Effects of intrauterine growth restriction during late pregnancy on the ovine fetal renal function and antioxidant capacity

This study investigated the effects of intrauterine growth restriction during late pregnancy on the ovine fetal renal function and renal antioxidant capacity. Eighteen ewes pregnant were randomly divided into control group (CG, ad libitum, 0.67 MJ ME·BW^−0.75·day⁻¹, n = 6), restricted group 1 (RG1, 0.18 MJ ME·BW^−0.75·day⁻¹, n = 6), and restricted group 2 (RG2, 0.33 MJ ME·BW^−0.75·day⁻¹, n = 6). At 140 days, the fetal blood, allantoic fluid and kidney tissue were collected to determinate fetal renal function and renal antioxidant capacity. The results showed that the fetal weight, kidney weight, superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), aquaporin-2 (AQP-2) and aquaporin-3 (AQP-3), and total antioxidant capacity (T-AOC) in RG1 group were decreased compared with the CG (P < 0.05), but the contents of β2-Microglobulin (β 2-MG), cystatin C (Cys-C), filtered sodium excretion fraction (FENa), malondialdehyde (MDA), and hydroxyl radical (OH) in RG1 group were increased (P < 0.05). The impaired ovine fetal renal growth, antioxidant imbalance and dysfunction of glomerulus ultrafiltration, and the renal tubules reabsorption were induced by maternal malnutrition during late pregnancy.     

抗生素相关性腹泻对小鼠血常规的影响

以小鼠为对象,通过抗生素混合液灌胃5 d建立小鼠肠道菌群失调模型,以等量生理盐水为对照,研究抗生素相关腹泻对小鼠血常规的影响。结果表明:抗生素相关性腹泻使小鼠血小板数量及平均体积均显著小于对照组(P0.05),红细胞分布宽度显著大于对照组(P0.05),其余各项指标均与对照组差异无统计学意义(P0.05)。这表明抗生素相关性腹泻可显著降低血小板计数、血小板平均体积和红细胞分布宽度,对小鼠的凝血功能有显著的影响。     

Histamine receptor antagonist prevent and ameliorate airway remodeling and acid-base imbalance in asthma of guinea pig

AIM:To investigate the effect of histamine receptor antagonist on airway remodeling and acid-base imbalance in asthma of guinea pig. METHODS:Guinea pigs were divided into 5 groups: the normal control group, the asthma model group, the continued asthma model group, histamine group and histamine receptor antagonist group. For each group, the content of histamine, Na+, Cl-, PaO2, PaCO2, pH, AB, SB in serum, and thickness of airway mucosa and smooth muscle cell layer were measured and compared with each other. RESULTS:(1) According to the content of histamine in serum and thickness of airway mucosa and smooth muscle, the order was: the histamine group>continued asthma model group>the asthma model group>the normal control group (P<0.01), and the histamine receptor antagonist groupthe continued asthma model group (P<0.01), but for PaCO2, the order was conversed. Airway remodeling, increase in histamine in serum, respiratory acidosis and metabolic acidosis in asthmatic guinea pig were observed. Exogenous histamine accentuated the change, however, histamine receptor antagonist attenuated it. CONCLUSION:Histamine may take part in the airway remodeling of asthma. Histamine receptor antagonist can prevent and ameliorate airway remodeling and acid-base imbalance in asthma of guinea pig.     

我国省际农林高等院校科技资源配置效率分析

基于2010~2012年各省农林高等院校的面板数据,以DEA方法测算农林高等院校的科技资源配置效率,结合各省农业总产值情况找出制约我国省际农林高等院校科技资源配置效率的关键因素。研究表明,我国省际农林高等院校科技资源的配置过程受到自上而下的各种考核制度牵引、人力资源投入结构的失衡、科技资源集中度与农业产业集中度不匹配、高校的科技园区有短板效应因素的影响。因而,要综合运用市场、政府和社会3种资源配置方式,通过3个层面的制度变迁,实现省际农林高等院校科技资源优化配置。     

国内文献传递发展不平衡性与改进途径研究

针对国内主要文献传递系统CALLS,CSDL,NSTL近几年的运行状况,结合已有的文献传递工作经验,分析文献传递发展过程中存在的制度管理、基础设施、服务方式等不平衡性因素.探讨各因素之间的因果关系与改进途径,为我国文献传递,资源共享的健康发展提供理论与技术支撑.     

营养学中氨基酸平衡的度量

本文基于聚类分析理论,提出了失衡度(IBD)这一新的化学指数,借以定量地研究蛋白质营养中的氨基酸平衡问题。当样品中氨基酸完全平衡时,IBD取值为零;而当其氨基酸平衡最差时。IBD取值为1。IBD的氨基酸增量模型为非对称最大值式;且IBD与变异系数(CV)之间有着密切的关系。通过IBD这一指数,可以对各种单一饲料的蛋白质营养价值加以分类列等;通过计算两种以上饲料蛋白质混合物的IBD,可以从理论上预测它们之间是否互补,以及何时发生最佳互补关系。若引申IBD的概念框架,还可以用来研究其它养分之间的平衡关系,并有助于实现计算机配方过程的自动鉴别和筛选。     

区域城市化战略格局下的人口再分布研究——以江西省为例

以江西省为研究区域,在人口增长和现状分析的基础上,采用了数理统计和空间分析等方法,研究了城市化发展战略对人口再分布的影响。结果显示:江西省城市化水平的区域发展不平衡,空间差异明显,赣北人口多而密,赣南人口少而稀,区域经济发展差异明显,人口发展、流动、分布特征与城市发展格局之间的矛盾突出。鉴于此,提出了人口合理再分布的对策建议。     

Coping with imbalanced data problem in digital mapping of soil classes

An unsolved problem in the digital mapping of categorical soil variables and soil types is the imbalanced number of observations, which leads to reduced accuracy and the loss of the minority class (the class with a significantly lower number of observations compared to other classes) in the final map. So far, synthetic over- and under-sampling techniques have been explored in soil science; however, more efficient approaches that do not have the drawbacks of these techniques and guarantee retention of the minority classes in the produced map are essentially required. Such approaches suggested in the present study for digital mapping of soil classes include machine learning models of ensemble gradient boosting, cost-sensitive learning and one-class classification (OCC) of the minority class combined with multi-class classification. In this regard, extreme gradient boosting (XGB) as an ensemble gradient learner, a cost-sensitive decision tree (CSDT) within the C5.0 algorithm, and a one-class support vector machine combined with multi-class classification (OCCM) were investigated to map eight soil great groups with a naturally imbalanced frequency of observations in northwest Iran. A total of 453 profile data points were used for mapping the soil great groups of the study area. A data split was done manually for each class separately, which resulted in an overall 70% of the data for calibration and 30% for validation. The bootstrapping approach of calibration (with 10 runs) was performed to produce multiple maps for each model. The 10 bootstraps were evaluated against the hold-out validation dataset. The average values of accuracy measures, including Kappa (K), overall accuracy (OA), producer's accuracy (PA) and user's accuracy (UA), were explored. In addition, the results of this study were compared with a previous study in the same area, in which resampling techniques were used to deal with imbalanced data for digital soil class mapping. The findings show that all three suggested methods can deal well with the imbalanced classification problem, with OCCM showing the highest K (= 0.76) and OA (= 82) in the validation stage. Also, this model can guarantee the retention of the minority classes in the final map. Comparing the present approaches with the previous study approach demonstrates that the three newly suggested methods can remarkably increase both overall and individual class accuracy for mapping.     

Predicting Rice Yield Under Salinity Stress Using K/Na Ratio Variable in Plant Tissue

Estimation of yield reduction in crop caused by the salinity stress is mostly based on variations of soil electrical conductivity and the severity of water stress. Crop response curves to salinity were developed without considering ion toxicity and nutritional imbalance in the plant. The objective of this study was to explore the possibility of using the ratio of the concentration of potassium by sodium in rice leaf (leaf-K/Na) to predict yield under the salinity stress. The rice (Oryza sativa L.) yield under fresh and saline condition and the leaf-K/Na related database was created. Data were collected from consecutive three seasons of a field experiment in the Africa Rice Center experimental farm in Senegal (16° 11? N, 16° 15?W). We studied the relationship between the relative yield (Y_r), a ratio of yield under the salinity stress to the potential yield and the leaf-K/Na (x). Furthermore, we did regression analyses and F-test to determine the best fitting function. Results indicate that the exponential function [i.e. Y_r = 100 exp (-b x)] was the best fitting model with the lowest root mean square error (9.683) and the highest R² value (0.90). Example applications on independent data from published papers showed relatively good predictions, suggesting that the model can be used to predict rice yield in saline soils.