In search of optimal compression therapy for venous leg ulcers: a meta-analysis of studies comparing diverse [corrected] bandages with specifically designed stockings

OBJECTIVE: In search of an optimal compression therapy for venous leg ulcers, a systematic review and meta-analysis was performed of randomized controlled trials (RCT) comparing compression systems based on stockings (MCS) with divers bandages. METHODS: RCT were retrieved from six sources and reviewed independently. The primary endpoint, completion of healing within a defined time frame, and the secondary endpoints, time to healing, and pain were entered into a meta-analysis using the tools of the Cochrane Collaboration. Additional subjective endpoints were summarized. RESULTS: Eight RCT (published 1985-2008) fulfilled the predefined criteria. Data presentation was adequate and showed moderate heterogeneity. The studies included 692 patients (21-178/study, mean age 61 years, 56% women). Analyzed were 688 ulcerated legs, present for 1 week to 9 years, sizing 1 to 210 cm(2). The observation period ranged from 12 to 78 weeks. Patient and ulcer characteristics were evenly distributed in three studies, favored the stocking groups in four, and the bandage group in one. Data on the pressure exerted by stockings and bandages were reported in seven and two studies, amounting to 31-56 and 27-49 mm Hg, respectively. The proportion of ulcers healed was greater with stockings than with bandages (62.7% vs 46.6%; P < .00001). The average time to healing (seven studies, 535 patients) was 3 weeks shorter with stockings (P = .0002). In no study performed bandages better than MCS. Pain was assessed in three studies (219 patients) revealing an important advantage of stockings (P < .0001). Other subjective parameters and issues of nursing revealed an advantage of MCS as well. CONCLUSIONS: Leg compression with stockings is clearly better than compression with bandages, has a positive impact on pain, and is easier to use.

Privacy-Preserving Optimal Meeting Location Determination on Mobile Devices

Equipped with state-of-the-art smartphones and mobile devices, today's highly interconnected urban population is increasingly dependent on these gadgets to organize and plan their daily lives. These applications often rely on current (or preferred) locations of individual users or a group of users to provide the desired service, which jeopardizes their privacy; users do not necessarily want to reveal their current (or preferred) locations to the service provider or to other, possibly untrusted, users. In this paper, we propose privacy-preserving algorithms for determining an optimal meeting location for a group of users. We perform a thorough privacy evaluation by formally quantifying privacy-loss of the proposed approaches. In order to study the performance of our algorithms in a real deployment, we implement and test their execution efficiency on Nokia smartphones. By means of a targeted user-study, we attempt to get an insight into the privacy-awareness of users in location-based services and the usability of the proposed solutions.

Mobility and Bandwidth Prediction as a Service in Virtualized LTE Systems

Recently telecommunication industry benefits from infrastructure sharing, one of the most fundamental enablers of cloud computing, leading to emergence of the Mobile Virtual Network Operator (MVNO) concept. The most momentous intents by this approach are the support of on-demand provisioning and elasticity of virtualized mobile network components, based on data traffic load. To realize it, during operation and management procedures, the virtualized services need be triggered in order to scale-up/down or scale-out/in an instance. In this paper we propose an architecture called MOBaaS (Mobility and Bandwidth Availability Prediction as a Service), comprising two algorithms in order to predict user(s) mobility and network link bandwidth availability, that can be implemented in cloud based mobile network structure and can be used as a support service by any other virtualized mobile network services. MOBaaS can provide prediction information in order to generate required triggers for on-demand deploying, provisioning, disposing of virtualized network components. This information can be used for self-adaptation procedures and optimal network function configuration during run-time operation, as well. Through the preliminary experiments with the prototype implementation on the OpenStack platform, we evaluated and confirmed the feasibility and the effectiveness of the prediction algorithms and the proposed architecture.

Passive wireless sensor systems can recognize activites of daily living

The ability to determine what activity of daily living a person performs is of interest in many application domains. It is possible to determine the physical and cognitive capabilities of the elderly by inferring what activities they perform in their houses. Our primary aim was to establish a proof of concept that a wireless sensor system can monitor and record physical activity and these data can be modeled to predict activities of daily living. The secondary aim was to determine the optimal placement of the sensor boxes for detecting activities in a room. A wireless sensor system was set up in a laboratory kitchen. The ten healthy participants were requested to make tea following a defined sequence of tasks. Data were collected from the eight wireless sensor boxes placed in specific places in the test kitchen and analyzed to detect the sequences of tasks performed by the participants. These sequence of tasks were trained and tested using the Markov Model. Data analysis focused on the reliability of the system and the integrity of the collected data. The sequence of tasks were successfully recognized for all subjects and the averaged data pattern of tasks sequences between the subjects had a high correlation. Analysis of the data collected indicates that sensors placed in different locations are capable of recognizing activities, with the movement detection sensor contributing the most to detection of tasks. The central top of the room with no obstruction of view was considered to be the best location to record data for activity detection. Wireless sensor systems show much promise as easily deployable to monitor and recognize activities of daily living.

Binary recombinase systems for high-resolution conditional mutagenesis.

Conditional mutagenesis using Cre recombinase expressed from tissue specific promoters facilitates analyses of gene function and cell lineage tracing. Here, we describe two novel dual-promoter-driven conditional mutagenesis systems designed for greater accuracy and optimal efficiency of recombination. Co-Driver employs a recombinase cascade of Dre and Dre-respondent Cre, which processes loxP-flanked alleles only when both recombinases are expressed in a predetermined temporal sequence. This unique property makes Co-Driver ideal for sequential lineage tracing studies aimed at unraveling the relationships between cellular precursors and mature cell types. Co-InCre was designed for highly efficient intersectional conditional transgenesis. It relies on highly active trans-splicing inteins and promoters with simultaneous transcriptional activity to reconstitute Cre recombinase from two inactive precursor fragments. By generating native Cre, Co-InCre attains recombination rates that exceed all other binary SSR systems evaluated in this study. Both Co-Driver and Co-InCre significantly extend the utility of existing Cre-responsive alleles.

CHEOPS Performance for Exomoons: The Detectability of Exomoons by Using Optimal Decision Algorithm

Many attempts have already been made to detect exomoons around transiting exoplanets, but the first confirmed discovery is still pending. The experiences that have been gathered so far allow us to better optimize future space telescopes for this challenge already during the development phase. In this paper we focus on the forthcoming CHaraterising ExOPlanet Satellite (CHEOPS), describing an optimized decision algorithm with step-by-step evaluation, and calculating the number of required transits for an exomoon detection for various planet moon configurations that can be observable by CHEOPS. We explore the most efficient way for such an observation to minimize the cost in observing time. Our study is based on PTV observations (photocentric transit timing variation) in simulated CHEOPS data, but the recipe does not depend on the actual detection method, and it can be substituted with, e.g., the photodynamical method for later applications. Using the current state-of-the-art level simulation of CHEOPS data we analyzed transit observation sets for different star planet moon configurations and performed a bootstrap analysis to determine their detection statistics. We have found that the detection limit is around an Earth-sized moon. In the case of favorable spatial configurations, systems with at least a large moon and a Neptune-sized planet, an 80% detection chance requires at least 5-6 transit observations on average. There is also a nonzero chance in the case of smaller moons, but the detection statistics deteriorate rapidly, while the necessary transit measurements increase quickly. After the CoRoT and Kepler spacecrafts, CHEOPS will be the next dedicated space telescope that will observe exoplanetary transits and characterize systems with known Doppler-planets. Although it has a smaller aperture than Kepler (the ratio of the mirror diameters is about 1/3) and is mounted with a CCD that is similar to Kepler's, it will observe brighter stars and operate with larger sampling rate; therefore, the detection limit for an exomoon can be the same as or better, which will make CHEOPS a competitive instruments in the quest for exomoons.