Squalene-Rich Amaranth Oil Pickering Emulsions Stabilized by Native α-Lactalbumin Nanoparticles.

The stabilization of Pickering emulsions by nanoparticles has drawn great interest in the field of food science and technology. In this study, α-Lactalbumin nanoparticles prepared by the desolvation and cross-linking method from protein solutions with initial pH values of 9 and 11 were used to stabilize squalene-rich amaranth oil Pickering o/w emulsions. The effect of different concentrations of nanoparticles on the size, size distribution, ζ potential, and emulsion stability was evaluated using dynamic light scattering, electron microscopy, and light backscattering. Dependence of the emulsions' droplet size on the nanoparticle concentration was observed, and the critical coverage ratio was reached when 5-10% nanoparticles concentration was used. Our findings suggest that α-LA nanoparticles at a 10% concentration can be used as novel stabilizers for Pickering emulsions to provide protection for beneficial lipophilic bioactive compounds. This is the first time that native α-LA nanoparticles have been used as stabilizers of Pickering emulsions.

Deconvolution of complex differential scanning calorimetry profiles for protein transitions under kinetic control.

A frequent outcome in differential scanning calorimetry (DSC) experiments carried out with large proteins is the irreversibility of the observed endothermic effects. In these cases, DSC profiles are analyzed according to methods developed for temperature-induced denaturation transitions occurring under kinetic control. In the one-step irreversible model (native → denatured) the characteristics of the observed single-peaked endotherm depend on the denaturation enthalpy and the temperature dependence of the reaction rate constant, k. Several procedures have been devised to obtain the parameters that determine the variation of k with temperature. Here, we have elaborated on one of these procedures in order to analyze more complex DSC profiles. Synthetic data for a heat capacity curve were generated according to a model with two sequential reactions; the temperature dependence of each of the two rate constants involved was determined, according to the Eyring's equation, by two fixed parameters. It was then shown that our deconvolution procedure, by making use of heat capacity data alone, permits to extract the parameter values that were initially used. Finally, experimental DSC traces showing two and three maxima were analyzed and reproduced with relative success according to two- and four-step sequential models.