Endoplasmic reticulum stress and autophagy in cerebral ischemia/reperfusion injury:PERK as a potential target for intervention

Several studies have shown that activation of unfolded protein response and endoplasmic reticulum(ER)stress plays a crucial role in severe cerebral ischemia/reperfusion injury.Autophagy occurs within hours after cerebral ischemia,but the relationship between ER stress and autophagy remains unclear.In this study,we established experimental models using oxygen-glucose deprivation/reoxygenation in PC12 cells and primary neurons to simulate cerebral ischemia/reperfusion injury.We found that prolongation of oxygen-glucose deprivation activated the ER stress pathway protein kinase-like endoplasmic reticulum kinase(PERK)/eukaryotic translation initiation factor 2 subunit alpha(e IF2α)-activating transcription factor 4(ATF4)-C/EBP homologous protein(CHOP),increased neuronal apoptosis,and induced autophagy.Furthermore,inhibition of ER stress using inhibitors or by si RNA knockdown of the PERK gene significantly attenuated excessive autophagy and neuronal apoptosis,indicating an interaction between autophagy and ER stress and suggesting PERK as an essential target for regulating autophagy.Blocking autophagy with chloroquine exacerbated ER stress-induced apoptosis,indicating that normal levels of autophagy play a protective role in neuronal injury following cerebral ischemia/reperfusion injury.Findings from this study indicate that cerebral ischemia/reperfusion injury can trigger neuronal ER stress and promote autophagy,and suggest that PERK is a possible target for inhibiting excessive autophagy in cerebral ischemia/reperfusion injury.

Machine learning of turbulent transport in fusion plasmas with neural network

Turbulent transport resulting from drift waves,typically,the ion temperature gradient(ITG)mode and trapped electron mode(TEM),is of great significance in magnetic confinement fusion.It is also well known that turbulence simulation is a challenging issue in both the complex physical model and huge CPU cost as well as long computation time.In this work,a credible turbulence transport prediction model,extended fluid code(ExFC-NN),based on a neural network(NN)approach is established using simulation data by performing an ExFC,in which multi-scale multi-mode fluctuations,such as ITG and TEM turbulence are involved.Results show that the characteristics of turbulent transport can be successfully predicted including the type of dominant turbulence and the radial averaged fluxes under any set of local gradient parameters.Furthermore,a global NN model can well reproduce the radial profiles of turbulence perturbation intensities and fluxes much faster than existing codes.A large number of comparative predictions show that the newly constructed NN model can realize rapid experimental analysis and provide reference data for experimental parameter design in the future.

H_(2)S^(+)在325nm附近的光解动力学

本文通过研究H_(2)S^(+)的光解动力学,结合时间切片离子速度成像技术和高精度的理论计算,获得了解离波长从3.25158×10^(2)nm到3.25307×10^(2)nm范围内,对应的正离子激发态为H_(2)S^(+)A_(2)A_(1)(0,13,0)K=1态的高分辨离子速度影像.基于离子速度影像获得了不同解离波长下转动态分辨的产物总平动能谱及产物角分布能谱.从实验结果中可以清楚地观察到产物转动态分布和角分布各向异性渗数随着光解波长改变.结合理论计算得到的全维势能面推测光解过程中发挥关键作用的是离子在C2v对称性下A_(2)A_(1)和B_(2)B_(2)态的非绝热耦合以及Cg对称性下在锥形交叉区域的弛豫.

Influence of physiological and environmental factors on the diurnal variation in emissions of biogenic volatile compounds from Pinus tabuliformis

Biological volatile organic compounds(BVOCs) have a large influence on atmospheric environmental quality, climate change and the carbon cycle. This study assesses the composition and diurnal variation in emission rates of BVOCs from Pinus tabuliformis, using an enclosure technique. Environmental parameters(temperature and light intensity) and physiological parameters(net photosynthetic rate, P_n; stomatal conductance, g_s; intercellular CO_2 concentration, C_i; and transpiration rate, T_r) that may affect emission behavior were continuously monitored. The 10 most abundant compound groups emitted by P. tabuliformis were classified by gas chromatography–mass spectrometry. The dominant monoterpenoid compounds emitted were α-pinene, β-myrcene, α-farnesene and limonene. The diurnal emission rate of BVOCs changed with temperature and light intensity, with dynamic analysis of BVOCs emissions revealing that their emission rates were more affected by temperature than light. The variation in monoterpene emission rates was consistent with estimates of P_n, g_s and T_r. Basal emission rates(at 30 °C,) of the main BVOCs ranged from 0.006 to 0.273 μg^(-1)/(hr g),while the basal ER standardization coefficients ranged from 0.049 to 0.144 °C^(-1). Overall, these results provide a detailed reference for the effective selection and configuration of tree species to effectively prevent and control atmospheric pollution.