Yu-Jie Ding

Interference-free determination of fluoroquinolone antibiotics in plasma by using excitation–emission matrix fluorescence coupled with second-order calibration algorithms

Fluoroquinolones or so-called second-generation quinolones, in particular, ofloxacin (OFL), norfloxacin (NOR), and enoxacin (ENO), with therapeutic advantages possess strongly overlapped fluorescence spectra. In this paper, two strategies were proposed for simultaneous direct determination of OFL, NOR and ENO in plasma by combining fluorescence excitation-emission matrix (EEM) with second-order calibration based on the alternating trilinear decomposition algorithm (ATLD) and parallel factor analysis (PARAFAC). The results showed that both algorithms could solve the problem of serious fluorescence spectral overlapping of the sought-for analytes even in the presence of uncalibrated interferents. However, ATLD has advantages of being insensitive to overestimated component number and fast convergence. The results by using ATLD with an estimated component number of five were reasonably acceptable for clinical analysis. The average recoveries of OFL, NOR and ENO in synthetic samples were 99.7+/-2.4, 101.5+/-2.4 and 97.3+/-3.8%, respectively; the average recoveries of OFL, NOR and ENO in complex plasma were 94.3+/-2.6, 85.6+/-3.3 and 103.3+/-3.0%, respectively.

Vertex vector sequential projection for the resolution of three-way data.

Usually, the PARAFAC2 method is utilized for handling retention time shifts in resolving chromatographic three-way data. It requires all profiles shift the same amount, which, unfortunately, seems unlikely the case in the practice of chromatographic analysis of multi-component samples. The present authors deal with the problem by unfolding the three-way data array along a certain direction into one matrix and setting up a multi-bilinear model. Then, a new method called vertex vector sequential projection (VVSP) is proposed to select pure variables and then the alternating least squares (ALS) procedure is used to iteratively improve the fit of the data to the multi-bilinear model. With a good estimate that is as close as possible to the pure variables, a fast convergence can be expected. Moreover, no prerequisite on the shifting is required and the multi-bilinear model provides a plausible manner to make use of the multi-sample information. An additional advantage is that the present fitting procedure is easier to adjust when constraints such as non-negativity, unimodality, etc., are to be imposed on the loading matrix. The proposed method is evaluated with simulated and real chemical data sets. Satisfactory resolution results are obtained, which demonstrates the performance of the proposed method.

Simultaneous and interference-free determination of eleven non-steroidal anti-inflammatory drugs illegally added into Chinese patent drugs using chemometrics-assisted HPLC-DAD strategy

In this work, a smart strategy that combines three-way high performance liquid chromatography-diode array detection (HPLCDAD) data with second-order calibration method based on alternating trilinear decomposition (ATLD) algorithm was proposed for simultaneous determination of eleven non-steroidal anti-inflammatory drugs (NSAIDs) illegally added into Chinese patent drugs and health products. All target analytes were rapidly eluted out within 14.5 min under a simple gradient elution. With the aid of the prominent “second-order advantage” of the ATLD algorithm, three HPLC problems, i.e. peak overlaps, unknown interferences and baseline drift, could be mathematically calibrated, and pure signals of target analytes could be extracted out from heavy-interference but information-rich HPLC-DAD data. The average spiked recoveries for all target analytes were in the range of 95.9%–106.4% with standard deviations lower than 7.5%. Validation parameters including sensitivity (SEN), selectivity (SEL), limit of detection (LOD), limit of quantitation (LOQ) and precisions of intra-day and inter-day were calculated to validate the accuracy of the proposed method, quantitative results were further confirmed by the classic HPLC method, which proved that chemometrics-assisted HPLC-DAD analytical strategy was highly efficient, accurate and green for drug-abuse monitoring of NSAIDs in Chinese patent drugs and health products.

Chemometrics-assisted liquid chromatography-full scan mass spectrometry for simultaneous determination of multi-class estrogens in infant milk powder

In the present study, a smart analytical strategy that combines liquid chromatography-full scan mass spectrometry with the second-order calibration method based on the alternating trilinear decomposition (ATLD) algorithm was developed for the simultaneous determination of seven estrogens in infant milk powders. The seven estrogens were rapidly eluted out within 7.0 min under a simple gradient condition and then, they were detected by mass spectrometry operated in the full scan mode. With the aid of the prominent “second-order advantage” of the algorithm, specific qualitative and quantitative information about the target analytes could be extracted from the complex system even in the presence of considerable peak overlaps, baseline drifts and unknown interferences. The proposed strategy avoided time-consuming and laborious sample pretreatment procedures, resulting in minimal loss of analytes, which improved the analytical accuracy. Average recoveries of the seven estrogens in two spiked infant milk powder samples were in the range of 91.2–104.2% with the relative standard deviations (RSDs) lower than 5.0% (with the exception for 17α-estradiol), and the limits of detection (LOD) ranged from 0.07 to 2.49 ng mL−1. Besides, to further confirm the feasibility and reliability of the proposed method, the same batch of samples was analyzed using the LC-MS/MS method, and the statistical tests showed that no significant difference existed between the two methods, which fully indicated that the proposed strategy could provide satisfactory prediction results in real infant milk powder samples as well as other actual chemical systems.