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Simultaneous quantification of salvianolic acid B and tanshinone IIA of salvia tropolone tablets by UPLC-MRM-MS/MS for pharmacokinetic studies

Li J. R., Li D. X., Li L., Deng W. L., Ding L. S., Xu H. X., Zhou Y.

Acta Chromatographica

2014

Vol. 26, no. 4

711--725

A rapid and sensitive ultraperformance liquid chromatography-multiple reaction monitoring-multi-stage/mass spectrometry (UPLC-MRM-MS/MS) method has been developed for simultaneous quantification of salvianolic acid B and tanshinone IIA of salvia tropolone tablets in dog plasma. This was achieved by performing quantification using the MRM acquisition with two channels of MRM-MS/MS and MS full scan for more accuracy qualitative results, and the fragmentation transitions of m/z 295→249, 191 for tanshinone IIA and m/z 297→279, 251 for IS in positive mode, m/z 717→519, 321 for salvianolic acid B and m/z 295→267, 239 for IS in negative mode were selected. The UPLC separation was achieved within 3 min in a single UPLC run. Linear calibration curves were obtained over the concentration range of 10 pg/mL-1 ng/mL for tanshinone IIA and 100 pg/mL-1 for salvianolic acid B. Lower limit of quantitation (LLOQ) was 10 pg/mL and 100 pg/mL for tanshinone IIA and salvianolic acid B, respectively. The inter-day and intra-day precision (relative standard deviation, RSD) in all samples were less than 8.21%, and the recoveries were over 85.9% for both tanshinone IIA and salvianolic acid B. The two channels of MRM with MS full scan approach could provide both qualitative and quantitative results without the need for repetitive analyses and resulted in the reduction of further confirmation experiments and analytical time. The pharmacokinetic study of the two active components of salvia tropolone tablets following oral gavage administration of dogs was thus explored with this method.

Reduction of Large Circuit Models Via Low Rank Approximate Gramians

Li J. R., White J.

International Journal of Applied Mathematics and Computer Science

2001

Vol. 11, no 5

1151-1171

We describe a model reduction algorithm which is well-suited for the reduction of large linear interconnect models. It is an orthogonal projection method which takes as the projection space the sum of the approximate dominant controllable subspace and the approximate dominant observable subspace. These approximate dominant subspaces are obtained using the Cholesky Factor ADI (CF-ADI) algorithm. We describe an improvement upon the existing implementation of CF-ADI which can result in significant savings in computational cost. We show that the new model reduction method matches moments at the negative of the CF-ADI parameters, and that it can be easily adapted to allow for DC matching, as well as for passivity preservation for multi-port RLC circuit models which come from modified nodal analysis.