The surface coating of biomaterials by conductive polymers, such as polypyrrole (PPy), demonstrates to be a promising strategy due to its unique electrical properties. Our previous study showed that the pretreatment of titanium (Ti) surfaces by Plasma Electrolytic Oxidation (PEO) followed by the deposition of the PPy film (PEO+PPy), improved the mechanical and electrochemical properties of Ti. However, considering that the main implant failures are related to polymicrobial infection induced by biofilms and the deficiency in the osseointegration process, other features of Ti also need to be enhanced. Therefore, this study aims to develop a PEO+PPy coating with antibacterial properties through the zinc oxide (ZnO) incorporation (by electrodeposition) and to promote a surface with osteogenic activity through the electrical stimulus (ES) application. For this, the surface characteristics, mechanical, physicochemical, tribological, electrochemical, antimicrobial, biological, and osteogenic properties will be investigated. Commercially pure titanium discs will be allocated into 3 groups for the following surface treatments: (1) PEO-treated; (2) treated with PEO followed by electrodeposition of PPy (PEO+PPy); (3) treated with PEO followed by electrodeposition of PPy and ZnO (PEO+PPy/ZnO). Surface characteristics and mechanical properties will be evaluated by physical and tribological tests, respectively. Electrochemical behavior will be assessed to evaluate the coatings' corrosion resistance. The antimicrobial effect of the coatings will be evaluated against monospecies and polymicrobial biofilms. The albumin and fetal bovine serum (FBS) protein interaction with the surfaces will be measured. The three groups described above (controls) and three more groups that will undergo ES (experimental) will be considered for the ES stage. In order to evaluate the effect of ES, pre-osteoblastic cells will be used. In addition, the influence of ES parameters on the Zn2+ ion release mechanism and on the modulation of the microbiota composition will also be investigated. The quantitative data will be analyzed statistically considering ± = 0.05.
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