稀土富勒烯生成的影响因素初探

采用某些特殊的放电和提取方法，如反向放电和甲苯高温高压提取等可以有效地提高稀土富勒烯的生成效率［‘，‘’，并已先后成功高效地合成了许多含稀土富勒烯「‘’．对其提纯、表征、衍生和应用也进行了研究［‘－’j．但对影响稀土富勒烯生成的因素研究较少．在石墨律中同时填入La，Y，Sc的稀土氧化物，对其稀土富勒烯生成效率的情况进行了研究，认为稀土元素的第一电离能是影响稀土富勒烯生成的主要因素‘’，’‘．Moro等采用激光和热解吸质谱对稀土富勒烯的研究结果表明，稀土元素的氧化态是影响稀土富勒烯生成的决定性因素”’．本…     

具有酯基和酰氨基的新型杯[4]冠醚与杯[6]冠醚的合成

乙醇胺与氯乙酰氯反应得到Ⅳ一(2．氯乙酸酯基乙基)一氯乙酰胺(1)．1与杯 [4]芳烃和杯[6]芳烃分别在K2c03／苯和K2c03／甲苯体系中反应48 h，以37％和 25％的产率得到具有酯基和酰氨基的杯芳烃冠醚．经核磁、质谱、元素分析等表征 证实杯[4]冠醚为l，3．桥联方式，杯[6]冠醚为l，4．桥联方式，且均采取杯式构 象．     

电喷雾质谱动力学方法测定磷酰化丙丙二肽的气相质子亲和能

自 1 98 4年 Yamashita等[1] 提出电喷雾质谱技术 ( ESI-MS)以来 ,它已成为现代生物学研究的重要工具 ,已被用于蛋白 [2 ]和寡聚核苷酸序列 [3 ]的测定、蛋白折叠途径表征 [4 ]、非共轭复合物检测 [5]及酶催化反应的定量研究 [6 ]等 .前文 [7]研究发现 ,氨基酸和小肽的氮端磷酰化使其在快原子轰击质谱和电喷雾质谱正离子模式下峰强明显增强 ,表现出很强的增敏效应 .这一现象可能在蛋白质组学质谱小肽序列的测定中得到应用 .因此 ,阐明其产生机理非常重要 .一个可能的机理是磷酰化基团的引入增加了氨基酸和小肽的气相质子亲和能 ( Proton …     

新型富勒烯衍生物的激光质谱结构表征

对3种电化学方法合成的新型结构富勒烯衍生物进行了激光质谱表征,确认了1,2加成以及[5,6]开环富勒烯衍生物结构.质谱结果发现了富勒烯以及富勒烯衍生物与氧的结合峰,核磁共振结果进一步证明了富勒烯衍生物的结构,为含有C60结构衍生物的研究提供了有力的表征手段.     

钛锆钒异核双金属配合物[Cp2V（μ—η^2：η^4—PhC4Ph）MCp2‘]（M=Ti,Zr;Cp’=C5H5,C5H4SiMe3）的合成与表征

室温下，[Cp2Ti(C≡Cph)2],[Cp2Zr(C≡CPh)2]和[C5H4SiMe3)2Zr(C≡CPh)2]分别与二茂钒作用，合成了钛锆钒异核双金属配合物[Cp2V(μ-η^2:η^4-PhC4Ph)MCp2‘](M=Ti,Zr;Cp‘=C5H5,C5H4SiMe3)。用元素分析、质谱、核磁共振谱、磁矩、红外和拉曼光谱对配合物进行了表征。3个配合物具有相似的磁化率。配合物3的晶体结构分析表明PhC4Ph通过内部2个碳原子键合到Cp2V上，内部2个碳原子和外部2个碳原子均与Cp2‘Zr键合，丁二烯骨架内部的2个碳原子都具有四配位的平面结构。     

取代苄基吡啶类季铵盐的制备及其杀菌活性

采用吡啶或2-氨基吡啶与取代苄基衍生物反应获得3种苄基吡啶类季铵盐．即：溴化苄基吡啶盐（[Bz—Py]Br）,溴化苄基-2-氨基吡啶盐（[Bz-2-NH2Py]Br）和溴化对硝基苄基吡啶盐（[NO2Bzpy]Br]）．通过元素分析,红外光谱和电子喷雾质谱等手段进行了组成分析和结构表征,并以绿脓杆菌和金葡萄球菌为致病菌体测定了3种盐的杀菌活性．实验结果表明,所制备的3种吡啶类季铵盐具有良好的杀菌性能．     

产物可用电喷雾质谱检测的氨基酸/肽季铵化新方法

氨基酸和肽中氨基的化学修饰反应,如乙酰化反应和烷基化反应已被广泛用于蛋白组学研究中蛋白质的定量分析．氨基酸和肽的季铵化产物具有独特的优点,在电喷雾质谱中具有很好的离子化效率,可大大提高检测的灵敏度．文献[6～8]报道的氨基酸和肽的季铵化方法均使用高浓度的盐(如KHCO3),严重影响了质谱的检测结果,难以直接用于蛋白质组学研究．     

有机盐类化合物醋酸钠的电喷雾质谱研究

利用电喷雾质谱技术研究了有机盐类化合物醋酸钠(NaAc)的特征质谱行为,实验结果表明,在全扫描电喷雾正负离子谱中都出现了质量数相差82的质谱峰簇．这与醋酸钠的相对分子质量相一致,正负质谱峰簇分别对应于簇合物离子Na^ (NaAc)n和Ac^-(NaAc)m:簇合物离子的多级串联质谱进一步证明了簇合物离子的存在。该结果为类似结构的盐类化合物的表征提供了一种新的质谱证据。     

富勒烯负离子的自聚行为

C6。可以说是迄今发现的具有最美妙对称性的分子——60个碳原子均位于完全等价的几何位置上，而且由于形成了覆盖整个‘咏’面的大。键，结构非常稳定．最近一系列实验发现，C。。在激光的作用下还能进一步聚合饲．我们在实验中首次发现了C。。在脉冲激光溅射下自聚成的负离子，并对实验记录的质谱作了分析．1实验实验在自制的激光等离子体源飞行时间质谱计问上进行．C。。粉末压紧后以n面胶固定在样品架上．实验所用的激光波长532urn，脉宽7us．会聚后作用于样品的激光功率密度在10’－10‘W·cm－’之间．激光产生的等离子体中的正负离…     

四氢咪唑取代亚甲基β—二酮质谱碎裂机理的理论研究

理论计算非常适用于气相离子化学研究[1，2]，它与质谱实验相结合可以识别许多非常规的和以往所不知道的自由基离子，也可以提供反应能和机理方面的信息，有助于探讨可能的异构化过程和不同异构体结构的相对稳定性．离子／中性复合物（离子和中性碎片通过静电引力结合在一起）[3]作为有机离子质谱单分子碎裂的重要中间体已被越来越多的理论和实验结果所证实[3，4]．串联质谱低能碰撞诱导解离和同位素标记技术的实验结果表明[5]：四氢咪唑取代亚甲基β-二酮分子结构中氮原子上氢表现出不同活性，其气相单分子碎裂经历了离子／中性复合物的中…     

Validation using sensitivity and target transform factor analyses of neural network models for classifying bacteria from mass spectra

Temperature constrained cascade correlation networks (TCCCNs) are computational neural networks that configure their own architecture, train rapidly, and give reproducible prediction results. TCCCN classification models were built using the Latin-partition method for five classes of pathogenic bacteria. Neural networks are problematic in that the relationships among the inputs (i.e., mass spectra) and the outputs (i.e., the bacterial identities) are not apparent. In this study, neural network models were constructed that successfully classified the targeted bacteria and the classification model was validated using sensitivity and target transformation factor analysis (TTFA). Without validation of the classification model, it is impossible to ascertain whether the bacteria are classified by peaks in the mass spectrum that have no causal relationships with the bacteria, but instead randomly correlate with the bacterial classes. Multiple single output network models did not offer any benefits when compared to single network models that had multiple outputs. A multiple output TCCCN model achieved classification accuracies of 96 +/- 2% and exhibited improved performance over multiple single output TCCCN models. Chemical ionization mass spectra were obtained from in situ thermal hydrolysis methylation of freeze-dried bacteria. Mass spectral peaks that pertain to the neural network classification model of the pathogenic bacterial classes were obtained by sensitivity analysis. A significant number of mass spectral peaks that had high sensitivity corresponded to known biomarkers, which is the first time that the significant peaks used by a neural network model to classify mass spectra have been divulged. Furthermore, TTFA furnishes a useful visual target as to which peaks in the mass spectrum correlate with the bacterial identities.     

温度限制串联相关网络-近红外光谱法用于药物甲硝唑的质量控制

近红外漫反射光谱是一种简便、快速的有机物分析方法,样品不需处理即可直接测量,易于实现固态样非破坏测定.近红外漫反射光谱分析技术广泛应用于农业、食品、化妆品、烟草和石油等方面的组分分用近红外漫反射光谱法进行药品的非破坏性分析正成为国际热门课题.但近红外漫反射光谱的光谱范宽,吸收强度很弱,且组分间光谱严重重叠,给非破坏性分析带来了困难.而近红外漫反射光谱法与化量学相结合,能有效地解决光谱重叠带来的问题[1～3].     

Identification of rhubarbs by using NIR spectrometry and temperature-constrained cascade correlation networks

Temperature-constrained cascade correlation networks (TCCCNs) were used to identify powdered rhubarbs based on their near-infrared spectra. Different network configurations that used multiple network models with single output (Uni-TCCCN) and single networks with multiple outputs (Multi-TCCCN) were compared. Comparative studies were made by using Latin-partitions and leave-one-out cross-validation methods. Results showed that multiple networks with single output predicted generally better than single network with multiple outputs. Better results with TCCCN models were obtained compared with conventional back propagation neural networks (BPNNs). The effects of parameters on correct identification and parameter optimizations were discussed in detail. With optimized neural network training parameters, NIR spectra from powdered rhubarb samples were classified by a TCCCN model with 100% accuracy.     

Application of Density Functional Theoretic Descriptors to Quantitative Structure-Activity Relationships with Temperature Constrained Cascade Correlation Network Models of Nitrobenzene Derivatives

IntroductionNitrobenzene derivatives have been used as organ-ic chemical materials and intermediates for many yearsin the chemical industry. Many of those chemicals arereleased into environment and especially into aquaticsystems, and thus have a high pote…     

Quality control of the powder pharmaceutical samples of sulfaguanidine by using NIR reflectance spectrometry and temperature-constrained cascade correlation networks

Temperature-constrained cascade correlation networks (TCCCNs) were applied to the identification of the powder pharmaceutical samples of sulfaguanidine based on near infrared (NIR) diffuse reflectance spectra and their first derivative spectra. This work focused on the comparison of performances of the uni-output TCCCN (Uni-TCCCN) and multi-output (Multi-TCCCN) by near infrared diffuse reflectance spectra and their first derivative spectra of sulfaguanidine. The TCCCN models were verified with independent prediction samples by using the “cross-validation” method. The networks were used to discriminate qualified, un-qualified and counterfeit sulfaguanidines pharmaceutical powders. The results showed that single outputs network generally worked better than the multiple outputs networks, and the first derivative spectra were more suitable for the identification comparing with original diffuse reflectance spectra. With proper network parameters the pharmaceutical powders can be classified at rate of 100% in this work. Also, the effects of parameters and related problems were discussed.     

Optimization of matrix assisted desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) for the characterization of Bacillus and Brevibacillus species

Over the past few decades there has been an increased interest in using various analytical techniques for detecting and identifying microorganisms. More recently there has been an explosion in the application of matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS) for bacterial characterization, and here we optimize this approach in order to generate reproducible MS data from bacteria belonging to the genera Bacillus and Brevibacillus. Unfortunately MALDI-TOF-MS generates large amounts of data and is prone to instrumental drift. To overcome these challenges we have developed a preprocessing pipeline that includes baseline correction, peak alignment followed by peak picking that in combination significantly reduces the dimensionality of the MS spectra and corrects for instrument drift. Following this two different prediction models were used which are based on support vector machines and these generated satisfactory prediction accuracies of approximately 90%.     

Radial Basis Function Networks Applied in Bacterial Classification Based on MALDI-TOF-MS

IntroductionWith the improvement of living standard,people pay more and more attention to health.Theaccurate and sensitive identification ofmicroorganisms plays an important role indiagnosing disease,identifying public healthhazards from pathogens,monitoring potential foodcontamination,regulating bioprocessingoperations,and detecting or identifying the natureof biological agents[1,2 ] . There are two major goalsfor the identification of microorganisms. Onewould be to develop a method to use in…     

Biochemical Characterization of Novel Bioactive Protein from Silkworm (Bombyx mori L) Fecal Matter

In this study, complete purification and biochemical characterization of protein is presented. The protein was purified by using Sephadex G-75 gel filtration column followed by reverse-phase high-performance liquid chromatography in a C18 column. The molecular weight of the protein was determined by sodium dodecyl sulfate polyacrylamide gel electrophoresis, mass spectrum matrix-assisted laser desorption/ionization-time-of-flight-mass spectrometry (MALDI-TOF-MS) and liquid chromatography-electrospray ionization tandem mass spectrometry. Protein was fragmented by trypsin based on the m/z values obtained by MALDI-TOF-MS analysis. The peptide fragments sequence showed homology with DEAD-box-ATP-dependent RNA helicase 45, present in a public domain, National Centre for Biotechnology Information. The protein exhibited antibacterial activity against selected Gram +/? bacteria. The analgesic activity was determined by conducting acetic-acid-induced writhing test in mice.     

寡糖衍生化及基质辅助激光解吸电离飞行时间质谱分析方法研究

为提高中性寡糖在基质辅助激光解吸电离飞行时间质谱(MALDI-TOF)中的检测灵敏度,建立了以1-(4-氰基苯基)-4-哌啶碳酰肼(CPH)为衍生化试剂对寡糖的标记方法。寡糖的还原端与CPH的酰肼基团反应生成腙,使得寡糖被CPH标记,衍生物以MALDI-TOF质谱进行分析。结果表明:在反应温度95℃,醋酸浓度为0.125%(V/V),CPH过量100倍的条件下,衍生产率可达最大,并且CPH衍生可使中性寡糖在MALDI-TOF质谱中的检测灵敏度提高10倍。本方法简便快速,灵敏度高,适合微量寡糖链的质谱分析。     

Au@SiO2 core-shell nanoparticles for laser desorption/ionization time of flight mass spectrometry

In matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS), the analysis capability, especially for small molecules, is often compromised by the addition of organic matrices due to the existence of background signals. Herein we report a new detection method on the utility of core-shell nanoparticles (CSNPs) as energy transfer structure in LDI-TOF-MS. The LDI-TOF-MS based on gold-silica core-shell nanoparticles with ultrathin silica shell of 2-4 nm (Au@utSiO(2) CSNPs) was effectively applied to the analysis of many compounds, especially for small functional molecules and polymers, which was more promising than MALDI-TOF-MS.