Mycoplasma pneumoniae induces IL-1β production through activating NLRP3 inflammasome by ROS in RAW264.7 cells

AIM: To investigate whether Mycoplasma pneumoniae (Mp)-induced interleukin-1β (IL-1β) production in RAW264.7 cells is through the activation of NLRP3 inflammasome via reactive oxygen species (ROS). ME-THODS: RAW264.7 cells were randomly divided into 3 groups. In normal group, RAW264.7 cells were treated without Mp. In model group, RAW264.7 cells were treated with 1∶ 10 multiplicity of infection (MOI) of Mp. In NAC group, RAW264.7 cells were pretreated with N- acetylcysteine (NAC) at a concentration of 5 mmol/L for 30 min before infection with Mp. The RAW264.7cells were infected with Mp (1∶ 10 MOI) for 4, 8, 16 and 24 h in model group and NAC group, respectively. The intracellular ROS level was analyzed by flow cytometry. The mRNA expressions of NLRP3, ASC and caspase-1 were detected by real-time PCR. The protein levels of NLRP3, ASC and caspase-1 p20 were determined by Western blot. The levels of pro-inflammatory cytokine IL-1β in the supernatant were measured by ELISA. RESULTS: Compared with normal group, the production of ROS were significantly increased at 4, 8, 16 and 24 h after infection, the mRNA expression of NLRP3, ASC and caspase-1 were increased at 8, 16 and 24 h after infection, the protein levels of NLRP3, ASC and caspase-1 p20 were increased at 16 and 24 h after infection, and the releases of IL-1β were increased at 24 h after infection in model group (P<0.01). Compared with the model group, the level of ROS in NAC group decreased, so as the expression of NLRP3, ASC and caspase-1 at mRNA and protein levels and the releases of IL-1β in the supernatant at the corresponding time points. CONCLUSION: Mp may stimulate the ROS production to activate NLRP3 inflammasome in RAW264.7 cells.     

大型喷杆喷雾机钟摆式主被动悬架自适应鲁棒控制研究

针对大型喷雾机喷杆钟摆式主被动悬架系统存在的参数不确定性和随机干扰导致控制精度低、稳定性差的问题，对基于模型补偿的自适应鲁棒控制算法进行研究。建立了钟摆式主被动悬架的非线性动力学模型和调节机构几何方程，基于模型设计了自适应鲁棒控制器，综合悬架系统和电液位置伺服系统模型中存在的参数不确定性，同时兼顾系统未补偿的摩擦力和外部扰动等不确定非线性因素，通过理论分析和试验证明，在同时存在模型参数不确定和不确定非线性的情况下，设计的控制器可以保证系统输出跟踪控制的暂态性能和稳态精度。以单出杆液压作动器驱动的28m大型喷杆主被动悬架为例，借助建立的大型喷杆悬架半实物仿真平台进行了控制算法的试验验证，并使用Stewart六自由度运动平台模拟底盘的运动干扰，与反馈线性化控制器、鲁棒反馈控制器、PID控制器进行了试验对比，结果表明，设计的基于模型补偿的自适应鲁棒控制器最大跟踪误差0.148°，而反馈线性化控制器最大跟踪误差0.201°，鲁棒反馈控制器最大跟踪误差0.51°，PID控制器最大跟踪误差0.48°。设计的控制器在同时存在参数不确定性和扰动的情况下，使用较小的反馈增益能够保证渐进跟踪性能和稳态跟踪精度。     

不同贮藏温度结合热处理对黄瓜品质及生理生化指标的影响

利用二次回归正交旋转组合设计测出的不同贮藏温度（2、4和8℃）下各自对应的最佳热处理条件，研究不同贮藏温度（2、4和8℃）结合其对应的最佳热处理条件对贮藏期间黄瓜果实品质及生理生化指标的影响，分别对该贮藏条件下黄瓜果实的冷害、硬度、失重率、多酚氧化酶(PPO)、可溶性蛋白、过氧化氢酶(CAT)、过氧化物酶(POD)、H₂O₂、超氧阴离子自由基O^2-?、ASA和GSH含量进行测定。结果表明，热处理可以抑制冷害，而热处理结合4℃低温贮藏可以有效地抑制黄瓜果实硬度和失重率的下降，延缓过氧化物酶(POD)、多酚氧化酶(PPO)活性的上升，抑制H₂O₂和超氧阴离子自由基O^2-?的上升，对黄瓜的褐变有显著抑制作用，延缓抗坏血酸的下降，维持还原性谷胱甘肽(GSH)的含量，有利于调节活性氧系统的平衡。研究表明，在4℃贮藏条件下，黄瓜的热水处理条件为39.4℃、24.3 min时，可延缓黄瓜果实的衰老，较好地保持了果实的品质。     

Cultivar Specific Response of CO2 Fertilization on Two Tropical Mung Bean (Vigna radiata L.) Cultivars: ROS Generation,Antioxidant Status,Physiology, Growth,Yield and Seed Quality

Increasing atmospheric carbon dioxide concentration (CO₂) is an important component of global climate change that will have a significant impact on the productivity of crop plants. In recent years, growth and yield of agricultural crop plants have been shown to increase with elevated CO₂ (EC) and have enticed considerable interest due to variation in the response of crop plants. In this study, comparative response of two mung bean cultivars (HUM‐2 and HUM‐6) was evaluated against EC at different growth stages under near‐natural conditions for two consecutive years. The plants were grown in ambient as well as EC (700 ppm) in specially designed open‐top chambers. Under elevated CO₂, marked down‐regulation of reactive oxygen species (ROS) levels, membrane disruption and activities of superoxide dismutase and catalase were noticed in both the cultivars, but the extent of reduction was more in HUM‐6. As compared to ambient CO₂, EC increased total chlorophyll, photosynthetic rate, growth and yield parameters. Cultivar‐specific response was noticed as HUM‐6 showed higher increase in yield attributes than HUM‐2. Under CO₂ treatment, soluble protein and reducing sugars decreased while total soluble sugars and starch showed an opposite trend. Principal component analysis showed that both the cultivars responded more or less similarly to EC in their respective groupings of physiological and growth parameters, but the magnitude of ROS and antioxidative enzymes was variable. The experimental findings depict that both the cultivars of mung bean showed contrasting response against EC and paved the way for selecting the suitable cultivar having higher productivity in a future high‐CO₂ environment.     

灰霉菌侵染对番茄幼苗活性氧积累及抗氧化酶活性的影响

为进一步分析活性氧和抗氧化防御系统在番茄抗病信号调控机制中的作用,为提高产量和品质提供科学依据,以4叶1心的番茄幼苗为试验材料,比较番茄幼苗受灰霉菌侵染后叶片O_2~-·以及抗氧化酶、内源褪黑素等的变化。结果表明:番茄幼苗接种灰霉菌后,随着时间的延长,幼苗叶片上病斑斑点逐渐增多,灰霉菌含量显著增多,叶色逐渐变浅,植株表现明显的发病症状;灰霉病菌侵染后番茄体内O_2~-·活性爆发,超氧化物歧化酶(SOD)和过氧化物酶(POD)活性下降,过氧化氢酶(CAT)和谷胱甘肽还原酶(GR)活性上升,褪黑素含量增加;上述变化都是番茄幼苗为了抵御灰霉菌的生物胁迫而发生的应激反应。综上,植物在遭受病原菌等生物胁迫时不能简单地推断SOD、CAT和POD等抗氧化酶活性一定升高,植物抵御病原菌侵染更多地依赖于抗性信号路径中信号物质的激活和积累。     

基于改进极限学习机的水体溶解氧预测方法

为了有效地指导水产养殖生产，提高溶解氧浓度预测的精度，提出了基于因子筛选和改进极限学习机（Extreme Learning Machine，ELM）的水产养殖溶解氧预测模型。首先，利用皮尔森相关系数法计算各影响因子与溶解氧浓度间的相关系数，提取强关联因子，降低预测模型的输入量维度；采用偏最小二乘算法（Partial Least Square, PLS）优化传统ELM神经网络，避免网络中隐含层共线性问题，保障输出权值的稳定性；然后，结合新型激活函数，构建水体溶解氧浓度预测模型。最后，将SPLS-ELM（Selection Based Partial Least Square Optimized Extreme Learning Machine）预测模型应用到江苏省无锡市南泉基地某试验池塘的水体溶解氧预测中。试验结果表明：该模型的预测均方根误差为0.3232，与最小二乘支持向量机（Least Square Support Vector Machine，LSSVM）、BP神经网络、粒子群（Particle Swarm Optimization，PSO）优化LSSVM和遗传算法（Genetic Algorithm, GA）优化BP神经网络相比分别降低40.98%、44.48%、34.73%和44.18%。且该模型的运行时间仅0.6231s，预测精度和运行效率明显优于其他模型。该模型的溶解氧预测曲线接近真实溶解氧变化曲线，能够满足水产养殖实际生产对水体溶解氧预测的要求。     

果蔬籽油生物活性研究进展

果蔬籽油是由果蔬籽经压榨或萃取工艺制得的植物油脂。果蔬籽油含有丰富的维生素、多不饱和脂肪酸、有机酸等活性成分,这些成分赋予了果蔬籽油抗氧化、抗癌、调节血脂和调节免疫系统等生物活性。本文综述了果蔬籽油生物活性的研究进展,旨在为果蔬籽油的综合开发和利用提供理论依据和指导。     

Establishment and Optimization of INH Epitope Peptide Vaccine for Detection of Antibody

In this study, an indirect ELISA method was established to detect inhibin hormone (INH) epitope peptide vaccine antibody, it would provide oretical reference for the determination of Fine-wool sheep after active immune body INH epitope peptide vaccine antibody. On the basis of the predecessors, using indirect ELISA method to determinate serum INH epitope peptide antibody levels of sheep, and through control different experimental conditions to look for the best experimental conditions. Through explorating the experimental conditions, finally, the testing experiment conditions were determined, which was blocked solution with skimmed milk powder, INH and GnIH synthetic peptides dilution degrees for 20 000 times, the optimum reaction time was 60 min, the best color action time was 15 min. In this experiment, a kind of method to detection antibody in the body after INH active immune sheep was built, it would provide a reference for future research.     

Simulation of future dissolved oxygen distribution in pond culture based on sliding window-temporal convolutional network and trend surface analysis

Dissolved oxygen (DO) is a key ecological factor to measure the quality of water in the aquaculture. As the pond water body is affected by the breeding environment, the spatial distribution of DO shows a certain law in the entire pond. Therefore, to simulate the distribution of DO in aquaculture waters and grasp the temporal and spatial variation of DO is the key to achieving precise regulation of DO. For this purpose, this paper proposed a method for simulating the temporal and spatial distribution of DO in pond culture based on a sliding window-temporal convolutional network together with trend surface analysis (SW-TCN-TSA). This paper first utilized SW to construct DO data sets with different prediction durations, and then used the improved TCN model to realize one-dimensional time series prediction for DO at single monitoring point. Based on the prediction results of DO, a TSA method was performed on the predicted values of DO at the extreme moments of all discrete monitoring points, so as to realize the simulation of the temporal and spatial distribution of DO in the pond. Experimental results show that the SW-TCN model has better prediction performance for one-dimensional time series prediction of DO. Compared with traditional deep networks, such as CNN, GRU, LSTM, CNN-GRU and CNN-LSTM, the values of evaluation indicators (MSE, MAE and RMSE) have been greatly improved. In the process of trend surface fitting, all fitting R² of DO at different water depths are higher than 0.9, indicating that the TSA can accurately reflect the temporal and spatial distribution of DO. This method can provide a basis for the prediction and early warning of DO in the three-dimensional space of the pond and has high practicability in aquaculture.     

基于氧同位素的玉米农田蒸散发估算和区分

农田蒸散发(evapotranspiration,ET)的估算和区分是土壤-植物-大气连续体中的重要研究内容,是农业水资源高效利用的重要基础。该研究分析了土壤水、蒸发水汽、蒸腾水汽和大气背景混合水汽氧同位素组成分布特征,并采用2种同位素的方法对玉米农田蒸散发进行估算和区分:1)结合Keeling plot和Craig-Gordon模型的同位素方法(Iso-CG);2)基于土壤水同位素守恒和水量平衡的方法(Iso-WB)。结果表明,在玉米生育期内Iso-WB方法与Iso-CG方法所计算的玉米蒸腾比例分别为0.64~0.91和0.52~0.91,平均值分别为0.80和0.78。玉米蒸散发总量在前期、中期和后期均值分别为3.95、5.30和4.98 mm/d。通过比较参数并与前人研究结果对比分析,表明采用Iso-CG方法估算区分ET相对精确,采用Iso-WB方法计算蒸散发要求的测量精度相对较高,计算误差较大。该研究成果不仅为玉米农田制定灌溉制度及提高用水效率提供了理论依据,而且对深入探索氧同位素水文学领域具有重要意义。