Allergie aux venins d'hyménopteres: nouveautés diagnostiques et prise en charge [Hymenoptera venom allergy: new diagnostic tools and management].

Anaphylactic reactions to hymenoptera venoms are common and, in our latitudes, mainly concern wasps and bees. Recently, molecular biology techniques have contributed to identifying and to sequencing the major allergens of insect venoms and led to the production of recombinant allergens. Assays for specific IgE directed against these recombinant allergens have recently been made available in clinical practice. They provide considerable assistance in identifying the insect responsible for an anaphylactic reaction, in particular when standard tests are positive for both wasp and bee. This article focuses on these new laboratory tests and also reviews the management of patients experiencing an anaphylactic reaction after hymenoptera sting.

Intérêt de l'angiographie numérisée au vert d'indocyanine dans le diagnostic différentiel des tumeurs non pigmentées de la choroïde [Value of indocyanine green videoangiography in differential diagnosis of nonpigmented tumors of the choroid]

BACKGROUND: Indocyanine green video-angiography (ICG) is a recent examination technique, its possibilities and limitations as far as intraocular tumours are concerned, haven't been fully explored yet. MATERIAL AND METHODS: We have studied 50 cases of non-pigmented choroidal tumours, including 14 cases of choroidal hemangioma's, 11 cases of posterior uveal metastases and 25 cases of non-pigmented melanoma's. RESULTS: Characteristic images were obtained when examining choroidal hemangioma's and, until a certain point, posterior choroidal metastases. Non pigmented melanoma's on the contrary, presented a great variety of different indocyanine green angiographic pictures. CONCLUSION: Indocyanine green video-angiography (ICG) has a definite value in the differential diagnosis of non-pigmented posterior choroidal tumours.

Implementing statistical learning methods through Bayesian networks (Part 2): bayesian evaluations for results of black toner analyses in forensic document examination

This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software.

Maladie de Fabry: du diagnostic a l'enzymotherapie substitutive. [Fabry disease: diagnostic due of substitutive enzyme-therapy]

Fabry disease is a X-linked sphingolipid storage disorder resulting from the defective activity of the lysosomal enzyme, alpha-galactosidase A. Hemizygotes develop severe multisystemic disease, dominated by renal failure and progressive neurological and cardiac involvement, causing premature death. Thirty percent of heterozygotes have severe involvement of one or several organs. With developments in molecular biology, it is now possible to produce the human recombinant enzyme alpha-galactosidase A. More than 20 patients are now treated in Switzerland.

Bayesian Markov chain Monte Carlo inversion of geophysical data for the purpose of estimating the hydraulic properties of the unsaturated zone

Ground-penetrating radar (GPR) has the potential to provide valuable information on hydrological properties of the vadose zone because of their strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR data within a coupled geophysical-hydrological framework may allow for effective estimation of subsurface van-Genuchten-Mualem (VGM) parameters and their corresponding uncertainties. An important and still unresolved issue, however, is how to best integrate GPR data into a stochastic inversion in order to estimate the VGM parameters and their uncertainties, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first introduce a fully Bayesian inversion called Markov-chain-Monte-carlo (MCMC) strategy to perform the stochastic inversion of steady-state GPR data to estimate the VGM parameters and their uncertainties. Within this study, the choice of the prior parameter probability distributions from which potential model configurations are drawn and tested against observed data was also investigated. Analysis of both synthetic and field data collected at the Eggborough (UK) site indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when these data are combined with a realistic, informative prior. A subsequent study explore in detail the dynamic infiltration case, specifically to what extent time-lapse ZOP GPR data, collected during a forced infiltration experiment at the Arrenaes field site (Denmark), can help to quantify VGM parameters and their uncertainties using the MCMC inversion strategy. The findings indicate that the stochastic inversion of time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions. In turn, this significantly improves knowledge of the hydraulic properties, which are required to predict hydraulic behaviour. Finally, another aspect that needed to be addressed involved the comparison of time-lapse GPR data collected under different infiltration conditions (i.e., natural loading and forced infiltration conditions) to estimate the VGM parameters using the MCMC inversion strategy. The results show that for the synthetic example, considering data collected during a forced infiltration test helps to better refine soil hydraulic properties compared to data collected under natural infiltration conditions. When investigating data collected at the Arrenaes field site, further complications arised due to model error and showed the importance of also including a rigorous analysis of the propagation of model error with time and depth when considering time-lapse data. Although the efforts in this thesis were focused on GPR data, the corresponding findings are likely to have general applicability to other types of geophysical data and field environments. Moreover, the obtained results allow to have confidence for future developments in integration of geophysical data with stochastic inversions to improve the characterization of the unsaturated zone but also reveal important issues linked with stochastic inversions, namely model errors, that should definitely be addressed in future research.

A measure of dysfunctional eating-related cognitions in people with psychotic disorders.

Obesity and binge eating disorder are common in individuals with psychotic disorders. Eating and weight-related cognitions are known to influence eating behaviors. The study was designed to assess the psychometric properties of the Mizes Anorectic Cognitions Questionnaire (MAC-R) in patients with psychotic disorders. Binge eating disorder (BED), body mass index (BMI), the MAC-R and the three factor eating questionnaire (TFEQ) were assessed in 125 patients with a diagnosis of schizophrenia or schizoaffective disorder. Whereas the MAC-R has not acceptable psychometric properties, a brief version of the MAC-R (BMAC) has good psychometrical properties and is correlated with TFEQ and BMI. Binge eating disorder is also correlated to the Rigid Weight Regulation and Fear of Weight Gain subscale. The BMAC is a useful brief measure to assess eating and weight related cognitions in people with psychotic disorders.