In vivo and in vitro tracking of erosion in biodegradable materials using non-invasive fluorescence imaging

Author Manuscript 2012 March 1.The design of erodible biomaterials relies on the ability to program the in vivo retention time, which necessitates real-time monitoring of erosion. However, in vivo performance cannot always be predicted by traditional determination of in vitro erosion[superscript 1, 2] , and standard methods sacrifice samples or animals[superscript 3], preventing sequential measures of the same specimen. We harnessed non-invasive fluorescence imaging to sequentially follow in vivo material-mass loss to model the degradation of materials hydrolytically (PEG:dextran hydrogel) and enzymatically (collagen). Hydrogel erosion rates in vivo and in vitro correlated, enabling the prediction of in vivo erosion of new material formulations from in vitro data. Collagen in vivo erosion was used to infer physiologic in vitro conditions that mimic erosive in vivo environments. This approach enables rapid in vitro screening of materials, and can be extended to simultaneously determine drug release and material erosion from a drug-eluting scaffold, or cell viability and material fate in tissue-engineering formulations.National Institutes of Health (U.S.) (GM/HL 49039)National Institutes of Health (U.S.) (UL1 RR 025758

A Systematic Literature Review of the Relationships Between Policy Analysis and Information Technologies: Understanding and Integrating Multiple Conceptualizations

Part 3: Policy Modeling and Policy InformaticsInternational audienceResearchers and practitioners are increasingly aware of changes in the environment, broadly defined, that affect the policy process and the current capabilities for policy analysis. Examples of these changes are emergent information technologies, big and interconnected data, and the availability of computational power to perform analysis at a very disaggregate level. These and other forces have the potential to significantly change multiple stages of the policy process, from design to implementation and evaluation. The emergence of this phenomenon has led to the use of a variety of labels to define it. Potentially, a variety of labels might contribute to some conceptual confusion, but most importantly to concept stretching. This article aims to provide a conceptual space by identifying the attributes that compose the phenomenon. Based on a systematic literature review, this paper identifies the terms that have been used to refer to this phenomenon and analyzes their associated attributes. Based on Gerring & Barrosi’s Min-Max strategy of concept formation, we propose two sets of attributes to define the phenomenon