Autonomous systems and artificial intelligence – Hype or prerequisite for P5 medicine?

For meeting the challenge of aging, multi-diseased societies, cost containment, workforce development and consumerism by improved care quality and patient safety as well as more effective and efficient care processes, health and social care systems around the globe undergo an organizational, methodological and technological transformation towards personalized, preventive, predictive, participative precision medicine (P5 medicine). This paper addresses chances, challenges and risks of specific disruptive methodologies and technologies for the transformation of health and social care systems, especially focusing on the deployment of intelligent and autonomous systems

Trust Model for Protection of Personal Health Data in a Global Environment

Successful health care, eHealth, digital health, and personal health systems increasingly take place in cross-jurisdictional, dynamic and risk-encumbered information space. They require rich amount of personal health information (PHI). Trust is and will be the cornerstone and prerequisite for successful health services. In global environments, trust cannot be expected as granted. In this paper, health service in the global environment is perceived as a meta-system, and a trust management model is developed to support it. The predefined trusting belief currently used in health care is not transferable to global environments. In the authors' model, the level of trust is dynamically calculated from measurable attributes. These attributes describe trust features of the service provider and its environment. The calculated trust value or profile can be used in defining the risk service user has to accept when disclosing PHI, and in definition of additional privacy and security safeguards before disclosing PHI and/or using services

The SaPPART COST Action: Towards Positioning Integrity for Road Transport

Global Navigation Satellite Systems (GNSS) is becoming one of the main components supporting Intelligent Transport Systems (ITS) and value-added services in road transport and personal mobility. The use of GNSS is expected to grow significantly due to improvements in positioning performance, with positive impacts such as: finding the optimal route; improving traffic and travel efficiency as well as safety and security; reducing congestion and optimizing fuel consumption. The deployment of mission critical applications needs high reliability in the positioning information. However, the positioning reliability is not easy to achieve because of the heterogeneous quality of the GNSS signal, which is highly influenced by the road environment and the operational scenario of the application. It is important to understand the requirements and performance GNSS can achieve for various road transport applications. This paper is presenting the SaPPART COST Action on the Satellite Positioning Performance Assessment for Road Transport. It introduces the goal and the framework of the Action with the research programme and some related activities dedicated to dissemination and supporting standardisation working groups

Data Modeling Challenges of Advanced Interoperability

Progressive health paradigms, involving many different disciplines and combining multiple policy domains, requires advanced interoperability solutions. This results in special challenges for modeling health systems. The paper discusses classification systems for data models and enterprise business architectures and compares them with the ISO Reference Architecture. On that basis, existing definitions, specifications and standards of data models for interoperability are evaluated and their limitations are discussed. Amendments to correctly use those models and to better meet the aforementioned challenges are offered

Shape coexistence at the proton drip-line: First identification of excited states in 180Pb

Excited states in the extremely neutron-deficient nucleus, 180Pb, have been identified for the first time using the JUROGAM II array in conjunction with the RITU recoil separator at the Accelerator Laboratory of the University of Jyvaskyla. This study lies at the limit of what is presently achievable with in-beam spectroscopy, with an estimated cross-section of only 10 nb for the 92Mo(90Zr,2n)180Pb reaction. A continuation of the trend observed in 182Pb and 184Pb is seen, where the prolate minimum continues to rise beyond the N=104 mid-shell with respect to the spherical ground state. Beyond mean-field calculations are in reasonable correspondence with the trends deduced from experiment.Comment: 5 pages, 4 figures, submitted to Phys.Rev.

Beta-Lactam Sensitive Bacteria Can Acquire ESBL-Resistance via Conjugation after Long-Term Exposure to Lethal Antibiotic Concentration

Beta-lactams are commonly used antibiotics that prevent cell-wall biosynthesis. Beta-lactam sensitive bacteria can acquire conjugative resistance elements and hence become resistant even after being exposed to lethal (above minimum inhibitory) antibiotic concentrations. Here we show that neither the length of antibiotic exposure (1 to 16 h) nor the beta-lactam type (penam or cephem) have a major impact on the rescue of sensitive bacteria. We demonstrate that an evolutionary rescue can occur between different clinically relevant bacterial species (Klebsiella pneumoniae and Escherichia coli) by plasmids that are commonly associated with extended-spectrum beta-lactamase (ESBL) positive hospital isolates. As such, it is possible that this resistance dynamic may play a role in failing antibiotic therapies in those cases where resistant bacteria may readily migrate into the proximity of sensitive pathogens. Furthermore, we engineered a Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) -plasmid to encode a guiding CRISPR-RNA against the migrating ESBL-plasmid. By introducing this plasmid into the sensitive bacterium, the frequency of the evolutionarily rescued bacteria decreased by several orders of magnitude. As such, engineering pathogens during antibiotic treatment may provide ways to prevent ESBL-plasmid dispersal and hence resistance evolution

First observation of excited states in 173Hg

The neutron-deficient nucleus 173Hg has been studied following fusion-evaporation reactions. The observation of gamma rays decaying from excited states are reported for the first time and a tentative level scheme is proposed. The proposed level scheme is discussed within the context of the systematics of neighbouring neutron-deficient Hg nuclei. In addition to the gamma-ray spectroscopy, the alpha decay of this nucleus has been measured yielding superior precision to earlier measurements.Comment: 5 pages, 4 figure

Segmentation of Striatal Brain Structures from High Resolution PET Images

We propose and evaluate an automatic segmentation method for extracting striatal brain structures (caudate, putamen, and ventral striatum) from parametric 11C-raclopride positron emission tomography (PET) brain images. We focus on the images acquired using a novel brain dedicated high-resolution (HRRT) PET scanner. The segmentation method first extracts the striatum using a deformable surface model and then divides the striatum into its substructures based on a graph partitioning algorithm. The weighted kernel k-means algorithm is used to partition the graph describing the voxel affinities within the striatum into the desired number of clusters. The method was experimentally validated with synthetic and real image data. The experiments showed that our method was able to automatically extract caudate, ventral striatum, and putamen from the images. Moreover, the putamen could be subdivided into anterior and posterior parts. An automatic method for the extraction of striatal structures from high-resolution PET images allows for inexpensive and reproducible extraction of the quantitative information from these images necessary in brain research and drug development