火焰原子吸收法测定中药土大黄中四种微量元素的含量

目的运用火焰原子吸收光谱法测定中药土大黄根中的Fe、Zn、Mg、Ca等4种金属元素的含量。方法用浓HNO3-HClO4消解样品,采用标准曲线法测定其4种金属元素含量。结果所测的样品中含有丰富的人体必需微量元素,尤其是Ca含量极高。方法回收率在96．90％～102．3％之间,样品相对偏差小于5％。结论方法简单、准确,结果令人满意。     

一种新型双亲性有机小分子催化剂在水相体系中催化环己酮与硝基烯烃直接不对称Michael加成反应

设计合成了一系列基于脯氨酸巯基咪唑衍生物的新型双亲性有机小分子催化剂,在水相中加入酸作为助催化剂,可以高效高选择性的催化环己酮与硝基烯烃的不对称Michael加成反应,非对映选择性和对映选择性分别高达99：1和96%.     

非晶Ce-Ti氧化物用于NH3选择性催化还原NO的原位红外研究

采用原位红外光谱研究了在具有短程有序Ce-O-Ti结构的非晶Ce-Ti氧化物上NH₃选择性催化还原（SCR） NO_x反应. 在反应条件下,催化剂表面主要被NH₃吸附物种覆盖,而检测不到NO_x吸附物种. 经测定,NO的反应级数为0.5-0.6,表明Langmuir-Hinshelwood机理和Eley-Rideal机理同时存在. 可能的机理是NH₃吸附物种和弱吸附的NO_x反应,生成NH_yNO₃ （y = 0-4）活性中间物种,并通过GAUSSIAN计算和原位红外结果证实了它们的存在. Ce-O-Ti结构中Ce与Ti之间表现出原子尺度的相互作用,所以在SCR反应的活性温度窗口下,催化剂的氧化还原活性提高.     

Parity Alternation of Silicon-doped Ternary Cationic Clusters HC_nSi_2~+(n=1～9)

Systematic study on the electronic/geometrical structures and the parity alternation effect of silicon-doped ternary cationic clusters HCnSi2＋（n = 1 ~9） have been carried out at the coupled cluster level. The ground-state （G-S） isomers of the clusters have been defined. The C, chains of the G-S isomers display polyacetylene-like structures. The even-n cations are more stable than the odd-n ones. Such a trend of even/odd alternation has been elaborated based on concepts of the bond character, atomic charge, incremental binding energy, ionization potential, proton affinity and fragmentation energies of the systems. The findings accord with the relative intensities of HC,,Si2＋ species recorded in the related mass spectrometric experiments.     

Plasma-Induced Synthesis of CuO Nanofibers and ZnO Nanoflowers in Water

Fiber-shaped cupric oxide (CuO) nanoparticles and flower-shaped ZnO nanoparticles were facilely synthesized by plasma-induced technique directly from copper and zinc electrode pair in water, respectively. The phase composition, morphologies and optical property of nanoparticles have been investigated by energy dispersive X-ray analysis, X-ray powder diffraction, transmission electron microscopy and UV–vis. The in situ analysis by an optical emission spectroscopy clarified the formation mechanism. Plasma was generated from the discharge between a metal electrode pair in water by a pulse direct current power. CuO and ZnO nanoparticles were synthesized via almost the same formation mechanism, which were prepared via the rapid energetic radicals’ bombardment to electrodes’ surface, atom vapour diffusion, plasma expansion, solution medium condensation, and in situ oxygen reaction and further growth. This novel plasma-induced technique will become a potential application in nanomaterials synthesis.     

Synthesis of Nano-hydroxyapatite via Microbial Method and Its Characterization

Nanoparticles of hydroxyapatite were successfully synthesized by microbial method at ambient temperature and pressure, using calcium chloride and specific substrate as reactants. The compositional and morphological properties of products of the syntheses were studied by means of X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and thermogravimetric analysis (TGA). The characterization data obtained showed that the phase composition, functional groups, and surface morphology of samples obtained by microbial method were mainly similar to that by chemical precipitation method. The hydroxyapatite powder was shown to be nanometer-grade in size and sphere-like in shape.     

Preparation of raspberry-like silica microcapsules via sulfonated polystyrene template and aniline medium assembly method

Raspberry-like composite particles and microcapsules were prepared with anionic sulfonated polystyrene (PSS) particles as templates and cationic aniline monomer as assembly medium. With the help of the sulfonated microgel shells, aniline and silica particles could not only adsorbed onto template surfaces but also go inward shells and finally form microcapsules with varied silica shell thickness. The sulfonation extent of PSS particles first climbed up and then decreased with sulfonation time due to the competition of sulfonation reaction and PSS chain detachment. The silica content in composite particles and shell thickness of microcapsules followed similar trend with sulfonation extent. The choice of aniline as assembly medium was checked by comparing with methyl methacrylate and [2-(methacryloyloxy) ethyl] trimethylammonium chloride, and it was found that the cationic and water-insoluble properties of aniline are both important for the composite efficiency.     

Preparation of a visible light-driven Bi2O3–TiO2 composite photocatalyst by an ethylene glycol-assisted sol–gel method,and its photocatalytic properties

A visible light-driven Bi₂O₃–TiO₂ composite photocatalyst was prepared by an ethylene glycol-assisted sol–gel method in which ethylene glycol acted as a polycondensation agent to capture metal ions by reacting with bismuth and titanium sources via a complex polycondensation pathway. The photocatalyst was characterized by X-ray photoelectron spectroscopy, X-ray diffraction, acquisition of N₂ adsorption–desorption isotherms, transmission electron microscopy, and UV–visible diffuse reflectance spectroscopy. The results revealed that the Bi₂O₃–TiO₂ composite was of smaller particle size, greater specific surface area, and had stronger absorbance in the visible light region than pure TiO₂. The photocatalytic activity of the as-prepared catalyst was evaluated by degradation of rhodamine B under visible light irradiation (λ > 400 nm); the as-prepared Bi₂O₃–TiO₂ composite was substantially more active than pure TiO₂. This was ascribed to the high surface area and the heterojunction structure.     

ChemStable: a web server for rule-embedded naïve Bayesian learning approach to predict compound stability

Predicting compound chemical stability is important because unstable compounds can lead to either false positive or to false negative conclusions in bioassays. Experimental data (COMDECOM) measured from DMSO/H₂O solutions stored at 50 °C for 105 days were used to predicted stability by applying rule-embedded naïve Bayesian learning, based upon atom center fragment (ACF) features. To build the naïve Bayesian classifier, we derived ACF features from 9,746 compounds in the COMDECOM dataset. By recursively applying naïve Bayesian learning from the data set, each ACF is assigned with an expected stable probability (p _s ) and an unstable probability (p _uns ). 13,340 ACFs, together with their p _s and p _uns data, were stored in a knowledge base for use by the Bayesian classifier. For a given compound, its ACFs were derived from its structure connection table with the same protocol used to drive ACFs from the training data. Then, the Bayesian classifier assigned p _s and p _uns values to the compound ACFs by a structural pattern recognition algorithm, which was implemented in-house. Compound instability is calculated, with Bayes’ theorem, based upon the p _s and p _uns values of the compound ACFs. We were able to achieve performance with an AUC value of 84 % and a tenfold cross validation accuracy of 76.5 %. To reduce false negatives, a rule-based approach has been embedded in the classifier. The rule-based module allows the program to improve its predictivity by expanding its compound instability knowledge base, thus further reducing the possibility of false negatives. To our knowledge, this is the first in silico prediction service for the prediction of the stabilities of organic compounds.     

Structural insight into exosite binding and discovery of novel exosite inhibitors of botulinum neurotoxin serotype A through in silico screening

Botulinum neurotoxin serotype A (BoNT/A) is the most lethal toxin among the Tier 1 Select Agents. Development of potent and selective small molecule inhibitors against BoNT/A zinc metalloprotease remains a challenging problem due to its exceptionally large substrate binding surface and conformational plasticity. The exosites of the catalytic domain of BoNT/A are intriguing alternative sites for small molecule intervention, but their suitability for inhibitor design remains largely unexplored. In this study, we employed two recently identified exosite inhibitors, D-chicoric acid and lomofungin, to probe the structural features of the exosites and molecular mechanisms of synergistic inhibition. The results showed that D-chicoric acid favors binding at the α-exosite, whereas lomofungin preferentially binds at the β-exosite by mimicking the substrate β-sheet binding interaction. Molecular dynamics simulations and binding interaction analysis of the exosite inhibitors with BoNT/A revealed key elements and hotspots that likely contribute to the inhibitor binding and synergistic inhibition. Finally, we performed database virtual screening for novel inhibitors of BoNT/A targeting the exosites. Hits C1 and C2 showed non-competitive inhibition and likely target the α- and β-exosites, respectively. The identified exosite inhibitors may provide novel candidates for structure-based development of therapeutics against BoNT/A intoxication.