SummaryMetagenomic studies use high-throughput sequence data to investigate microbial communities in situ. However, considerable challenges remain in the analysis of these data, particularly with regard to speed and reliable analysis of microbial species as opposed to higher level taxa such as phyla. We here present Genometa, a computationally undemanding graphical user interface program that enables identification of bacterial species and gene content from datasets generated by inexpensive high-throughput short read sequencing technologies. Our approach was first verified on two simulated metagenomic short read datasets, detecting 100% and 94% of the bacterial species included with few false positives or false negatives. Subsequent comparative benchmarking analysis against three popular metagenomic algorithms on an Illumina human gut dataset revealed Genometa to attribute the most reads to bacteria at species level (i.e. including all strains of that species) and demonstrate similar or better accuracy than the other programs. Lastly, speed was demonstrated to be many times that of BLAST due to the use of modern short read aligners. Our method is highly accurate if bacteria in the sample are represented by genomes in the reference sequence but cannot find species absent from the reference. This method is one of the most user-friendly and resource efficient approaches and is thus feasible for rapidly analysing millions of short reads on a personal computer.AvailabilityThe Genometa program, a step by step tutorial and Java source code are freely available from http://genomics1.mh-hannover.de/genometa/ and on http://code.google.com/p/genometa/. This program has been tested on Ubuntu Linux and Windows XP/7.

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There are several previously published approaches of measuring local pulse transit time (PTT). One of these approaches is to use two optical sensors based on photoplethysmography (PPG). However, little information about reproducibility in PPG based PTT measurement is available. Therefore, we performed a small sample size study (n = 5) to investigate quantitative criteria for reproducible PTT measurement. The inflection point as a characteristic feature of the pulse wave showed the most stabile results under varying conditions. Furthermore, we found that correlation between related pulse waves could be used as a threshold for signal quality. We suggest to implement a real-time operator feedback based on the found criteria to ensure reproducible PTT measurements.

In this paper, we describe the development of a behavior change support system to improve health. The system is designed for people in the age range of 50–65 with an interdisciplinary approach. The basic structure of the presented system consists of two main modules: a monitoring module to collect and analyze data and an intervention module to support behavior changes. Based on the results of a requirements analysis and findings gathered from a conducted literature review and own analyses, the behavior change system addresses the following lifestyle areas: physical activity, nutrition, mental fitness, sleep, and nature contact. We outline how the concept is developed with regards to the results of the requirements analysis and psychological foundations to explain and predict motivation and behavior change processes. We describe how single system components match phases of behavior change models and how they were implemented into an Android application. Finally, we present the results of usability studies where the comprehensibility of the concept and application was tested together with the usability of navigation structure and design. The results show that the target group is able to understand the concept and can navigate through the system easily.