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Proteomic evaluation of osseointegration of implants with hydrophilic surface in rats with systemic complications involving diabetes and smoking.

Grant number: 22/11630-4
Support Opportunities:Scholarships in Brazil - Master
Effective date (Start): March 01, 2023
Effective date (End): February 29, 2024
Field of knowledge:Health Sciences - Dentistry - Periodontology
Principal Investigator:Rosemary Adriana Chierici Marcantonio
Grantee:Karoline Bernardes do Nascimento
Host Institution: Faculdade de Odontologia (FOAr). Universidade Estadual Paulista (UNESP). Campus de Araraquara. Araraquara , SP, Brazil


The use of implants to replace lost teeth and to restore the quality of life of patients is becoming more and more common in our daily clinical practice, but to be successful in this treatment we must consider, among many other factors, the osseointegration process of the implants and the systemic condition of the patients. Studies have shown over the years that modifying the implant surface, whether chemically or physically, can improve osseointegration. However, some of the mechanisms of how osseointegration is different at the molecular level according to these surface modifications still need to be better elucidated. It is also known from the literature that patients who smoke and have diabetes may have alterations in tissue healing, which may generate problems for rehabilitation with implants in these conditions. Thus, the aim of this experimental randomized animal study is to analyze the molecular mechanisms involved in osseointegration of implants with hydrophilic surfaces in animals with systemic involvement, focusing on diabetes and smoking. Previously collected samples from 48 Holtzman rats will be used. Implants with hydrophilic surfaces were installed in the tibia of the animals. They were randomly divided into 3 groups with 16 animals each and evaluated in 2 experimental periods of 15 and 45 days. All received the implant with the same type of surface treatment and what differed between the groups was their systemic condition such as diabetes and smoking. The samples previously collected will undergo protein expression by mass spectrometry, where the data of the expressed proteins found in these samples will be obtained. The proteins will be identified using the STRING and KEGG databases and aiming to search for proteins that signal bone formation. The statistical analysis will be done, in case of normality, the parametric ANOVA tests and complemented with Turkey test and otherwise the non-parametric Kruskall-Wallis test and complemented by Dunn's test.

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