Effect of enhanced masticatory force on OPG, RANKL and MGF in alveolar bone of ovariectomized rats

Menopause induces oral bone loss, leading to various oral diseases. Mastication importantly affects bone metabolism in the jawbone. Objective: To analyze the effect of enhanced masticatory force on osteoprotegerin (OPG), receptor activator of nuclear factor kappa B ligand (RANKL), and mechano–growth factor (MGF) in alveolar bone of ovariectomized rats and to study the mechanics mechanism of the alveolar bone of ovariectomized rats response to enhanced masticatory force. Methodology: Thirty Sprague Dawley rats were randomly divided into three groups: sham–operation group (fat around the removed ovary + normal hard diet), model group (ovariectomy + normal hard diet), and experimental group (ovariectomy + high hard diet). It was a 2–month experiment. Enzyme–linked immunosorbent assay (ELISA) detected serum estradiol (E2), osteocalcin (BGP) and alkaline phosphatase (ALP) in rats. Bone histomorphometric indices in the third molar region of maxilla were detected by micro-CT; protein expressions of OPG, RANKL, and MGF in the third molar region of maxilla was detected by Western blot; and gene expression of OPG, RANKL, and MGF in the third molar region of maxilla was detected by Quantitative Real–Time PCR. Results: Comparing with model group, serum E2 in experimental group increased but not significantly, serum BGP and serum ALP in experimental group decreased but not significantly, OPG in experimental group in alveolar bone increased significantly, RANKL in experimental group in alveolar bone decreased significantly, RANKL/OPG ratio in experimental group decreased significantly, MGF in experimental group in alveolar bone increased significantly, bone volume to total volume fraction increased significantly in experimental group, trabecular thickness increased significantly in experimental group, and trabecular separation decreased significantly in experimental group. Conclusion: Enhanced masticatory force affected the expression of OPG, RANKL, and MGF in alveolar bone of ovariectomized rats, improved the quality of jaw bone of ovariectomized rats, and delayed oral bone loss by ovariectomy

Database modeling for industrial data management : emerging technologies and applications

xiii, 374 p. : ill. ; 29 cm

Advances in probabilistic databases for uncertain information management

This book covers a fast-growing topic in great depth and focuses on the technologies and applications of probabilistic data management. It aims to provide a single account of current studies in probabilistic data management. The objective of the book is to provide the state of the art information to researchers, practitioners, and graduate students of information technology of intelligent information processing, and at the same time serving the information technology professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible

Fuzzy XML data management

This book presents an exhaustive and timely review of key research work on fuzzy XML data management, and provides readers with a comprehensive resource on the state-of-the art tools and theories in this fast growing area.  Topics covered in the book include: representation of fuzzy XML, query of fuzzy XML, fuzzy database models, extraction of fuzzy XML from fuzzy database models, reengineering of fuzzy XML into fuzzy database models, and reasoning of fuzzy XML. The book is intended as a reference guide for researchers, practitioners and graduate students working and/or studying in the field of Web Intelligence, as well as for data and knowledge engineering professionals seeking new approaches to replace traditional methods, which may be unnecessarily complex or even unproductive

Interpolation and Prediction of Spatiotemporal Data Based on XML Integrated with Grey Dynamic Model

Interpolation and prediction of spatiotemporal data are integral components of many real-world applications. Thus, approaches of interpolating and predicting spatiotemporal data have been extensively investigated. Currently, the grey dynamic model has been used to enhance the performance of interpolating and predicting spatiotemporal data. Meanwhile, the Extensible Markup Language (XML) has unique characteristics of information representation and exchange. In this paper, we first couple the grey dynamic model with the spatiotemporal XML model. Based on a definition of the position part of the spatiotemporal XML model, we extract the corresponding position information of each time interval and propose an algorithm for constructing an AVL tree to store them. Then, we present the architecture of an interpolating and predicting process and investigate change operations in positions. On this basis, we present an algorithm for interpolation and prediction of spatiotemporal data based on XML integrated with the grey dynamic model. Experimental results demonstrate the performance advantages of the proposed approach

Fuzzy XML Data Management

This book presents an exhaustive and timely review of key research work on fuzzy XML data management, and provides readers with a comprehensive resource on the state-of-the art tools and theories in this fast growing area.  Topics covered in the book include: representation of fuzzy XML, query of fuzzy XML, fuzzy database models, extraction of fuzzy XML from fuzzy database models, reengineering of fuzzy XML into fuzzy database models, and reasoning of fuzzy XML. The book is intended as a reference guide for researchers, practitioners and graduate students working and/or studying in the field of Web Intelligence, as well as for data and knowledge engineering professionals seeking new approaches to replace traditional methods, which may be unnecessarily complex or even unproductive

Sampling scattered data with Bernstein polynomials: stochastic and deterministic error estimates

Viewing the classical Bernstein polynomials as sampling operators, we study a generalization by allowing the sampling operation to take place at scattered sites. We utilize both stochastic and deterministic approaches. On the stochastic side, we consider the sampling sites as random variables that obey some naturally derived probabilistic distributions, and obtain Chebyshev type estimates. On the deterministic side, we incorporate the theory of uniform distribution of point sets (within the framework of Weyl\u27s criterion) and the discrepancy method. We establish convergence results and error estimates under practical assumptions on the distribution of the sampling sites