An architecture for using commodity devices and smart phones in health systems

The potential of patient-centred care and a connected eHealth ecosystem can be developed through socially responsible innovative architectures. The purpose of this paper is to define key innovation needs. This is achieved through conceptual development of an architecture for common information spaces with emergent end-user applications by supporting intelligent processing of measurements, data and services at the Internet of Things (IoT) integration level. The scope is conceptual definition, and results include descriptions of social, legal and ethical requirements, an architecture, services and connectivity infrastructures for consumer-oriented healthcare systems linking co-existing healthcare systems and consumer devices. We conclude with recommendations based on an analysis of research challenges related to how to process the data securely and anonymously and how to interconnect participants and services with different standards and interaction protocols, and devices with heterogeneous hardware and software configurations

Surgery for colorectal liver metastases: the impact of resection margins on recurrence and overall survival

Background: Several reports have presented conflicting results regarding the association between resection margins (RMs) and outcome after surgery for colorectal liver metastases (CLM), especially in the era of modern chemotherapy. The purpose of this study was to evaluate the impact of RMs on overall survival (OS), time to recurrence (TTR) and local recurrence (LR) status, particularly for patients treated with preoperative chemotherapy. Methods: A combined retrospective (1998 to 2008) and prospective (2008 to 2010) cohort study of consecutive patients with CLM without extrahepatic disease treated with primary resection at a medium volume centre. Results: A total of 253 patients with known R status and 242 patients with defined margin width were included in the study. Patients were stratified according to margin width; A: R1, <1 mm (n = 48, 19%), B: 1 to 4 mm (n = 77), C: 5 to 9 mm (n = 46) and D: ≥10 mm (n = 71). Median time to recurrence was 12.8 months, and after five years 21.5% had no recurrence. LR (inclusive combined recurrence in other hepatic sites or extrahepatic) occurred in 40 (16.5%) cases, most frequently seen with RMs below 5 mm. Five-year OS was 42.5% in R0 and 16.1% in R1 resections (P = 0.011). Patients were also stratified according to preoperative chemotherapy (n = 88), and the difference in five-year OS between R0 (45.1%) and R1 (14.7%) was maintained (P = 0.037). By multiple Cox regression analysis R1 resections tended to an adverse outcome (P = 0.067), also when adjusting for preoperative chemotherapy (P = 0.081). Conclusions: R1 resections for colorectal liver metastases predict adverse outcome. RMs below 5 mm increased the risk for LR and shortened the time to recurrence. Preoperative chemotherapy did not alter an adverse outcome in R1 vs. R0 patients

Expression and production of thermophilic alginate lyases in Bacillus and direct application of culture supernatant for seaweed saccharification

Brown seaweeds are rich in carbohydrates and may be used as a source of fermentable sugars. Saccharification of the seaweed biomass can be carried out enzymatically by a combination of cellulases and alginate lyases. In this study, thermotolerant exo- and endo alginate lyases were cloned and expressed in Bacillus subtilis. The lyases were secreted to the culture supernatant and used directly together with a commercial cellulase preparation to saccharify Saccharina latissima biomass. The results showed that the strategy of using the culture supernatants directly as a source of alginate lyases worked very well, releasing glucose, mannitol, and uronic acids. The ratio between the exo- and endo-acting alginate lyases proved to be very important for saccharification yield, and under optimal reaction conditions the use of culture supernatants containing alginate lyases improved final glucose concentration by 73%, when compared to only applying cellulases. This direct use of culture supernatants as a source of alginate lyases shows that enzyme purification steps are not needed, saving seaweed processing costs and points to the possibility of a relatively simple on-site enzyme production for seaweed biorefining.publishedVersio

An application of a game of discrete generalised pursuit automata to solve a multi-constraint partitioning problem

This paper presents a Learning Automaton (LA) solution to the Multi-Constrained Mapping problem, which has its applications in the allocation of processes on processors so as to satisfy multiple (possibly conflicting) constraints. Mathematically, it considers the problem of partitioning a set of elements (or objects) into mutually exclusive classes (or groups), where elements which are "similar" to each other are, hopefully, located in the same class. This problem has been shown to be NP-Hard, and the literature reports solutions in which the similarity constraint consists of a single index. For example, typical "similarity" conditions that have been used in the literature include those in which "similar" objects are accessed together (as in the context of query systems), or when they communicate (as processes do) with each other. The application at hand is the Static Mapping Problem (SMP) of distributing the processes of a parallel application onto a set of computing nodes. Such an application may run on multiple GRID sites where it is desirable avoid centralised control and mapping. This paper proposes a solution to this combinatorial optimization problem resulting from the collective behaviour of independent Discrete General Pursuit Automata (DGPA) that tries to learn the digraph of the communication among the processes of the application, and group together processes with strong mutual dependencies. Earlier learning solutions to the problem were either based on centralised mapping with full system knowledge. In this paper, we attempt to relax this assumptions, thus rendering the problem more complex. The present solution performs very well when the system size is small. However, the simulated results demonstrate that the quality of the final solution decreases with the number of elements. Thus, although this is the first reported solution to the problem which incorporates the specific digraph properties of the objects, the scalability of the solution remains open