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To achieve the ultimate goal of periodontal tissue engineering, it is of great importance to develop bioactive scaffolds which could stimulate the osteogenic/cementogenic differentiation of periodontal ligament cells (PDLCs) for the favorable regeneration of alveolar bone, root cementum, and periodontal ligament. Strontium (Sr) and Sr-containing biomaterials have been found to induce osteoblast activity. However, there is no systematic report about the interaction between Sr or Sr-containing biomaterials and PDLCs for periodontal tissue engineering. The aims of this study were to prepare Sr-containing mesoporous bioactive glass (Sr-MBG) scaffolds and investigate whether the addition of Sr could stimulate the osteogenic/cementogenic differentiation of PDLCs in tissue engineering scaffold system. The composition, microstructure and mesopore properties (specific surface area, nano-pore volume and nano-pore distribution) of Sr-MBG scaffolds were characterized. The proliferation, alkaline phosphatase (ALP) activity and osteogenesis/cementogenesis-related gene expression (ALP, Runx2, Col I, OPN and CEMP1) of PDLCs on different kinds of Sr-MBG scaffolds were systematically investigated. The results show that Sr plays an important role in influencing the mesoporous structure of MBG scaffolds in which high contents of Sr decreased the well-ordered mesopores as well as their surface area/pore volume. Sr2+ ions could be released from Sr-MBG scaffolds in a controlled way. The incorporation of Sr into MBG scaffolds has significantly stimulated ALP activity and osteogenesis/cementogenesis-related gene expression of PDLCs. Furthermore, Sr-MBG scaffolds in simulated body fluids environment still maintained excellent apatite-mineralization ability. The study suggests that the incorporation of Sr into MBG scaffolds is a viable way to stimulate the biological response of PDLCs. Sr-MBG scaffolds are a promising bioactive material for periodontal tissue engineering application.

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Nowadays, Workflow Management Systems (WfMSs) and, more generally, Process Management Systems (PMPs) are process-aware Information Systems (PAISs), are widely used to support many human organizational activities, ranging from well-understood, relatively stable and structures processes (supply chain management, postal delivery tracking, etc.) to processes that are more complicated, less structured and may exhibit a high degree of variation (health-care, emergency management, etc.). Every aspect of a business process involves a certain amount of knowledge which may be complex depending on the domain of interest. The adequate representation of this knowledge is determined by the modeling language used. Some processes behave in a way that is well understood, predictable and repeatable: the tasks are clearly delineated and the control flow is straightforward. Recent discussions, however, illustrate the increasing demand for solutions for knowledge-intensive processes, where these characteristics are less applicable. The actors involved in the conduct of a knowledge-intensive process have to deal with a high degree of uncertainty. Tasks may be hard to perform and the order in which they need to be performed may be highly variable. Modeling knowledge-intensive processes can be complex as it may be hard to capture at design-time what knowledge is available at run-time. In realistic environments, for example, actors lack important knowledge at execution time or this knowledge can become obsolete as the process progresses. Even if each actor (at some point) has perfect knowledge of the world, it may not be certain of its beliefs at later points in time, since tasks by other actors may change the world without those changes being perceived. Typically, a knowledge-intensive process cannot be adequately modeled by classical, state of the art process/workflow modeling approaches. In some respect there is a lack of maturity when it comes to capturing the semantic aspects involved, both in terms of reasoning about them. The main focus of the 1st International Workshop on Knowledge-intensive Business processes (KiBP 2012) was investigating how techniques from different fields, such as Artificial Intelligence (AI), Knowledge Representation (KR), Business Process Management (BPM), Service Oriented Computing (SOC), etc., can be combined with the aim of improving the modeling and the enactment phases of a knowledge-intensive process. The 1st International Workshop on Knowledge-intensive Business process (KiBP 2012) was held as part of the program of the 2012 Knowledge Representation & Reasoning International Conference (KR 2012) in Rome, Italy, in June 2012. The workshop was hosted by the Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio Ruberti of Sapienza Universita di Roma, with financial support of the University, through grant 2010-C26A107CN9 TESTMED, and the EU Commission through the projects FP7-25888 Greener Buildings and FP7-257899 Smart Vortex. This volume contains the 5 papers accepted and presented at the workshop. Each paper was reviewed by three members of the internationally renowned Program Committee. In addition, a further paper was invted for inclusion in the workshop proceedings and for presentation at the workshop. There were two keynote talks, one by Marlon Dumas (Institute of Computer Science, University of Tartu, Estonia) on "Integrated Data and Process Management: Finally?" and the other by Yves Lesperance (Department of Computer Science and Engineering, York University, Canada) on "A Logic-Based Approach to Business Processes Customization" completed the scientific program. We would like to thank all the Program Committee members for the valuable work in selecting the papers, Andrea Marrella for his valuable work as publication and publicity chair of the workshop, and Carola Aiello and the consulting agency Consulta Umbria for the organization of this successful event.