Constitution, Diversification and Normalisation of a Health Problem: Organising the Fight against AIDS in Switzerland (1984-2005)

The article traces the formation, diversification and normalization of the AIDS cause in Switzerland. Particular emphasis is placed on interactions between the medical field, public authorities and associative space, the latter being understood as the place where individual and collective actors compete to define the cause. The authors argue that the major phases in the structuring of the struggle, the pace of state intervention and the creation of a multi-organizational field, can only be understood if one adopts a 'configurational perspective' attentive to the manner in which, in a given context and under the effect of particular constraints, key actors strategically interact and contribute to transforming their environment and their chances of reaching their goals. This approach takes into account the changing socio-biological characteristics of those who have committed themselves to the cause. In turn, internal movement divisions about how to respond to the epidemic as well as the changing perceptions of the disease have modified the opportunities for commitment, encouraging certain individual kinds of people and excluding others.

The prognostic value of minimally involved melanoma sentinel lymph nodes

Introduction: la biopsie du ganglion sentinelle (GS) est une procédure reconnue et fiable pour établir le stade ganglionnaire du mélanome cutané. Le GS est le facteur pronostique le plus puissant pour la survie des patients atteints d'un mélanome à risque intermédiaire, cliniquement localisé. Celui-ci est métastatique dans environ 15-30% des cas. Lorsque le GS est positif, un curage de l'aire ganglionnaire concernée est généralement entrepris. Néanmoins, seuls 20-25% de ces patients présentent des ganglions non-sentinelles (GNS) métastatiques. Ces données suggèrent que le curage, et les risques opératoires qui y sont associés, n'est peut-être pas nécessaire chez le trois-quarts de ces patients. Un autre aspect est que l'impact sur la survie des curages basé sur le résultat du GS n'est pas clairement démontré. La nécessité de ce curage d'emblé est actuellement en cours d'évaluation par un protocole international (Multicenter Selective Lymphadenectomy Trial II : MSLT II). Plusieurs auteurs ont essayé de classifier la charge tumorale du GS afin d'évaluer s'il était possible d'épargner le curage à certains patients et de mieux affiner ce facteur pronostic sans succès. En 2009, le Groupe Mélanome de l'EORTC (European Organisation for Research and Treatment of Cancer) a recommandé un protocole d'évaluation anatomopathologique du GS-positif en trois items: (1) la localisation micro-anatomique des métastases à l'intérieur du ganglion selon Dewar (A = sous-capsulaire, B = combinée sous-capsulaire and parenchymateuse, C = parenchymateuse, D = multifocale, and'E = extensive) ; (2) la mesure de la taille tumorale dans le ganglion selon les critères de Rotterdam pour le diamètre maximal. Le diamètre de la plus grande métastase est exprimé en nombre absolu et (3) la taille tumorale stratifiée par catégories : <0.1mm, 0.1-1.0mm et >1.0 mm. Le but de cette étude rétrospective d'une cohorte de patients, était d'investiguer les résultats des GS-positifs et d'analyser les facteurs pronostiques de la survie à la lumière des recommandations de l'EORTC. Ainsi que de comparer les sous-groupes du GS-positif avec une invasion minimale (taille tumorale <0.1mm et/ou atteinte sous-capsulaire) avec le GS-négatif. Les facteurs pouvant prédire la présence de GNS- positif ont également été analysés. Matériel et méthode : une étude des dossiers a été réalisée pour les 499 patients consécutifs entre 1997 et 2008 qui ont eu une biopsie du GS dans notre institution. Le dégrée d'envahissement du GS-positif a été entièrement revue par l'équipe référente de l'Institut de Pathologie (Dresse E. Saiji et Dresse H. Bouzourène) selon les recommandations de l'EORTC. Des analyses univariées et multivariées des potentiels facteuis pronostics ont été réalisées. Des analyses de survie ont également été effectuées avec des courbes d'estimation de Kaplan-Meier combinées à une régression de Cox. Le protocole a été accepté par la Commission d'Ethique. Résultats: un GS-positif a été trouvé chez 123 (25%) patients panni les 499 qui ont bénéficié d'une biopsie. Avec un suivi médian de 52 mois, la survie à 5 ans sans récidive (SSR), spécifique à la maladie (SS) et globale (SG) étaient de 88%, 94%, et 90% respectivement pour les patients avec GS-négatif. Concernant les GS avec invasion minimale, 21 patients étaient dans le sous-groupe <0.1 mm selon les critères de Rotterdam et 52 patients dans le sous-groupe sous-capsulaire selon Dewar. La survie dans ces deux sous-groupes était de 80% et 57% pour la SSR, 87% et 70% pour la SS, 87% et 68% pour la SG, respectivement. L'analyse multivariée des GS-positifs a montré que les facteuis suivants influençaient significativement la survie (SSR, SS et SG): l'épaisseur selon Breslow de la tumeur primaire (p=0.002, 0.006, 0.004), la taille tumorale du GS-positif >0.1 mm (p= 0.01, 0.04, 0.03), le genre masculin (p=0.06, 0.005, 0.002) et l'ulcération de la tumeur primaire (p=0.05, 0.03, 0.007). L'analyse des sous-groupes avec invasion minimale n'a pas permis d'établir de facteur pour prédire la négativité des GNSs. Conclusion: La classification du GS-positif par la taille tumorale selon les critères de Rotterdam est un facteur pronostique simple et utile pour évaluer la survie des patients atteints de mélanome. Nous avons observé une tendance (non statistiquement significative) d'une survie diminuée pour le sous-groupe des patients avec GS-positif et une taille de la métastase <0.1 mm comparée à celle des patients avec GS-négatif. Ceci nous incite à conclure que ce sous-groupe de patients ne devrait pas être assimilé et traité comme ceux qui ont un GS-négatif. D'autre part nos résultats montrent que la localisation micro-anatomique selon Dewar n'est pas un outil pronostique utile pour évaluer la survie, ni pour prédire le status des GNSs.

Jeux de miroir de la « politisation » : les acteurs associatifs de quartier à Casablanca

Suivre le parcours de quelques membres des bureaux de trois associations de quartier à Casablanca, notamment via les qualifications que les acteurs donnent eux-mêmes de leurs actions, révèle les intrications de l'espace associatif et de la sphère politique au Maroc. À travers un jeu de miroir, les frontières entre ces deux univers font l'objet de luttes continuelles. L'action associative se construit tantôt en dissociation avec « la politique », tantôt en connexion avec elle. Elle est alors investie comme « activité sociale », substitut à la participation politique, tribune pour des acteurs marginalisés ou tremplin à l'échelle locale, et peut conduire à une renégociation du rapport au politique. Du fait même des points de jonction entre scènes associative, partisane, électorale, syndicale et protestataire, l'action associative expose les primo-engagés à plusieurs types de participations. Elle les dote de compétences praxiques et cognitives, les projette encore davantage dans un terrain propice aux interactions avec diverses agences de gouvernementalité, favorise dans un va-et-vient la reconversion circulaire de ressources et de savoir-faire. Il peut arriver également qu'elle éveille des appétences pour « la politique », pour la compétition électorale, ou qu'elle produise de l'empowerment. D'une situation à l'autre, elle fait l'objet d'une palette de définitions, d'investissements et de (micro)stratégies aussi vastes que variables, diachroniquement et synchroniquement.

Rhizosphere bacterial communities of potato cultivars evaluated through PCR-DGGE profiles

The objective of this work was to determine the shifts on the PCR-DGGE profiles of bacterial communities associated to the rhizosphere of potato cultivars, in order to generate baseline information for further studies of environmental risk assessment of genetically modified potato plants. A greenhouse experiment was carried out with five potato cultivars (Achat, Bintje, Agata, Monalisa and Asterix), cultivated in pots containing soil from an integrated system for agroecological production. The experiment was conducted in a split plot randomized block design with five cultivars, three sampling periods and five replicates. Rhizosphere samples were collected in three sampling dates during plant development. DNA of rhizosphere microorganisms was extracted, amplified by PCR using bacterial universal primers, and analyzed through DGGE. Shifts on the rhizosphere bacterial communities associated to rhizosphere of different cultivars were related to both cultivar and plant age. Differences among rhizosphere bacterial communities were clearest at the earliest plant age, tending to decrease in later stages. This variation was detected among bacterial communities of the five tested cultivars. The characterization of soil microbial communities can be part of plant breeding programs to be used on studies of environmental risk assessment of genetically modified potatoes.

Reduced left hemisphere dominance for multiple versus single anagram solutions and its modulation by individuals' schizotypy

Problem solving (including insight, divergent thinking) seems to rely on the right hemisphere (RH). These functions are difficult to assess behaviorally. We propose anagram resolution as a suitable paradigm. University students (n=32) performed three tachistoscopic lateralized visual half-field experiments (stimulus presentation 150ms). In Experiment 1, participants recalled four-letter strings. Subsequently, participants provided solutions for four-letter anagrams (one solution in Experiment 2; two solutions in Experiment 3). Additionally, participants completed a schizotypy questionnaire (O-LIFE). Results showed a right visual field advantage in Experiment 1 and 2, but no visual field advantage in Experiment 3. In Experiment 1, increasing positive schizotypy associated with a RH performance shift. Problem solving seems to require increasingly the RH when facing several rather than one solution. This result supports previous studies on the RH's role in remote associative, metaphor and discourse processing. The more complex language requirements, the less personality traits seem to matter.

An epidemiological evaluation of pediatric long bone fractures - a retrospective cohort study of 2716 patients from two Swiss tertiary pediatric hospitals.

BACKGROUND: Children and adolescents are at high risk of sustaining fractures during growth. Therefore, epidemiological assessment is crucial for fracture prevention. The AO Comprehensive Injury Automatic Classifier (AO COIAC) was used to evaluate epidemiological data of pediatric long bone fractures in a large cohort. METHODS: Data from children and adolescents with long bone fractures sustained between 2009 and 2011, treated at either of two tertiary pediatric surgery hospitals in Switzerland, were retrospectively collected. Fractures were classified according to the AO Pediatric Comprehensive Classification of Long Bone Fractures (PCCF). RESULTS: For a total of 2716 patients (60% boys), 2807 accidents with 2840 long bone fractures (59% radius/ulna; 21% humerus; 15% tibia/fibula; 5% femur) were documented. Children's mean age (SD) was 8.2 (4.0) years (6% infants; 26% preschool children; 40% school children; 28% adolescents). Adolescent boys sustained more fractures than girls (p < 0.001). The leading cause of fractures was falls (27%), followed by accidents occurring during leisure activities (25%), at home (14%), on playgrounds (11%), and traffic (11%) and school accidents (8%). There was boy predominance for all accident types except for playground and at home accidents. The distribution of accident types differed according to age classes (p < 0.001). Twenty-six percent of patients were classed as overweight or obese - higher than data published by the WHO for the corresponding ages - with a higher proportion of overweight and obese boys than in the Swiss population (p < 0.0001). CONCLUSION: Overall, differences in the fracture distribution were sex and age related. Overweight and obese patients seemed to be at increased risk of sustaining fractures. Our data give valuable input into future development of prevention strategies. The AO PCCF proved to be useful in epidemiological reporting and analysis of pediatric long bone fractures.

Estimating soybean crop areas using spectral-temporal surfaces derived from MODIS images in Mato Grosso, Brazil

The objective of this work was to evaluate the application of the spectral-temporal response surface (STRS) classification method on Moderate Resolution Imaging Spectroradiometer (MODIS, 250 m) sensor images in order to estimate soybean areas in Mato Grosso state, Brazil. The classification was carried out using the maximum likelihood algorithm (MLA) adapted to the STRS method. Thirty segments of 30x30 km were chosen along the main agricultural regions of Mato Grosso state, using data from the summer season of 2005/2006 (from October to March), and were mapped based on fieldwork data, TM/Landsat-5 and CCD/CBERS-2 images. Five thematic classes were considered: Soybean, Forest, Cerrado, Pasture and Bare Soil. The classification by the STRS method was done over an area intersected with a subset of 30x30-km segments. In regions with soybean predominance, STRS classification overestimated in 21.31% of the reference values. In regions where soybean fields were less prevalent, the classifier overestimated 132.37% in the acreage of the reference. The overall classification accuracy was 80%. MODIS sensor images and the STRS algorithm showed to be promising for the classification of soybean areas in regions with the predominance of large farms. However, the results for fragmented areas and smaller farms were less efficient, overestimating soybean areas.

IFN Stimulated Gene Expression in the Liver is a Better Predictor of Treatment Response in Chronic Hepatitis C than the IL28B (IFN lambda 3) Genotype

BACKGROUND: Therapy of chronic hepatitis C (CHC) with pegIFNα/ribavirin achieves a sustained virologic response (SVR) in ∼55%. Pre-activation of the endogenous interferon system in the liver is associated with non-response (NR). Recently, genome-wide association studies described associations of allelic variants near the IL28B (IFNλ3) gene with treatment response and with spontaneous clearance of the virus. We investigated if the IL28B genotype determines the constitutive expression of IFN stimulated genes (ISGs) in the liver of patients with CHC. METHODS: We genotyped 93 patients with CHC for 3 IL28B single nucleotide polymorphisms (SNPs, rs12979860, rs8099917, rs12980275), extracted RNA from their liver biopsies and quantified the expression of IL28B and of 8 previously identified classifier genes which discriminate between SVR and NR (IFI44L, RSAD2, ISG15, IFI22, LAMP3, OAS3, LGALS3BP and HTATIP2). Decision tree ensembles in the form of a random forest classifier were used to calculate the relative predictive power of these different variables in a multivariate analysis. RESULTS: The minor IL28B allele (bad risk for treatment response) was significantly associated with increased expression of ISGs, and, unexpectedly, with decreased expression of IL28B. Stratification of the patients into SVR and NR revealed that ISG expression was conditionally independent from the IL28B genotype, i.e. there was an increased expression of ISGs in NR compared to SVR irrespective of the IL28B genotype. The random forest feature score (RFFS) identified IFI27 (RFFS = 2.93), RSAD2 (1.88) and HTATIP2 (1.50) expression and the HCV genotype (1.62) as the strongest predictors of treatment response. ROC curves of the IL28B SNPs showed an AUC of 0.66 with an error rate (ERR) of 0.38. A classifier with the 3 best classifying genes showed an excellent test performance with an AUC of 0.94 and ERR of 0.15. The addition of IL28B genotype information did not improve the predictive power of the 3-gene classifier. CONCLUSIONS: IL28B genotype and hepatic ISG expression are conditionally independent predictors of treatment response in CHC. There is no direct link between altered IFNλ3 expression and pre-activation of the endogenous system in the liver. Hepatic ISG expression is by far the better predictor for treatment response than IL28B genotype.

A connectome-based comparison of diffusion MRI schemes.

Diffusion MRI has evolved towards an important clinical diagnostic and research tool. Though clinical routine is using mainly diffusion weighted and tensor imaging approaches, Q-ball imaging and diffusion spectrum imaging techniques have become more widely available. They are frequently used in research-oriented investigations in particular those aiming at measuring brain network connectivity. In this work, we aim at assessing the dependency of connectivity measurements on various diffusion encoding schemes in combination with appropriate data modeling. We process and compare the structural connection matrices computed from several diffusion encoding schemes, including diffusion tensor imaging, q-ball imaging and high angular resolution schemes, such as diffusion spectrum imaging with a publically available processing pipeline for data reconstruction, tracking and visualization of diffusion MR imaging. The results indicate that the high angular resolution schemes maximize the number of obtained connections when applying identical processing strategies to the different diffusion schemes. Compared to the conventional diffusion tensor imaging, the added connectivity is mainly found for pathways in the 50-100mm range, corresponding to neighboring association fibers and long-range associative, striatal and commissural fiber pathways. The analysis of the major associative fiber tracts of the brain reveals striking differences between the applied diffusion schemes. More complex data modeling techniques (beyond tensor model) are recommended 1) if the tracts of interest run through large fiber crossings such as the centrum semi-ovale, or 2) if non-dominant fiber populations, e.g. the neighboring association fibers are the subject of investigation. An important finding of the study is that since the ground truth sensitivity and specificity is not known, the comparability between results arising from different strategies in data reconstruction and/or tracking becomes implausible to understand.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Contribution of neural networks to Alzheimer disease's progression.

The neuropathology of Alzheimer disease is characterized by senile plaques, neurofibrillary tangles and cell death. These hallmarks develop according to the differential vulnerability of brain networks, senile plaques accumulating preferentially in the associative cortical areas and neurofibrillary tangles in the entorhinal cortex and the hippocampus. We suggest that the main aetiological hypotheses such as the beta-amyloid cascade hypothesis or its variant, the synaptic beta-amyloid hypothesis, will have to consider neural networks not just as targets of degenerative processes but also as contributors of the disease's progression and of its phenotype. Three domains of research are highlighted in this review. First, the cerebral reserve and the redundancy of the network's elements are related to brain vulnerability. Indeed, an enriched environment appears to increase the cerebral reserve as well as the threshold of disease's onset. Second, disease's progression and memory performance cannot be explained by synaptic or neuronal loss only, but also by the presence of compensatory mechanisms, such as synaptic scaling, at the microcircuit level. Third, some phenotypes of Alzheimer disease, such as hallucinations, appear to be related to progressive dysfunction of neural networks as a result, for instance, of a decreased signal to noise ratio, involving a diminished activity of the cholinergic system. Overall, converging results from studies of biological as well as artificial neural networks lead to the conclusion that changes in neural networks contribute strongly to Alzheimer disease's progression.

Comparison of molecular signatures from multiple skin diseases identifies mechanisms of immunopathogenesis.

The ability to obtain gene expression profiles from human disease specimens provides an opportunity to identify relevant gene pathways, but is limited by the absence of data sets spanning a broad range of conditions. Here, we analyzed publicly available microarray data from 16 diverse skin conditions in order to gain insight into disease pathogenesis. Unsupervised hierarchical clustering separated samples by disease as well as common cellular and molecular pathways. Disease-specific signatures were leveraged to build a multi-disease classifier, which predicted the diagnosis of publicly and prospectively collected expression profiles with 93% accuracy. In one sample, the molecular classifier differed from the initial clinical diagnosis and correctly predicted the eventual diagnosis as the clinical presentation evolved. Finally, integration of IFN-regulated gene programs with the skin database revealed a significant inverse correlation between IFN-β and IFN-γ programs across all conditions. Our study provides an integrative approach to the study of gene signatures from multiple skin conditions, elucidating mechanisms of disease pathogenesis. In addition, these studies provide a framework for developing tools for personalized medicine toward the precise prediction, prevention, and treatment of disease on an individual level.

Multispectral remote sensing for site-specific nitrogen fertilizer management

The objective of this work was to evaluate the use of multispectral remote sensing for site-specific nitrogen fertilizer management. Satellite imagery from the advanced spaceborne thermal emission and reflection radiometer (Aster) was acquired in a 23 ha corn-planted area in Iran. For the collection of field samples, a total of 53 pixels were selected by systematic randomized sampling. The total nitrogen content in corn leaf tissues in these pixels was evaluated. To predict corn canopy nitrogen content, different vegetation indices, such as normalized difference vegetation index (NDVI), soil-adjusted vegetation index (Savi), optimized soil-adjusted vegetation index (Osavi), modified chlorophyll absorption ratio index 2 (MCARI2), and modified triangle vegetation index 2 (MTVI2), were investigated. The supervised classification technique using the spectral angle mapper classifier (SAM) was performed to generate a nitrogen fertilization map. The MTVI2 presented the highest correlation (R²=0.87) and is a good predictor of corn canopy nitrogen content in the V13 stage, at 60 days after cultivating. Aster imagery can be used to predict nitrogen status in corn canopy. Classification results indicate three levels of required nitrogen per pixel: low (0-2.5 kg), medium (2.5-3 kg), and high (3-3.3 kg).

On the Condition Monitoring of Induction machines

The research of condition monitoring of electric motors has been wide for several decades. The research and development at universities and in industry has provided means for the predictive condition monitoring. Many different devices and systems are developed and are widely used in industry, transportation and in civil engineering. In addition, many methods are developed and reported in scientific arenas in order to improve existing methods for the automatic analysis of faults. The methods, however, are not widely used as a part of condition monitoring systems. The main reasons are, firstly, that many methods are presented in scientific papers but their performance in different conditions is not evaluated, secondly, the methods include parameters that are so case specific that the implementation of a systemusing such methods would be far from straightforward. In this thesis, some of these methods are evaluated theoretically and tested with simulations and with a drive in a laboratory. A new automatic analysis method for the bearing fault detection is introduced. In the first part of this work the generation of the bearing fault originating signal is explained and its influence into the stator current is concerned with qualitative and quantitative estimation. The verification of the feasibility of the stator current measurement as a bearing fault indicatoris experimentally tested with the running 15 kW induction motor. The second part of this work concentrates on the bearing fault analysis using the vibration measurement signal. The performance of the micromachined silicon accelerometer chip in conjunction with the envelope spectrum analysis of the cyclic bearing faultis experimentally tested. Furthermore, different methods for the creation of feature extractors for the bearing fault classification are researched and an automatic fault classifier using multivariate statistical discrimination and fuzzy logic is introduced. It is often important that the on-line condition monitoring system is integrated with the industrial communications infrastructure. Two types of a sensor solutions are tested in the thesis: the first one is a sensor withcalculation capacity for example for the production of the envelope spectra; the other one can collect the measurement data in memory and another device can read the data via field bus. The data communications requirements highly depend onthe type of the sensor solution selected. If the data is already analysed in the sensor the data communications are needed only for the results but in the other case, all measurement data need to be transferred. The complexity of the classification method can be great if the data is analysed at the management level computer, but if the analysis is made in sensor itself, the analyses must be simple due to the restricted calculation and memory capacity.

Fuzzy Principal Components Analysis

Due to the large number of characteristics, there is a need to extract the most relevant characteristicsfrom the input data, so that the amount of information lost in this way is minimal, and the classification realized with the projected data set is relevant with respect to the original data. In order to achieve this feature extraction, different statistical techniques, as well as the principal components analysis (PCA) may be used. This thesis describes an extension of principal components analysis (PCA) allowing the extraction ofa finite number of relevant features from high-dimensional fuzzy data and noisy data. PCA finds linear combinations of the original measurement variables that describe the significant variation in the data. The comparisonof the two proposed methods was produced by using postoperative patient data. Experiment results demonstrate the ability of using the proposed two methods in complex data. Fuzzy PCA was used in the classificationproblem. The classification was applied by using the similarity classifier algorithm where total similarity measures weights are optimized with differential evolution algorithm. This thesis presents the comparison of the classification results based on the obtained data from the fuzzy PCA.