Improving gelling properties of myofibrillar proteins incorporating with cellulose micro/nanofibres

The effects of cellulose microfibres (CMFs, Average size: 100 ± 5 μm) and cellulose nanofibres (CNFs, Average size: 60 ± 3 nm) on the properties of myofibrillar protein (MP) gels from duck breast meat were studied. The results demonstrated that CMFs and CNFs were mostly connected to MP by non-covalent bonds, the diffusion and cross-linking of MP molecules was promoted, and a denser and more complete gel network was formed. With the increases of CMFs and CNFs concentration (0–10%), the hardness was increased by 13.15% and 19.78% for CMFs10% and CNFs10% gels, respectively, and the elasticity was increased by 40% and 80%, respectively. At the same concentration (0–10%), the increase in gel hardness, viscoelasticity and immobilised water content was greater in the CNFs-MP group than in the CMFs-MP group. The CNFs-MP group had a tighter gel network, and CNFs had a better potential to improve the gelation performance of MP.     

Effect of microwave heating time on the gel properties of chicken myofibrillar proteins and their formation mechanism

The present work was conducted to illustrate the mechanism of gel formation of myofibrillar proteins (MPs) under different microwave heating times. The results showed that the denaturation enthalpy (ΔH) of the MPs significantly decreased when the heating time increased from 3 to 9 s and then completely disappeared as the heating time progressed, indicating that the MPs gradually denatured and subsequently aggregated with increasing heating time, which was further verified by the changes in the secondary structure, electrophoretic bands, and gel properties (e.g., water holding capacity and textural profiles) of the MPs. Microstructural images indicated that the MP gel formed under 12 s had the most compact network, indicating that extended microwave heating time could induce quality deterioration of MP gels. Moreover, the hydrophobic forces, electrostatic forces, and disulphide bonds of the MPs gradually intensified with increasing microwave heating time, suggesting that both non-covalent and covalent bonds could promote molecular denaturation and subsequent aggregation of MPs. In addition, correlation analysis revealed that the changes in the molecular conformation of MPs induced by different microwave heating times could effectively regulate the formation of MP gels and their related properties.     

Designing amorphous formulations of polyphenols with naringin by spray-drying for enhanced solubility and permeability

Naringin (NAR), a major flavanone (FVA) glycoside, is a component of food mainly obtained from grapefruit. We used NAR as a food additive to improve the solubility and permeability of hydrophobic polyphenols used as supplements in the food industry. The spray-dried particles (SDPs) of NAR alone show an amorphous state with a glass transition temperature (T_g) at 93.2 °C. SDPs of hydrophobic polyphenols, such as flavone (FVO), quercetin (QCT), naringenin (NRG), and resveratrol (RVT) were prepared by adding varying amounts of NAR. All SDPs of hydrophobic polyphenols with added NAR were in an amorphous state with a single T_g, but SDPs of hydrophobic polyphenols without added NAR showed diffraction peaks derived from each crystal. The SDPs with NAR could keep an amorphous state after storage at a high humidity condition for one month, except for SDPs of RVT/NAR. SDPs with NAR enhanced the solubility of hydrophobic polyphenols, especially NRG solubility, which was enhanced more than 9 times compared to NRG crystal. The enhanced solubility resulted in the increased membrane permeability of NRG. The antioxidant effect of the hydrophobic NRG was also enhanced by the synergetic effect of NAR. The findings demonstrated that NAR could be used as a food additive to enhance the solubility and membrane permeability of hydrophobic polyphenols.     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

Exactly satisfying initial conditions neural network models for numerical treatment of first Painlevé equation

In this paper, novel computing approach using three different models of feed-forward artificial neural networks (ANNs) are presented for the solution of initial value problem (IVP) based on first Painlevé equation. These mathematical models of ANNs are developed in an unsupervised manner with capability to satisfy the initial conditions exactly using log-sigmoid, radial basis and tan-sigmoid transfer functions in hidden layers to approximate the solution of the problem. The training of design parameters in each model is performed with sequential quadratic programming technique. The accuracy, convergence and effectiveness of the proposed schemes are evaluated on the basis of the results of statistical analyses through sufficient large number of independent runs with different number of neurons in each model as well. The comparisons of these results of proposed schemes with standard numerical and analytical solutions validate the correctness of the design models.     

Characterization of a Tryptophan 6-Halogenase from Streptomyces albus and Its Regioselectivity Determinants

Tryptophan halogenases are found in diverse organisms and catalyze regiospecific halogenation. They play an important role in the biosynthesis of halogenated indole alkaloids, which are biologically active and of therapeutic importance. Here, a tryptophan 6-halogenase (SatH) from Streptomyces albus was characterized by using a whole-cell reaction system in Escherichia coli. SatH showed substrate specificity for chloride and bromide ions, leading to regiospecific halogenation at the C6-position of l -tryptophan. In addition, SatH exhibited higher performance in bromination than that of previously reported tryptophan halogenases in the whole-cell reaction system. Through structure-based protein mutagenesis, it has been revealed that two consecutive residues, A78/V79 in SatH and G77/I78 in PyrH, are key determinants in the regioselectivity difference between tryptophan 6- and 5-halogenases. Substituting the AV with GI residues switched the regioselectivity of SatH by moving the orientation of tryptophan. These data contribute to an understanding of the key residues that determine the regioselectivity of tryptophan halogenases.     

Combined effects of wheat gluten and carboxymethylcellulose on dough rheological behaviours and gluten network of potato–wheat flour-based bread

Incorporating high level of potato flour into wheat flour enhances nutritional values of bread but induces a series of problems that lead to the decline of the bread quality. To overcome the barrier, wheat gluten and carboxymethylcellulose (CMC) were added into potato–wheat composite flour to improve dough machinability and bread quality. The rheological properties, thermo-mechanical properties and microstructures of dough were investigated. The results showed that the interaction between gluten and CMC mitigated the discontinuity of gluten matrix and gluten protein aggregation caused by the addition of potato flour, which yielded a more branched and compact gluten network. The compact three-dimensional viscoelastic structure induced improvements of gas retention capacity and dough stability, making it mimic the machinability properties of wheat flour dough. Bread qualities were apparently improved with the combined use of 4% gluten and 6% CMC, of which specific volume increased by 42.86%, and simultaneously, hardness reduced by 75.93%.     

Modeling the effect of deep traps on the capacitance–voltage characteristics of p-type Si-doped GaAs Schottky diodes grown on high index GaAs substrates

Numerical simulation, using SILVACO-TCAD, is carried out to explain experimentally observed effects of different types of deep levels on the capacitance–voltage characteristics of p-type Si-doped GaAs Schottky diodes grown on high index GaAs substrates. Two diodes were grown on (311)A and (211)A oriented GaAs substrates using Molecular Beam Epitaxy (MBE). Although, deep levels were observed in both structures, the measured capacitance–voltage characteristics show a negative differential capacitance (NDC) for the (311)A diodes, while the (211)A devices display a usual behaviour. The NDC is related to the nature and spatial distribution of the deep levels, which are characterized by the Deep Level Transient Spectroscopy (DLTS) technique. In the (311)A structure only majority deep levels (hole traps) were observed while both majority and minority deep levels were present in the (211)A diodes. The simulation, which calculates the capacitance–voltage characteristics in the absence and presence of different types of deep levels, agrees well with the experimentally observed behaviour.     

Design,Synthesis, and Self-Assembly Studies of a Suite of Monodisperse,Facially Amphiphilic,Protein–Dendron Conjugates

The custom design of protein–dendron amphiphilic macromolecules is at the forefront of macromolecular engineering. Macromolecules with this architecture are very interesting because of their ability to self-assemble into various biomimetic nanoscopic structures. However, to date, there are no reports on this concept due to technical challenges associated with the chemical synthesis. Towards that end, herein, a new chemical methodology for the modular synthesis of a suite of monodisperse, facially amphiphilic, protein–dendron bioconjugates is reported. Benzyl ether dendrons of different generations (G1–G4) are coupled to monodisperse cetyl ethylene glycol to form macromolecular amphiphilic activity-based probes (AABPs) with a single protein reactive functionality. Micelle-assisted protein labeling technology is utilized for site-specific conjugation of macromolecular AABPs to globular proteins to make monodisperse, facially amphiphilic, protein–dendron bioconjugates. These biohybrid conjugates have the ability to self-assemble into supramolecular protein nanoassemblies. Self-assembly is primarily mediated by strong hydrophobic interactions of the benzyl ether dendron domain. The size, surface charge, and oligomeric state of protein nanoassemblies could be systematically tuned by choosing an appropriate dendron or protein of interest. This chemical method discloses a new way to custom-make monodisperse, facially amphiphilic, protein–dendron bioconjugates.