Sphingosine 1-phosphate receptor 1 regulates bloodbrain barrier permeability in epileptic mice

Destruction of the blood-brain barrier is a critical component of epilepsy pathology.Several studies have demonstrated that sphingosine 1-phosphate receptor 1 contributes to the modulation of vascular integrity.However,its effect on blood-brain barrier permeability in epileptic mice remains unclear.In this study,we prepared pilocarpine-induced status epilepticus models and pentylenetetrazol-induced epilepsy models in C57BL/6 mice.S1P1 expression was increased in the hippocampus after status epilepticus,whereas tight junction protein expression was decreased in epileptic mice compared with controls.Intraperitoneal injection of SEW2871,a specific agonist of sphingosine-1-phosphate receptor 1,decreased the level of tight junction protein in the hippocampus of epileptic mice,increased blood-brain barrier leakage,and aggravated the severity of seizures compared with the control.W146,a specific antagonist of sphingosine-1-phosphate receptor 1,increased the level of tight junction protein,attenuated blood-brain barrier disruption,and reduced seizure severity compared with the control.Furthermore,sphingosine 1-phosphate receptor 1 promoted the generation of interleukin-1βand tumor necrosis factor-αand caused astrocytosis.Disruption of tight junction protein and blood-brain barrier integrity by sphingosine 1-phosphate receptor 1 was reversed by minocycline,a neuroinflammation inhibitor.Behavioral tests revealed that sphingosine 1-phosphate receptor 1 exacerbated epilepsy-associated depression-like behaviors.Additionally,specific knockdown of astrocytic S1P1 inhibited neuroinflammatory responses and attenuated blood-brain barrier leakage,seizure severity,and epilepsy-associated depression-like behaviors.Taken together,our results suggest that astrocytic sphingosine 1-phosphate receptor 1 exacerbates blood-brain barrier disruption in the epileptic brain by promoting neuroinflammation.

Centralized isolation of Helicobacter pylori from multiple centers and transport condition influences

AIM:To evaluate the efficacy of centralized culture and possible influencing factors.METHODS:From January 2010 to July 2012,66452 patients with suspected Helicobacter pylori(H.pylori) infection from 26 hospitals in Zhejiang and Jiangsu Provinces in China underwent gastrointestinal endoscopy.Gastric mucosal biopsies were taken from the antrum for culture.These biopsies were transported under natural environmental temperature to the central laboratory in Hangzhou city and divided into three groups based on their transport time:5,24 and 48 h.The culture results were reported after 72 h and the positive culture rates were analyzed by a χ2 test.An additional 5736 biopsies from H.pylori-positive patients(5646 rapid urease test-positive and 90 14C-urease breath test-positive) were also cultured for quality control in the central laboratory setting.RESULTS:The positive culture rate was 31.66%(21036/66452) for the patient samples and 71.72%(4114/5736) for the H.pylori-positive quality control specimens.In the 5 h transport group,the positiveculture rate was 30.99%(3865/12471),and 32.84%(14960/45553) in the 24 h transport group.In contrast,the positive culture rate declined significantly in the 48 h transport group(26.25%; P < 0.001).During transportation,the average natural temperature increased from 4.67 to 29.14℃,while the positive culture rate declined from 36.67%(1462/3987) to 24.12%(1799/7459).When the temperature exceeded 24℃,the positive culture rate decreased significantly,especially in the 48 h transport group(23.17%).CONCLUSION:Transportation of specimens within 24 h and below 24℃ is reasonable and acceptable for centralized culture of multicenter H.pylori samples.

Numerical simulation of a direct internal reforming solid oxide fuel cell using computational fluid dynamics method

A detailed mathematical model of a direct internal reforming solid oxide fuel cell(DIR-SOFC) incorporating with simulation of chemical and physical processes in the fuel cell is presented. The model is developed based on the reforming and electrochemical reaction mechanisms,mass and energy conservation,and heat transfer. A computational fluid dynamics(CFD) method is used for solving the complicated multiple partial differential equations(PDEs) to obtain the numerical approximations. The resulting distributions of chemical species concentrations,temperature and current density in a cross-flow DIR-SOFC are given and analyzed in detail. Further,the influence between distributions of chemical species concentrations,temperature and current density during the simulation is illustrated and discussed. The heat and mass transfer,and the kinetics of reforming and electrochemical reactions have significant effects on the parameter distributions within the cell. The results show the particular characteristics of the DIR-SOFC among fuel cells,and can aid in stack design and control.

A maximum power point tracker for photovoltaic energy systems based on fuzzy neural networks

To extract the maximum power from a photovoltaic(PV) energy system,the real-time maximum power point(MPP) of the PV array must be tracked closely. The non-linear and time-variant characteristics of the PV array and the non-linear and non-minimum phase characteristics of a boost converter make it difficult to track the MPP for traditional control strategies. We propose a fuzzy neural network controller(FNNC),which combines the reasoning capability of fuzzy logical systems and the learning capability of neural networks,to track the MPP. With a derived learning algorithm,the parameters of the FNNC are updated adaptively. A gradient estimator based on a radial basis function neural network is developed to provide the reference information to the FNNC. Simulation results show that the proposed control algorithm provides much better tracking performance compared with the fuzzy logic control algorithm.

Predictive control of a direct internal reforming SOFC using a self recurrent wavelet network model

In this paper,an application of a nonlinear predictive controller based on a self recurrent wavelet network (SRWN) model for a direct internal reforming solid oxide fuel cell (DIR-SOFC) is presented. As operating temperature and fuel utilization are two important parameters,the SOFC is identified using an SRWN with inlet fuel flow rate,inlet air flow rate and current as inputs,and temperature and fuel utilization as outputs. To improve the operating performance of the DIR-SOFC and guarantee proper operating conditions,the nonlinear predictive control is implemented using the off-line trained and on-line modified SRWN model,to manipulate the inlet flow rates to keep the temperature and the fuel utilization at desired levels. Simulation results show satisfactory predictive accuracy of the SRWN model,and demonstrate the excellence of the SRWN-based predictive controller for the DIR-SOFC.

基于遗传算法优化最小二乘支持向量回归机的平板型固体氧化物燃料电池的控制相关动态辨识建模（英文）

研究目的:为了同时预测固体氧化物燃料电池(SOFC)的电压、温度动态特性和设计控制器,建立SOFC的控制相关动态辨识模型。创新要点:为了建立SOFC更精确的最小二乘支持向量回归机(LSSVR)动态模型,采用遗传算法(GA)优化LSSVR的参数。所建GA-LSSVR模型可同时预测SOFC的电压和温度动态特性。研究方法:1.分析SOFC的电化学和能量平衡子模型。2.利用所选择的最优LSSVR参数,建立了SOFC的GA-LSSVR动态辨识模型。通过仿真分析和比较,验证了所建模型的有效性(图3和4)。3.利用所建模型的预测结果,与模拟退火算法优化最小二乘支持向量回归机(SAA-LSSVR)和5折交叉验证最小二乘支持向量回归机(5FCV-LSSVR)模型的预测结果进行了比较,表明所建立的GA-LSSVR模型具有较高的预测精度(表3和4)。重要结论:通过比较SAA-LSSVR和5FCV-LSSVR模型的预测结果,发现所建GA-LSSVR模型具有较好的预测性能和精度。基于所建立的GA-LSSVR模型可进行有效的多变量控制器设计。