Impact of an extension tube on operator radiation exposure during coronary procedures performed through the radial approach

SummaryBackgroundOperator radiation exposure is high during coronary procedures. The radial access decreases the rate of local vascular complications but increases operator radiation exposure. As the X-ray exposure is related to the distance between the operator and the radiation source, the use of an extension tube between the proximal part of the coronary catheter and the ‘injection device’ might decrease operator radiation exposure.AimsTo demonstrate that the use of an extension tube during coronary procedures performed through the radial approach decreases operator radiation.MethodsOverall, 230 patients were included consecutively and randomized to procedures performed with or without an extension tube. Radiation exposure measures were obtained using two electronic dosimeters, one under the lead apron and the other exposed on the physician's left arm.ResultsA non-significant trend towards lower left-arm operator exposure was noted in the extension tube group (28.7±31.0μSv vs 38.4±44.2μSv, p=0.0739). No significant difference was noted according to the type of procedure. Radiation levels were low compared with the series published previously and decreased for each operator during the study.ConclusionThe use of an extension tube did not reduce operator radiation exposure during procedures performed through the radial approach. However, physician awareness was increased during the study due to the use of an exposed electronic dosimeter. The use of exposed electronic dosimeters could therefore be recommended to allow operators to improve their protection techniques

Time- and Dose-Related Effects of Di-(2-ethylhexyl) Phthalate and Its Main Metabolites on the Function of the Rat Fetal Testis in Vitro

International audienceBACKGROUND: Endocrine-disrupting effects of phthalates are understood primarily from in utero exposures within the fetal rat testis. Nevertheless, their path of action, dose-response character, and cellular target(s) within the fetal testis are not known. OBJECTIVES: In this study we investigated the effects of di-(2-ethylhexyl) phthalate (DEHP), mono-(2-ethylhexyl) phthalate (MEHP), and several of their metabolites on the development of organo-cultured testes from rat fetus. METHODS: We removed testes from 14.5-day-old rat fetuses and cultured them for 1-3 days with or without DEHP, MEHP, and the metabolites. RESULTS: DEHP (10(-5) M) produced a proandrogenic effect after 3 days of culture, whereas MEHP disrupted testis morphology and function. Leydig cells were the first affected by MEHP, with a number of them being inappropriately located within some seminiferous tubules. Additionally, we found a time- and dose-dependent reduction of testosterone. By 48 hr, gonocyte proliferation had decreased, whereas apoptosis increased. Sertoli cell number was unaffected, although some cells appeared vacuolated, and production of anti-Müllerian hormone decreased in a time- and dose-dependent manner. The derived metabolite mono-(2-ethyl-5-hydroxyhexyl) phthalate was the only one to cause deleterious effects to the rat fetal testis in vitro. CONCLUSION: We hope that this in vitro method will facilitate the study of different phthalate esters and other endocrine disruptors for direct testicular effects

Trust-Aware Peer Sampling: Performance and Privacy Tradeoffs

International audienceThe ability to identify people that share one's own interests is one of the most interesting promises of the Web 2.0 driving user-centric applications such as recommendation systems or collaborative marketplaces. To be truly useful, however, information about other users also needs to be associated with some notion of trust. Consider a user wishing to sell a concert ticket. Not only must she find someone who is interested in the concert, but she must also make sure she can trust this person to pay for it. This paper addresses the need for trust in user-centric applications by propos- ing two novel distributed protocols that combine interest-based connections be- tween users with explicit links obtained from social networks à-la Facebook. Both protocols build trusted multi-hop paths between users in an explicit so- cial network supporting the creation of semantic overlays backed up by social trust. The first protocol, TAPS2 , extends our previous work on TAPS (Trust- Aware Peer Sampling), by improving the ability to locate trusted nodes. Yet, it remains vulnerable to attackers wishing to learn about trust values between ar- bitrary pairs of users. The second protocol, PTAPS (Private TAPS ), improves TAPS2 with provable privacy guarantees by preventing users from revealing their friendship links to users that are more than two hops away in the social network. In addition to proving this privacy property, we evaluate the per- formance of our protocols through event-based simulations, showing significant improvements over the state of the art

Catch Me If You Can Privacy-Preserving Dissemination in Micro-Blogging

Online micro-blogging services and social networks, as ex- emplified by Twitter and Facebook, have emerged as an im- portant means of disseminating information quickly and at large scale. A standard mechanism in micro-blogging that allows for interesting content to reach a wider audience is that of reposting (i.e., retweeting in Twitter, or sharing in Facebook) of content initially posted by another user. Moti- vated by recent events in which users were prosecuted merely for reposting anti-government information, we present Ri- poste, a randomized reposting scheme that provides pri- vacy guarantees against such charges. The idea is that if the user likes a post, Riposte will re- post it only with some (carefully chosen) probability; and if the user does not like it, Riposte may still repost it with a slightly smaller probability. These probabilities are com- puted for each user as a function of the number of connec- tions of the user in the network, and the extent to which the post has already reached those connections. The choice of these probabilities is based on results for branching pro- cesses, and ensures that interesting posts (liked by a large fraction of users) are likely to disseminate widely, whereas uninteresting posts (or spam) do not spread. Riposte is ex- ecuted locally at the user, thus the user's opinion on the post is not communicated to the micro-blogging server. We quantify Riposte's ability to protect users in terms of differential privacy and provide analytical bounds on the dissemination of posts. We also report on experimental re- sults based on topologies of real networks, including Twitter, Facebook, Renren, Google+ and LiveJournal

FreeRec: an Anonymous and Distributed Personalization Architecture

We present and evaluate FreeRec, an anonymous decentral- ized peer-to-peer architecture, designed to bring personalization while protecting the privacy of its users. FreeRec's decentralized approach makes it independent of any entity wishing to collect personal data about users. At the same time, its onion-routing-like gossip-based overlay protocols effectively hide the association between users and their inter- est profiles without affecting the quality of personalization. The core of FreeRec consists of three layers of overlay protocols: the bottom layer, rps, consists of a standard random peer sampling protocol ensur- ing connectivity; the middle layer, PRPS, introduces anonymity by hid- ing users behind anonymous proxy chains, providing mutual anonymity; finally, the top clustering layer identifies for each anonymous user, a set of anonymous nearest neighbors. We demonstrate the effectiveness of FreeRec by building a decentralized and anonymous content dis- semination system. Our evaluation by simulation and through extensive PlanetLab experiments show that FreeRec effectively decouples users from their profiles without hampering the quality of personalized content delivery

Harnessing the power of implicit and explicit social networks through decentralization

La personnalisation de contenu est devenu une fonctionnalité cruciale sur Internet, car elle aide les utilisateurs à filtrer le contenu qu'ils ne trouvent pas intéressant. Ces systèmes collectent une grande quantité de données pour fournir un service efficace. Cela implique que les utilisateurs perdent le contrôle sur leurs données, ce qui pose un problème de respect de la vie privée. Les systèmes pair-à-pair (P2P) offrent une intéressante alternative aux services centralisés. Dans ces systèmes, chaque utilisateur est responsable de ses données et contrôle lesquelles sont utilisées par le système. Néanmoins, ces systèmes ne règlent que partiellement le problème de respect de la vie privée car, en général, tous les utilisateurs du système peuvent accéder aux données des autres utilisateur. De plus il est difficile de s'assurer de l'identité des utilisateurs, et donc de leur faire confiance. C'est un problème dans un contexte comme une place de marché en ligne, comme par exemple eBay. Dans un contexte P2P, il est difficile de s'assurer qu'un utilisateur est bien qui il dit être, et qu'il remplira sa part du marché. Malgré ces défauts nous pensons que le P2P est le meilleur moyen de résoudre le problème de vie privée. Il faut néanmoins améliorer les systèmes P2P afin de mieux protéger les données utilisateur et augmenter la confiance entre les utilisateurs. Dans cette thèse nous présentons quatre contributions allant dans ce sens. La première, TAPS, fournit aux utilisateurs une estimation de la fiabilité des autres utilisateurs en fonction d'informations extraites d'un réseau social, ainsi que chemin reliant les deux utilisateurs sur le réseau. Par exemple, TAPS informera un utilisateur, Bob, qu'un autre utilisateur, Carole, est la sœur d'un collègue de sa femme Alice. Ainsi, Bob connaît l'identité de Carole et sait si il peut lui faire confiance. La seconde, PTAPS, est une alternative à TAPS préservant la vie privée des utilisateurs. Dans TAPS, les utilisateurs fournissent au système la liste de leurs amis. Dans PTAPS ces informations sont masqué et ne sont accessibles qu'aux amis de l'utilisateur. La troisième, FreeRec, est un système de personnalisation assurant l'anonymat des utilisateurs. Les problèmes de vie privée touchant les réseaux P2P sont dû en grande partie au fait qu'il est possible d'associer les actions d'un utilisateur à son identité . Une solution est de masquer l'identité de l'utilisateur aux autres utilisateurs. FreeRec fournit des recommandations tout en assurant l'anonymat des utilisateurs grâce à du routage en ognon. La dernière, DPPC, est un algorithme masquant les données des utilisateurs dans un système de recommandation. Les données des utilisateurs peuvent contenir des informations précises sur l'utilisateur. Il a été démontré que ces données sont parfois suffisantes pour découvrir l'identité de l'utilisateur. DPPC masques ces données tout en permettant à l'utilisateur de bénéficier du système de recommandation.Content personalization became an important functionality on the Internet, as it helps users to filter out uninteresting content. These systems collect a lot of data to provide accurate recommendations. This implies that the users loose control over their data, which causes a problem of privacy. Peer-to-peer (P2P) systems offer an interesting alternative to centralized services. In these systems, each user is responsible for her own data and control which ones are used by the system. Nevertheless, these systems solve only partially the privacy issue as, in general, all users of the system can access the data of the other users. In addition, it is difficult to know the true identity of users, and thus it is difficult to trust them. Thus is a problem in a context such as an online marketplace, such as eBay. In a P2P context, it is difficult to ensure that a user is really who she says she is, and that she will do her part of the job. Despites these weaknesses, we believe that P2P is the best way to solve the privacy issue. It is however necessary to improve P2P systems in order to better protect the users data and increase the trust between users. In this thesis we present four contributions going in that direction. The first one, TAPS, provides users with an estimation of the trustworthiness of other users based on information extracted from a social network, as well as a path linking the two users in this network. For example, TAPS will inform a user, Bob, that another user, Carol, is the sister of a colleague of his wife, Alice. Thus, Bob knows the identity of Carole and knows if he can trust her. The second one, PTAPS, is an alternative version of TAPS preserving the users' privacy. In TAPS, users provide the system with their list of friends. In PTAPS this information is hidden and only accessible by the user's friends. The third one, FreeRec, is a personalization system ensuring the users' anonymity. Privacy issues in P2P systems are mainly caused by the fact that it is possible to associate the action of a user with her identity. A solution is to hide the user's identity to the other users. FreeRec provides recommendations while ensuring users's anonymity thanks to onion routing. The last contribution, DPPC, is an algorithm hiding users' data in a recommendation system. Users data can contain precise information about the user. It has been showed that these data are sometimes enough to discover the user's true identity. DPPC hides these data while allowing the user to receive recommendations

Réseaux sociaux implicites et explicites, exploiter leur puissance grâce à la décentralisation

Content personalization became an important functionality on the Internet, as it helps users to filter out uninteresting content. These systems collect a lot of data to provide accurate recommendations. This implies that the users loose control over their data, which causes a problem of privacy. Peer-to-peer (P2P) systems offer an interesting alternative to centralized services. In these systems, each user is responsible for her own data and control which ones are used by the system. Nevertheless, these systems solve only partially the privacy issue as, in general, all users of the system can access the data of the other users. In addition, it is difficult to know the true identity of users, and thus it is difficult to trust them. Thus is a problem in a context such as an online marketplace, such as eBay. In a P2P context, it is difficult to ensure that a user is really who she says she is, and that she will do her part of the job. Despites these weaknesses, we believe that P2P is the best way to solve the privacy issue. It is however necessary to improve P2P systems in order to better protect the users data and increase the trust between users. In this thesis we present four contributions going in that direction. The first one, TAPS, provides users with an estimation of the trustworthiness of other users based on information extracted from a social network, as well as a path linking the two users in this network. For example, TAPS will inform a user, Bob, that another user, Carol, is the sister of a colleague of his wife, Alice. Thus, Bob knows the identity of Carole and knows if he can trust her. The second one, PTAPS, is an alternative version of TAPS preserving the users' privacy. In TAPS, users provide the system with their list of friends. In PTAPS this information is hidden and only accessible by the user's friends. The third one, FreeRec, is a personalization system ensuring the users' anonymity. Privacy issues in P2P systems are mainly caused by the fact that it is possible to associate the action of a user with her identity. A solution is to hide the user's identity to the other users. FreeRec provides recommendations while ensuring users's anonymity thanks to onion routing. The last contribution, DPPC, is an algorithm hiding users' data in a recommendation system. Users data can contain precise information about the user. It has been showed that these data are sometimes enough to discover the user's true identity. DPPC hides these data while allowing the user to receive recommendations.La personnalisation de contenu est devenu une fonctionnalité cruciale sur Internet, car elle aide les utilisateurs à filtrer le contenu qu'ils ne trouvent pas intéressant. Ces systèmes collectent une grande quantité de données pour fournir un service efficace. Cela implique que les utilisateurs perdent le contrôle sur leurs données, ce qui pose un problème de respect de la vie privée. Les systèmes pair-à-pair (P2P) offrent une intéressante alternative aux services centralisés. Dans ces systèmes, chaque utilisateur est responsable de ses données et contrôle lesquelles sont utilisées par le système. Néanmoins, ces systèmes ne règlent que partiellement le problème de respect de la vie privée car, en général, tous les utilisateurs du système peuvent accéder aux données des autres utilisateur. De plus il est difficile de s'assurer de l'identité des utilisateurs, et donc de leur faire confiance. C'est un problème dans un contexte comme une place de marché en ligne, comme par exemple eBay. Dans un contexte P2P, il est difficile de s'assurer qu'un utilisateur est bien qui il dit être, et qu'il remplira sa part du marché. Malgré ces défauts nous pensons que le P2P est le meilleur moyen de résoudre le problème de vie privée. Il faut néanmoins améliorer les systèmes P2P afin de mieux protéger les données utilisateur et augmenter la confiance entre les utilisateurs. Dans cette thèse nous présentons quatre contributions allant dans ce sens. La première, TAPS, fournit aux utilisateurs une estimation de la fiabilité des autres utilisateurs en fonction d'informations extraites d'un réseau social, ainsi que chemin reliant les deux utilisateurs sur le réseau. Par exemple, TAPS informera un utilisateur, Bob, qu'un autre utilisateur, Carole, est la sœur d'un collègue de sa femme Alice. Ainsi, Bob connaît l'identité de Carole et sait si il peut lui faire confiance. La seconde, PTAPS, est une alternative à TAPS préservant la vie privée des utilisateurs. Dans TAPS, les utilisateurs fournissent au système la liste de leurs amis. Dans PTAPS ces informations sont masqué et ne sont accessibles qu'aux amis de l'utilisateur. La troisième, FreeRec, est un système de personnalisation assurant l'anonymat des utilisateurs. Les problèmes de vie privée touchant les réseaux P2P sont dû en grande partie au fait qu'il est possible d'associer les actions d'un utilisateur à son identité . Une solution est de masquer l'identité de l'utilisateur aux autres utilisateurs. FreeRec fournit des recommandations tout en assurant l'anonymat des utilisateurs grâce à du routage en ognon. La dernière, DPPC, est un algorithme masquant les données des utilisateurs dans un système de recommandation. Les données des utilisateurs peuvent contenir des informations précises sur l'utilisateur. Il a été démontré que ces données sont parfois suffisantes pour découvrir l'identité de l'utilisateur. DPPC masques ces données tout en permettant à l'utilisateur de bénéficier du système de recommandation

Social Market: Combining Explicit and Implicit Social Networks

International audiencehe pervasiveness of the Internet has lead research and applications to focus more and more on their users. Online social networks such as Facebook provide users with the ability to maintain an unprecedented number of social connections. Recommendation systems exploit the opinions of other users to suggest movies or products based on our similarity with them. This shift from machines to users motivates the emergence of novel applications and research challenges. In this paper, we embrace the social aspects of the Web 2.0 by considering a novel problem. We build a distributed social market that combines interest-based social networks with explicit networks like Facebook. Our Social Market (SM) allows users to identify and build connections to other users that can provide interesting goods, or information. At the same time, it backs up these connections with trust, by associating them with paths of trusted users that connect new acquaintances through the explicit network. This convergence of implicit and explicit networks yields \taps, a novel gossip protocol that can be applied in applications devoted to commercial transactions, or to add robustness to standard gossip applications like dissemination or recommendation systems

DynaSoRe: Efficient In-Memory Store for Social Applications

Part 5: Social NetworksInternational audienceSocial network applications are inherently interactive, creating a requirement for processing user requests fast. To enable fast responses to user requests, social network applications typically rely on large banks of cache servers to hold and serve most of their content from the cache. In this work, we present DynaSoRe: a memory cache system for social network applications that optimizes data locality while placing user views across the system. DynaSoRe storage servers monitor access traffic and bring data frequently accessed together closer in the system to reduce the processing load across cache servers and network devices. Our simulation results considering realistic data center topologies show that DynaSoRe is able to adapt to traffic changes, increase data locality, and balance the load across the system. The traffic handled by the top tier of the network connecting servers drops by 94% compared to a static assignment of views to cache servers while requiring only 30% additional memory capacity compared to the whole volume of cached data