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Abstract:  
Background: Self-assembling peptides (SApeptides) have growing applications in tissue engineering and regenerative medicine. The application of SApeptide-based hydrogels depends strongly on their viscoelastic properties. Optimizing the properties is of importance in tuning the characteristics of the hydrogels for a variety of applications. Methods: In this study, we employed statistical modeling, conducted with the response surface methodology (RSM) and particle tracking microrheology to investigate the effects of self-assembling SPG-178 peptide and added salt (NaCl) concentrations and milieu type (deionized water or blood serum) on the viscoelastic properties of SPG-178 hydrogels. A central composite RSM model was employed for finding the optimum value of the parameters to achieve the highest storage modulus and the lowest tan δ. Results: Viscoelastic properties of each sample, including storage modulus, loss modulus, and tan δ, were determined. Storage modulus and tan δ were modeled, accounting for the impact of the SPG-178 peptide and NaCl concentrations and milieu type on the viscoelastic properties. It was found that the SPG-178 hydrogel storage modulus was positively influenced by the SPG-178 peptide concentration and the serum. Conclusion: A combination of microrheology and RSM is a useful test method for statistical modeling and analysis of rheological behavior of solid-like gels, which could be applied in various biomedical applications such as hemostasis.

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