Conflit radio-ulnaire distal révélant un kyste anévrysmal osseux

Le conflit radio-ulnaire distal résulte d'un pincement de l'articulation radio-ulnaire occasionnant un syndrome douloureux du poignet. Le conflit radio-ulnaire distal est le plus souvent d'origine dégénérative ou post-traumatique avec une atteinte du complexe triangulaire fibro-cartilagineux et un conflit ulno-lunaire associés par une inversion de l'index radio-ulnaire. Nous rapportons un cas de conflit de l'articulation radio-ulnaire distal chez une patiente de 35 ans, secrétaire de profession, consultant pour des douleurs chroniques du poignet gauche. Une radiographie du poignet en incidence de face objectivait une volumineuse lacune de l'extrémité inférieure du radius épiphyso-métaphysaire, bien limitée, aux contours irréguliers, d'aspects multi-cloisonné « soufflant l'os » sans rupture de la corticale osseuse du versant interne. Cette lésion expansive envahissait la membrane interosseuse et entrainait un conflit radio-ulnaire. La biopsie osseuse a été effectuée et revenait en faveur d'un kyste anévrysmal osseux. Le traitement chez notre patiente a consisté à un curetage des cavités kystiques associé à une greffe osseuse

C-SPARQL Extension for Sampling RDF Graphs Streams

International audienceOur daily use of Internet and related technologies generates continuously large amount of heterogeneous data flows. Several RDF Stream Processing (RSP) systems have been proposed. Existing RSP systems benefit from the advantages of semantic web technologies and traditional data flow management systems. C-SPARQL, CQELS, SPARQL stream , EP-SPARQL, and Sparkwave extend the semantic query language SPARQL and are examples of those systems. Considering that the storage and processing of all these streams become expensive, we propose a solution to reduce the load while keeping data semantics, and optimizing treatments. In this paper, we propose to extend C-SPARQL for continuously generating samples on RDF graphs. We add three sampling operators (UNIFORM, RESERVOIR and CHAIN) to the C-SPARQL query syntax. These operators have been implemented into Esper, the C-SPARQL's data flow management module. The experiments show the performance of our extension in terms of execution time and preserving data semantics

Apport de l’écho-doppler artériel des membres inférieurs dans la prise en charge du pied diabétique à l’hôpital Saint-Jean de Dieu de Thiès (Sénégal)

Introduction: Le pied diabétique se définit comme l'ensemble des manifestations trophiques du pied survenant chez le diabétique par atteinte nerveuse, artérielle et ou infectieuse. Le pied diabétique est un problème majeur de santé publique à l'échelle mondiale avec un taux d'amputation de membres inférieurs très élevé. L'écho-doppler artériel des membres inférieurs est de nos jours incontournable dans la prise en charge du pied diabétique. Le but de cette étude est de montrer la place prépondérante qu'occupe l'écho-doppler artériel dans le bilan lésionnel du pied diabétique. Méthodes: Nous avons mené une étude rétrospective monocentrique incluant 46 patients sur une période de 24 mois, de mars 2012 à mars 2014 à l'hôpital Saint-Jean de Dieu, un des deux hôpitaux de référence de la région de Thiès, doté depuis juillet 2011 d'un centre moderne de traitement du diabète et des maladies cardio-métaboliques (Diabcarmet). Dans les critères d'inclusion, nous avons sélectionné tous les patients diabétiques adressés pour un écho-doppler artériel des membres inférieurs dans le cadre d'une prise en charge du pied diabétique. Etaient exclus de l'étude, les patients artéritiques non-diabétiques et les patients diabétiques asymptomatiques référés pour un bilan écho-doppler de routine. Résultats: Le sex-ratio était de 1.42 (27 hommes pour 19 femmes). L'âge moyen des patients était de 62,86 ans avec des extrêmes de 23 et 88 ans. 60% des patients (n=28) étaient âgés entre 50 et 70 ans. Le diabète de type 2 était retrouvé chez 95% des patients (n=44) alors que le diabète de type 1 représentait 5% (n=2). La moyenne d'évolution du diabète était estimée à 8 ans, avec des extrêmes de 2 et 20 ans. On notait une atteinte du pied droit chez 24 patients, une atteinte du pied gauche chez 18 patients et une atteinte bilatérale chez 4 patients.La plupart du temps, les lésions du pied diabétique survenaient sur un terrain de diabète déséquilibré (95%). Cliniquement, ces lésions étaient dominées par la gangrène infectieuse du pied (43.47%), l'abolition des pouls tibiaux et pédieux (17.4%), la gangrène infectieuse des orteils (13.07%), la gangrène mixte du pied (4.34%) et le mal perforant plantaire (4.34%).Sur le plan échographique, vingt-six patients ne présentaient aucune anomalie hémodynamique significative, même si sur le plan morphologique la médiacalcose était retrouvée chez tous nos patients (n=46). Les autres lésions morphologiques et hémodynamiques artérielles étaient dominées par la sténose serrée de l'artère fémorale superficielle chez 6 patients soit 13.04%, les sténoses des artères tibiales antérieures et postérieures chez 4 patients (6.52%) et l'association de plusieurs lésions artérielles chez 4 patients (8.7%). Le taux d'amputation, dans notre série, était de 21.7%. Conclusion: Le pied diabétique est une complication potentiellement grave du diabète, en Afrique sub-saharienne du fait d'un fort taux d'amputation de membre. L'écho-doppler artériel des membres inférieurs est un moyen d'imagerie non irradiant et non invasif indispensable dans la prise de décision thérapeutique du pied diabétique.Pan African Medical Journal 2015; 2

DRSS: Distributed RDF SPARQL Streaming

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Fast SPARQL join processing between distributed streams and stored RDF graphs using bloom filters

International audienceThe growth of real-time data generation and stored data leads us to be constantly in thinking about the three V's big data challenges: volume, velocity and variety. Existing RDF Stream Processing (RSP) systems have solved the variety lock by defining a common model for producing, transmitting and continuously querying data in RDF model. On the volume and velocity side, the performances of RSP systems need to be improved particularly in terms of joins process between stored and streaming RDF graphs. Stored RDF data are very important in streaming context (related ontologies, summarized RDF data, non-evolutive RDF data or evolve very slowly over time, etc.) but existing RSP systems such as C-SPARQL, CQELS, SPARQL stream , EP-SPARQL, Sparkwave, etc. use non-optimized and non-scalable approaches for performing join operations between stored and dynamic RDF data. Indeed, these systems need to read the entire local or remote stored RDF data sets while RDF data streams continuously arrived and need to be processed in near real-time. This latency may negatively affect performances in terms of continuous processing and often causes multiple bottlenecks within the network in a distributed environment. That also makes impractical to refresh data or update the stored contents. This paper proposes an approach for distributed real-time joins between stored and streaming RDF graphs using Bloom filters. The join procedure consists of adding fast processing by greatly reducing intermediate results, in-memory indices storage and precomputing query partitions according to the picked SPARQL query variable(s) between the two natures of RDF data. Experimental and evaluations results confirm the performances gained with our approach which significantly speeds up the query processing compared to the actual RSP's techniques

Efficient Graph-Oriented Summary for Optimized Resource Description Framework Streams Processing Using Extended Centrality Measures

International audienceExisting RDF Stream Processing (RSP) systems allow continuous processing of RDF data issued from different application domains such as weather station measuring phenomena, geolocation,IoT applications, drinking water distribution management and so on. However processing window phase often expires before finishing the entire session and RSP systems immediately delete data streams after each processed window. Such mechanism does not allow an optimized exploitation of the RDF data streams as the most relevant and pertinent information of the data is often not used in a due time and almost impossible to be exploited for further analyzes. It should be better to keep the most informative part of data within streams while minimizing the memory storage space. In this work, we propose an RDF graph summarization system based on an explicit and implicit expressed needs through three (3) main approaches: (1) an approach for user queries (SPARQL) in order to extract their needs and group them into a more global query, (2) an extension of the closeness centrality measure issued from Social Network Analysis (SNA) to determine the most informative parts of the graph and (3) an RDF graph summarization technique combining extracted user query needs and the extended centrality measure. Experiments and evaluations show efficient result in term of memory space storage and the most expected approximate query results on summarized graphs compared to the source ones.Existing RDF Stream Processing (RSP) systems allow continuous processing of RDF data issued from different application domains such as weather station measuring phenomena, geolocation,IoT applications, drinking water distribution management and so on. However processing window phase often expires before finishing the entire session and RSP systems immediately delete data streams after each processed window. Such mechanism does not allow an optimized exploitation of the RDF data streams as the most relevant and pertinent information of the data is often not used in a due time and almost impossible to be exploited for further analyzes. It should be better to keep the most informative part of data within streams while minimizing the memory storage space. In this work, we propose an RDF graph summarization system based on an explicit and implicit expressed needs through three (3) main approaches: (1) an approach for user queries (SPARQL) in order to extract their needs and group them into a more global query, (2) an extension of the closeness centrality measure issued from Social Network Analysis (SNA) to determine the most informative parts of the graph and (3) an RDF graph summarization technique combining extracted user query needs and the extended centrality measure. Experiments and evaluations show efficient result in term of memory space storage and the most expected approximate query results on summarized graphs compared to the source ones

Application of non-Gaussian water diffusional kurtosis imaging in the assessment of uterine tumors: A preliminary study.

To evaluate the interobserver reliability and value of diffusional kurtosis imaging (DKI) in the assessment of uterine tumors compared with those of conventional diffusion-weighted imaging (DWI).This retrospective study was approved by our institutional review board, which waived the requirement for informed consent. Fifty-eight women (mean age: 55.0 ± 13.6 years; range: 30-89 years) with suspected malignant uterine tumors underwent 3-T magnetic resonance imaging using DKI and DWI. Twelve had coexisting leiomyoma. Two observers analyzed region-of-interest measurements of diffusivity (D), kurtosis (K), and the apparent diffusion coefficient (ADC) of uterine lesions and healthy adjacent tissues. Interobserver agreement was evaluated using the intra-class correlation coefficient (ICC). The mean values were compared using one-way analysis of variance with a post-hoc Tukey's honestly significant difference test. The diagnostic accuracy of D and ADC in differentiating malignant tumors from benign leiomyomas was analyzed using receiver operating characteristic (ROC) analysis.The ICCs between the two observers in evaluating D, K, and the ADC of the malignant tumors were higher than 0.84, suggesting excellent interobserver agreements. The mean D (×10-3 mm2/s) of uterine cancers (1.05 ± 0.41 and 1.09 ± 0.40 for observers 1 and 2, respectively) were significantly lower than those of leiomyoma (1.40 ± 0.37 and 1.56 ± 0.33, respectively; P 0.1).Interobserver agreements in evaluating D, K, and ADC were moderate to excellent. D performed equally to conventional DWI in differentiating between benign and malignant uterine lesions. The mean K of malignant uterine lesions was significantly higher than that of non-tumorous myometrium or endometrium

Statistical modeling of the abundance of vectors of West African Rift Valley fever in Barkédji, Senegal.

Rift Valley fever is an emerging mosquito-borne disease that represents a threat to human and animal health. The exophilic and exophagic behavior of the two main vector in West Africa (Aedes vexans and Culex poicilipes), adverse events post-vaccination, and lack of treatment, render ineffective the disease control. Therefore it is essential to develop an information system that facilitates decision-making and the implementation of adaptation strategies. In East Africa, RVF outbreaks are linked with abnormally high rainfall, and can be predicted up to 5 months in advance by modeling approaches using climatic and environmental parameters. However, the application of these models in West Africa remains unsatisfactory due to a lack of data for animal and human cases and differences in the dynamics of the disease emergence and the vector species involved in transmission. Models have been proposed for West Africa but they were restricted to rainfall impact analysis without a spatial dimension. In this study, we developed a mixed Bayesian statistical model to evaluate the effects of climatic and ecological determinants on the spatiotemporal dynamics of the two main vectors. Adult mosquito abundance data were generated from July to December every fortnight in 2005-2006 at 79 sites, including temporary ponds, bare soils, shrubby savannah, wooded savannah, steppes, and villages in the Barkédji area. The results demonstrate the importance of environmental factors and weather conditions for predicting mosquito abundance. The rainfall and minimum temperature were positively correlated with the abundance of Cx. poicilipes, whereas the maximum temperature had negative effects. The rainfall was negatively correlated with the abundance of Ae. vexans. After combining land cover classes, weather conditions, and vector abundance, our model was used to predict the areas and periods with the highest risks of vector pressure. This information could support decision-making to improve RVF surveillance activities and to implement better intervention strategies

Shifting Patterns of Influenza Circulation during the COVID-19 Pandemic, Senegal

Historically low levels of seasonal influenza circulation were reported during the first years of the COVID-19 pandemic and were mainly attributed to implementation of nonpharmaceutical interventions. In tropical regions, influenza’s seasonality differs largely, and data on this topic are scarce. We analyzed data from Senegal’s sentinel syndromic surveillance network before and after the start of the COVID-19 pandemic to assess changes in influenza circulation. We found that influenza shows year-round circulation in Senegal and has 2 distinct epidemic peaks: during January–March and during the rainy season in August–October. During 2021–2022, the expected January–March influenza peak completely disappeared, corresponding to periods of active SARS-CoV-2 circulation. We noted an unexpected influenza epidemic peak during May–July 2022. The observed reciprocal circulation of SARS-CoV-2 and influenza suggests that factors such as viral interference might be at play and should be further investigated in tropical settings

Application of non-Gaussian water diffusional kurtosis imaging in the assessment of uterine tumors: A preliminary study - Fig 4

<p>Box-and-whisker plot of mean diffusivity (D) of uterine malignant tumor, leiomyoma, healthy myometrium, and healthy endometrium for (a) observer 1 and (b) observer 2. Outliers are also represented (° and *). The top and bottom of each box represent the 25th and 75th percentiles of the mean D, respectively. The horizontal line inside each box represents the median value. The graphs show a significantly lower mean D for uterine malignant tumor than for leiomyoma, healthy myometrium, and healthy endometrium. There were no significant differences in D between leiomyoma and endometrium (<i>P</i> = 0.74), or myometrium and endometrium (<i>P</i> = 0.21) for observer 1. There were no significant differences in D between leiomyoma and myometrium (<i>P</i> = 0.71), or leiomyoma and endometrium (<i>P</i> = 0.70) for observer 2.</p