Treatment of multiple adjacent RT 1 gingival recessions with the modified coronally advanced tunnel (MCAT) technique and a collagen matrix or palatal connective tissue graft: 9-year results of a split-mouth randomized clinical trial

Clinical Oral Investigations - To evaluate t he long-term outcomes following treatment of RT 1 multiple adjacent gingival recessions (MAGR) using the modified coronally advanced tunnel (MCAT) with...     

A Coupled FEM-BEM Approach for the Solution of the Free-Boundary Axi-Symmetric Plasma Equilibrium Problem

In this paper we present a coupled Finite Element Method – Boundary Element Method (FEM-BEM) approach for the solution of the free-boundary axi-symmetric plasma equilibrium problem. The proposed method, obtained from an improvement of the Hagenow-Lackner coupling method, allows to efficiently model the equilibrium problem in unbounded domains by discretizing only the plasma region; the external conductors can be modelled either as 2D or 3D models, according to the problem of interest. The paper explores different iterative methods for the solution of the nonlinear Grad-Shafranov equation, such as Picard, Newton-Raphson and Newton-Krylov, in order to provide a robust and reliable tool, able to handle large-scale problems (e.g. high resolution equilibria). This method has been implemented in the FRIDA code (FRee-boundary Integro-Differential Axisimmetric – https://github. om/matteobonotto/ FRIDA), together with a suitable Adaptive Integration Technique (AIT) for the computation of the source term. FRIDA has been successfully tested and validated against experimental data from RFX-mod device, and numerical equilibria of an ITER-like device.     

Introduction: Novel Frontiers in Cancer Metastasis

Clinical & Experimental Metastasis -     

Prosthetic treatment in the adult French population: Prevalence and relation with demographic,socioeconomic and medical characteristics

BackgroundThe aim of this study was to estimate the prevalence of dental prosthetic treatment and to investigate the demographic, social, economic and medical factors associated with the use of fixed and removable dentures in a representative sample of adults living in France.MethodsThe data were obtained from the 2002–2003 Decennial Health Survey, a cross-sectional study of a representative sample of the population living in France, which included 29,679 adults. Information was collected by interview. The variables collected were fixed denture, removable denture, age, gender, number of children, area of residence, nationality, educational attainment, family social status, employment status, annual household income per capita, supplementary insurance, chronic disease, eyesight problems/glasses, hearing problems/hearing aids. Multinomial logistic regression models were used to study the relationship between prosthetic treatment and demographic, socioeconomic and medical characteristics unadjusted, adjusted for age and adjusted for all the characteristics.ResultsThe prevalence of prosthetic treatment was 34.6% (95% confidence interval (CI): [34.1; 35.2]) for fixed prosthetic dentures and 13.8% (95% CI: [13.4; 14.2]) for removable prosthetic dentures. We showed a gradient between educational attainment and removable dentures; the odds ratio adjusted for all the variables (aOR) associated with no or primary education compared to post-secondary education was 2.56; 95% CI: [2.09; 3.13]. When annual household income per capita was low, subjects were less likely to report fixed dentures (aOR = 0.68; 95% CI: [0.62; 0.75]) than those with high annual household income per capita. Individuals without insurance less often reported fixed dentures than those with private insurance. Those reporting chronic disease were less likely to report fixed dentures (aOR = 0.87; 95% CI: [0.79; 0.95]) but more likely to report removable dentures (aOR = 1.29; 95% CI: [1.17; 1.43]) than those without chronic disease.ConclusionThis study reveals social, economic and medical inequalities in fixed and removable prosthetic treatment among adults in France.