Differential Production of Macrophage Inflammatory Protein-1 alpha, Stromal-Derived Factor-1, and IL-6 by Human Cultured Periodontal Ligament and Gingival Fibroblasts Challenged With Lipopolysaccharide From P. gingivalis

Background: Fibroblasts are considered important cells in periodontitis. When challenged by different agents, they respond through the release of cytokines that participate in the inflammatory process. The aim of this study is to evaluate and compare the expression and production of macrophage inflammatory protein (MIP)-1 alpha, stromal-derived factor (SDF)-1, and interleukin (IL)-6 by human cultured periodontal ligament and gingival fibroblasts challenged with lipopolysaccharide (LPS) from Porphyromonas gingivalis. Methods: Fibroblasts were cultured from biopsies of gingival tissue and periodontal ligament of the same donors and used on the fourth passage. After confluence in 24-well plates, the culture medium alone (control) or with 0.1 to 10 mu g/ml of LPS from P. gingivalis was added to the wells, and after 1, 6, and 24 hours, the supernatant and the cells were collected and analyzed by enzyme-linked immunosorbent assay and real-time polymerase chain reaction, respectively. Results: MIP-1 alpha, SDF-1, and IL-6 protein production was significantly greater in gingival fibroblasts compared to periodontal ligament fibroblasts. IL-6 was upregulated in a time-dependent manner, mainly in gingival fibroblasts (P<0.05), which secreted more MIP-1 alpha in the lowest concentration of LPS used (0.1 mu g/ml). In contrast, a basal production of SDF-1 that was inhibited with the increase of LPS concentration was detected, especially after 24 hours (P<0.05). Conclusion: The distinct ability of the gingival and periodontal ligament fibroblasts to secrete MIP-1 alpha, SDF-1, and IL-6 emphasizes that these cells may differently contribute to the balance of cytokines in the LPS-challenged periodontium. J Periodontol 2010;81:310-317.

The composite Euler method for stiff stochastic differential equations

In this paper we present the composite Euler method for the strong solution of stochastic differential equations driven by d-dimensional Wiener processes. This method is a combination of the semi-implicit Euler method and the implicit Euler method. At each step either the semi-implicit Euler method or the implicit Euler method is used in order to obtain better stability properties. We give criteria for selecting the semi-implicit Euler method or the implicit Euler method. For the linear test equation, the convergence properties of the composite Euler method depend on the criteria for selecting the methods. Numerical results suggest that the convergence properties of the composite Euler method applied to nonlinear SDEs is the same as those applied to linear equations. The stability properties of the composite Euler method are shown to be far superior to those of the Euler methods, and numerical results show that the composite Euler method is a very promising method. (C) 2001 Elsevier Science B.V. All rights reserved.

Implicit Taylor methods for stiff stochastic differential equations

In this paper we discuss implicit Taylor methods for stiff Ito stochastic differential equations. Based on the relationship between Ito stochastic integrals and backward stochastic integrals, we introduce three implicit Taylor methods: the implicit Euler-Taylor method with strong order 0.5, the implicit Milstein-Taylor method with strong order 1.0 and the implicit Taylor method with strong order 1.5. The mean-square stability properties of the implicit Euler-Taylor and Milstein-Taylor methods are much better than those of the corresponding semi-implicit Euler and Milstein methods and these two implicit methods can be used to solve stochastic differential equations which are stiff in both the deterministic and the stochastic components. Numerical results are reported to show the convergence properties and the stability properties of these three implicit Taylor methods. The stability analysis and numerical results show that the implicit Euler-Taylor and Milstein-Taylor methods are very promising methods for stiff stochastic differential equations.

Three-point boundary value problems for second-order, ordinary, differential equations

We establish existence results for solutions to three-point boundary value problems for nonlinear, second-order, ordinary differential equations with nonlinear boundary conditions. (C) 2001 Elsevier Science Ltd. All rights reserved.

Differential inclusions and robust control theory

Uncontrolled systems (x) over dot is an element of Ax, where A is a non-empty compact set of matrices, and controlled systems (x) over dot is an element of Ax + Bu are considered. Higher-order systems 0 is an element of Px - Du, where and are sets of differential polynomials, are also studied. It is shown that, under natural conditions commonly occurring in robust control theory, with some mild additional restrictions, asymptotic stability of differential inclusions is guaranteed. The main results are variants of small-gain theorems and the principal technique used is the Krasnosel'skii-Pokrovskii principle of absence of bounded solutions.

Stability of linear difference and differential inclusions

Any given n X n matrix A is shown to be a restriction, to the A-invariant subspace, of a nonnegative N x N matrix B of spectral radius p(B) arbitrarily close to p(A). A difference inclusion x(k+1) is an element of Ax(k), where A is a compact set of matrices, is asymptotically stable if and only if A can be extended to a set B of nonnegative matrices B with \ \B \ \ (1) < 1 or \ \B \ \ (infinity) < 1. Similar results are derived for differential inclusions.

Stiffly accurate Runge-Kutta methods for stiff stochastic differential equations

In this paper we discuss implicit methods based on stiffly accurate Runge-Kutta methods and splitting techniques for solving Stratonovich stochastic differential equations (SDEs). Two splitting techniques: the balanced splitting technique and the deterministic splitting technique, are used in this paper. We construct a two-stage implicit Runge-Kutta method with strong order 1.0 which is corrected twice and no update is needed. The stability properties and numerical results show that this approach is suitable for solving stiff SDEs. (C) 2001 Elsevier Science B.V. All rights reserved.

A review of the impact of education and prior experience on new venture performance

The importance of education and experience to the successful performance of new firms is well recognized both by management practitioners and academics. Yet empirical research to support the significance of this relationship is inconclusive. This paper discusses theories describing the relationship between education and experience and firm performance. It also analyses and classifies the differing measures of performance, education and experience, and compares the results of multiple studies undertaken between 1977 and 2000. Possible reasons for conflicting results are identified, such as lack of sound theoretical bases that relate education and experience to performance, varying definitions of the key variables and the diversity of measures used. Finally, a framework is developed that incorporates variables that interact with experience and education to influence new venture performance.