Recent advances and challenges in the recovery and purification of cellular exosomes

Exosomes are nanovesicles secreted by most cellular types that carry important biochemical compounds throughout the body with different purposes, playing a preponderant role in cellular communication. Because of their structure, physicochemical properties and stability, recent studies are focusing in their use as nanocarriers for different therapeutic compounds for the treatment of different diseases ranging from cancer to Parkinson's disease. However, current bioseparation protocols and methodologies are selected based on the final exosome application or intended use and present both advantages and disadvantages when compared among them. In this context, this review aims to present the most important technologies available for exosome isolation while discussing their advantages and disadvantages and the possibilities of being combined with other strategies. This is critical since the development of novel exosome‐based therapeutic strategies will be constrained to the effectiveness and yield of the selected downstream purification methodologies for which a thorough understanding of the available technological resources is needed.     

Simulation of the nonlinear vibration of a string using the Cellular Automata based on the reflection rule

In this study, the nonlinear dynamic responses of a string are simulated using the Cellular Automata method based on the reflection rule. In the case of nonlinear systems, the velocity of wave propagation is not constant and depends on the amplitude. A new treatment of the dynamic time step is proposed for the Cellular Automata method considering the effect of the propagation velocity. As numerical examples, first, the dynamic responses of a string with linear characteristic are simulated using the Cellular Automata method. A typical resonance curve can be obtained. Second, the dynamic responses of a string with nonlinear characteristic are simulated using the proposed method. Some characteristic types of vibration can be obtained. It is concluded that the linear and nonlinear dynamic responses of a string may be obtained by simulation using the Cellular Automata method.     

Influence of surfactant and lipid chain length on the solubilisation of phosphatidylcholine vesicles by micelles comprised of polyoxyethylene sorbitan monoesters

Photon correlation spectroscopy and freeze-fracture electron microscopy have been used to determine the ability of a range of micelle-forming, polyoxyethylene (20) sorbitan monoesters (Tweens) to solubilise vesicles prepared from phosphatidylcholines of different acyl chain lengths and degrees of saturation with a view to rationalising (in terms of their membrane toxicity) which of the micelle-forming surfactants to use as drug delivery vehicles. The phosphatidylcholines used were dimyristoyl-, dipalmitoyl-, distearoyl- and dioleoylphosphatidylcholine (DMPC, DPPC, DSPC and DOPC, respectively) while the nonionic polyoxyethylene sorbitan monoesters studied were polyoxyethylene (20) sorbitan monolaurate (Tween 20), a 9:1 weight ratio mixture of polyoxyethylene (20) sorbitan monopalmitate and monostearate (Tween 40), a 1:1 weight ratio mixture of polyoxyethylene (20) sorbitan monopalmitate and monostearate (Tween 60), and polyoxyethylene (20) sorbitan monooleate (Tween 80). The ability of the Tween micelles to solubilise phospholipid vesicles was found to depend both upon the length of the surfactant acyl chain and the length of the acyl chains of the phospholipid comprising the vesicle. Vesicles composed of long saturated diacyl chain phospholipids, namely DSPC and DPPC, were the most resistant to solubilisation, while those prepared from the shorter acyl chained DMPC were more readily solubilised. In terms of their solubilisation behaviour, vesicles made from phospholipids containing long, unsaturated acyl chains, namely DOPC behaved more akin to those vesicles prepared from DMPC. None of the Tween surfactants were effective at solubilising vesicles prepared from DPPC or DSPC. In contrast, there were clear differences in the ability of the various surfactants to solubilise vesicles prepared from DMPC and DOPC, in that micelles formed from Tween 20 were the most effective solubilising agent while those formed by Tween 60 were the least effective. As a consequence of these observations it was considered that Tween 60 was the surfactant least likely to cause membrane damage in vivo and, therefore, is the most suitable surfactant for use as a micellar drug delivery vehicle.     

具有时滞的细胞神经网络的全局指数稳定性

利用Liapunov函数方法,结合积分不等式技巧,分析了时滞细胞神经网络的平衡点存在的唯一性和全局指数稳定性,保证时滞细胞神经网络全局指数稳定的一个新的充分判据被得到.所得判据比已有文献具有更少的限制,为实际应用提供了方便.     

A cellular automaton technique for modelling of a binary dendritic growth with convection

A two-dimensional model for the simulation of a binary dendritic growth with convection has been developed in order to investigate the effects of convection on dendritic morphologies. The model is based on a cellular automaton (CA) technique for the calculation of the evolution of solid/liquid (s/l) interface. The dynamics of the interface controlled by temperature, solute diffusion and Gibbs–Thomson effects, is coupled with the continuum model for energy, solute and momentum transfer with liquid convection. The solid fraction is calculated by a governing equation, instead of some approximate methods such as lever rule method [A. Jacot, M. Rappaz, Acta Mater. 50 (2002) 1909–1926.] or interface velocity method [L. Nastac, Acta Mater. 47 (1999) 4253; L. Beltran-Sanchez, D.M. Stefanescu, Mat. and Mat. Trans. A 26 (2003) 367.]. For the dendritic growth without convection, mesh independency of simulation results is achieved. The simulated steady-state tip velocity are compared with the predicted values of LGK theory [Lipton, M.E. Glicksmanm, W. Kurz, Metall. Trans. 18(A) (1987) 341.] as a function of melt undercooling, which shows good agreement. The growth of dendrite arms in a forced convection has been investigated. It was found that the dendritic growth in the upstream direction was amplified, due to larger solute gradient in the liquid ahead of the s/l interface caused by melt convection. In the isothermal environment, the calculated results under very fine mesh are in good agreement with the Oseen–Ivanstov solution for the concentration-driven growth in a forced flow.     

Widrow-cellular neural network and optoelectronic implementation

A new type of optoelectronic cellular neural network has been developed by providing the capability of coefficients adjusment of cellular neural network (CNN) using Widrow based perceptron learning algorithm. The new supervised cellular neural network is called Widrow-CNN. Despite the unsupervised CNN, the proposed learning algorithm allows to use the Widrow-CNN for various image processing applications easily. Also, the capability of CNN for image processing and feature extraction has been improved using basic joint transform correlation architecture. This hardware application presents high speed processing capability compared to digital applications. The optoelectronic Widrow-CNN has been tested for classic CNN feature extraction problems. It yields the best results even in case of hard feature extraction problems such as diagonal line detection and vertical line determination.     

Emergence of self-replicating structures in a cellular automata space

Past cellular automata models of self-replication have always been initialized with an original copy of the structure that will replicate, and have been based on a transition function that only works for a single, specific structure. This article demonstrates for the first time that it is possible to create cellular automata models in which a self-replicating structure emerges from an initial state having a random density and distribution of individual components. These emergent self-replicating structures employ a fairly general rule set that can support the replication of structures of different sizes and their growth from smaller to larger ones. This rule set also allows “random” interactions of self-replicating structures with each other and with other structures within the cellular automata space. Systematic simulations show that emergence and growth of replicants occurs often and is essentially independent of the cellular space size, initial random pattern of components, and initial density of components, over a broad range of these parameters. The number of replicants and the total number of components they incorporate generally approach quasi-stable values with time.     

A graph theory approach to subcontracting, machine duplication and intercell moves in cellular manufacturing

We address in this paper the problem of finding an optimal strategy for dealing with bottleneck machines and bottleneck parts in the cell formation process in group technology. Three types of economic decisions are considered: subcontracting, machine duplication and intercell moves. The problem is formulated as a minimum weighted node covering problem in a hypergraph, and we show that it can be solved in polynomial time by finding a maximum weighted stable set in a bipartite graph. We extend this result to cellular manufacturing systems in which the sequence of operations of each part is known in advance.