In vitro apatite-forming ability of calcium aluminate blends
Source abstract
Abstract
Abstract Calcium aluminate cement (CAC) blends show great potential as biomaterial when compared to commercial products used in odontology and orthopedics. Mixtures of CAC +4 wt% of different additives (alumina, zirconia, zinc oxide, tricalcium phosphate or hydroxyapatite) containing compositions, resulted in samples with low porosity levels and smaller pore sizes after their contact with simulated body fluid (SBF) solution, which was associated with apatite precipitation on the materials’ surface. In order to certify these aspects, the in vitro apatite-formation ability (bioactivity) of CAC blends was evaluated by pH and calcium concentration measurements in SBF for samples previously treated (or not) with sodium silicate (SS) solution. The surface of the samples after immersion in SBF or SBF/SS was analyzed by scanning electron microscopy (SEM), energy dispersive X-ray (EDX) analysis and confocal Raman spectroscopy. In addition, the in vitro apatite deposition and the osteoblastic cell viability were also evaluated. SEM results showed that the precipitation of phases was detected on the CAC blend samples’ surfaces. The presence of calcium and mainly phosphorus by EDX indicated the formation of calcium phosphate phases. Moreover, the presence of a more homogeneous apatite-like layer on the samples’ surface was observed after treatment with sodium silicate solution. The detection of the Raman signature at 960 cm −1 , confirmed the presence of an apatite-like layer on the surface of the compositions after immersion in SBF or SBF/SS. Regarding the osteoblastic cell viability results, blends with collagen, zinc oxide and zirconia presented better results when compared to commercial products.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Bone Tissue Engineering Materials · Endodontics and Root Canal Treatments · Dental Implant Techniques and Outcomes
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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