Investigation of the impact of feeding Lactobacillus plantarum CRL 1815 encapsulated in microbially derived polymers on the rat faecal microbiota

AIMS: The aim of this study was to evaluate the impact of the administration of microencapsulated Lactobacillus plantarum CRL 1815 with two combinations of microbially derived polysaccharides, xanthan : gellan gum (1%:0·75%) and jamilan : gellan gum (1%:1%), on the rat faecal microbiota. METHODS AND RESULTS: A 10-day feeding study was performed for each polymer combination in groups of 16 rats fed either with placebo capsules, free or encapsulated Lact. plantarum or water. The composition of the faecal microbiota was analysed by fluorescence in situ hybridization and temporal temperature gradient gel electrophoresis. Degradation of placebo capsules was detected, with increased levels of polysaccharide-degrading bacteria. Xanthan : gellan gum capsules were shown to reduce the Bifidobacterium population and increase the Clostridium histolyticum group levels, but not jamilan : gellan gum capsules. Only after administration of jamilan : gellan gum-probiotic capsules was detected a significant increase in Lactobacillus-Enterococcus group levels compared to controls (capsules and probiotic) as well as two bands were identified as Lact. plantarum in two profiles of ileum samples. CONCLUSIONS: Exopolysaccharides constitute an interesting approach for colon-targeted delivery of probiotics, where jamilan : gellan gum capsules present better biocompatibility and promising results as a probiotic carrier. SIGNIFICANCE AND IMPACT OF STUDY: This study introduces and highlights the importance of biological compatibility in the encapsulating material election, as they can modulate the gut microbiota by themselves, and the use of bacterial exopolysaccharides as a powerful source of new targeted-delivery coating material.

Enabling Scientific Workflow Sharing through Coarse-Grained Interoperability

E-scientists want to run their scientific experiments on Distributed Computing Infrastructures (DCI) to be able to access large pools of resources and services. To run experiments on these infrastructures requires specific expertise that e-scientists may not have. Workflows can hide resources and services as a virtualization layer providing a user interface that e-scientists can use. There are many workflow systems used by research communities but they are not interoperable. To learn a workflow system and create workflows in this workflow system may require significant efforts from e-scientists. Considering these efforts it is not reasonable to expect that research communities will learn new workflow systems if they want to run workflows developed in other workflow systems. The solution is to create workflow interoperability solutions to allow workflow sharing. The FP7 Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs (SHIWA) project developed two interoperability solutions to support workflow sharing: Coarse-Grained Interoperability (CGI) and Fine-Grained Interoperability (FGI). The project created the SHIWA Simulation Platform (SSP) to implement the Coarse-Grained Interoperability approach as a production-level service for research communities. The paper describes the CGI approach and how it enables sharing and combining existing workflows into complex applications and run them on Distributed Computing Infrastructures. The paper also outlines the architecture, components and usage scenarios of the simulation platform.

Analyzing and Modeling Medical Data on Distributed Computing Infrastructures

Researchers want to analyse Health Care data which may requires large pools of compute and data resources. To have them they need access to Distributed Computing Infrastructures (DCI). To use them it requires expertise which researchers may not have. Workflows can hide infrastructures. There are many workflow systems but they are not interoperable. To learn a workflow system and create workflows in a workflow system may require significant effort. Considering these efforts it is not reasonable to expect that researchers will learn new workflow systems if they want to run workflows of other workflow systems. As a result, the lack of interoperability prevents workflow sharing and a vast amount of research efforts is wasted. The FP7 Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs (SHIWA) project developed the Coarse-Grained Interoperability (CGI) to enable workflow sharing. The project created the SHIWA Simulation Platform (SSP) to support CGI as a production-level service. The paper describes how the CGI approach can be used for analysis and simulation in Health Care.