全二维液相色谱（NPLC×RPLC）接口及其应用

用内径为0．53mm的填充毛细管正相液相色谱为第一维，用4．6mm（i．d．）×50mmRP-18e整体柱反相色谱为第二维，建立了定量环一阀切换接口的全二维液相色谱系统（NPLC×RPLC）．第一维色谱分离洗脱出的组分交替存储在十通阀上的两个定量环中，同时定量环中前一个组分被转移到第二维进行反相分离．因为第一维的流动相流量仅是第二维的1／500，自然解决了流动相兼容问题．采用芳香族化合物的混合物和中药丹参正己烷提取液对该全二维液相系统的分离能力进行了评价．     

Prediction of Complexation Properties of Crown Ethers Using Computational Neural Networks

A computational neural network method was used for the prediction of stability constants of simple crown ether complexes. The essence of the method lies in the ability of a computer neural network to recognize the structure-property relationships in these host-guest systems. Testing of the computational method has demonstrated that stability constants of alkali metal cation (Na+, K+, Cs+)-crown ether complexes in methanol at 25 °C can be predicted with an average error of ±0.3 log K units based on the chemical structure of the crown ethers alone. The computer model was then used for the preliminary analysis of trends in the stabilities of the above complexes.     

An <Emphasis Type="BoldItalic">in silico</Emphasis> approach for screening flavonoids as P-glycoprotein inhibitors based on a Bayesian-regularized neural network

Summary P-glycoprotein (P-gp), an ATP-binding cassette (ABC) transporter, functions as a biological barrier by extruding cytotoxic agents out of cells, resulting in an obstacle in chemotherapeutic treatment of cancer. In order to aid in the development of potential P-gp inhibitors, we constructed a quantitative structure–activity relationship (QSAR) model of flavonoids as P-gp inhibitors based on Bayesian-regularized neural network (BRNN). A dataset of 57 flavonoids collected from a literature binding to the C-terminal nucleotide-binding domain of mouse P-gp was compiled. The predictive ability of the model was assessed using a test set that was independent of the training set, which showed a standard error of prediction of 0.146 ± 0.006 (data scaled from 0 to 1). Meanwhile, two other mathematical tools, back-propagation neural network (BPNN) and partial least squares (PLS) were also attempted to build QSAR models. The BRNN provided slightly better results for the test set compared to BPNN, but the difference was not significant according to F-statistic at p = 0.05. The PLS failed to build a reliable model in the present study. Our study indicates that the BRNN-based in silico model has good potential in facilitating the prediction of P-gp flavonoid inhibitors and might be applied in further drug design.     

Modeling of the relationship between electroosmotic flow and separation parameters in capillary zone electrophoresis using artificial neural networks and experimental design

The prediction of migration time of electroosmotic flow (EOF) marker was achieved by applying artificial neural networks (ANN) model based on principal component analysis (PCA) and standard normal distribution simulation to the input variables. The voltage of performance, the temperature in the capillary, the pH and the ionic strength of background electrolytes (BGE) were applied as the input variables to ANN. The range of the performance voltage studied was from 15 to 27 kV, and that of the temperature in the capillary was from 20 to 30 °C. For the pH values studied, the range was from 5.15 to 8.04. The range of the ionic strength investigated in this paper was from 0.040 to 0.097. The prediction abilities of ANN with different pre-processing procedure to the input variables were compared. Under the same performance conditions, the average prediction error of the migration time of the EOF marker was 5.46% with RSD = 1.76% according to 10 parallel runs of the optimized ANN structure by the proposed approach, and that of the 10 parallel predictions of the optimal ANN structure for the different performance conditions was 12.95% with RSD = 2.29% according to the proposed approach. The study showed that the proposed method could give better predicted results than other approaches discussed.     

Special Mixing Behavior of Chelate-based Ionic Liquid with Methanol

Compared to the general ionic liquids (ILs), a significant deviation of the binary mixtures of 1-decyl-3-methylimidazolium tri(hexafluoroacetylaceto)-copper(II) ([C₁₀mim][Cu(hfacac)₃]) with methanol was found, indicating the way methanol interacts with ILs might be governed by the special structure of the chelating anion. IR results showed that the (C2-H) of 1-decyl-3-methylimidazolium hexafluoroacetylacetonate ([C₁₀mim][hfacac]) blue-shifted more significantly than that of [C₁₀mim][Cu(hfacac)₃], meanwhile the (C=O) red-shifted in [C₁₀mim][Cu(hfacac)₃], which is contrast with that in [C₁₀mim][hfacac]. Two-dimensional correlation analysis of the FTIR spectra indicated that the chelating cavity has little effect on the sequence of the ILs sites that interact with methanol. Combined with small angle X-ray scattering (SAXS) results, the picture of mixing processes in these two systems were proposed. Methanol interacts directly with the anion followed by the cation in [C₁₀mim][hfacac], while methanol preferentially enters the chelating cavity and enhances the packing effect in the [C₁₀mim][Cu(hfacac)₃] system.     

Optimization of the Microwave-Assisted Saponification and Extraction of Organic Pollutants from Marine Biota Using Experimental Design and Artificial Neural Networks

Several improvements in sample pretreatment for the determination of organic pollutants (i.e. n-alkanes, polycyclic aromatic hydrocarbons, PAHs) in marine biota (mussels) are presented. The use of liquid nitrogen and homogenization of the samples are shown to be an alternative to the time consuming liophilization step required for the analysis of biota samples. Microwave-assisted hydrolysis and extraction are combined to isolate organic pollutants (19 n-alkanes and 27 PAHs) from biota matrices. Experimental design (ED) and artificial neural networks (ANNs) were used to optimize the experimental conditions. NIST-CRM 2978 was used to test the validity of the developed method which shows a good agreement with certified values.     

Sequential injection system with higher dimensional electrochemical sensor signals Part 1. Voltammetric e-tongue for the determination of oxidizable compounds

A sequential injection analysis (SIA) system was developed with the aim of obtaining an automatic and versatile way to prepare standards needed in the study of systems with higher dimensional sensor signals. To illustrate this, different analytical techniques were used in determinations of several analytes. Automated potentiometric calibrations of different potentiometric sensors, with and without interference, were carried out. Useful determinations of selectivity coefficients with two degrees of freedom were obtained. Simultaneous voltammetric determinations have also been done. Firstly, simultaneous determinations of lead and cadmium, using epoxy-graphite composite as the working electrode, have enabled a separate calibration for each metal to be obtained. Next, a voltammetric electronic tongue was designed and applied to the determination of oxidizable species. The use of artificial neural networks has solved the overlapped signal of ascorbic acid, 4-aminophenol and 4-acetamidophenol (paracetamol). A set of 63 data points was prepared automatically and has facilitated the training of an electronic tongue for these three analytes. Accurate predictions of test solutions, in the range of 12–410 μM for ascorbic acid, 17–530 μM for 4-aminophenol and 10–420 μM for paracetamol, have been achieved with RMSEs lower than 0.10 μM.     

Measurement of PCDDs, PCDFs, and non-ortho-PCBs by comprehensive two-dimensional gas chromatography-isotope dilution time-of-flight mass spectrometry (GC x GC-IDTOFMS)

Comprehensive two-dimensional gas chromatography with isotope-dilution time-of-flight mass spectrometry (GC × GC-IDTOFMS) was used to measure polychlorinated dibenzo-p-dioxin (PCDD), polychlorinated dibenzofuran (PCDF), and coplanar polychlorinated biphenyl (cPCB) concentrations in ash, sediment, vegetation, and fish samples. The GC × GC capability was achieved by using a quad jet, dual stage, thermal modulator. Zone compression of the GC peaks from modulation resulted in a significant increase of the signal intensity over classical GC-IDTOFMS. The GC × GC column set used an Rtx-Dioxin 2 phase as the first dimension (¹D) and an Rtx-500 as the second dimension (²D). The chromatographic separation of the 17 PCDD/Fs and the 4 cPCBs was attained in ¹D except for 2,3,7,8-TCDD and CB126 for which deconvoluted ion currents (DIC) were required to be reported separately. The Rtx-500 phase separated the bulk matrix interfering compounds from the target analytes in ²D. The instrumental limit of detection (iLODs) was 0.5 pg for 2,3,7,8-TCDD. The calibration curves showed good correlation coefficients for all the compounds investigated in the concentration range of 0.5–200 pg. GC × GC-IDTOFMS results compared favorably to those from conventional isotope-dilution one-dimensional gas chromatography-high resolution mass spectrometry (GC-IDHRMS). The comprehensive mass analysis of the TOFMS further permitted the identification of other contaminants of concern in the samples.     

A Novel Uranyl Complex with Dimeric Lacunary Polyoxoanion: [(A-α-SiW<Subscript>9</Subscript>O<Subscript>33</Subscript>)<Subscript>2</Subscript>K{UO<Subscript>2</Subscript>(H<Subscript>2</Subscript>O)}<Subscript>2</Subscript>]<Superscript>11−</Superscript>

A novel uranyl complex with dimeric lacunary polyoxoanion like open-mouthed clam, Na₅[(A-α-SiW₉O₃₃H₃)₂K{UO₂(H₂O)}₂], was prepared and characterized by elemental analysis, infrared and ultraviolet–visible spectroscopy and single crystal X-ray diffraction. In the anion, two A-α-SiW₉O₃₄¹⁰⁻ groups share two terminal oxygen atoms O_d′ derived from removal of three corner-shared W atoms from saturated α-Keggin anion, forming a dimeric anion with an open mouth in which potassium ion and uranyl ions are coordinated. Uranium atom adopts a pentagonal bipyramidal geometry. The coordinating anions are linked by sodium ions via coordination of terminal or bridging oxygen atoms, forming two-dimensional layer arrangement. Between the layers are the hydrogen bonds from which a supramolecular architecture is created. UV–VIS spectrum gives W–O and U–O charge transfer transitions at 230–265 and 432 nm, showing the change of geometry of the polyanion and weakening of the U–O bonds of the uranyl cation. Electronic supplementary material The online version of this article () contains supplementary material, which is available to authorized users.