基于GIS的福建省水土保持功能重要性评价

[目的] 对福建省水土保持功能重要性进行评价，为该省生态保护红线划定提供科学参考。[方法] 基于GIS技术，利用降水、土壤、数字高程和植被指数等数据，采用修正通用水土流失方程（RUSLE），估算福建省土壤保持量，并对其分级。[结果] 全省土壤保持总量为2.65×10⁹ t/a，平均土壤保持模数为20 789.82 t/（km²·a）。水土保持功能极其重要区、高度重要区、中等重要区、较为重要区和一般重要区面积分别为3 192.54，8 205.54，15 547.71，21 519.81，74 000.20 km²，分别占全省面积的2.61%，6.70%，12.70%，17.57%和60.42%。[结论] 福建省水土保持功能极其重要区、高度重要区和中等重要区主要分布在闽西和闽中2大山带及其周边丘陵山地区。     

全国水土保持功能年度价值评价研究

依据《中华人民共和国水土保持法释义》对水土保持功能的定义,分析了水土保持设施、地貌植被所发挥或蕴藏的有利于保护水土资源、防灾减灾、改善生态、促进社会进步等作用的内涵。在借鉴国内外先进经验和研究成果基础上,结合我国水土流失特点、水土保持现状,界定出水土保持功能价值概念。采用生态经济学计量方法,结合实际调研情况,分析各个指标之间的逻辑关系,建立了水土保持功能价值评价模型。按照国家水土保持区划一级分区,适当考虑二级分区和三级分区,以及全国水土流失动态监测站网分布概况,收集39个典型县(市、区)2016年度的土壤、水文、气象等观测资料,测算出其水土保持功能价值,进而推算至全类型区,再从8个水土保持一级分区的水土保持功能价值推算出2016年度全国水土保持功能价值,并在对测算结果进行分析讨论的基础上,对国家制定水土保持生态文明对策提出了建议。     

茶叶中甲基化EGCG的分离及功能研究进展

综述了茶叶中甲基化EGCG的分离方法和功能研究进展。茶叶甲基化EGCG分离方法有制备液相色谱(p HPLC)、高速逆流色谱(HSCCC)、Sephadex LH-20凝胶柱层析、Toyopearl HW-40S中压柱层析等,主要具有抗过敏、保护肝脏、调节肠道菌群、治疗哮喘、清除自由基等功效。     

革兰阴性菌外膜囊泡的研究进展

外膜囊泡(outer membrane vesicles,OMVs)是革兰阴性(G^-)菌从细胞膜上脱落下来的囊泡,携带有细菌的大量组分,如外膜蛋白、脂多糖、脱氧核糖核酸等。由于OMVs无活性、不能复制且具有免疫原性,所以被认为是最具潜力的亚单位疫苗,同时OMVs对细菌本身具有多种作用,故OMVs成为研究的热点。本文从G^-菌OMVs的组成成分、形成机制、生物学功能、提取纯化方法及其开发应用前景5个方面综述其研究现状,为G^-菌的致病机制研究、OMVs的疫苗开发应用提供技术指导。     

育苗基质对榉树容器苗质量的影响

【目的】为了筛选出适于榉树容器苗生长的最佳基质配比,以提高榉树容器苗的培育质量。【方法】以泥炭土、珍珠岩、蛭石、锯木屑和腐殖土5种材料为原料,按照一定的比例配制成6种基质,以此6种配方基质为供试的育苗基质(其处理编号分别为T1、T2、T3、T4、T5、T6),选择10 cm×5 cm×5 cm的无纺布袋作为育苗容器,进行了榉树容器育苗试验。测定了榉树容器苗的出苗率、形态指标、生物量及生理指标等19个指标,并采用隶属函数法对以不同配方基质培育的容器苗的苗木质量进行了综合评价。【结果】6种基质处理的出苗率从大到小依次为T3>T5>T1>T2>T6>T4,其中T3基质处理的出苗率最高,T4基质处理的出苗率最低,T3基质处理的出苗率是T4基质处理的出苗率的3.47倍;T1基质处理的苗高、地径均极显著高于其他基质处理的,T2基质处理的叶片数显著高于除T1和T5外的其他基质处理的。T2基质处理的侧枝数显著高于其他基质处理的,不同基质处理间容器苗的高径比、侧根数、主根长均无显著差异;T1基质处理的茎干质量、根干质量、苗木干质量及其质量指数均极显著高于其他基质处理的,不同基质处理间容器苗的茎根比无显著差异;T1基质处理的根系活力强度和叶绿素a含量均极显著高于除T2外的其他基质处理的,T2基质处理的叶绿素总量极显著高于除T1外的其他基质处理的,不同基质处理间容器苗的叶绿素b、叶绿素a/b之值均无显著差异,T4基质处理的净光合速率最低,极显著低于其他基质处理的。【结论】采用模糊数学的隶属函数法综合评价得出:以T1基质(其配比为:腐殖土∶泥炭土∶珍珠岩=2∶1∶1)培育的榉树容器苗其质量最好,这种配方基质是榉树容器苗的最佳育苗基质。     

Heme oxygenase-1 protects renal function in septic rats via influencing expression of thrombomodulin

AIM: To investigate the protective effect of heme oxygenase-1 (HO-1) on the kidney of septic rats and the influence of HO-1 on the expression of thrombomodulin (TM) in the kidney. METHODS: Sepsis in rats was developed with cecal ligation and puncture (CLP). The septic rats were randomly divided into sham group, CLP group, CLP+HO-1 inducer group and CLP+HO-1 inhibitor group (n=18). The plasma levels of creatinine (Cr), cystatin-C (Cys-C), carboxyhemoglobin (COHb), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and TM, and the changes of prothrombin time (PT) and activated partial thromboplastin time (APTT) in each group were measured. Histopathological examination was performed in the kidney. The expression of TM in the kidney tissue was detected by Western blot. RESULTS: Compared with sham group, significantly elevated plasma levels of Cr, Cys-C, TNF-α, IL-1β and TM (P<0.05), shortened PT and APTT (P<0.05), significantly increased microthrombus formation, and lowered TM expression in the kidney (P<0.05) of CLP group were observed. The administration of hemin lowered the plasma levels of Cr, Cys-C, TNF-α, IL-1β and TM (P<0.05), prolonged PT and APTT (P<0.05), attenuated microthrombus formation, and up-regulated the expression of TM in the kidney (P<0.05). In contrast, ZnPP had the opposite effects. CONCLUSION: HO-1 increases the expression of TM in the kidney and exerts anticoagulatory and antiinflammatory effects, thereby improving renal function in the septic rats.     

Isolation and Characterization of GhLEA3 Gene from Upland Cotton and Its Expression in Response to Low Temperature Stress

[Objective] Based on the analysis of cotton GhLEA3 gene structure and its expression model in chilling stress, we investigated the resistance function of GhLEA3 in response to cold stress. [Method] We cloned GhLEA3 from upland cotton by homologous sequence cloning way. We analyzed the properties of the GhLEA3, and constructed phylogenetic tree by bioinformatics analysis. We constructed the transient expression vector 35S∷GhLEA3-GFP by In-Fusion connection technology and studied the subcellular localization of GhLEA3. The expression of GhLEA3 gene in leaves of TM-1 at three-leaf stage under low temperature stress treatments (4 ℃, 24 h) was performed. Agrobacterium tumefaciens mediated floral dipping method was used to transform the gene with expression vector 35S∷GhLEA3-GFP into Arabidopsis thaliana wild type. Low temperature germination experiment at 4 ℃ was conducted to verify germination ability of the transgenic Arabidopsis thaliana T₃ seed. The transgenic Arabidopsis seedlings were treated at 4 ℃(low temperature), and all the leaves were taken to measure their electrical conductivity. [Result] The coding sequence of GhLEA3 gene is 1 218 bp, which encodes 405 amino acids. GhLEA3 protein includes 4 functional domains of PF02987. Phylogenetic analysis showed that the similarity of amino acid sequences between upland cotton GhLEA3 and Arabidopsis thaliana AtLEA3 was 52.6%. GhLEA3 might be mainly localized in vacuoles and small vesicles. GhLEA3 was up-regulated in leaves after low temperature treatment. The germination rate of transgenic Arabidopsis thaliana of T₃ generation at low temperature was significantly higher than that of wild type, and its electrical conductivity of leaves after low temperature treatment was significantly lower than that of wild type. [Conclusion] GhLEA3 belonged to the member of LEA3 family. Phylogenetic analysis showed that GhLEA3 had the closest relationship with AtLEA3. GhLEA3 was induced by low temperature stress and may play an important role in improving cold resistance.     

硒多糖的来源、提取及其生物学功能研究进展

硒多糖是硒与多糖结合在一起的有机硒化合物，是一种新型的硒源，具有清除自由基、保护神经活性、增强免疫力、抗肿瘤、抗炎等多种功能。硒多糖具有特殊的化学结构——硒氧键（O=Se=O），有别于普通多糖，其能够发挥硒和多糖的双重功效，活性远高于硒或多糖。本文就硒多糖的来源、提取、分离纯化及生物学功能等方面的研究进展进行综述，以期为未来畜牧业新型饲料添加剂的开发、应用和推广提供理论依据。 [关键词] 硒多糖|来源|提取|生物学功能     

基于高斯函数的春玉米叶片功能期模型构建与应用

叶片功能期是影响光合生产能力的关键因素,冠层叶片功能期的量化评估对玉米植株生长和产量形成具有重要意义。本研究于2015—2017年在中国农业科学院作物科学研究所吉林公主岭试验站进行,定株观测先玉335和郑单958两个品种各个叶位叶片展开时间和衰老时间,基于2015年和2016年试验数据,以高斯函数(■)模拟玉米各叶位叶片功能期的动态变化,并用2017年数据验证,在此基础上进一步明确了模型特征参数的生理学意义,简化了叶片功能期模型构建的方法。研究条件下利用高斯函数构建的玉米叶片功能期模型年际间稳定性好、品种间区分度大。进一步解析利用一阶导(功能期最大值)、二阶导(功能期变化速率最大的点)、三阶导(功能期开始快速增大的点)等于零取整后的叶位并配合最顶部叶位(n)和基部第1叶这5个转折叶位叶片功能期构建的模型拟合度良好,极大地简化了该模型参数拟合的数据需求,并探讨了利用该模型函数对玉米叶片功能分组的可能性。本研究为玉米生产能力的量化分析提供了思路和方法,对各类玉米生长模型的完善和其他相关研究也有借鉴意义。     

Enhancing pedotransfer functions with environmental data for estimating bulk density and effective cation exchange capacity in a data‐sparse situation

Soil bulk density (BD) and effective cation exchange capacity (ECEC) are among the most important soil properties required for crop growth and environmental management. This study aimed to explore the combination of soil and environmental data in developing pedotransfer functions (PTFs) for BD and ECEC. Multiple linear regression (MLR) and random forest model (RFM) were employed in developing PTFs using three different data sets: soil data (PTF‐1), environmental data (PTF‐2) and the combination of soil and environmental data (PTF‐3). In developing the PTFs, three depth increments were also considered: all depth, topsoil (<0.40 m) and subsoil (>0.40 m). Results showed that PTF‐3 (R²; 0.29–0.69) outperformed both PTF‐1 (R²; 0.11–0.18) and PTF‐2 (R²; 0.22–0.59) in BD estimation. However, for ECEC estimation, PTF‐3 (R²; 0.61–0.86) performed comparably as PTF‐1 (R²; 0.58–0.76) with both PTFs out‐performing PTF‐2 (R²; 0.30–0.71). Also, grouping of data into different soil depth increments improves the estimation of BD with PTFs (especially PTF‐2 and PTF‐3) performing better at subsoils than topsoils. Generally, the most important predictors of BD are sand, silt, elevation, rainfall, temperature for estimation at topsoil while EVI, elevation, temperature and clay are the most important BD predictors in the subsoil. Also, clay, sand, pH, rainfall and SOC are the most important predictors of ECEC in the topsoil while pH, sand, clay, temperature and rainfall are the most important predictors of ECEC in the subsoil. Findings are important for overcoming the challenges of building national soil databases for large‐scale modelling in most data‐sparse countries, especially in the sub‐Saharan Africa (SSA).