Heterostructured electrode with concentration gradient shell for highly efficient oxygen reduction at low temperature

Heterostructures of oxides have been widely investigated in optical, catalytic and electrochemical applications, because the heterostructured interfaces exhibit pronouncedly different transport, charge, and reactivity characteristics compared to the bulk of the oxides. Here we fabricated a three-dimensional (3D) heterostructured electrode with a concentration gradient shell. The concentration gradient shell with the composition of Ba0.5-xSr0.5-yCo0.8Fe0.2O3-δ (BSCF-D) was prepared by simply treating porous Ba0.5Sr0.5Co0.8Fe0.2O3-δ (BSCF) backbone with microwave-plasma. Electrochemical impedance spectroscopy reveals that the oxygen surface exchange rate of the BSCF-D is enhanced by ~250% that of the pristine BSCF due to the appearance of the shell. The heterostructured electrode shows an interfacial resistance as low as 0.148 Ω cm2 at 550°C and an unchanged electrochemical performance after heating treatment for 200 h. This method offers potential to prepare heterostructured oxides not only for electrochemical devices but also for many other applications that use ceramic materials

A Sodium Leak Current Regulates Pacemaker Activity of Adult Central Pattern Generator Neurons in Lymnaea Stagnalis

The resting membrane potential of the pacemaker neurons is one of the essential mechanisms underlying rhythm generation. In this study, we described the biophysical properties of an uncharacterized channel (U-type channel) and investigated the role of the channel in the rhythmic activity of a respiratory pacemaker neuron and the respiratory behaviour in adult freshwater snail Lymnaea stagnalis. Our results show that the channel conducts an inward leak current carried by Na+ (ILeak-Na). The ILeak-Na contributed to the resting membrane potential and was required for maintaining rhythmic action potential bursting activity of the identified pacemaker RPeD1 neurons. Partial knockdown of the U-type channel suppressed the aerial respiratory behaviour of the adult snail in vivo. These findings identified the Na+ leak conductance via the U-type channel, likely a NALCN-like channel, as one of the fundamental mechanisms regulating rhythm activity of pacemaker neurons and respiratory behaviour in adult animals

Mono-dispersed Functional Polymeric Nanocapsules with Multi-lacuna via Soapless Microemulsion Polymerization with Spindle-like α-Fe2O3Nanoparticles as Templates

The mono-dispersed crosslinked polymeric multi-lacuna nanocapsules (CP(St–OA) nanocapsules) about 40 nm with carboxylic groups on their inner and outer surfaces were fabricated in the present work. The small conglomerations of the oleic acid modified spindle-like α-Fe2O3nanoparticles (OA–Fe2O3) were encapsulated in the facile microemulsion polymerization with styrene (St) as monomer and divinyl benzene (DVB) as crosslinker. Then the templates, small conglomerations of OA–Fe2O3, were etched with HCl in tetrahydrofuran (THF). The surface carboxylic groups of the crosslinked polymeric multi-lacuna nanocapsules were validated by the Zeta potential analysis

Carbene footprinting accurately maps binding sites in protein–ligand and protein–protein interactions

Specific interactions between proteins and their binding partners are fundamental to life processes. The ability to detect protein complexes, and map their sites of binding, is crucial to understanding basic biology at the molecular level. Methods that employ sensitive analytical techniques such as mass spectrometry have the potential to provide valuable insights with very little material and on short time scales. Here we present a differential protein footprinting technique employing an efficient photo-activated probe for use with mass spectrometry. Using this methodology the location of a carbohydrate substrate was accurately mapped to the binding cleft of lysozyme, and in a more complex example, the interactions between a 100 kDa, multi-domain deubiquitinating enzyme, USP5 and a diubiquitin substrate were located to different functional domains. The much improved properties of this probe make carbene footprinting a viable method for rapid and accurate identification of protein binding sites utilizing benign, near-UV photoactivation

A combined model reduction algorithm for controlled biochemical systems

Background: Systems Biology continues to produce increasingly large models of complex biochemical reaction networks. In applications requiring, for example, parameter estimation, the use of agent-based modelling approaches, or real-time simulation, this growing model complexity can present a significant hurdle. Often, however, not all portions of a model are of equal interest in a given setting. In such situations methods of model reduction offer one possible approach for addressing the issue of complexity by seeking to eliminate those portions of a pathway that can be shown to have the least effect upon the properties of interest. Methods: In this paper a model reduction algorithm bringing together the complementary aspects of proper lumping and empirical balanced truncation is presented. Additional contributions include the development of a criterion for the selection of state-variable elimination via conservation analysis and use of an ‘averaged’ lumping inverse. This combined algorithm is highly automatable and of particular applicability in the context of ‘controlled’ biochemical networks. Results: The algorithm is demonstrated here via application to two examples; an 11 dimensional model of bacterial chemotaxis in Escherichia coli and a 99 dimensional model of extracellular regulatory kinase activation (ERK) mediated via the epidermal growth factor (EGF) and nerve growth factor (NGF) receptor pathways. In the case of the chemotaxis model the algorithm was able to reduce the model to 2 state-variables producing a maximal relative error between the dynamics of the original and reduced models of only 2.8% whilst yielding a 26 fold speed up in simulation time. For the ERK activation model the algorithm was able to reduce the system to 7 state-variables, incurring a maximal relative error of 4.8%, and producing an approximately 10 fold speed up in the rate of simulation. Indices of controllability and observability are additionally developed and demonstrated throughout the paper. These provide insight into the relative importance of individual reactants in mediating a biochemical system’s input-output response even for highly complex networks. Conclusions: Through application, this paper demonstrates that combined model reduction methods can produce a significant simplification of complex Systems Biology models whilst retaining a high degree of predictive accuracy. In particular, it is shown that by combining the methods of proper lumping and empirical balanced truncation it is often possible to produce more accurate reductions than can be obtained by the use of either method in isolation

A new multi-anticipative car-following model with consideration of the desired following distance

We propose in this paper an extension of the multi-anticipative optimal velocity car-following model to consider explicitly the desired following distance. The model on the following vehicle’s acceleration is formulated as a linear function of the optimal velocity and the desired distance, with reaction-time delay in elements. The linear stability condition of the model is derived. The results demonstrate that the stability of traffic flow is improved by introducing the desired following distance, increasing the time gap in the desired following distance or decreasing the reaction-time delay. The simulation results show that by taking into account the desired following distance as well as the optimal velocity, the multi-anticipative model allows longer reaction-time delay in achieving stable traffic flows

The Beneficial Effects of Antifreeze Proteins in the Vitrification of Immature Mouse Oocytes

Antifreeze proteins (AFPs) are a class of polypeptides that permit organismal survival in sub-freezing environments. The purpose of this study was to investigate the effect of AFP supplementation on immature mouse oocyte vitrification. Germinal vesicle-stage oocytes were vitrified using a two-step exposure to equilibrium and vitrification solution in the presence or absence of 500 ng/mL of AFP III. After warming, oocyte survival, in vitro maturation, fertilization, and embryonic development up to the blastocyst stage were assessed. Spindle and chromosome morphology, membrane integrity, and the expression levels of several genes were assessed in in vitro matured oocytes. The rate of blastocyst formation was significantly higher and the number of caspase-positive blastomeres was significantly lower in the AFP-treated group compared with the untreated group. The proportion of oocytes with intact spindles/chromosomes and stable membranes was also significantly higher in the AFP group. The AFP group showed increased Mad2, Hook-1, Zar1, Zp1, and Bcl2 expression and lower Eg5, Zp2, Caspase6, and Rbm3 expression compared with the untreated group. Supplementation of the vitrification medium with AFP has a protective effect on immature mouse oocytes, promoting their resistance to chilling injury. AFPs may preserve spindle forming ability and membrane integrity at GV stage. The fertilization and subsequent developmental competence of oocytes may be associated with the modulation of Zar1, Zp1/Zp2, Bcl2, Caspase6, and Rbm3

Methods of model reduction for large-scale biological systems: a survey of current methods and trends

Complex models of biochemical reaction systems have become increasingly common in the systems biology literature. The complexity of such models can present a number of obstacles for their practical use, often making problems difficult to intuit or computationally intractable. Methods of model reduction can be employed to alleviate the issue of complexity by seeking to eliminate those portions of a reaction network that have little or no effect upon the outcomes of interest, hence yielding simplified systems that retain an accurate predictive capacity. This review paper seeks to provide a brief overview of a range of such methods and their application in the context of biochemical reaction network models. To achieve this, we provide a brief mathematical account of the main methods including timescale exploitation approaches, reduction via sensitivity analysis, optimisation methods, lumping, and singular value decomposition-based approaches. Methods are reviewed in the context of large-scale systems biology type models, and future areas of research are briefly discussed