Using HPLC retention parameters to estimate fish bioconcentration factors of organic compounds

Reversed-phase high performance liquid chromatography (RP-HPLC) was employed to develop predictive models for fish bioconcentration factors (BCF) of organic compounds. Estimation of BCF from RP-HPLC retention parameters on octadecyl-bonded silica gel (ODS), cyanopropyl-bonded silica gel (CN), and phenyl-bonded silica gel (Ph) columns were investigated. The results show that, for a set of compounds belonging to different chemical classes, the CN stationary phase is the best one among the three columns and better than n-octanol/water model for BCF estimation. A multi-column RP-HPLC model, using the retention parameters on the CN and Ph columns as the variables of multiple linear regression equations, was further evaluated to estimate BCF of organic compounds belonging to different chemical classes, and the results show that the multi-column RP-HPLC model is better than that of any single RP-HPLC column for BCF estimation.

Study on conical columns with different conical angles for semi-preparative liquid chromatography

The dynamic flow profiles and separation performances in conically shaped preparative liquid chromatographic columns (inlet i.d. larger than outlet i.d.) with three different angles (7, 10 and 15degrees) were studied and compared with cylindrical column of the same length and internal volume. The shapes of dynamic flow profiles were studied by on-column visualization method. The transparent chromatographic columns made of polymethyl methacrylate (PMMA), packed with C-18 bonded silica, were immerged into a cubic pool filled with glycerol to eliminate the cylindrical and conical lens effect. The flow profiles of colored iodine solution in the columns were observed clearly using cyclohexane as mobile phase since the refractive indices of C-18, column wall and the mobile phase are very close. In the conical column of 15degrees (20-7 mm i.d.) the mobile phase in the central region migrated slower than in wall region as it moved toward the column outlet, while in the conical column of 7degrees (17-11 mm i.d.) the mobile phase in the central region migrated faster than in wall region just like in cylindrical column. We found that a plug-like flow profile was generated in the conical column of 10degrees (18-9 mm i.d.) during the whole migration process. A carmine and brilliant blue mixture was used as a probe to test the separation ability of the columns. The resolutions of the two compounds on the conical column of 7, 10, 15degrees and on the cylindrical column were 0.6, 1.57, 1.29 and 0.8, respectively. (C) 2003 Elsevier B.V. All rights reserved.

Study on conical columns for semi-preparative liquid chromatography

The dynamic flow profiles and column efficiencies in conically shaped semi-preparative liquid chromatographic columns (inlet ID larger than outlet ID) with two different conical angles (7degrees and 15degrees) were studied. The dynamic flow profiles were studied by an on-column visualization method. Conical columns were compared with cylindrical column of the same length and internal volume. The results showed that the flow profile of a sample band in the conical column of 7degrees (50 mm x 17 mm --> 11 mm ID) was parabolic in shape. The sample band migrated slower in the wall region than in the central region, as in the cylindrical column (50 mm x 14 mm ID). However, the sample band in the conical column of 15degrees (50 mm x 20 mm --> 7 mm ID) migrated slower in the central region than in the wall region, resulting in a reverse parabolic flow profile, in contrast to that in cylindrical column. This indicated that a flat flow profile might be realized in a conical column with a conical angle between 7degrees and 15degrees. The conical column of 15degrees had the highest column efficiency among the three columns under the same conditions. Compared with the cylindrical column packed with identical packing material, the conical column of 15degrees had 22%-45% higher column efficiency and 11%-27% higher peak height.

Retention modeling and simultaneous optimization of pH value and gradient steepness in RP-HPLC using feed-forward neural networks

A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP-HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two-dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An "early stopping" strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.

Retention modeling and optimization of pH value and solvent composition in HPLC using back-propagation neural networks and uniform design

A novel method for the optimization of pH value and composition of mobile phase in HPLC using artificial neural networks and uniform design is proposed. As the first step. seven initial experiments were arranged and run according to uniform design. Then the retention behavior of the solutes is modeled using back-propagation neural networks. A trial method is used to ensure the predicting capability of neural networks. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for both basic and acidic samples.

Study of normal and modified nucleosides in serum by RP-HPLC

Modified nucleosides derived predominantly from transfer ribonucleic acid (tRNA) have been studied as possible tumor markers. In this paper a reversed-phase high-performance liquid chromatographic (RP-HPLC) method has been applied to study 15 normal and modified nucleosides in serum. The nucleoside levels in normal human serum were established, and the concentrations of 15 nucleosides in serum from 19 cancer patients were determined, it was found that the concentrations of modified nucleosides were significantly higher in patient sera. Based on 15 nucleoside concentrations in serum, factor analysis could classify correctly 90% of cancer patients from the normal humans Further work showed that urine was slightly better than serum when determining nucleosides as biological marker candidates. More work is ongoing to determine the clinical usefulness of modified nucleosides as tumor markers.

Excretion pattern investigation of urinary normal and modified nucleosides of breast cancer patients by RP-HPLC and factor analysis method

Modified nucleosides, formed post-transcriptionally in RNA by a number of modification enzymes, are excreted in abnormal levels in the urine of patients with malignant tumors. To test their usefulness as tumor markers, and to compare them with the conventional tumor markers, a reversed-phase high-performance liquid chromatographic (RP-HPLC) method and a factor analysis method have been used to study the excretion pattern of nucleosides of breast cancer patients. A clear cut differentiation of the breast cancer group and the healthy individuals in two clusters without overlapping was obtained. Copyright (C) 2000 John Wiley & Sons, Ltd.