Analysis of aromatic amines by high-performance liquid chromatography with pre-column derivatization by 2-(9-carbazole)-ethyl-chloroformate

2-(9-Carbazole)-ethyl-chloroformate (CEOC), a novel pre-column fluorescence derivatization reagent, has been developed for the analysis of aromatic amines. Taking five monocyclic aromatic amines (o-toluidine, aniline, 3,4-dimethylaniline, N-ethyl-p-toluidine, and p-phenylenediamine) as testing compounds, derivatization conditions such as pH of borate buffer, reaction time and fluorescent tagging reagent concentration have been investigated. By a one-step procedure, CEOC reacts readily with the aromatic amines to form stable derivatives with excitation and emission wavelengths, respectively, at 293 and 360 nm. This derivatization reaction could be finished within 20 min even at room temperature. The peak shapes of the derivatized aromatic amines can be improved greatly without any addition of competition amines into the mobile phase. Furthermore, this method can offer excellent quantitative precision with high tolerance of the matrix of samples. (C) 2003 Elsevier B.V. All rights reserved.

Determination of 1-phenyl-3-methyl-5-pyrazolone-labeled carbohydrates by liquid chromatography and micellar electrokinetic chromatography

In this paper, the method for the derivatization of carbohydrates with 1-phenyl-3-methyl-5-pyrazolone (PMP) was simplified. One-third of the derivatization time was saved. Five monosaccharide derivatives have been well separated by MEKC and HPLC under optimized conditions. Good reproducibility could be obtained with relative standard deviation (RSD) values of the migration times within 5.0 and 2.3%, respectively. Furthermore, the developed methods have been successfully applied to the analysis of carbohydrates in Aloe powder and food. These methods are quite useful for routine analysis of monosaccharides and oligosaccharides in real samples. (C) 2003 Elsevier B.V. All rights reserved.

Binding of metal ions with protein studied by a combined technique of microdialysis with liquid chromatography

A method has been developed for the determination of interactions of metal ions and protein by using microdialysis sampling technique combined with pre-column derivation and reversed-phase ion-pair liquid chromatographic (HPLC analysis. Cu(II), Zn(II) and human serum albumin (HSA) were chosen as model metal ions and protein, respectively. The mixed solutions of metal ions and HSA with different molar ratios buffered with 0.1 M Tris-HCl containing 0.1 M NaCl at pH 7.43 were sampled with a mirodialysis probe by keeping perfusion rate at 1 mul/min and the temperature at 37 degreesC. The free concentrations of metal ions in microdialysates were assayed by precolumn derivatization with meso-tetra(4-sulfophenyl)-porphyrin (TPPS4) followed ion-pair HPLC analysis. The recovery (R) of microdialysis sampling was measured in vitro under similar conditions as 65.74% for Cu(II), 70.45% for Zn(II) with R.S.D. below 3.2%. The primary binding constants and number of binding site estimated by the Scatchard plot analysis are 5.04 x 10(6) M-1 and 0.85 for Cu(II), and 9.87 x 10(6) M-1 and 1.10 for Zn(II), respectively. The competition of Cu(II) and Zn(II) at the second binding site on HSA was investigated, and it was observed that there is a second site on HSA to bind Cu(II) and Zn(II), the affinity of Cu(II) is stronger than that of Zn(II) to this second site of HSA. (C) 2001 Elsevier Science B.V. All rights reserved.

Affinity membrane chromatography for the analysis and purification of proteins

Affinity chromatography is unique among separation methods as it is the only technique that permits the purification of proteins based on biological functions rather than individual physical or chemical properties. The high specificity of affinity chromatography is due to the strong interaction between the ligand and the proteins of interest. Membrane separation allows the processing of a large amount of sample in a relatively short time owing to its structure, which provides a system with rapid reaction kinetics. The integration of membrane and affinity chromatography provides a number of advantages over traditional affinity chromatography with porous-bead packed columns, especially with regard to time and recovery of activity. This review gives detailed descriptions of materials used as membrane substrates, preparation of basic membranes, coupling of affinity ligands to membrane supports, and categories of affinity membrane cartridges. It also summarizes the applications of cellulose/glycidyl methacrylate composite membranes for proteins separation developed in our laboratory. (C) 2001 Elsevier Science B.V. All rights reserved.

Multivariate optimization in micellar electrokinetic capillary chromatography

The optimization of the organic modifier concentration in micellar electrokinetic capillary chromatography (MECC) has been achieved by a uniform design and iterative optimization method, which has been developed for the optimization of composition of the mobile phase in high performance liquid chromatography. According to the proposed method, the uniform design technique has been applied to design the starting experiments, which can reduce the number of experiments compared with traditional simultaneous methods, such as the orthano design. The hierarchical chromatographic response function has been modified to evaluate the separation quality of a chromatogram in MECC. An iterative procedure has been adopted to search the optimal concentration of organic modifiers for improving the accuracy of retention predicted and the quality of the chromatogram. Validity of the optimization method has been proved by the separation of 31 aromatic compounds in MECC. (C) 2000 John Wiley & Sons, Inc.

Artificial neural network classification based on high-performance liquid chromatography of urinary and serum nucleosides for the clinical diagnosis of cancer

Nucleosides in human urine and serum have frequently been studied as a possible biomedical marker for cancer, acquired immune deficiency syndrome (AIDS) and the whole-body turnover of RNAs. Fifteen normal and modified nucleosides were determined in 69 urine and 42 serum samples using high-performance liquid chromatography (HPLC). Artificial neural networks have been used as a powerful pattern recognition tool to distinguish cancer patients from healthy persons. The recognition rate for the training set reached 100%. In the validating set, 95.8 and 92.9% of people were correctly classified into cancer patients and healthy persons when urine and serum were used as the sample for measuring the nucleosides. The results show that the artificial neural network technique is better than principal component analysis for the classification of healthy persons and cancer patients based on nucleoside data. (C) 2002 Elsevier Science B.V. All rights reserved.