非编码sRNA在细菌耐药机制方面的研究进展

近年来的研究发现,细菌应答抗生素压力时会产生特异的非编码小RNA(small RNA,sRNA)谱,进而可能调控下游基因的表达,帮助细菌克服抗生素压力。sRNA以各种方式调控细菌耐药相关基因(如抗生素转运蛋白、药物外排泵、细胞被膜的合成与修饰),参与细菌耐药网络。因此,sRNA及其相关因子(如Hfq)可能被用作抗菌治疗的靶标。本文将从sRNA应答抗生素压力并产生抗生素耐药及其作为药物靶点的前景等方面,综述sRNA在细菌耐药调控方面的研究进展。国家自然科学基金(No.31370166、No.81473251和No.81301474);;福建省自然科学基金(No.2015J01345和No.2014J01139);;厦门大学校长基金(No.20720160060

Platinum-nickel alloy excavated nano-multipods with hexagonal close-packed structure and superior activity towards hydrogen evolution reaction

铂镍合金在氢析出(HER)、氧还原(ORR)等重要能量转化反应中具有优异催化性质，受到了人们广泛的关注。近日，谢兆雄教授课题组通过简单的溶剂热方法，首次合成出六方晶系的铂镍合金枝状纳米晶，其中每个枝杈结构由六个{11-20}高能晶面裸露的超薄纳米片组装而成。与面心立方晶系铂镍合金相比，亚稳态的六方晶系铂镍合金在HER反应中表现出更加优异的性质。当电流密度为10 mA·cm-2时，其过电位仅有65 mV，同时质量电流密度高达3.03 mA·µgPt-1 (-70 m V vs. RHE)，是目前为止报道的HER催化剂中质量活性最高的，其突出的催化性能主要来源于晶相作用(同质异晶)及大的比表面积。该项工作为发展高催化性能的铂基合金纳米晶提供了新的研究思路。该研究是在谢兆雄教授和蒋亚琪副教授指导下，与傅钢教授共同合作完成。实验部分由博士生曹振明（第一作者）、陈巧丽、沈守宇、卢邦安，硕士生李慧齐以及博士后张嘉伟共同完成，理论计算部分由傅钢教授课题组完成。【Abstract】Crystal phase regulations may endow materials with enhanced or new functionalities. However, syntheses of noble metal-based allomorphic nanomaterials are extremely difficult, and only a few successful examples have been found. Herein, we report the discovery of hexagonal close-packed Pt–Ni alloy, despite the fact that Pt–Ni alloys are typically crystallized in face-centred cubic structures. The hexagonal close-packed Pt–Ni alloy nano-multipods are synthesized via a facile one-pot solvothermal route, where the branches of nano-multipods take the shape of excavated hexagonal prisms assembled by six nanosheets of 2.5nm thickness. The hexagonal close-packed Pt–Ni excavated nano-multipods exhibit superior catalytic property towards the hydrogen evolution reaction in alkaline electrolyte. The overpotential is only 65mV versus reversible hydrogen electrode at a current density of 10 mAcm-2 , and the mass current density reaches 3.03mA µgPt-1 at -70mV versus reversible hydrogen electrode, which outperforms currently reported catalysts to the best of our knowledge.This work was supported by the National Basic Research Program of China (Grant 2015CB932301), the National Natural Science Foundation of China (Grants 21333008, 21603178 and J1030415) and the Natural Science Foundation of Fujian Province of China (No. 2014J01058). 该研究工作得到科技部（批准号：2015CB932301）、国家自然科学基金委（批准号：21333008, 21603178 和 J1030415）和福建省自然科学基金委（No. 2014J01058）的大力资助与支持

Research on hybridization compatibility, tissue culture and heat tolerance Cardiocrium giganteum

本实验以大百合和百合东方杂种系“索蚌”为材料，对大百合、百合杂交的亲和性、大百合离体培养及其耐热性进行了研究，以期为大百合与百合杂交育种及相应的耐热百合材料的筛选、种质保存、新品种快繁及栽培应用提供理论依据。 　　以大百合为母本，百合为父本，对属间杂交授粉后花粉管的行为进行观察，结果表明：大百合与百合属间杂交授粉后，百合的花粉在大百合的花柱内的伸长过程中，出现少部分花粉管末端分叉、膨胀或变细，胼胝质大量不规则沉淀，及部分花粉管在伸长过程中受阻等不亲和现象，但大部分花粉仍能够正常萌发，穿过花柱道，进入子房，到达胚珠，且能够观测到早期的胚。虽然杂交亲和性与花粉管的行为有关，但杂交的成功与否还受到受精后诸多因素的影响，还需要从胚胎学和遗传学方面进一步探讨。 　　以大百合的鳞片、叶柄和子房为外植体，进行离体培养，结果表明：大百合的鳞片和叶柄外植体均可成功地诱导小鳞茎，叶柄相对更容易。鳞茎诱导小鳞茎的最佳培养基为MS＋NAA0.5－1.0mg/ml +BA2.5mg/ml +KT2.5mg/ml +蔗糖3%＋琼脂0.7%，28周后，每个外植体平均可以分化4-11个小鳞茎；叶柄诱导小鳞茎的最佳培养基为MS＋NAA1.0－2.0mg/ +BA2.5-3.0mg/ml +KT2.5-3.0mg/ml +蔗糖3%＋琼脂0.7%，26周后，每个外植体平均可以分化3-9个小鳞茎。同时也发现，用鳞茎作为外植体，污染率较高。在大百合的子房离体培养实验中发现：BA和KT 是影响大百合子房分化途径的关键因素，其浓度分别为0.1-1.0mg/L、2.0-4.0 mg/L和高于4.0mg/L时，外植体分别分化为愈伤组织、芽和叶。外植体分化的基本培养基以N6、B5为佳。愈伤组织诱导小鳞茎的最佳培养基为MS+0.1-0.5mg/L NAA +2.5mg/L BA+2.5mg/L KT +10%蔗糖+0.7%琼脂。在1/2MS +3%的蔗糖+0.7%琼脂+1%活性炭的生根培养基上，生根率为100%。炼苗一周后移栽，长势良好。 　　对长至5－6片真叶的大百合植株在不同高温（30℃、35℃和40℃）下，分别进行4h、10h及24h(热胁迫10h，然后在22℃对照温度下缓苗14h)的热胁迫处理，测定了不同处理下，植株的净光合速率（Pn），实际光化学效率（φPS2），最大光化学效率（Fv/Fm）和叶片的相对电导率，游离脯氨酸含量，可溶性蛋白含量，以及叶片中超氧化物歧化酶（SOD）和过氧化氢酶(CAT)的活性。结果表明：大百合对30℃的高温胁迫有较好的适应能力，表现为可溶性蛋白、游离脯氨酸等渗透调节物质的积累，抗氧化酶活性的提高，以及缓苗后细胞膜的自我修复和光合能力的恢复；随着胁迫温度的升高（35℃、40℃）和胁迫时间的延长（4h、10h），大百合一方面对高温胁迫做出了积极的响应，另一方面，光系统的光合能力，细胞膜的稳定性，抗氧化酶的活性，也受到了一定程度的伤害，在缓苗后,细胞膜的稳定性、细胞的渗透势、抗氧化酶的活性等都在一定程度上得到恢复。 　

Brain spontaneous activity alterations in patients with Alzheimer's disease and mild cognitive impairment

目的 采用功能磁共振(fMRI)技术,观察轻度阿尔茨海默病(AD)、遗忘型轻度认知功能障碍(aMCI)患者静息态脑自发活动变化,探讨fMRI成像标志物对诊断AD及aMCI的临床价值.方法 以临床诊断aMCI、诊断很可能AD患者和正常认知对照组各12例为研究对象,对其进行简易精神状态检查(MMSE)评分和静息态fMRI扫描,利用分数低频振幅(fA LFF)方法对静息态大脑自发活动进行对比分析,观察AD患者、aMCI患者相对于对照组在fALFF指标有显著差异的区域.结果 静息态fMRI结果显示,在楔前叶,AD组fALFF值(1.11±0.07)与对照组(1.24 ±0.11,t=2.89,P=0.012)和aMCI组(1.34±0.17,t=3.49,P=0.004)相比均显著下降,aMCI组fALFF值最高,但与对照组相比差异无统计学意义;在顶下小叶,AD组fALFF值(0.96±0.07)和对照组(1.11±0.07,t4.31,P =0.001)、aMCI组(1.09±0.08,t=3.44,P=0.004)相比均显著下降.结论 AD患者较aMCI患者及正常认知老年人脑内特定区域自发活动受损明显;aMCI患者脑内特定区域自发活动与对照组相比无显著改变,但在某些和高级神经功能密切相关的区域如楔前叶有代偿增强的倾向

Study on Discrimination of Tea Based on Color of Multispectral Image

提出了一种利用多光谱图像颜色特征进行茶叶分类的新方法,对两种颜色几乎一样用肉眼几乎不能分辨的茶叶进行了分类。图像由MS3100-3CCD光谱成像仪和普通数码相机同时获得,光谱成像仪提供3个波段的图像,由近红外(NIR)、红色(R)和绿色(G)组成,因此它比普通数码照相机包含更丰富的信息,特别NIR波段的图像对有机物的颜色比可见光敏感。提取3CCD光谱成像仪和普通数码照相机各个波段图像颜色的特征即像素偏方差值和平均值进行统计分析,用多光谱图像的NIR图像所提供颜色信息能够辨别这两种颜色几乎一样的茶叶,而普通数码相机无法提供信息进行识别。然后应用人工神经网络技术,对NIR图像像素偏方差值和平均值这两个参数进行建模,建模样本40个,每个样本为20个,预测样本20个,每个样本为10个。结果表明,在阈值为0.3,对两种茶叶进行分类得到了100%识别率,此研究为茶叶的分类提供一种快速和无损的新方法。Tea is one of the most popular beverages worldwide.Its categories have a great relationship to its beneficial medicinal properties.The present work attempted to study the feasibility to use multispectral imaging technique as a rapid and non-destructive method to discriminate tea varieties.Two categories of tea discriminated hardly by naked eye were sorted.The images were 1 036 pixels vertically by 1 384 pixels horizontally with 24-bit depth,and were captured using a red(R) waveband,near infrared(NIR) waveband and green(G) waveband multispectral digital imager,MS3100(Duncan Technologies,Inc.,CA,USA).The three wavebands of image(Red,Green,NIR) can be composed into one image which contains more information than images recorded by ordinary digital cameras,especially,the NIR image is more sensitive to the color of organic matter than visible spectrum.The three images of one sample can be obtained simultaneously.The color features of tea were calculated using the standard notations: mean and mean square deviation.Then,the two color features of 3CCD and ordinary digital cameras were extracted and calculated by Matlab 7.3 software respectively,and were contrasted.A total of 60 samples were adopted,and the features of mean and mean square deviation of NIR waveband image were applied as inputs to a back propagation neural network(BP-ANN) with one hidden layer.The forty samples(twenty for each category) were selected randomly to build BP-ANN model,and this model was used to predict the varieties of 20 unknown samples(ten for each category).The two categories of tea can be discriminated by the information of color of images of 3CCD,but can not by the ordinary digital cameras.The result indicted that the discrimination rate of classification set of BP-ANN model was up to 100% within 0.3 of threshold.It concluded that multi-spectral imaging technique has a high potential to identify categories of green tea fast and non-destructively.国家“十一五”科技支撑项目(2006BAD10A0403);; 国家自然科学基金项目(30671213,30600371);; 高等学校博士学科点专项科研基金课题项目(20040335034)资