Screening for congenital cytomegalovirus infection using newborn urine samples collected on filter paper: feasibility and outcomes from a multicentre study

PublisherBackground As congenital cytomegalovirus (CMV) infection causes significant clinical consequences not only at birth but also later as neurological sequelae, it is critical to establish a strategy for screening congenitally infected newborns. Previous studies have identified an insufficient sensitivity in screening methods based on the use of dried blood spots (DBSs). Objectives To evaluate the feasibility of the authors' recently developed method for large-scale screening for congenital CMV infection and to identify risk factors for congenital infection. Methods More than 21 000 newborns were enrolled at 25 sites in six geographically separate areas of Japan. Urine was collected onto filter cards placed in the diapers, which were then analysed by quantitative PCR using the filter disc directly as a template. Clinical and physical findings of the newborns were extracted from their medical records. CMV strains from the cases and their siblings were genetically compared. Viral loads in DBSs obtained from some of the cases were compared with those in the urine filters. Results Congenital CMV infection was identified in 0.31% (95% CI 0.24% to 0.39%) of the newborns, and 30% of the cases (20/66) had typical clinical manifestations and/or showed abnormalities in brain images at birth. Although the positive predictive value of our screening was 94%, the lack of any comparison with a gold standard assay prevented calculation of the negative predictive value. Almost two-thirds of the cases had siblings, a significantly higher frequency than for uninfected newborns. Most of the cases (21/25) excreted CMV strains identical to those of their siblings. CMV DNA was undetectable in three out of 12 retrievable DBS specimens. Conclusions Implementation of an effective large-scale screening programme for congenital CMV infection is feasible. Siblings are the major risk factor for congenital CMV infection, which emphasises the need for education of mothers-to-be as well as vaccine development

Meaningful Conversation with a Mobile Robot

We describe an implementation integrating a spoken dialogue system with a mobile robot, which the user can direct to specific locations, ask for information about its status, and supply information about its environment. The robot uses an internal map for navigation, and communicates its current orientation and accessible locations to the dialogue system using a topological map as interface

Programming Environments for Developing Real Time Autonomous Agents based on a Functional Module Network Model

In this paper, we present programming environments for developing real time autonomous agents on multi-processor systems based on a hardware independent description model. BeNet, our model is a network of functional modules that calculate elements of the internal representation of the agent in real time with their own frequencies. A system that interacts with a dynamical environment is described completely as a BeNet, because it consists of real time computational modules. An autonomous agent can be described much more easily as a BeNet than a common parallel program and its behavior will be much easier to understand if it is described in an appropriate language. Since a BeNet is a parallel system and the description is not specific to any hardware, it is possible to realize environments for programming BeNets in generic object oriented programming languages on various multiprocessor systems. We implemented environments in which the developer can program a BeNet in languages such as C++ and test its behavior immediately on a multi-processor system. In our environments, the developer only needs to describe components as sequential programs, determine their intervals and connect the components in a simplified manner. The internal data structures and procedures for calculation of the agent are described, by defining classes with appropriate slots and methods. It makes it to possible to design real time agents on an abstract level. The realized environments will be of great benefit to designers and researchers of real time agents and autonomous robots.

An Inference-based Approach to Dialogue System Design

We present an architecture for spoken dialogue systems where first-order inference (both theorem proving and model building) plays a crucial role in interpreting utterances of dialogue participants and deciding how the system should respond and carry out instructions. The dialogue itself is represented as a DRS which is translated into first-order logic for inference tasks. The system is implemented as a society of OAA-agents, and evaluated against a specific application (home automation)

DIPPER: Description and Formalisation of an Information-State Update Dialogue System Architecture

The DIPPER architecture is a collection of software agents for prototyping spoken dialogue systems. Implemented on top of the Open Agent Architecture (OAA), it comprises agents for speech input and output, dialogue management, and further supporting agents. We define a formal syntax and semantics for the DIPPER information state update language. The language is independent..