高效液相色谱-质谱法测定水产品中孔雀石绿及其代谢物

在水产养殖过程中,人们经常使用各种药物进行水体消毒和防止鱼病害,孔雀石绿就是其中的一种染料类杀菌剂,近年来发现它特别是其代谢物在水产体内有明显的残留现象,且代谢物的残留时间较长,由于孔雀石绿化学官能团三苯甲烷是一种致癌物质,所以欧盟、美国等宣布禁止其在经济鱼类(观赏鱼除外)养殖过程中使用。经文献检索,国内虽有水产品中孔雀石绿残留量检验方法的报道,但未涉及代谢物残留量检测方法的报道。国外已建立的检测方法主要采用了气相色谱质谱联用法测定孔雀石绿代谢物、高效液相-色谱法同时测定孔雀石绿及其代谢物和高效液相色谱-质谱法同时测定孔雀石绿及其代谢物。我们利用HPLC-VIS和Q-TOFMS技术分别建立了高效液相色谱法(初筛法)和高效液相串联质谱法(确证法)两种检测方法。     

Selective bonding of pyrazine to silicon(100)-2x1 surfaces: the role of nitrogen atoms

The covalent binding of pyrazine on Si(100) have been investigated using high-resolution electron energy loss spectroscopy (HREELS) and x-ray photoelectron spectroscopy. Experimental results clearly suggest that the attachment occurs exclusively through the bonding of the two para-nitrogen atoms with the surface without the involvement of the carbon atoms, as evidenced from the retention of the (sp2) C-H stretching mode in HREELS and a significant down shift of 1.6 eV in the binding energy of N 1s. The binding mechanism for pyrazine on Si(100) demonstrates that reaction channels for heteroatomic aromatic molecules are strongly dependent on the electronic properties of the constituent atoms.     

Fe（acac）3-Al（i-Bu）3-α，α＇-联吡啶催化丙烯腈与苯乙烯共聚合

研究了Fe（acac）3-Al（i-Bu）3-α，α＇-联吡啶（acac=乙酰丙酮）催化体系催化丙烯腈（AN）与苯乙烯共聚合，用元素分析和核磁共振研究了共聚物的结构，在单体比为1：1时共聚物中丙烯腈／苯乙烯含量分别为49．3％和50．7％．用凝胶渗透色谱研究了聚合物分子量和分子量分布，共聚物分子量分布较窄．动力学研究表明共聚合反应对单体浓度呈一级关系，表观活化能为57．8kJ／mol．     

含羧酸配体的鼓形有机锡氧簇合物：六聚苯基锡氧3-吲哚丁酸酯的合成及晶体结构

利用Ph3SnOH和3-吲哚丁酸以1：1摩尔比反应，合成了新型含羧酸配体的鼓形 有机锡氧簇合物：六聚苯基锡氧3-吲哚西酸酯。通过元素分析、红外光谱和X射线 单晶衍射对其结构进行了表征。测试结果表明：该化合物为三斜晶系，空间群P1， a=1.1722(6),b=1.5694（8）nm，c=1.7227(9)nm，α=116.251（8）°，β=100. 854（10）°，γ=95.606（9）°，Z=1，V=2.732(3)nm^3，Dc=1.554g·cm^-3，μ =1.420mm^-1，F(000)=1276，R=0.0630，ωR=0.0762。晶体结构中，六配位的锡原 子呈畸变的八面体构型。     

Carbohydrate-binding module O-mannosylation alters binding selectivity to cellulose and lignin

Improved understanding of the effect of protein glycosylation is expected to provide the foundation for the design of protein glycoengineering strategies. In this study, we examine the impact of O-glycosylation on the binding selectivity of a model Family 1 carbohydrate-binding module (CBM), which has been shown to be one of the primary sub-domains responsible for non-productive lignin binding in multi-modular cellulases. Specifically, we examine the relationship between glycan structure and the binding specificity of the CBM to cellulose and lignin substrates. We find that the glycosylation pattern of the CBM exhibits a strong influence on the binding affinity and the selectivity between both cellulose and lignin. In addition, the large set of binding data collected allows us to examine the relationship between binding affinity and the correlation in motion between pairs of glycosylation sites. Our results suggest that glycoforms displaying highly correlated motion in their glycosylation sites tend to bind cellulose with high affinity and lignin with low affinity. Taken together, this work helps lay the groundwork for future exploitation of glycoengineering as a tool to improve the performance of industrial enzymes.

Improved understanding of the effect of protein glycosylation is expected to provide the foundation for the design of protein glycoengineering strategies.

The cell walls of terrestrial plants primarily comprise the polysaccharides cellulose, hemicellulose, and pectin, as well as the heterogeneous aromatic polymer, lignin. In nature, carbohydrates derived from plant polysaccharides provide a massive carbon and energy source for biomass-degrading fungi, bacteria, and archaea, which together are the primary organisms that recycle plant matter and are a critical component of the global carbon cycle. Across the various environments in which these microbes break down lignocellulose, a few known enzymatic and chemical systems have evolved to deconstruct polysaccharides to soluble sugars.^1–6 These natural systems are, in several cases, being evaluated for industrial use to produce sugars for further conversion into renewable biofuels and chemicals.From an industrial perspective, overcoming biomass recalcitrance to cost-effectively produce soluble intermediates, including sugars for further upgrading remains the main challenge in biomass conversion. Lignin, the evolution of which in planta provided a significant advantage for terrestrial plants to mitigate microbial attack, is now widely recognized as a primary cause of biomass recalcitrance.⁷ Chemical and/or biological processing scenarios of lignocellulose have been evaluated⁸ and several approaches have been scaled to industrial biorefineries to date. Many biomass conversion technologies overcome recalcitrance by partially or wholly removing lignin from biomass using thermochemical pretreatment or fractionation. This approach enables easier polysaccharide access for carbohydrate-active enzymes and/or microbes. There are however, several biomass deconstruction approaches that employ enzymes or microbes with whole, unpretreated biomass.^9,10 In most realistic biomass conversion scenarios wherein enzymes or microbes are used to depolymerize polysaccharides, native or residual lignin remains.^11,12 It is important to note that lignin can bind and sequester carbohydrate-active enzymes, which in turn can affect conversion performance.¹³Therefore, efforts aimed at improving cellulose binding selectivity relative to lignin have emerged as major thrusts in cellulase studies.^14–25 Multiple reports in the past a few years have made exciting new contributions to our collective understanding of how fungal glycoside hydrolases, which are among the most well-characterized cellulolytic enzymes given their importance to cellulosic biofuels production, bind to lignin from various pretreatments.^15,17 Taken together, these studies have demonstrated that the Family 1 carbohydrate-binding modules (CBMs) often found in fungal cellulases are the most relevant sub-domains for non-productive binding to lignin,^15,17,20,26 likely due to the hydrophobic face of these CBMs that is known to be also responsible for cellulose binding (Fig. 1).²⁷Open in a separate windowFig. 1Model of glycosylated CBM binding the surface of a cellulose crystal. Glycans are shown in green with oxygen atoms in red, tyrosines known to be critical to binding shown in purple, and disulfide bonds Cys8–Cys25 and Cys19–Cys35 in yellow.Furthermore, several studies have been published recently using protein engineering of Family 1 CBMs to improve CBM binding selectivity to cellulose with respect to lignin. Of particular note, Strobel et al. screened a large library of point mutations in both the Family 1 CBM and the linker connecting the catalytic domain (CD) and CBM.^21,22 These studies demonstrated that several mutations in the CBM and one in the linker led to improved cellulose binding selectivity compared to lignin. The emerging picture is that the CBM-cellulose interaction, which occurs mainly as a result of stacking between the flat, hydrophobic CBM face (which is decorated with aromatic residues) and the hydrophobic crystal face of cellulose I, is also likely the main driving force in the CBM-lignin interaction given the strong potential for aromatic–aromatic and hydrophobic interactions.Alongside amino acid changes, modification of O-glycosylation has recently emerged as a potential tool in engineering fungal CBMs, which Harrison et al. demonstrated to be O-glycosylated.^28–31 In particular, we have revealed that the O-mannosylation of a Family 1 CBM of Trichoderma reesei cellobiohydrolase I (TrCel7A) can lead to significant enhancements in the binding affinity towards bacterial microcrystalline cellulose (BMCC).^30,32,33 This observation, together with the fact that glycans have the potential to form both hydrophilic and hydrophobic interactions with other molecules, led us to hypothesize that glycosylation may have a unique role in the binding selectivity of Family 1 CBMs to cellulose relative to lignin and as such, glycoengineering may be exploited to improve the industrial performance of these enzymes. To test this hypothesis, in the present study, we systematically probed the effects of glycosylation on CBM binding affinity for a variety of lignocellulose-derived cellulose and lignin substrates and investigated routes to computationally predict the binding properties of different glycosylated CBMs.     

交替三线性分解算法与反相高效液相-二极管阵列检测方法相结合同时测定苯二酚的位置异构体

 利用交替三线性分解算法与反相高效液相 二极管阵列检测 (RP HPLC DAD)相结合 ,在洗脱时间为1 0 86min～ 1 399min(间隔 1 / 1 50min)、紫外吸收波长为 2 68nm～ 2 98nm(间隔 1nm)时对苯二酚位置异构体的重叠及光谱体系进行了分辨研究。分辨结果与实际结果一致。同时测定了水溶液中共存的邻苯二酚、间苯二酚和对苯二酚的含量 ,回收率分别为 (1 0 0 1± 1 0 ) % ,(99 4± 1 4) % ,(1 0 0 5± 1 7) %。研究结果表明 :该方法定量快速准确 ,实验操作步骤简单 ,解决了在干扰物存在条件下三者很难同时分辨的问题。     

A Perturbation Approach to Vector Optimization Problems: Lagrange and Fenchel–Lagrange Duality

Journal of Optimization Theory and Applications - In this paper, we study a general minimization vector problem which is expressed in terms of a perturbation mapping defined on a product of locally...     

基于双解码路径DD-UNet的脑肿瘤图像分割算法

针对医学图像中病灶区域尺度不一、边界模糊和周围组织强度不均匀所导致的分割精度降低问题,提出了一种基于双解码器的脑肿瘤图像分割模型。为了增强特征的表征力,提出了高阶微分残差模块并使用不同空洞率的扩张卷积用于提取特征编码,提高了网络模型的分割性能;引入上下文语义信息感知模块(multi scale dilation, MSD),从不同的目标尺度中提取更多的精细信息,提高了对结构细节信息的捕获能力,同时减少了编解码器之间的特征差异;在空间解码路径中使用选择性聚合空间注意力模块(spatial aggregation attention module, SAAM),增加了对有效空间特征的权重比例,减少了无效的特征干扰。在脑肿瘤数据集上进行了实验验证,实验结果表明,所提算法的Dice系数、平均交并比、敏感性、特异性、准确率等指标分别为：93.35%、90.71%、91.15%、99.94%、96.75%。     

基于无监督学习的低照度图像增强算法

针对目前低照度图像增强算法存在恢复细节丢失、网络复杂度高和配对数据集获取难度大等问题,提出了一种基于无监督学习的图像增强算法。在YIQ色彩空间中,通过构建的轻量化网络和幂指函数计算亮度通道Y的增强曲线,从而获得曝光较差区域增强和高光区域遏制的图像。该网络使用的无参考损失函数可以隐式地评估图像增强质量并驱动网络学习。实验对比结果表明,该算法在可训练参数和模型权重仅占9.5 k/88 kB的情形下,在视觉效果与图像质量指标上都取得了具有竞争力的结果。