Immediate and long-term evaluation of the adhesive interface after dentin biomodification with chitosan solution and application of different adhesive systems

• Grant number: 17/21855-5
• Support type: Scholarships in Brazil - Scientific Initiation
• Effective date (Start): December 01, 2017
• Effective date (End): November 30, 2018
• Field of knowledge: Health Sciences - Dentistry - Dental Clinics
• Principal Investigator: Aline Evangelista de Souza Gabriel
• Grantee: Vitória Leite Paschoini
• Home Institution: Faculdade de Odontologia de Ribeirão Preto (FORP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

Biomodification of dentin collagen with biopolymers have been proposed as a strategy to preserve the hybrid layer. The aim of this study is to evaluate, in vitro, the bond strength of the adhesive interface and to characterize it chemically and morphologically, after the treatment of dentin with chitosan solution and application of different adhesive systems, in immediate and long-term periods. The sample will be composed of 80 healthy third molars, which will be divided into 2 groups according to the dentin treatment: without biomodification (control) and bio modified with 2.5% chitosan solution, and subdivided into 2 according to the adhesive systems: total-etching (Adper Single Bond 2, 3M) and self-etching (Clear Fil SE Bond, Kuraray). The dental surface will be restored with composite resin (Filtek Z250, 3M) and half of the teeth of each subgroup will be subjected to the interface aging (6 months of storage in water + enzymatic degradation) and the other half will be used for immediate analysis (24h) (n=10). The teeth will be sectioned into sticks (transversal area of 1.0 ± 0.2 mm²) and subjected to the following analyzes: 1) microtensile bond strength (MPa); 2) degree of conversion of the adhesive system (%) by means of FTIR; 3) chemical composition (%) of the adhesive interface by EDS and 4) morphology of the adhesive interface by SEM. The selection of statistical tests will be based on data set characteristics such as adherence to normal curve and homoscedasticity. The statistical inferences will be done considering the significance level of 5%. (AU)