manière flexible d'un comportement à l'autre. Cependant, deux questions non résolues sont importantes afin d'améliorer notre savoir quant aux avantages évolutifs procurés par l'apprentissage. Premièrement, puisqu'il est possible d'apprendre un comportement incorrect quand une tâche est trop complexe, les règles d'apprentissage qui permettent d'atteindre un com¬portement réellement adaptatif doivent être identifiées avec une plus grande précision, et doivent être mises en relation avec les problèmes écologiques spécifiques rencontrés par chaque espèce. Un cadre théorique ayant pour but de prédire le comportement à partir de la définition d'une règle d'apprentissage est développé ici. Il est démontré que les caractéristiques cognitives, telles que la tendance à explorer ou la capacité d'inférer les récompenses liées à des actions non ex¬périmentées, interagissent de manière non-intuitive dans les interactions sociales pour produire des comportements adaptatifs. Ces prédictions comportementales sont utilisées dans un modèle évolutif afin de démontrer que, de manière surprenante, l'apprentissage simple par essai-et-erreur n'est pas toujours battu par l'apprentissage basé sur l'inférence qui est pourtant plus exigeant en puissance de calcul, lorsque les membres d'une population interagissent socialement par pair. Une deuxième question quant à l'évolution de l'apprentissage concerne son lien et son avantage relatif vis-à-vis d'autres formes plus simples de plasticité phénotypique. Après avoir clarifié la distinction entre réponses aux stimuli génétiquement déterminées ou apprises, un nouveau fac¬teur favorisant l'évolution de l'apprentissage est proposé : la complexité environnementale. Un modèle mathématique permet de montrer qu'une mesure de la complexité environnementale - le nombre de stimuli rencontrés dans l'environnement - a un rôle fondamental pour l'évolution de l'apprentissage. En conclusion, ce travail ouvre de nombreuses perspectives quant à la mo¬délisation des interactions entre les espèces en évolution et leur environnement, dans le but de comprendre comment la sélection naturelle façonne les capacités cognitives des animaux.

Synchronous versus asynchronous modeling of gene regulatory networks.

MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

Preliminary regional rockfall hazard mapping using LIDAR-based slope frequency distribution and CONEFALL modeling

A factor limiting preliminary rockfall hazard mapping at regional scale is often the lack of knowledge of potential source areas. Nowadays, high resolution topographic data (LiDAR) can account for realistic landscape details even at large scale. With such fine-scale morphological variability, quantitative geomorphometric analyses become a relevant approach for delineating potential rockfall instabilities. Using digital elevation model (DEM)-based ?slope families? concept over areas of similar lithology and cliffs and screes zones available from the 1:25,000 topographic map, a susceptibility rockfall hazard map was drawn up in the canton of Vaud, Switzerland, in order to provide a relevant hazard overview. Slope surfaces over morphometrically-defined thresholds angles were considered as rockfall source zones. 3D modelling (CONEFALL) was then applied on each of the estimated source zones in order to assess the maximum runout length. Comparison with known events and other rockfall hazard assessments are in good agreement, showing that it is possible to assess rockfall activities over large areas from DEM-based parameters and topographical elements.