Chromatographic fingerprint based on serially coupled columns combined with multiple-component quantitation with a single reference standard for quality evaluation of Shen–Zhi–Ling oral liquid

The HPLC fingerprints of Shen–Zhi–Ling oral liquid were developed based on the serial coupling of two columns.

Capillary Isotachophoresis Determination of Trace Oxidized Glutathione in Blood

A capillary isotachophoresis (CITP) method performed in a column-coupling apparatus has been developed for the simultaneous determination of glutathione (GSH) and glutathione disulfide (GSSG) concentrations in blood samples. The determination of GSSG and GSH concentrations in biological samples is important because of their roles in oxidative stress. Different concentrations of a leading ion in the coupled columns (concentration cascade) and a large volume (37 µ ) of the injected sample facilitated a GSSG concentration of between 2 and 25 µmol/l. A reaction between iodoacetate and GSH under alkaline conditions was used to prepare the sample in order to avoid oxidation of GSH to GSSG. This step eliminated the main source of systematic errors with regard to the determination of the GSSG concentration. A linear relationship (R2=0.9969) between the zone length of S-(carboxymethyl)glutathione (the product of the reaction between GSH and iodoacetate) and the concentration of GSH (40-120 µmol/l) was obtained. The method was applied to the analysis of bovine blood samples that had been diluted by a factor of ten with satisfactory results

Hybrid multilevel solution of sparse least-squares linear systems

Purpose Large sparse least-squares problems arise in different scientific disciplines such as optimization, data analysis, machine learning and simulation. This paper aims to propose a two-level hybrid direct-iterative scheme, based on novel block independent column reordering, for efficiently solving large sparse least-squares linear systems. Design/methodology/approach Herewith, a novel block column independent set reordering scheme is used to separate the columns in two groups: columns that are block independent and columns that are coupled. The permutation scheme leads to a two-level hierarchy. Using this two-level hierarchy, the solution of the least-squares linear system results in the solution of a reduced size Schur complement-type square linear system, using the preconditioned conjugate gradient (PCG) method as well as backward substitution using the upper triangular factor, computed through sparse Q-less QR factorization of the columns that are block independent. To improve the convergence behavior of the PCG method, the upper triangular factor, computed through sparse Q-less QR factorization of the coupled columns, is used as a preconditioner. Moreover, to further reduce the fill-in, then the column approximate minimum degree (COLAMD) algorithm is used to permute the block consisting of the coupled columns. Findings The memory requirements for solving large sparse least-squares linear systems are significantly reduced compared to Q-less QR decomposition of the original as well as the permuted problem with COLAMD. The memory requirements are reduced further by choosing to form larger blocks of independent columns. The convergence behavior of the iterative scheme is improved due to the chosen preconditioning scheme. The proposed scheme is inherently parallel due to the introduction of block independent column reordering. Originality/value The proposed scheme is a hybrid direct-iterative approach for solving sparse least squares linear systems based on the implicit computation of a two-level approximate pseudo-inverse matrix. Numerical results indicating the applicability and effectiveness of the proposed scheme are given.