Protective effect of S-allyl cysteine against cerebral ischemia/reperfusion injury in experimental rats

Purpose: To investigate the protective effect of S-allyl cysteine (SAC) against cerebral ischemiareperfusion injury (CRI) in rats.Methods: The protective effect of SAC was determined in a male Wistar rat model of middle cerebral artery occlusion (MCAO)-stimulated transient focal ischemia, followed by reperfusion. Cerebral ischemia reperfusion injury was induced via 90 min of MCAO, followed by 24-h reperfusion. The cerebral infarct size was determined by staining with 2,3,5- triphenyl tetrazolium chloride. The onset of cellular derangement, neurological deficit score and neuronal oedema were determined. In addition, the expressions of CRI markers and inflammatory cytokines were measured by enzyme-linked immunosorbent assay (ELISA).Results: Rats subjected to CRI showed marked increases in cellular oxidative stress, as evidenced by significant increase in the levels of inflammatory markers, including MDA (p < 0.05), MPO (p < 0.05) and nitric oxide (p < 0.01). In addition, CRI increased the mRNA expression levels of the marker genes TLR4, syndecan-1, CSF, aquaporin-1, OCT3, and RFX1. In contrast, rats pre-treated with SAC prior to CRI displayed reduced levels of inflammatory cytokines, with a near-normal cellular arrangement. SAC treatment significantly reduced the mRNA expression levels of the marker genes in CRI rats.Conclusion: These findings suggest that SAC may protect the brain of rats from cerebral ischemiareperfusion injury caused by amplification of oxidative stress and inflammatory signaling. Thus, S-allyl cysteine is a potential therapy for the management of CRI

Dynamical Behavior of Nonautonomous Stochastic Reaction-Diffusion Neural Network Models

This brief investigates nonautonomous stochastic reaction-diffusion neural-network models with S-type distributed delays. First, the existence and uniqueness of mild solution are studied under the Lipschitz condition without the linear growth condition. Due to the existence of a nonautonomous reaction-diffusion term and the infinite dimensional Wiener process, the criteria for the well-posedness of the models are established based on the evolution system theory. Then, the S-type distributed delay, which is an infinite delay, is handled by the truncation method, and sufficient conditions for the global exponential stability are obtained by constructing a simple Lyapunov-Krasovskii functional candidate. Finally, neural-network examples and an illustrative example are given to show the applications of the obtained results.</p

Exponential Stability for a Class of Stochastic Reaction-Diffusion Hopfield Neural Networks with Delays

This paper studies the asymptotic behavior for a class of delayed reaction-diffusion Hopfield neural networks driven by finite-dimensional Wiener processes. Some new sufficient conditions are established to guarantee the mean square exponential stability of this system by using Poincaré’s inequality and stochastic analysis technique. The proof of the almost surely exponential stability for this system is carried out by using the Burkholder-Davis-Gundy inequality, the Chebyshev inequality and the Borel-Cantelli lemma. Finally, an example is given to illustrate the effectiveness of the proposed approach, and the simulation is also given by using the Matlab

STKE: Temporal Knowledge Graph Embedding in the Spherical Coordinate System

Knowledge graph embedding (KGE) aims to learn the representation of entities and predicates in low-dimensional vector spaces which can complete the missing parts of the Knowledge Graphs (KGs). Nevertheless, temporal knowledge graphs (TKGs) that include time information are more consistent with real-world application scenarios. Meanwhile, the facts with time constraints make the results of reasoning over time more accurate. Because of these, we propose a novel temporal knowledge graph embedding (TKGE) model, namely Spherical Temporal Knowledge Graph Embedding (STKE), which embeds facts into a spherical coordinate system. We treat each fact as a rotation from the subject to the object. The entities and predicates in STKE are divided into three parts--the radial part, the azimuth part, and the polar part. The radial part aims to resize the modulus between two entities. The azimuth part is mainly used to distinguish entities with the same module length and the polar part aims to represent the transformation of the time embedding with the change of polar angle. We evaluate the proposed model via the link prediction task on four typical temporal datasets. Experiments demonstrate that STKE achieves a significant surpass compared with the state-of-the-art static knowledge graph embedding (SKGE) model and TKGE model. In addition, we analyze the representation ability of different facts in the spherical coordinate system and confirm that our model can better represent time-constrained facts

Mean Square Almost Periodic Solutions for Impulsive Stochastic Differential Equations with Delays

We establish a result on existence and uniqueness on mean square almost periodic solutions for a class of impulsive stochastic differential equations with delays, which extends some earlier works reported in the literature

Modelling and Simulation of Aerostatic Thrust Bearings

This paper demonstrates the modelling and simulation comparison of the static characteristics of a porous, orifice, and multiple type aerostatic thrust bearings on the basis of load-carrying capacity(LCC) and stiffness. The equations Navier-Stokes (N-S) are used to solve the internal distribution of pressure in computational fluid dynamics(CFD) simulation environment. An axisymmetric model, which minimizes the computational time and increases efficiency, is used to evaluate the static characteristics of a porous, orifice, and multiple restrictors of aerostatic bearings. Our numerical analysis and empirical results show the agreement with the significant effect of material and geometrical parameters on the LCC and stiffness. The thickness of the air film is less than 10\mu \text{m} , the multiple orifice restrictors have more LCC than porous and orifice restrictor. The porous restrictor's stiffness is larger than orifice and multiple restrictors. The LCC of porous and orifice is notably smaller than multiple orifice restrictors. Additionally, it is analyzed that LCC of porous, orifice, and multiple orifice restrictors can be improved with an increase in the supply of air pressure

Electrochemical determination of chemical oxygen demand using Ti/TiO2 electrode.

To overcome the shortcomings of the conventional potassium dichromate method (PDM) for monitoring chemical oxygen demand (COD) of waters, many efforts have been made on developing quick and environment-friendly techniques. Among all alternatives, electrochemical (EC) techniques are very competitive due to their relatively simple devices and quickness. A number of electrodes have been fabricated to investigate electrochemical determination of COD. However, little work has been reported on Ti/TiO2 based electrode for this purpose. In the present work, Ti/Ti/TiO2 electrode was simply prepared by anodic oxidation of pure titanium. Aqueous solutions of potassium hydrogen phthalate and phenol were electrolyzed by chronocoulometry in a three-electrode system with Ti/Ti/TiO2 as working electrode (anode). Organic compounds were electrochemically oxidized on Ti/Ti/TiO2 electrode by hydroxyl radicals and the released electrons were recorded and transferred to currents. The electric currents were proportional to the COD values of the water samples being investigated. Based on data of COD values and corresponding currents, a linear regression equation was obtained for a certain kind of waste water. With the regression equation, current of an unknown water sample was transferred to its COD value. Conditions for the presented EC method were set up as cell voltage 2.0V v.s. SCE and pH 7.0. The linear range of COD was of about 25~530 mg/L. COD values of real waste water samples were measured by Ti/Ti/TiO2 electrode and the relative errors were all in the range of ±8% compared with data determined by conventional PDM. The electrochemicalmethodology was successfully applied to evaluate COD in waste water