IFN-Lambda (IFN-λ) Is Expressed in a Tissue-Dependent Fashion and Primarily Acts on Epithelial Cells In Vivo

Interferons (IFN) exert antiviral, immunomodulatory and cytostatic activities. IFN-α/β (type I IFN) and IFN-λ (type III IFN) bind distinct receptors, but regulate similar sets of genes and exhibit strikingly similar biological activities. We analyzed to what extent the IFN-α/β and IFN-λ systems overlap in vivo in terms of expression and response. We observed a certain degree of tissue specificity in the production of IFN-λ. In the brain, IFN-α/β was readily produced after infection with various RNA viruses, whereas expression of IFN-λ was low in this organ. In the liver, virus infection induced the expression of both IFN-α/β and IFN-λ genes. Plasmid electrotransfer-mediated in vivo expression of individual IFN genes allowed the tissue and cell specificities of the responses to systemic IFN-α/β and IFN-λ to be compared. The response to IFN-λ correlated with expression of the α subunit of the IFN-λ receptor (IL-28Rα). The IFN-λ response was prominent in the stomach, intestine and lungs, but very low in the central nervous system and spleen. At the cellular level, the response to IFN-λ in kidney and brain was restricted to epithelial cells. In contrast, the response to IFN-α/β was observed in various cell types in these organs, and was most prominent in endothelial cells. Thus, the IFN-λ system probably evolved to specifically protect epithelia. IFN-λ might contribute to the prevention of viral invasion through skin and mucosal surfaces

04201 Abstracts Collection -- Content Distribution Infrastructures

From 11.05.04 to 14.05.04, the Dagstuhl Seminar 04201 ``Content Distribution Infrastructures\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

A reconfigurable distributed CEP middleware for diverse mobility scenarios

Sensor nodes and complex event processing (CEP) are important and powerful means for gathering data and detecting phenomena of interest in mission-critical pervasive systems, e.g. for emergency and rescue operations. However, the dynamic network does not allow using centralized CEP. To address this issue, we present a component-based distributed CEP middleware. Its main goal is easy reconfigurability to different mobility scenarios. This is achieved by providing an extensible collection of algorithms that are tailored for specific scenarios. The middleware makes it possible to select on demand the algorithms that are most suitable for the current scenario. Our evaluation shows that the middleware works in a broad spectrum of mobility scenarios. We also investigate the trade-off between efficiency and reliability of distributed CEP. Copyright 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

04201 Summary -- Content Distribution Infrastructures

We provide a summary of the Dagstuhl workshop on content distribution infrastructures. The presentations and group discussions of the workshop are summarized in context, and visionary and outrageous opinions of the workshop participants are described

DCEP-Sim: An Open Simulation Framework for Distributed CEP: Introduction for Users and Prospective Developers

Evaluation of Distributed Complex Event Processing (CEP) systems is a rather challenging task. To simplify this task, we developed the open simulation framework for Distributed CEP, called DCEP-Sim. The goal of this tutorial is to facilitate the process of using DCEP-Sim. Since DCEP-Sim is designed and implemented in the popular network simulator ns-3 we introduce the most important concepts of ns-3. Simulations in ns-3 are configured and executed though a main program called an ns-3 script. We use a simple example script to explain how simulations with DCEP-Sim are set up and executed. To give an idea how DCEP-Sim can be adjusted to particular needs, we explain how DCEP-Sim can be adapted (e.g., through changing the workload and the network topology) and how new Distributed CEP solutions can be added by explaining how to add a new operator to DCEP-Sim

DCEP-Sim: An Open Simulation Framework for Distributed CEP

Distributed Complex Event Processing (CEP) is gaining increasing interest for two reasons: (1) to scale system performance to handle higher workloads in real-time, and (2) to perform in-network processing, e.g., in mobile networks to reduce the amount of data that has to be transferred through the network. System scalability and the complexity of mobile systems are some of the major challenges when evaluating the performance of new Distributed CEP solutions. We propose an open framework for distributed CEP (DCEP-Sim) built on a well-established network simulator, i.e, ns3. e design of DCEP-Sim is based on the engineering principles of separation of concerns and the separation of mechanisms and policies. By leveraging the ns-3 feature of object aggregation it is very easy to add new policies, e.g., placement or selection policies, and evaluate them without changing anything else in the DCEPSim. e fact that ns-3 includes many accurate network models implies that Distributed CEP simulation with DCEP-Sim will also be much more accurate than ad-hoc handcra ed simulations. We demonstrate in a use case how easy it is to con gure performance evaluation experiments and we perform experiments to con rm that the integration of the Distributed CEP in ns-3 is good foundation for large-scale experiments. e evaluation results demonstrate that DCEP-Sim substantially reduces the e ort and costs of Distributed CEP evaluation

Quantifying the Signal Quality of Low-cost Respiratory Effort Sensors for Sleep Apnea Monitoring

Obstructive Sleep Apnea (OSA) is a common, but severely under- diagnosed sleep disorder characterized by recurring periods of shallow or paused breathing during sleep. It is our long-term goal to allow people to perform the first step towards a sleep apnea de- tection at home by utilizing smartphones, low-cost consumer-grade sensors, and data mining techniques. In this work, we evaluate the signal quality of four respiratory effort sensors (BITalino, FLOW, RespiBAN, and Shimmer), using a RIP sensor from NOX Medical as the gold standard. We design a sixteen-minute signal capture procedure to simulate epochs of disrupted breathing, and capture data from twelve (BITalino and Shimmer) and eleven (RespiBAN and FLOW) subjects during wakefulness. Our signal quality eval- uation approach is based on the breath detection accuracy met- rics sensitivity and positive predictive value (PPV), along with the breath amplitude accuracy metric weighted absolute percentage er- ror (WAPE). These metrics are closely related to how apneic and hypopneic episodes are scored by medical personnel, making it straightforward to reason about their interpretation. Our results show that false breaths are the primary concern affecting the breath detection accuracy of BITalino, Shimmer, and RespiBAN. Respec- tively, the sensitivity of BITalino, Shimmer, RespiBAN, and FLOW is 99.61%, 98.53%, 98.41%, and 98.91%. Their PPV is 96.28%, 96.58%, 90.81%, and 98.81%. Finally, their WAPE is 13.82%, 16.89%, 13.60%, and 8.75%. The supine (back) position is consistently showing the overall best signal quality compared to the side position

An Activity Rule Based Approach to Simulate ADL Sequences

© 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. The concept of activities of daily living (ADL) has for many years successfully been used in a broad range of health and health care applications. Recent hardware and software developments suggest that the future use of ADL will not only benefit from the transition from manually created ADL logs to automatic sensor-based activity recognition and logging but also from the transition from manual inspection of ADL sequences to their automatic software-driven analysis. This ADL sequence analysis software will be core part in mission critical systems, like ambient assisted living, to detect for example changing health status. Therefore, proper testing and evaluation of this software is mandatory before its deployment. However, testing requires data sets that include normal ADL sequences, hazards, and various kinds of long term behavioral changes; which means it might require weeks or even months to monitor individuals to capture such ADL sequences. Thus, collecting such data sets is very costly, if feasible at all; and very few data sets are available on-line. Therefore, we present an approach to create the necessary data sets for testing through simulation. The simulation of ADL sequences is based on existing ADL sequences and uses probabilistic activity instigation and durations with a novel concept called activity rules to create data sets for proper testing. Activity rules are used to model how individuals resolve activity conflicts. We implemented these concepts as a discrete event simulator, called ADLSim. The evaluation of ADLsim shows that the simulated ADL sequences are realistic and able to capture the variability and non-predictable behavior found in the real world, and that activity rules can impact simulation results significantly

Event Modeling and Processing to Simplify Real-Time Analysis of Physiological Signals

Recent developments in wireless sensors to measure physiological parameters and environmental parameters enable a new generation of applications for health monitoring. However, the complexity of many physiological signals and the need to process sensor data in real-time makes programming such applications a challenging task. This chapter motivates the need to step-wise reduce the complexity of sensor data to enable medical experts to tailor and develop (parts of) applications without having in depth programming skills. To achieve this goal, a methodology for application development with real-time sensor data processing is presented. The methodology is based on the concepts of physical and logical sensors, which can detect atomic and composite events. The combination of using the declarative approach of Complex Event Processing and modularization allows processing most data in the event space instead of signal processing. A use case for a home care application demonstrates the strength of this methodology