Multifunctionality of Ti Surface: Synthesis and Characterization of Hybrid Phospholipid Films Containing Apatite and Silver Nanoparticles

• Grant number: 23/09402-6
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2023
• End date: September 30, 2024
• Field of knowledge: Health Sciences - Dentistry - Dental Materials
• Principal Investigator: Cássio Do Nascimento
• Grantee: Ailton Cravo Moraes Filho
• Host Institution: Faculdade de Odontologia de Ribeirão Preto (FORP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

The new generation of dental implants seeks constant improvements in their surface properties to promote implant-host interaction. In this regard, innovative solutions are proposed to enhance the multifunctional behavior of biomaterials for osseointegration, including the simultaneous capacity to induce apatite formation (bioactivity), rapid and effective colonization by osteoblasts, and antibacterial activity. This research project aims to develop a novel Ti surface coated with Dihexadecyl phosphate phospholipid and silver nanoparticles using the Langmuir-Blodgett film transfer technique, and to induce hydroxyapatite formation on Ti surfaces through biomimetic approaches. The topography characterization and analysis of surface properties, morphology, chemical composition, and structure of the films will be conducted using the following methodologies: scanning electron microscopy (SEM), confocal laser microscopy, wettability and surface energy, Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). In addition, in situ contamination assays will be performed to evaluate the microbial profile using 16S rDNA-based PCR sequencing methodology, and a qualitative Live/Dead fluorescence assay will be conducted to visualize the biofilm-covered area. Inductively coupled plasma mass spectrometry (ICP-MS) will be utilized for multi-elemental and isotopic analysis. Descriptive and inferential statistical data will be presented for quantitative variables, considering the homogeneity of variance and distribution of the obtained data.