We investigated the use of whey protein isolate (WPI) as oleogelator in liquid oil. First, heat-set WPI hydrogels were prepared varying in microstructure and network density. Then, by applying a ...stepwise solvent exchange procedure via an intermediate solvent, full replacement of the internal aqueous phase within the protein matrix by sunflower oil was achieved. The solvent exchange procedure was performed by using either acetone or tetrahydrofuran (THF) as intermediate solvent. The oil inside the protein matrix was homogeneously distributed without any noticeable damage to the structure. Analyzing the weight change of the protein gel as a result of the solvent exchange shows that the oil holding capacity depends on the microstructure, the polarity of the intermediate solvent, and the kinetics of the solvent exchange. Depending on the gel microstructure and protein concentration of the preceding hydrogel, the oil content in the oleogels was found to be as high as 91 wt %. Oil holding capacity correlated well with the water holding capacity of the preceding hydrogel, and its Young’s modulus (stiffness). It was found that the oleogels, compared to the hydrogels, were much stiffer, as the Young’s modulus increased by 2 orders of magnitude and showed a lower strain at fracture. Our novel route of structuring oil by immobilizing liquid oil inside a biodegradable protein gel matrix with tunable mechanical properties could be relevant for developing novel materials, e.g., in pharmaceutical, nutraceutical, and food applications.
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In this research we use heat-set whey protein aggregates (diameter∼200nm) as novel building blocks for structure formation in liquid oil to form oleogels. To transfer the aggregates ...to the oil phase, a solvent exchange procedure to sunflower oil was applied using acetone as an intermediate solvent. We found that agglomeration of the aggregates was prevented and the particle size in oil did not change from that in the initial aqueous phase. The small protein aggregates assemble into a space-spanning network, thereby providing solid-like properties to liquid oil. From oscillatory rheology we conclude that the aggregates are highly effective in forming a network. Already at ∼3% we found that G′>G″ and G′ scales with protein concentration as G′∼cp5.3. Applying a fractal gel network theory to the rheological data we deduce that the gels are in the strong link regime with a fractal dimension of 2.2. The results show that protein aggregates, besides their well-known functionality in aqueous solvents, are capable of forming a network in liquid oil. This provides a novel and promising way to design oleogels with tuneable rheological properties, applicable to e.g. foods, pharmaceuticals and/or cosmetics.
ABSTRACT
Purpose
In earlier studies, the corn protein zein is found to be suitable as a sustained release agent, yet the range of drugs for which zein has been studied remains small. Here, zein is ...used as a sole excipient for drugs differing in hydrophobicity and isoelectric point: indomethacin, paracetamol and ranitidine.
Methods
Caplets were prepared by hot-melt extrusion (HME) and injection moulding (IM). Each of the three model drugs were tested on two drug loadings in various dissolution media. The physical state of the drug, microstructure and hydration behaviour were investigated to build up understanding for the release behaviour from a zein based matrix for drug delivery.
Results
Drug crystallinity of the caplets increases with drug hydrophobicity. For ranitidine and indomethacin, swelling rates, swelling capacity and release rates were pH dependent as a consequence of the presence of charged groups on the drug molecules. Both hydration rates and release rates could be approached by existing models.
Conclusion
The drug state and pH dependant electrostatic interactions are hypothesised to influence release kinetics. Both factors can potentially be used to influence release kinetics release, thereby broadening the horizon for zein as a tuneable release agent.
Preparation methods of alginate nanoparticles Paques, Jerome P.; van der Linden, Erik; van Rijn, Cees J.M. ...
Advances in colloid and interface science,
07/2014, Letnik:
209
Journal Article
Recenzirano
This article reviews available methods for the formation of alginate nano-aggregates, nanocapsules and nanospheres. Primarily, alginate nanoparticles are being prepared by two methods. In the ...“complexation method”, complex formation on the interface of an oil droplet is used to form alginate nanocapsules, and complex formation in an aqueous solution is used to form alginate nano-aggregates. In a second method w/o emulsification coupled with gelation of the alginate emulsion droplet can be used to form alginate nanospheres. We review advantages and disadvantages of these methods, and give an overview of the properties of the alginate particles produced with these methods.
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•Alginate is one of the most used polymers in formation of (micro)particles.•Use of alginate in nanoparticles is not common.•Alginate nano-aggregates, nanocapsules and nanospheres are reviewed.•Alginate nanoparticle formation is based on two methods.•These are complexation and w/o emulsification
The behavior of an oil-in-water emulsion was studied in the presence of protein fibrils for a wide range of fibril concentrations by using rheology, diffusing wave spectroscopy, and confocal laser ...scanning microscopy. Results showed that above a minimum fibril concentration depletion flocculation occurred, leading to oil droplet aggregation and enhanced creaming of the emulsion. Upon further increasing the concentration of the protein fibrils, the emulsions were stabilized. In this stable regime both aggregates of droplets and single droplets are present, and these aggregates are smaller than the aggregates in the flocculated emulsion samples at the lower fibril concentrations. The size of the droplet aggregates in the stabilized emulsions is independent of fibril concentration. In addition, the droplet aggregation was reversible upon dilution both by a pH 2 HCl solution and by a fibril solution at the same concentration. The viscosity of the emulsions containing fibrils was comparable to that of the pure fibril solution. Neither fibril networks nor droplet gel networks were observed in our study. The stabilization mechanism of emulsions containing long protein fibrils at high protein fibril concentrations points toward the mechanism of a kinetic stabilization.
Abstract Predicting physical properties of complex multi-scale systems is a common challenge and demands analysis of various temporal and spatial scales. However, physics alone is often not ...sufficient due to lack of knowledge on certain details of the system. With sufficient data, however, machine learning techniques may aid. If data are yet relatively cumbersome to obtain, hybrid methods may come to the rescue. We focus in this report on using various types of neural networks (NN) including NN’s into which physics information is encoded (PeNN’s) and also studied effects of NN’s hyperparameters. We apply the networks to predict the viscosity of an emulsion as a function of shear rate. We show that using various network performance metrics as the mean squared error and the coefficient of determination ( $$R^2$$ R 2 ) that the PeNN’s always perform better than the NN’s, as also confirmed by a Friedman test with a p -value smaller than 0.0002. The PeNN’s capture extrapolation and interpolation very well, contrary to the NN’s. In addition, we have found that the NN’s hyperparameters including network complexity and optimization methods do not have any effect on the above conclusions. We suggest that encoding NN’s with any disciplinary system based information yields promise to better predict properties of complex systems than NN’s alone, which will be in particular advantageous for small numbers of data. Such encoding would also be scalable, allowing different properties to be combined, without repetitive training of the NN’s.
In this study, we investigated the gelation of WPI fibrils in the presence of bacterial cellulose (BC) microfibrils at pH 2 upon prolonged heating. Rheology and microstructure were investigated as a ...function of BC microfibril concentration. The presence of BC microfibrils did not influence the gelation dynamics and resulting overall structure of the WPI fibrillar gel. The storage modulus and loss modulus of the mixed WPI‐BC microfibril gels increased with increasing BC microfibril concentration, whereas the ratio between loss modulus and storage modulus remained constant. The WPI fibrils and BC microfibrils independently form two coexisting gel networks. Interestingly, near to the BC microfibrils more aligned WPI fibrils seemed to be formed, with individual WPI fibrils clearly distinguishable. The level of alignment of the WPI fibrils seemed to be dependent on the distance between BC microfibrils and WPI fibrils. This also is in line with our observation that with more BC microfibrils present, WPI fibrils are more aligned than in a WPI fibrillar gel without BC microfibrils. The large deformation response of the gels at different BC microfibril concentration and NaCl concentration is mainly influenced by the concentration of NaCl, which affects the WPI fibrillar gel structures, changing form linear fibrillar to a particulate gel. The WPI fibrillar gel yields the dominant contribution to the gel strength.
•Rheological and mechanical properties of foods determine oral processing behavior.•Consumers adapt bite size, consumption time, and eating rate to food properties.•Liking, familiarity, and frequency ...of consumption weakly impact oral processing.
Food oral processing plays a key role in sensory perception, consumer acceptance and food intake. However, little is known about the influence of physical food properties on oral processing of different type of food products. The primary objective of this study was to determine the influence of rheological and mechanical properties of foods on oral processing behavior of liquid (drinkable), semi-solid (spoonable) and solid foods (chewable). The secondary objective was to quantify the influence of product liking, frequency of consumption and familiarity on oral processing behavior. Rheological and mechanical properties of 18 commercially available foods were quantified. Parameters describing oral processing behavior such as sip and bite size, consumption time, eating rate, number of swallows, number of chews, cycle duration, and chewing rate were extracted from video recordings of 61 consumers. Subjects evaluated products’ liking, familiarity, and frequency of consumption using questionnaires. Consumers strongly adapted oral processing behavior with respect to bite size, consumption time, and eating rate to the rheological and mechanical properties of liquid, semi-solid and solid foods. This adaptation was observed within each food category. Chewing rate and chewing cycle duration of solid foods were not influenced by mechanical properties and remained relatively constant. Liking, familiarity, and consumption frequency showed to impact oral processing behavior, although to a lower degree than the rheological and mechanical properties of food. We conclude that the oral processing behaviors of liquid, semi-solid and solid foods are mainly determined by their rheological and mechanical properties.
In this study, water-in-oil emulsions were prepared from water containing different salt concentrations dispersed in an oil phase containing a mixture of β-sitosterol and γ-oryzanol. In pure oil, the ...β-sitosterol and γ-oryzanol molecules self-assemble into tubular microstructures to produce a firm organogel. However, in the emulsion, the water molecules bind to the β-sitosterol molecules, forming monohydrate crystals that hinder the formation of the tubules and resulting in a weaker emulsion-gel. Addition of salt to the water phase decreases the water activity, thereby suppressing the formation of sitosterol monohydrate crystals even after prolonged storage times (∼1 year). When the emulsions were prepared with less polar oils, the tubular microstructure was promoted, which significantly increased the firmness of the emulsion-gel. The main conclusion of this study is that the formation of oryzanol and sitosterol tubular microstructure in the emulsion can be promoted by reducing the water activity and/or by using oils of low polarity.
Proteins are known to be effective building blocks when it comes to structure formation in aqueous environments. Recently, we have shown that submicron colloidal protein particles can also be used to ...provide structure to liquid oil and form so-called oleogels ( de Vries, A. J. Colloid Interface Sci. 2017, 486, 75−83). To prevent particle agglomeration, a solvent exchange procedure was used to transfer the aggregates from water to the oil phase. The aim of the current paper was to elucidate on the enhanced stability against agglomeration of heat-set whey protein isolate (WPI) aggregates to develop an alternative for the solvent exchange procedure. Protein aggregates were transferred from water to several solvents differing in polarity to investigate the effect on agglomeration and changes in protein composition. We show that after drying protein aggregates by evaporation from solvents with a low polarity (e.g., hexane), the protein powder shows good dispersibility in liquid oil compared to powders dried from solvents with a high polarity. This difference in dispersibility could not be related to changes in protein composition or conformation but was instead related to the reduction of attractive capillary forces between the protein aggregates during drying. Following another route, agglomeration was also prevented by applying high freezing rates prior to freeze-drying. The rheological properties of the oleogels prepared with such freeze-dried protein aggregates were shown to be similar to that of oleogels prepared using a solvent exchange procedure. This Research Article provides valuable insights in how to tune the drying process to control protein agglomeration to allow for subsequent structure formation of proteins in liquid oil.
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