The chromatographic quantification of hydrophobicity using micellar mobile phases

Summary In micellar liquid chromatography (MLC), the hydrophobicity of a compound is the predominant factor in its retention and interaction with micelles. A non-linear empirical model can describe the dependence between the retention factor (logk) in MLC and the logarithm of partition coefficients octanol-water (logP). An algorithm based on such a model has been used to makelogP predictions. Retention data for series of neutral compounds eluted with different mobile phases and alkyl-bonded stationary phases have been used to test the predictive ability of the algorithm. The results of this approach are compared with those obtained from automatic computational software packages.     

Analysis of droplet behavior in a de-oiling hydrocyclone

A mechanical separation process in a de-oiling hydrocyclone is described in which disperse oil droplets are separated from a continuous water phase. This separation process is influenced by droplet breakage and coalescence. Based on experimental data and simulation results in a stirred tank, a modified breakage model, which can be applied to droplet breakage in the de-oiling hydrocyclone, is developed. Then, a simulation model is developed coupling the numerical solution of the flow field in the hydrocyclone based on computational fluid dynamics (CFD) with population balances. The homogenous discrete method and the inhomogeneous discrete method are applied for solving the population balance model (PBM). The investigations show that the numerical results obtained by the simulation model coupled with the modified PBM using the inhomogeneous discrete method are in good accordance with experimental data under a high flow rate. According to this simulation model, the effect of three different inlet designs on the separation efficiency of the de-oiling hydrocyclone has been discussed. The results indicate that the separation efficiency of the de-oiling hydrocyclone can be improved with an appropriate inlet design.     

高温超导体制备条件的人工神经网络识别

高温超导体的制备条件要求严格,其掺杂量大小、烧结温度控制等都直接影响实验样本的超导性质。近几年高温超导研究已积累大量实验数据,如何应用人工智能方法处理这些数据寻找更好的合成条件颇有意义。人工神经网络方法在许多领域己显示其处理复杂数据和模式识别的优越性,但尚未应用到化合物制备研究方面。本文对此作了初步尝试。     

A graph-theoretic approach to modeling metabolic pathways

Summary The metabolic pathways of medazepam, oxazepam, and diazepam were modeled using graph-theoretic transforms which are incorporable into computer-assisted metabolic analysis programs. The information, represented in the form of a graph-theoretic transform kit, which was obtained from these pathways was then used to predict the metabolites of other benzodiazepine compounds. The transform kits gave statistically significant predictions with respect to a statistical method for evaluating the performance of the transform kits.     

Determination of aminoglutethimide enantiomers in pharmaceutical formulations by capillary electrophoresis using methylated-β-cyclodextrin as a chiral selector and computational calculation for their respective inclusion complexes

A capillary electrophoretic method for the separation of the aminoglutethimide (AGT) enantiomers using methylated-β-cyclodextrin (M-β-CD) as chiral selector is described. Several parameters affecting the separation were studied, including the type and concentration of chiral selector, buffer pH, voltage and temperature. Good chiral separation of the racemic mixture was achieved in less than 9 min with resolution factor Rs = 2.1, using a fused-silica capillary and a background electrolyte (BGE) of tris-phosphate buffer solution (50 mmol L⁻¹, pH 3.0) containing 30 mg mL⁻¹ of M-β-CD. The separation was carried out in normal polarity mode at 25 °C, 16 kV and using hydrostatic injection. Acceptable validation criteria for selectivity, linearity, precision, and accuracy/recovery were included. The proposed method was successfully applied to the assay of AGT enantiomers in pharmaceutical formulations. The computational calculations for the inclusion complexes of the R- and S-AGT-M-β-CD rationalized the reasons for the different migration times between the AGT enantiomers.     

De novo analysis of electron impact mass spectra using fragmentation trees

The automated fragmentation analysis of high resolution EI mass spectra based on a fragmentation tree algorithm is introduced. Fragmentation trees are constructed from EI spectra by automated signal extraction and evaluation. These trees explain relevant fragmentation reactions and assign molecular formulas to fragments. The method enables the identification of the molecular ion and the molecular formula of a metabolite if the molecular ion is present in the spectrum. These identifications are independent of existing library knowledge and, thus, support assignment and structural elucidation of unknown compounds. The method works even if the molecular ion is of very low abundance or hidden under contaminants with higher masses. We apply the algorithm to a selection of 50 derivatized and underivatized metabolites and demonstrate that in 78% of cases the molecular ion can be correctly assigned. The automatically constructed fragmentation trees correspond very well to published mechanisms and allow the assignment of specific relevant fragments and fragmentation pathways even in the most complex EI-spectra in our dataset. This method will be very helpful in the automated analysis of metabolites that are not included in common libraries and it thus has the potential to support the explorative character of metabolomics studies.     

The development of an integrated platform to identify breast cancer glycoproteome changes in human serum

Protein glycosylation represents one of the major post-translational modifications and can have significant effects on protein function. Moreover, changes in the carbohydrate structure are increasingly being recognized as an important modification associated with cancer etiology. In this report, we describe the development of a proteomics approach to identify breast cancer related changes in either concentration and/or the carbohydrate structures of glycoprotein(s) present in blood samples. Diseased and healthy serum samples were processed by an optimized sample preparation protocol using multiple lectin affinity chromatography (M-LAC) that partitions serum proteins based on glycan characteristics. Subsequently, three separate procedures, 1D SDS-PAGE, isoelectric focusing and an antibody microarray, were applied to identify potential candidate markers for future study. The combination of these three platforms is illustrated in this report with the analysis of control and cancer glycoproteomic fractions. Firstly, a molecular weight based separation of glycoproteins by 1D SDS-PAGE was performed, followed by protein, glycoprotein staining, lectin blotting and LC–MS analysis. To refine or confirm the list of interesting glycoproteins, isoelectric focusing (targeting sialic acid changes) and an antibody microarray (used to detect neutral glycan shifts) were selected as the orthogonal methods. As a result, several glycoproteins including alpha-1B-glycoprotein, complement C3, alpha-1-antitrypsin and transferrin were identified as potential candidates for further study.