A comparative study of simulated body fluids in the presence of proteins

Publication date: Available online 4 February 2017
Source:Acta Biomaterialia
Author(s): Weitian Zhao, Jacques Lemaître, Paul Bowen
Simulated body fluid (SBF) is widely used as part of an in vitro method to evaluate implant materials such as their apatite forming ability (AFA), a typical indication of potential bone-bonding ability in vivo. We report the use of carbonate-buffered SBFs as potential solutions for implant evaluation and the effect of proteins, represented by bovine serum albumin (BSA) in SBFs on the nucleation and growth of hydroxyapatite (HA). These solutions are buffered by the thermodynamic equilibrium with 5% CO2 in an incubator, and result in a deposition of carbonated HA. Using several titanium-based surfaces, these solutions were studied in comparison with the widely-used SBF (ISO 23317). The presence of BSA strongly inhibited the formation of HA in traditional SBF, while HA can still be observed in carbonate-buffered SBFs. A kinetic study reveals that the inhibitory effect is concentration dependent with 0.1 g/L and 1 g/L of BSA having little effect on HA growth but a complete inhibition of HA formation at 5 g/L of BSA, as tested using NaOH treated titanium with a known positive AFA. The decrease in solution pH and free calcium concentrations in SBFs due to the addition of BSA is not significant, suggesting other causes for the strong inhibitory effect.Statement of significanceThe successful use of simulated body fluids (SBFs) to evaluate potential bioactive implants relies on the better understanding of the heterogeneous nucleation and growth of hydroxyapatite in solution. Although a standardized recipe for SBF was developed over a decade ago, a few key issues remain to be understood, i.e. the behavior of carbonate-buffered SBFs having similar buffering mechanism as human blood, and the effect of proteins on hydroxyapatite formation on bioactive materials. This paper addresses these two issues and would help the reader better understand the subtleties in this domain and better interpret the results generated using SBFs.

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