Dealing with overlapped and unaligned chromatographic peaks by second-order multivariate calibration for complex sample analysis: Fast and green quantification of eight selected preservatives in facial masks

Restoring trilinearity with the purpose of advanced modeling: towards a more effective analysis of Pericarpium Citri Reticulatae during storage periods

To accurately quantify Pericarpium Citri Reticulatae samples, trilinear structure was restored in the stacked fingerprints for more robust modeling. Initially, liquid chromatography - diode array detector - mass spectrometry (LC-DAD-MS) and head space-solid phase micro extraction coupled to gas chromatography - mass spectrometry (HS-SPME/GC-MS) were utilized to analyze Pericarpium Citri Reticulatae. Faced with the time-shifts in two-dimensional (2D) matrices across different samples, three algorithms were developed to synchronize them. Furthermore, bilinear and trilinear models were used to realize the quantifications with different principles. Through real cases based on LC-DAD, the advantages and disadvantages of trilinear decomposition over multivariate curve resolution-alternating least-squares can be clarified in the quantification of raw or synchronized fingerprints. Also in the data processing, a modification version of multi-scale peak alignment (^mMSPA) was proved to be more suitable for trilinearity restoring than the other two algorithms. Recognizing these facts, restoring trilinearity were developed for more robust modeling in the application of the Pericarpium Citri Reticulatae fingerprints from different storage periods. After effective analysis, the upward/downward trend of 13 flavonoids were drawn accurately; and several flavour components having the highest contribution rate during storage were outlined reasonably. In conclusion, more robust modeling can be realized in trilinear data synchronized by appropriate algorithms, leading to an accurate quantification in herbal quality researches.

Stationary Phases for Green Liquid Chromatography

Industrial research, including pharmaceutical research, is increasingly using liquid chromatography techniques. This involves the production of large quantities of hazardous and toxic organic waste. Therefore, it is essential at this point to focus interest on solutions proposed by so-called “green chemistry”. One such solution is the search for new methods or the use of new materials that will reduce waste. One of the most promising ideas is to perform chromatographic separation using pure water, without organic solvents, as a mobile phase. Such an approach requires novel stationary phases or specific chromatographic conditions, such as an elevated separation temperature. The following review paper aims to gather information on stationary phases used for separation under purely aqueous conditions at various temperatures.

An in vitro assessment for human skin exposure to parabens using magnetic solid phase extraction coupled with HPLC

Skin contact was a significant source of human exposure to parabens during the use of personal care products. In this study, a novel and simple in vitro evaluation method for human skin exposure to parabens was established for the first time. Firstly, magnetic porous carbon (MPC) derived from discarded cigarette butts was prepared as an adsorbent of magnetic solid-phase extraction (MSPE), which provided a fast and efficient sample preparation method with satisfactory extraction performance for parabens in cosmetics and was easy to couple with high performance liquid chromatography. Secondly, the extraction conditions were optimized including the etching ratio of KOH, amount of MPC, extraction time, pH, salt concentration, desorption solvent volume and desorption time. Under the optimized conditions, the limits of detection were between 0.25 and 0.34 ng mL^-1 and the spiked recoveries were in the range of 85.8-112.6%. Thirdly, the developed method was successfully employed to determine five typical parabens in real unspiked cosmetic samples, and two parabens were detected at a relatively high level. Then, the developed method was applied to in vitro assays. The absorbable dose of parabens in cream was investigated and in vitro experiments were further designed with agarose-simulated skin to demonstrate the penetration ability of parabens. In conclusion, these results indicated that parabens did have the risk of entering the body through the skin and the exposure was preferably no more than 3 h with skin contact.

Chromatographic Applications in the Multi-Way Calibration Field

In this review, recent advances and applications using multi-way calibration protocols based on the processing of multi-dimensional chromatographic data are discussed. We first describe the various modes in which multi-way chromatographic data sets can be generated, including some important characteristics that should be taken into account for the selection of an adequate data processing model. We then discuss the different manners in which the collected instrumental data can be arranged, and the most usually applied models and algorithms for the decomposition of the data arrays. The latter activity leads to the estimation of surrogate variables (scores), useful for analyte quantitation in the presence of uncalibrated interferences, achieving the second-order advantage. Recent experimental reports based on multi-way liquid and gas chromatographic data are then reviewed. Finally, analytical figures of merit that should always accompany quantitative calibration reports are described.

Multilinear Mathematical Separation in Chromatography

Chromatography is a powerful and generally applicable method for the analytical separation and quantification of the chemical constituents in complex mixtures because chromatographic separation can provide high selectivity by isolating all analytes from interferences. Multiway analysis based on the multilinear model is an increasingly widely used method for interference-free and fast determination of the chemical constituents also in complex mixtures because multilinear mathematical separation can provide high selectivity by extracting the pure signal of the analyte from the mixed signal of a real sample. By combining chromatographic separation with mathematical separation, multiway calibration method, multiway standard additions method, and multiway internal standard method can be established. Chromatography assisted by multiway analysis can reduce the requirements for complete chromatographic separation, save elution time, and decrease the consumption of the mobile phase, particularly when the peak coelution problem is difficult to solve. This review presents the fundamentals and analytical applications of multilinear mathematical separation in chromatography.

Comparison of three chemometric methods for processing HPLC-DAD data with time shifts: Simultaneous determination of ten molecular targeted anti-tumor drugs in different biological samples

Three intelligent chemometric multi-way calibration methods including alternating trilinear decomposition (ATLD), alternating trilinear decomposition assisted multivariate curve resolution (ATLD-MCR) and multivariate curve resolution-alternating least squares (MCR-ALS) combined with high performance liquid chromatography-diode array detection (HPLC-DAD) were used to quantify ten molecular targeted anti-tumor drugs in three complex biological matrices (plasma, urine and cell culture media matrices). All analytes can be successfully eluted in 6.5 min. In this experiment, various degrees of time shifts occurred in different samples. While slight time shifts exist in the chromatographic analysis, satisfactory results can be obtained by the three proposed methods. When the time shift was large (5.6 s), the average spiked recoveries obtained by ATLD analysis were in the range of 58.9%-116.5%, which was less than satisfactory. However, the average recoveries obtained by MCR-ALS and ATLD-MCR analysis were 89.8%-114.8% and 84.5%-106.1% respectively, and more satisfactory results were obtained. For further research, ATLD-MCR and MCR-ALS methods were compared, and the results were evaluated by statistical tests. Accuracies of concentrations obtained by them were considered to be no significant difference. In addition, compared with other methods currently published, the proposed chemometric methods combined with the HPLC-DAD can rapidly, simultaneously and accurately determine varieties of molecular targeted anti-tumor drugs in different complex biological matrices even in the presence of severe peak overlaps, severe time shifts, slight baseline drifts and different unknown background interferences.

An ultra-robust fingerprinting method for quality assessment of traditional Chinese medicine using multiple reaction monitoring mass spectrometry

Chromatographic fingerprinting has been perceived as an essential tool for assessing quality and chemical equivalence of traditional Chinese medicine. However, this pattern-oriented approach still has some weak points in terms of chemical coverage and robustness. In this work, we proposed a multiple reaction monitoring (MRM)-based fingerprinting method in which approximately 100 constituents were simultaneously detected for quality assessment. The derivative MRM approach was employed to rapidly design MRM transitions independent of chemical standards, based on which the large-scale fingerprinting method was efficiently established. This approach was exemplified on QiShenYiQi Pill (QSYQ), a traditional Chinese medicine-derived drug product, and its robustness was systematically evaluated by four indices: clustering analysis by principal component analysis, similarity analysis by the congruence coefficient, the number of separated peaks, and the peak area proportion of separated peaks. Compared with conventional ultraviolet-based fingerprints, the MRM fingerprints provided not only better discriminatory capacity for the tested normal/abnormal QSYQ samples, but also higher robustness under different chromatographic conditions (i.e., flow rate, apparent pH, column temperature, and column). The result also showed for such large-scale fingerprints including a large number of peaks, the angle cosine measure after min-max normalization was more suitable for setting a decision criterion than the unnormalized algorithm. This proof-of-concept application gives evidence that combining MRM technique with proper similarity analysis metrices can provide a highly sensitive, robust and comprehensive analytical approach for quality assessment of traditional Chinese medicine.

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MRM fingerprints are proposed for quality assessment of traditional medicine.

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MRM fingerprints show favorable robustness, coverage and discriminatory capacity.

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Similarity analysis methods for such large-scale fingerprints are proposed.

Coupling of digital image processing and three-way calibration to assist a paper-based sensor for determination of nitrite in food samples

In this work, a novel and very interesting analytical methodology based on coupling of digital image processing and three-way calibration has been developed for determination of nitrite in food samples.