Towards a framework for comparing functionalities of multimorbidity clinical decision support: A literature-based feature set and benchmark cases.

Multimorbidity, the coexistence of two or more health conditions, has become more prevalent as mortality rates in many countries have declined and their populations have aged. Multimorbidity presents significant difficulties for Clinical Decision Support Systems (CDSS), particularly in cases where recommendations from relevant clinical guidelines offer conflicting advice. A number of research groups are developing computer-interpretable guideline (CIG) modeling formalisms that integrate recommendations from multiple Clinical Practice Guidelines (CPGs) for knowledge-based multimorbidity decision support. In this paper we describe work towards the development of a framework for comparing the different approaches to multimorbidity CIG-based clinical decision support (MGCDS). We present (1) a set of features for MGCDS, which were derived using a literature review and evaluated by physicians using a survey, and (2) a set of benchmarking case studies, which illustrate the clinical application of these features. This work represents the first necessary step in a broader research program aimed at the development of a benchmark framework that allows for standardized and comparable MGCDS evaluations, which will facilitate the assessment of functionalities of MGCDS, as well as highlight important gaps in the state-of-the-art. We also outline our future work on developing the framework, specifically, (3) a standard for reporting MGCDS solutions for the benchmark case studies, and (4) criteria for evaluating these MGCDS solutions. We plan to conduct a large-scale comparison study of existing MGCDS based on the comparative framework

LONG TRANSPORT CHAINS: EXPORTING FROM A PERIPHERAL ISLAND

The crucial dependence on intermodal transport of an open island economy, where almost all external trade passes through the seaports, is examined. The rapid growth of the Irish economy puts great strains on the transport supply chains, particularly in the vicinity of the principal seaport in Dublin, where major congestion occurs. This adversely affects the competitiveness of small and medium-sized exporting companies. Increasing prosperity has resulted in an explosion in the numbers of private cars, which puts great strain on an inadequate internal infrastructure. A review of Irish ports confirms that congestion on the access routes to the Dublin port is the major bottleneck in the long transport chains for exporters. Relief from the freight traffic transiting the city center must await the completion of a dedicated port access tunnel, and interim solutions are needed. In the case of food exporters, globalization, the power of the retail conglomerates, and peripheral location demand a high level of supply chain efficiencies. A survey of export transport chains for selected products shows that transit costs can be a significant proportion of the total consignment value. At the level of the indigenous companies, supply chain management capabilities are shown to be below an acceptable standard in two-thirds of the firms surveyed. Possible solutions for facilitation of freight access in the vicinity of the port and for introduction of more sustainable solutions for goods deliveries in the historic city center are explored. Measures that can be taken to improve the logistics management capabilities in companies are also described

Real-time implicit bulging and area preservation

Implicit Surfaces are particularly suitable for the animation of deformable objects, although some problems still remain, especially in real time applications. One problem is that of volume loss when objects are squashed. This paper presents a real time solution for the preservation of volume using dynamic creation of primitives in two dimensions. We also look at the unwanted blending problem and propose a more efficient solution

The 2nd International Conference on Distributed Event-Based Systems

This paper defines and discusses the implementation of two novel extensions to the Siena Content-based Network (CBN) to extend it to become a Knowledge-based Network (KBN) thereby increasing the expressiveness and flexibility of its publications and subscription. One extension provides ontological concepts as an additional message attribute type, onto which subsumption relationships, equivalence, type queries and arbitrary ontological subscription filters can be applied. The second extension provides for a bag type to be used that allows bag equivalence, sub-bag and super-bag relationships to be used in subscription filters, possibly composed with any of the Siena subscription operators or the ontological operators previously mentioned. The performance of this KBN implementation has also been explored. However, to maintain scalability and performance it is important that these extensions do not break Siena?s subscription aggregation algorithm. We also introduce the necessary covering relationships for the new types and operators and examine the subscription matching overhead resulting from these new types and operators

Handbook of Research on Advanced Distributed Event-Based Systems, Publish-Subscribe and Message Filtering Technologies (Principles and Applications of Distributed Event-Based Systems)

Knowledge-Based Networking, which is built on-top of Content-based Networking (CBN), involves the forwarding of events across a network of brokers based on subscription filters applied to some semantics of the data and associated metadata of the events contents. Knowledge-based Networks (KBN) therefore support the efficient filtered dissemination of semantically enriched knowledge over a large, loosely coupled network of distributed heterogeneous agents. This is achieved by incorporating ontological semantics into event messages, allowing subscribers to define semantic filters, and providing a subscription brokering and routing mechanism. The KBN used for this work provides ontological concepts as an additional message attribute type, onto which subsumption relationships, equivalence, type queries and arbitrary ontological relationships can be applied. It also provides a bag type to be used that supports bags equivalence, sub-bag and super-bag relationships to be used in subscription filters, composed with traditional CBN subscription operators or the ontological operators. When combined with the benefits of Content?based Networking, this allows subscribers to easily express meaningful subscription interests and receive results in a more expressive and flexible distributed event system than heretofore. Within this chapter the detailed analysis of ontological operators and their application to a publish/subscribe (pub/sub) domain will be fully explored and evaluated

A Collagen Cardiac Patch Incorporating Alginate Microparticles Permits the Controlled Release of HGF and IGF-1 to Enhance Cardiac Stem Cell Migration and Proliferation

A major weakness in existing therapies for myocardial infarction is their inability to regenerate the resulting damaged cardiac muscle. Thus, the goal of current experimental strategies is finding the means for attenuation of the progressive processes leading to tissue destruction, while inducing myocardial tissue regeneration (1, 2).Regenerative cardiology’s Holy Grail has been the development of procedures to either replace lost myocytes with transplanted stem cells or to use stem cells to mediate functional repair through paracrine effects (3-6). The most primitive undifferentiated population of stem cells in the heart, the c-KitPOS Cardiac Stem Cell (CSC) pool which was the first stem cell identified in the rat heart and, up to date, this CSC pool is still the most extensively characterised (7, 8). CSCs are a heterogenic group of cells and they are concentrated in specific areas of the heart, such as the atria or pericardium (9). They represent a logical source to exploit in myocardial regeneration because of their likelihood to be intrinsically programmed to generate viable cardiac tissues in vitro and increase its viability in vivo (10-13). The ideal replacement for the lost myocardium after myocardial infarction is functional autologous myocardial tissue, which can bypass issues around immunosuppression associated with allogenic therapies (14). However, as presently practiced, the isolation and expansion of endogenous cardiac stem cells (eCSCs) for autologous cell transplantation is slow and expensive. In addition, endomyocardial biopsies are difficult to attain (12, 15). Thus, there is need for strategies to specifically activate in situ the intrinsic cardiac regenerative potential represented by the eCSCs using combinations of growth factors, cytokines and drugs, obviating the need for cell transplantation (15, 16). As presently practiced, the isolation and expansion of CSCs for autologous cell transplantation is slow, expensive and difficult to attain. Thus, there is need for strategies to specifically activate in situ the intrinsic cardiac regenerative potential represented by the CSCs using combinations of growth factors obviating the need for cell transplantation. By favouring the natural regenerative capability of CSCs, it is hypothesised that the cardiac patch presented here will result in positive therapeutic outcomes in myocardial infarction and heart failure patients in the future

Biomaterial-enhanced cell and drug delivery: lessons learned in the cardiac field and future perspectives

Heart failure is a significant clinical issue. It is the cause of enormous healthcare costs worldwide and results in significant morbidity and mortality. Cardiac regenerative therapy has progressed considerably from clinical and preclinical studies delivering simple suspensions of cells, macromolecule, and small molecules to more advanced delivery methods utilizing biomaterial scaffolds as depots for localized targeted delivery to the damaged and ischemic myocardium. Here, regenerative strategies for cardiac tissue engineering with a focus on advanced delivery strategies and the use of multimodal therapeutic strategies are reviewed

Expanding the biotechnology potential of lactobacilli through comparative genomics of 213 strains and associated genera

Lactobacilli are a diverse group of species that occupy diverse nutrient-rich niches associated with humans, animals, plants and food. They are used widely in biotechnology and food preservation, and are being explored as therapeutics. Exploiting lactobacilli has been complicated by metabolic diversity, unclear species identity and uncertain relationships between them and other commercially important lactic acid bacteria. The capacity for biotransformations catalysed by lactobacilli is an untapped biotechnology resource. Here we report the genome sequences of 213 Lactobacillus strains and associated genera, and their encoded genetic catalogue for modifying carbohydrates and proteins. In addition, we describe broad and diverse presence of novel CRISPR-Cas immune systems in lactobacilli that may be exploited for genome editing. We rationalize the phylogenomic distribution of host interaction factors and bacteriocins that affect their natural and industrial environments, and mechanisms to withstand stress during technological processes. We present a robust phylogenomic framework of existing species and for classifying new species.PUBLISHEDpeer-reviewe