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61.
The interactions of [Pt(CNN)(4-dpt)]PF(6), (1; 4-dpt=2,4-diamino-6-(4-pyridyl)-1,3,5-triazine, HCNN=6-phenyl-2,2'-bipyridine) with double-stranded DNA, poly(dA-dT)(2), and poly(dG-dC)(2) were examined by spectroscopic, electrophoretic, and hydrodynamic methods. The spectroscopic data were analyzed with McGhee, van't Hoff, and Gibbs-Helmholtz equations. In a comparative study, [Pt(CNN)(py)]PF(6) (2; py=pyridine) was prepared and the nature of its binding towards DNA was investigated [preliminary results: ChemBioChem 2003, 4, 62-68]. For reactions with calf thymus DNA at 20 degrees C, the intrinsic binding constants for 1 and 2 are (4.6+/-0.2)x10(5) and (2.3+/-0.3)x10(4) mol(-1) dm(3), respectively. Results of DNA-binding reactions revealed that 1 and 2 preferentially bind to the AT sequence of duplex DNA. Intercalation is the preferred binding mode for 2, whereas both intercalation and minor-groove binding are observed for 1. Complex 1 is cytotoxic against a number of carcinoma cell lines, including KB-3-1, CNE-3, and HepG2, and remains potent against multidrug- or cisplatin-resistant KB-V-1 and CNE1 cell lines, for which the resistance ratios are 1.6 and 1.5, respectively. Importantly, 1 is almost an order of magnitude less toxic to the normal cell line CCD-19Lu (IC(50)=176+/-1.7 microM) and it selectively induced apoptosis leading to cancer cell death with less than 5 % detectable necrosis.  相似文献   
62.
The reactions of [RuHCl(CO)(PPh3)3] and [(C6H6)RuCl2]2 with 2-benzoylpyridine have been examined, and two novel ruthenium(II) complexes – [RuCl(CO)(PPh3)2(C5H4NCOO)] and [RuCl2(C12H9NO)2] – have been obtained. The compounds have been studied by IR and UV–Vis spectroscopy, and X-ray crystallography. The molecular orbital diagrams of the complexes have been calculated with the density functional theory (DFT) method. The spin-allowed singlet–singlet electronic transitions of the compounds have been calculated with the time-dependent DFT method, and the UV–Vis spectra of the compounds have been discussed on this basis.  相似文献   
63.
In the presence of 5 mol% Sc(OTf)3, double indolylation of acetic acid 2-methylene-3-oxo-butyl ester with differently substituted indoles readily afforded beta,beta-bis(indolyl) ketones. The reaction may proceed via a Sc(OTf)3-catalyzed SN2'-type substitution and subsequent conjugate addition.  相似文献   
64.
We take up the question of when a state (= -additive measure) on the product of logics (=-orthomodular posets) depends on at most countably many coordinates. We show that it is always so provided there are no real-measurable cardinals. The manner of dependence is a kind of convex combination. We derive some consequences of the latter statement.  相似文献   
65.
Under the catalysis of 1 mol % Pd(PPh3)4, the reaction of 4,4-disubstituted 2,3-allenamides and organic iodides in toluene afforded iminolactones stereospecifically in >90% yields using K2CO3 (2 equiv)-5 mol % TBAB as the base. A similar reaction with 4-monosubstituted 2,3-allenamides afforded gamma-hydroxy-gamma-lactams in relatively lower yields. The N/O-attack selectivity may be determined by the steric effect at the 4-position of 2,3-allenamides.  相似文献   
66.
中药材重金属元素快速检测对污染监控及人们健康具有重要意义。激光诱导击穿光谱技术(Laser Induced Breakdown Spectroscopy, LIBS)属于一种快速检测方法,研磨压片等预处理方法相对样品消解已有所简化,但破坏了样品的物理性质,且不能满足中药材大宗品种、大批量检测需求。若进一步简化样品预处理,将更加凸显LIBS快速检测的优势。本文建立了激光诱导击穿光谱技术(LIBS)快速微损检测中药材样品重金属元素定标方法。线性相关系数R2为0.7764,建立的微损定标曲线线性可用于切片党参LIBS快速检测,对待测党参切片样品检测平均相对误差为3.74%,与电感耦合等离子体质谱法(ICP-MS)对比,相关系数R2为0.7957,验证了LIBS技术微损检测的可行性。制备的党参参考定标样品可多次重复用于待测样定标和仪器标定等。实验对待测党参样品仅进行切片处理,避免了研磨、压片等预处理,更加充分地体现LIBS快速检测的优势,为LIBS技术应用于中药材重金属元素快检等领域提供了一种新方法。  相似文献   
67.
建立了X射线荧光光谱法测定绿泥石中镁、铝、硅、磷、钾、钙、钛、铁元素含量的快速分析方法。以标准物质及标准物质与基准试剂氧化镁、氧化钙人工混合配制标样的方法建立标准工作曲线,重点讨论了熔剂和脱模剂的选取。最佳熔样条件:采用8.0g四硼酸锂和偏硼酸锂混合熔剂(质量比67: 33)+0.8g样品并添加溴化锂作为脱模剂,熔样温度1100℃,熔样时间10min。该方法相对标准偏差(n=12)均小于5.57%,绿泥石样品测定结果与化学法一致,硅酸盐标准物质测定结果均满足不确定度要求。  相似文献   
68.
Coronary heart disease (CHD), which has developed into one of the major diseases, was reported to be treated by the target of peroxisome proliferators-activate receptor γ (PPAR-γ). As a natural medicine long used in the treatment of CHD, there are few studies on how to screen the target active compounds with high specific activity from Choerospondias axillaris. To advance the pace of research on target-specific active compounds in natural medicines, we have combined magnetic ligand fishing and functionalized nano-microspheres to investigate the active ingredients of PPAR-γ targets in Choerospondias axillaris. The PPAR-γ functionalized magnetic nano-microspheres have been successfully synthesized and characterized by vibrating sample magnetometer (VSM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The specificity, reusability, and reproducibility of the nano-microspheres were investigated with the help of the specific binding of rosiglitazone to PPAR-γ. In addition, the incubation temperature and the pH of the buffer solution in the magnetic ligand fishing were optimized to improve the specific adsorption efficiency of the analytes. Finally, with the aid of ultraperformance liquid chromatography plus Q-Exactive Orbitrap tandem mass spectrometry (UHPLC-Q-Exactive Orbitrap-MS/MS), the 16 active ligands including 9 organic acids, 5 flavonoids, and 2 phenols were found in the ethanolic extracts of Choerospondias axillaris. Therefore, the study can provide a successful precedent for realizing the designated extraction and rapid isolation of target-specific active ingredient groups in the complex mixtures.  相似文献   
69.
A mild and efficient strategy for the synthesis of tricyclic 1,2,4-oxadiazolines-fused tetrahydro-isoquinolines derivatives via [3 + 2] cycloaddition reaction is reported. The reactions provided the functionalized tricyclic 1,2,4-oxadiazolines in high yields (up to 96%). This protocol is simple and easy to handle. Moreover, a gram-scale experiment further highlights the synthetic utility. The chemical structure of the product was determined by X-ray single-crystal structure analysis. A possible mechanism for this transformation is proposed to explain the reaction process.  相似文献   
70.
Rice blast is a serious threat to rice yield. Breeding disease-resistant varieties is one of the most economical and effective ways to prevent damage from rice blast. The traditional identification of resistant rice seeds has some shortcoming, such as long possession time, high cost and complex operation. The purpose of this study was to develop an optimal prediction model for determining resistant rice seeds using Ranman spectroscopy. First, the support vector machine (SVM), BP neural network (BP) and probabilistic neural network (PNN) models were initially established on the original spectral data. Second, due to the recognition accuracy of the Raw-SVM model, the running time was fast. The support vector machine model was selected for optimization, and four improved support vector machine models (ABC-SVM (artificial bee colony algorithm, ABC), IABC-SVM (improving the artificial bee colony algorithm, IABC), GSA-SVM (gravity search algorithm, GSA) and GWO-SVM (gray wolf algorithm, GWO)) were used to identify resistant rice seeds. The difference in modeling accuracy and running time between the improved support vector machine model established in feature wavelengths and full wavelengths (200–3202 cm−1) was compared. Finally, five spectral preproccessing algorithms, Savitzky–Golay 1-Der (SGD), Savitzky–Golay Smoothing (SGS), baseline (Base), multivariate scatter correction (MSC) and standard normal variable (SNV), were used to preprocess the original spectra. The random forest algorithm (RF) was used to extract the characteristic wavelengths. After different spectral preproccessing algorithms and the RF feature extraction, the improved support vector machine models were established. The results show that the recognition accuracy of the optimal IABC-SVM model based on the original data was 71%. Among the five spectral preproccessing algorithms, the SNV algorithm’s accuracy was the best. The accuracy of the test set in the IABC-SVM model was 100%, and the running time was 13 s. After SNV algorithms and the RF feature extraction, the classification accuracy of the IABC-SVM model did not decrease, and the running time was shortened to 9 s. This demonstrates the feasibility and effectiveness of IABC in SVM parameter optimization, with higher prediction accuracy and better stability. Therefore, the improved support vector machine model based on Ranman spectroscopy can be applied to the fast and non-destructive identification of resistant rice seeds.  相似文献   
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