Multi-way chemometric methodologies and applications: A central summary of our research work

Third-order calibration applied to process surfactant-modulated excitation-emission matrix four-way fluorescence data for the direct determination of four polycyclic aromatic hydrocarbons in oilfield produced water

Fluorescence spectroscopy is a powerful tool to determine polycyclic aromatic hydrocarbons (PAHs) owing to the strong endogenous fluorescence of these compounds. However, the presence of unknown interferences and overlapped spectra hinders the accurate determination of PAHs in oilfield produced water. Moreover, surfactants frequently coexist in oilfield produced water and will seriously affect the fluorescence signals of PAHs. Herein, a new methodology applying third-order calibration to process four-way (4D) fluorescence data was proposed to solve these problems and achieve accurate determination of pyrene, fluorene, phenanthrene, and fluoranthene as an example in oilfield produced water. The methodology is based on excitation-emission matrix fluorescence modulated by different concentrations of sodium dodecyl benzene sulfonate (SDBS) in the analyzed samples. The 4D fluorescence data were processed by third-order calibration methods including four-way parallel factor analysis (4-PARAFAC) and alternating weighted residue constraint quadrilinear decomposition (AWRCQLD), and the results were compared with those of second-order calibration methods. It was proved that third-order calibration was capable of accurately identifying and quantifying PAHs together with SDBS in oilfield produced water, which has better quantitative results and figures of merit compared to second-order calibration. This study provided a new approach to generating 4D fluorescence data and opened up an avenue for the accurate determination of PAHs in complex oilfield produced water with surfactants.

Chemometrics-assisted excitation-emission matrix fluorescence spectroscopy for real-time migration monitoring of multiple polycyclic aromatic hydrocarbons from plastic products to food simulants

Polycyclic aromatic hydrocarbons (PAHs), as a class of organic pollutants that have attracted much attention, are likely to be formed with the production and processing of plastic products, and they may migrate from contaminated plastic products to food, causing the risk of poisoning or cancer. In this study, migration tests were carried out on disposable plastic products for food contact, and a novel strategy that combines excitation-emission matrix (EEM) fluorescence spectroscopy with the advanced second-order calibration method based on the three-direction resection alternating trilinear decomposition (TDR-ATLD) algorithm was used to monitor the migration of three PAHs anthracene (ANT), pyrene (PYR), and phenanthrene (PHE) from the plastic products to food simulants in real-time. With the "second-order advantage", even if the fluorescence spectra of the target analytes overlapped seriously, and other unknown substances migrated from the plastic products to food simulants, accurate qualitative and quantitative results were still obtained by the proposed method. In the static system, the coefficient of determination (R2) of the three PAHs within the calibration range were all greater than 0.99, and the average spiked recoveries were 99.5-107.1%, with the standard deviation lower than 8.9%. The figures of merit (FOMs) and intra- or inter-day precision also showed good feasibility and reliability of the method. In the simulation study of the migration kinetic process, three PAHs can be quantified in real-time in complex matrix, then the related migration equations were established. The results indicate that the proposed method can be used for real-time migration quantitative monitoring of PAHs, providing a potential and available method for the study of the migration kinetics of hazardous substances from food contact materials to food or food simulants.

Anti-interference and non-destructive identification of textile fabrics using front-face excitation-emission matrix fluorescence spectroscopy combined with multi-way chemometrics

The identification of trace textile fabrics discovered at crime scenes plays a crucial role in the case of forensic investigations. Additionally, in practical situations, fabrics may be contaminated, making identification more challenging. To address the aforementioned issue and promote the application of fabrics identification in forensic analysis, front-face excitation-emission matrix (FF-EEM) fluorescence spectra coupled with multi-way chemometric methods were proposed for the interference-free and non-destructive identification of textile fabrics. Common commercial dyes in the same color range under different materials (cotton, acrylic, and polyester) that cannot be visually distinguished were investigated, and several binary classification models for the identification of dye were established using partial least squares discriminant analysis (PLS-DA). The identification of dyed fabrics in the presence of fluorescent interference was also taken into consideration. In each kind of pattern recognition model mentioned above, the classification accuracy (ACC) of the prediction set was 100%. The alternating trilinear decomposition (ATLD) algorithm was executed to separate mathematically and remove the interference, and the classification model based on the reconstructed spectra attained an accuracy of 100%. These findings indicate that FF-EEM technology combined with multi-way chemometric methods has broad prospects for forensic trace textile fabric identification, especially in the presence of interference.

A Comprehensive Review on the Excitation-Emission Matrix Fluorescence Spectroscopic Characterization of Petroleum-Containing Substances: Principles, Methods, and Applications

Petroleum-containing substance (PCS) is a general term used for petroleum and its derivatives. A comprehensive characterization of PCSs is crucial for resource exploitation, economic development and environmental protection. Fluorescence spectroscopy, especially excitation-emission matrix fluorescence (EEMF) spectroscopy, has been proved to be a powerful tool to characterize PCSs since its remarkable sensitivity, selectivity, simplicity and high efficiency. However, there is a lack of systematic review focusing on this field in the literature. This paper reviews the fundamental principles and measurements of EEMF for characterizing PCSs, and makes a systematic introduction to various information mining methods including basic peak information extraction, spectral parameterization and some commonly used chemometric methods. In addition, recent advances in applying EEMF to characterize PCSs during the whole life-cycle process of petroleum are also revisited. Furthermore, the current limitations of EEMF in the measurement and characterization of PCSs are discussed and corresponding solutions are provided. For promoting the future development of this field, the urgent need to build a relatively complete EEMF fingerprint library to trace PCSs, not only pollutants but also crude oil and petroleum products, is proposed. Finally, the extensions of EEMF to high-dimensional chemometrics and deep learning are prospected, with the expectation of solving more complex systems and problems.

Interference-free quantitation of aromatic amino acids in two complex systems by three-way calibration with ultraviolet-visible spectrophotometer: Exploration of trilinear decomposition of spectrum-pH data

Aromatic amino acids play an extremely important role in life activities and participate in many biological processes. Their concentration levels are associated with a variety of diseases, such as phenylketonuria and colorectal cancer. Therefore, the quantification of aromatic amino acids is an important task. In the present work, a novel and rapid three-way analytical method was proposed to detect the levels of aromatic amino acids in prostate cancer cells (PC3 cells) and Dulbecco's modified minimal essential medium (DMEM cell culture), by using the affordable ultraviolet-visible spectrophotometer. First, spectrum-pH second-order data were designed per sample; Second, properties of the resulted spectrum-pH-sample three-way data were investigated by utilizing the parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), and constrained alternating trilinear decomposition (CATLD) algorithms, and a flexible scanning approach for determining the constraint parameters of CATLD was proposed; Third, a three-way calibration method based on the CATLD algorithm with the proposed scanning approach was developed for interference-free quantification of aromatic amino acids in these systems. The average relative predictive errors of validation (ARPEV) for phenylalanine, tyrosine, and tryptophan were 1.4%, 3.0%, and 0.7% in prostate cancer cells, and ARPEV for phenylalanine, tyrosine, and tryptophan were 4.1%, 1.2%, and 0.7% in DMEM cell culture. The predicted contents of tyrosine and tryptophan in DMEM cell culture were 64.2 ± 2.9 μg mL^-1, 5.6 ± 0.3 μg mL^-1, there are no significant differences in the concentrations between the developed analytical method and high performance liquid chromatography method. The proposed spectrum-pH-sample three-way calibration method based on CATLD algorithm can provide an interesting analytical strategy with high selectivity and accuracy for ultraviolet-visible spectrophotometer.

Insight into the Recent Application of Chemometrics in Quality Analysis and Characterization of Bee Honey during Processing and Storage

The application of chemometrics, a widely used science in food studies (and not only food studies) has begun to increase in importance with chemometrics being a very powerful tool in analyzing large numbers of results. In the case of honey, chemometrics is usually used for assessing honey authenticity and quality control, combined with well-established analytical methods. Research related to investigation of the quality changes in honey due to modifications after processing and storage is rare, with a visibly increasing tendency in the last decade (and concentrated on investigating novel methods to preserve the honey quality, such as ultrasound or high-pressure treatment). This review presents the evolution in the last few years in using chemometrics in analyzing honey quality during processing and storage. The advantages of using chemometrics in assessing honey quality during storage and processing are presented, together with the main characteristics of some well-known chemometric methods. Chemometrics prove to be a successful tool to differentiate honey samples based on changes of characteristics during storage and processing.

High-Performance Liquid Chromatography–Diode Array Detection Combined with Chemometrics for Simultaneous Quantitative Analysis of Five Active Constituents in a Chinese Medicine Formula Wen-Qing-Yin

In this work, a simple analytical strategy combining high-performance liquid chromatography–diode array detection (HPLC-DAD) and the chemometric method was developed for the simultaneous quantification of 5-hydroxymethyl-2-furfural (HMF), paeoniflorin (PAE), ferulic acid (FER), baicalin (BAI), and berberine (BER) in a Chinese medicine formula Wen-Qing-Yin (WQY). The alternating trilinear decomposition (ATLD) algorithm and alternating trilinear decomposition assisted multivariate curve resolution (ATLD-MCR) algorithm were used to realize the separation and rapid determination of five target analytes under the presence of time shifts, solvent peaks, peak overlaps, and unknown interferences. All analytes were eluted within 10 min and the linear correlation coefficients of calibration sets were between 0.9969 and 0.9996. In addition, the average recoveries of the five active compounds obtained by ATLD and ATLD-MCR analysis were in the range of 91.8–112.5% and 88.6–101.6%, respectively. For investigating the accuracy and reliability of the proposed method, figures of merit including limit of detection (LOD), limit of quantitation (LOQ), sensitivity (SEN), and selectivity (SEL) were calculated. The proposed analytical strategy has the advantages of being fast, simple, and sensitive, and can be used for the qualitative and quantitative analysis of WQY, providing a feasible option for the quality monitoring of the traditional Chinese medicine formula.

The Application of Chemometrics for Efficiency Enhancement and Toxicity Reduction in Cancer Treatment with Combined Therapy

Chemometrics is an important emerging discipline with unique charm formed by the intersection of mathematics, statistics, chemistry and computer science. The application of chemometrics in the field of pharmacy has injected fresh blood into the scientific research and clinical practice of medicine and has provided a sufficient scientific basis for drug analysis and content determination to solve the problem of cancer treatment with combined therapy in different ranges. This paper introduces the basic principles, advantages and disadvantages of several commonly used pattern recognition and multidimensional correction methods of chemometrics, reviews the application of chemometrics for efficiency enhancement and toxicity reduction in cancer treatment with combined therapy and summarizes its development and prospects in the future.

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.

Impact of diverse background interferences on the alternating trilinear decomposition modeling of excitation-emission matrix fluorescence data acquired from different sample sources

Alternating trilinear decomposition (ATLD) method enables the qualitative and quantitative analysis of excitation-emission matrix fluorescence (EEMF) data acquired from complex samples. However, the impact of diverse background interferences from different sample sources on the performances of ATLD method has never been lucubrated. In this work, simulated and real EEMF data sets from different sample sources with diverse background interferences were collected and subjected to ATLD analysis. The performances of ATLD modeling individual and global EEMF data sets were comprehensively compared in terms of the resolved spectral profiles and quantitative results. It was found that ATLD method can use the same set of calibration samples to resolve and quantify multiple components of interest in multiple complex systems with diverse background interferences, regardless of individual or global modeling. The results revealed that the qualitative and quantitative results provided by ATLD method were affected neither by diversity of background interferences nor by data merging as long as the acquired EEMF data sets conform to the trilinear component model. This property of ATLD method can enrich the "second-order advantage", i.e. the term "unknown interferences" in the concept of "second-order advantage" refers to not only constant background interferences but also diverse background interferences, which will be certain to further expand the practicality of ATLD method in complex sample analysis, especially in the field of fluorescence spectroscopy.

Rapid and simultaneous determination of three fluoroquinolones in animal-derived foods using excitation-emission matrix fluorescence coupled with second-order calibration method

The matter of fluoroquinolone residues in various foods still arouses wide public concern nowadays. In the present work, the strategy of excitation-emission matrix (EEM) fluorescence data coupled with second-order calibration method based on alternating normalization-weighted error (ANWE) algorithm was used to determine ofloxacin, lomefloxacin and ciprofloxacin in milk powder, milk and beef. Owning the unique "second-order advantage", the ANWE-assisted analytical method was proved to successfully and eco-friendly resolve the overlapped fluorescence spectra of multi-component in complex food matrixes without tedious pretreatment steps and sophisticated high-cost instrumentations. The feasibility of the proposed method was validated by experiments. The average spiked recoveries of three fluoroquinolones range from 82.6% to 110.5% with relative standard deviations lower than 7.4%, and the limits of detection range from 0.18 and 2.41 ng mL^-1. For further evaluation, analytical figures of merit such as sensitivity and selectivity, as well as the RSDs of intra-day (≦10.6%) and inter-day (≦9.4%) were calculated. The satisfactory analytical results demonstrated that the proposed strategy could be a competitive alternative for simple, rapid and simultaneous determination of multiple fluoroquinolones in animal-derived food samples.

Soft-trilinear constraints for improved quantitation in multivariate curve resolution

Soft trilinearity constraints give a range of feasible solutions (grey) that envelop the true solution (blue). PARAFAC2 (green) and MCR-ALS results (black) are shown for comparison.

Four- and five-way excitation-emission luminescence-based data acquisition and modeling for analytical applications. A review

The latest advances in both theory and experimental procedures on third-order/four-way and fourth-order/five-way calibration methods are discussed. This report is focused on excitation-emission (fluorescence and phosphorescence) matrices generation, employing different variables as the third data mode (time retention in chromatography, pH gradient, fluorescence/phosphorescence lifetime, kinetics, or other chemical treatments). Fully capitalizing on the second-order advantage, it has been possible to develop appealing analytical applications in spite of the complexity of the data. Extraction of the significant chemical information about the system under study as well as the individual abundance of the contributing constituents after proper higher-order data decomposition has allowed to analytical researchers performing quantitative analysis of complex samples. The experimental works reported up to the present are introduced and discussed in order to illustrate concepts. Throughout this work, the analytical benefits achieved by modeling third- and fourth-order data are exposed, attempting to contribute to the ongoing debate in the chemometric community regarding the existence and the true nature of the third-order advantage.

Simultaneous and fast determination of bisphenol A and diphenyl carbonate in polycarbonate plastics by using excitation-emission matrix fluorescence couples with second-order calibration method

A new strategy for the determination of bisphenol A (BPA) and diphenyl carbonate (DPC) in polycarbonate plastics has been proposed, combing excitation-emission matrix fluorescence and second-order chemometrics methods. The studied compounds are two of the most frequently used chemical raw materials and intermediates, which is mainly used for bio-chemical products. The method is fast and sensitive as it can avoid tedious pretreatment steps and large amounts of organic solvents consumption. Chemometrics allowed accurate and precise quantification of two target analytes even in the presence of severe spectral overlap, unknown and background interferences, which benefit from "second-order advantages" provided by chemometrics multivariate calibration. Reasonable quantification results were obtained in real plastics samples, with limits of detection for two analytes were 0.04 and 1.18 × 10³ ng mL^-1 and limits of quantitation were 0.11 and 3.58 × 10³ ng mL^-1. In addition, the average recoveries for BPA and DPC were 99.35% and 83.50% with relative standard deviation <2.30%. It was proved that the proposed method can be a useful and sensitive tool to the determination of BPA and DPC in different polycarbonate plastics with a simple sample pretreatment at low cost.

A novel algorithm for second-order calibration of three-way data in fluorescence assays of multiple breast cancer-related DNAs

Fluorescent probes have been valuable tools for bioanalytical multiplex assays. However, as a common phenomenon in multiplex fluorescence assays, spectral overlap usually leads to difficulty in spectral analysis for multiple analytes. Although multiway calibrations have provided mathematic approaches for complex spectral analysis, it remains a grand challenge for these methods in practical applications because of the problems such as prior rank estimation. Herein, we report a novel second-order calibration algorithm of alternating residual trilinearization (ART) for the decomposition of complex spectra generated from multiplex fluorescence assays. By alternating iterative convergence to the spectral profiles of each component in convergence process, ART enables automatic rank estimation for second-order calibration, thus able to avoid the risk of chemical meaningless fitting of component spectra. Combined with fluorescence excitation-emission matrix (EEM) spectroscopy, the performance of ART has been demonstrated by a simulated example and an analytical experiment performed using molecular beacons (MBs) for the simultaneous assay of three breast cancer related DNA targets. The results revealed that the proposed algorithm is capable of automatic estimating the number of underlying components during its convergence process to produce acceptable performance in spectral profile resolution and concentration estimation. Compared with other existing iterative trilinear decomposition strategies such as parallel factor analysis (PARAFAC) requiring a prior rank estimation, the proposed ART therefore provides a robust second-order calibration strategy for complex spectral analysis in multiplex fluorescence assays.

Rapid, simultaneous and interference-free determination of three rhodamine dyes illegally added into chilli samples using excitation-emission matrix fluorescence coupled with second-order calibration method

In this study, a smart and green analytical method based on the second-order calibration algorithm coupled with excitation-emission matrix (EEM) fluorescence was developed for the determination of rhodamine dyes illegally added into chilli samples. The proposed method not only has the advantage of high sensitivity over the traditional fluorescence method but also fully displays the "second-order advantage". Pure signals of analytes were successfully extracted from severely interferential EEMs profiles via using alternating trilinear decomposition (ATLD) algorithm even in the presence of common fluorescence problems such as scattering, peak overlaps and unknown interferences. It is worth noting that the unknown interferents can denote different kinds of backgrounds, not only refer to a constant background. In addition, the method using interpolation method could avoid the information loss of analytes of interest. The use of "mathematical separation" instead of complicated "chemical or physical separation" strategy can be more effective and environmentally friendly. A series of statistical parameters including figures of merit and RSDs of intra- (≤1.9%) and inter-day (≤6.6%) were calculated to validate the accuracy of the proposed method. Furthermore, the authoritative method of HPLC-FLD was adopted to verify the qualitative and quantitative results of the proposed method. Compared with the two methods, it also showed that the ATLD-EEMs method has the advantages of accuracy, rapidness, simplicity and green, which is expected to be developed as an attractive alternative method for simultaneous and interference-free determination of rhodamine dyes illegally added into complex matrices.

A green chemometrics-assisted fluorimetric detection method for the direct and simultaneous determination of six polycyclic aromatic hydrocarbons in oil-field wastewaters

Oil-field wastewaters contain high level of polycyclic aromatic hydrocarbons (PAHs), which have to be analyzed to assess the environmental effects before discharge. In this work, a green fluorimetric detection method that combines excitation-emission matrix (EEM) fluorescence with parallel factor analysis (PARAFAC) algorithm was firstly developed to achieve the direct and simultaneous determination of six U.S. EPA PAHs in two different kinds of complex oil-field wastewaters. Due to the distinctive "second-order advantage", neither time-consuming sample pretreatments nor toxic organic reagents were involved in the determination. By using the environment-friendly "mathematical separation" of PARAFAC, satisfactory quantitative results and reasonable spectral profiles for six PAHs were successfully extracted from the total EEM signals of oil-field wastewaters without need of chromatographic separation. The limits of detection of six PAHs were in the range of 0.09-0.72ngmL^-1, and the average spiked recoveries were between (89.4±4.8)% and (109.1±5.8)%, with average relative predictive errors <2.93%. In order to further confirm the accuracy of the proposed method, the same batch oil-field wastewater samples were analyzed by the recognized GC-MS method. t-test demonstrated that no significant differences exist between the quantitative results of the two methods. Given the advantages of green, fast, low-cost and high-sensitivity, the proposed method is expected to be broadened as an appealing alternative method for multi-residue analysis of overlapped PAHs in complex wastewater samples.

Underdetermined blind separation of three-way fluorescence spectra of PAHs in water

In this work, underdetermined blind decomposition method is developed to recognize individual components from the three-way fluorescent spectra of their mixtures by using sparse component analysis (SCA). The mixing matrix is estimated from the mixtures using fuzzy data clustering algorithm together with the scatters corresponding to local energy maximum value in the time-frequency domain, and the spectra of object components are recovered by pseudo inverse technique. As an example, using this method three and four pure components spectra can be blindly extracted from two samples of their mixture, with similarities between resolved and reference spectra all above 0.80. This work opens a new and effective path to realize monitoring PAHs in water by three-way fluorescence spectroscopy technique.

Simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii using excitation-emission matrix fluorescence coupled with chemometrics methods

A chemometrics-assisted excitation-emission matrix (EEM) fluorescence method was proposed for simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii. Using the strategy of combining EEM data with chemometrics methods, the simultaneous determination of α-asarone and β-asarone in the complex Traditional Chinese medicine system was achieved successfully, even in the presence of unexpected interferents. The physical or chemical separation step was avoided due to the use of "mathematical separation". Six second-order calibration methods were used including parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), alternating penalty trilinear decomposition (APTLD), self-weighted alternating trilinear decomposition (SWATLD), the unfolded partial least-squares (U-PLS) and multidimensional partial least-squares (N-PLS) with residual bilinearization (RBL). In addition, HPLC method was developed to further validate the presented strategy. Consequently, for the validation samples, the analytical results obtained by six second-order calibration methods were almost accurate. But for the Acorus tatarinowii samples, the results indicated a slightly better predictive ability of N-PLS/RBL procedure over other methods.

Simultaneous Determination of Warfarin and Aspirin Contents in Biological Fluids Using Excitation-Emission Matrix Fluorescence Coupled with a Second-order Calibration Method

In the present work, a practical method that combines excitation-emission matrix fluorescence with a second-order calibration method based on an alternating trilinear decomposition (ATLD) algorithm was developed in order to simultaneously and directly determine the contents of warfarin (WAR) and aspirin (ASA) in human plasma and urine samples, even in the presence of unknown interferences. With the pre-estimated component number of 4, the obtained average spiked recoveries were 105.4 ± 7.8 and 104.2 ± 8.3% for WAR, 96.5 ± 2.8 and 91.2 ± 2.3% for ASA in human plasma and urine samples, respectively. Furthermore, the figures of merit were calculated and also inter- and intra-day experiments were performed that proved the proposed method is of great significance to the monitoring of clinical administration and also being a simple sample pretreatment at low-cost.

Quantitative fluorescence kinetic analysis of NADH and FAD in human plasma using three- and four-way calibration methods capable of providing the second-order advantage

The metabolic coenzymes reduced nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) are the primary electron donor and acceptor respectively, participate in almost all biological metabolic pathways. This study develops a novel method for the quantitative kinetic analysis of the degradation reaction of NADH and the formation reaction of FAD in human plasma containing an uncalibrated interferent, by using three-way calibration based on multi-way fluorescence technique. In the three-way analysis, by using the calibration set in a static manner, we directly predicted the concentrations of both analytes in the mixture at any time after the start of their reactions, even in the presence of an uncalibrated spectral interferent and a varying background interferent. The satisfactory quantitative results indicate that the proposed method allows one to directly monitor the concentration of each analyte in the mixture as the function of time in real-time and nondestructively, instead of determining the concentration after the analytical separation. Thereafter, we fitted the first-order rate law to their concentration data throughout their reactions. Additionally, a four-way calibration procedure is developed as an alternative for highly collinear systems. The results of the four-way analysis confirmed the results of the three-way analysis and revealed that both the degradation reaction of NADH and the formation reaction of FAD in human plasma fit the first-order rate law. The proposed methods could be expected to provide promising tools for simultaneous kinetic analysis of multiple reactions in complex systems in real-time and nondestructively.

Solving signal instability to maintain the second-order advantage in the resolution and determination of multi-analytes in complex systems by modeling liquid chromatography-mass spectrometry data using alternating trilinear decomposition method assisted with piecewise direct standardization

The application of calibration transfer methods has been successful in combination with near-infrared spectroscopy or other tools for prediction of chemical composition. One of the developed methods that can provide accurate performances is the piecewise direct standardization (PDS) method, which in this paper is firstly applied to transfer from one day to another the second-order calibration model based on alternating trilinear decomposition (ATLD) method built for the interference-free resolution and determination of multi-analytes in complex systems by liquid chromatography-mass spectrometry (LC-MS) in full scan mode. This is an example of LC-MS analysis in which interferences have been found, making necessary the use of second-order calibration because of its capacity for modeling this phenomenon, which implies analytes of interest can be resolved and quantified even in the presence of overlapped peaks and unknown interferences. Once the second-order calibration model based on ATLD method was built, the calibration transfer was conducted to compensate for the signal instability of LC-MS instrument over time. This allows one to reduce the volume of the heavy works for complete recalibration which is necessary for later accurate determinations. The root-mean-square error of prediction (RMSEP) and average recovery were used to evaluate the performances of the proposed strategy. Results showed that the number of calibration samples used on the real LC-MS data was reduced by using the PDS method from 11 to 3 while producing comparable RMSEP values and recovery values that were statistically the same (F-test, 95% confidence level) to those obtained with 11 calibration samples. This methodology is in accordance with the highly recommended green analytical chemistry principles, since it can reduce the experimental efforts and cost with regard to the use of a new calibration model built in modified conditions.

Simultaneous determination of eight flavonoids in propolis using chemometrics-assisted high performance liquid chromatography-diode array detection

A fast analytical strategy of second-order calibration method based on the alternating trilinear decomposition algorithm (ATLD)-assisted high performance liquid chromatography coupled with a diode array detector (HPLC-DAD) was established for the simultaneous determination of eight flavonoids (rutin, quercetin, luteolin, kaempferol, isorhamnetin, apigenin, galangin and chrysin) in propolis capsules samples. The chromatographic separation was implemented on a Wondasil™ C18 column (250mm×4.6mm, 5μm) within 13min with a binary mobile phase composed of water with 1% formic acid and methanol at a flow rate of 1.0mLmin(-1) after flavonoids were only extracted with methanol by ultrasound extraction for 15min. The baseline problem was overcome by considering background drift as additional compositions or factors as well as the target analytes, and ATLD was employed to handle the overlapping peaks from analytes of interest or from analytes and co-eluting matrix compounds. The linearity was good with the correlation coefficients no less than 0.9947; the limit of detections (LODs) within the range of 3.39-33.05ngmL(-1) were low enough; the accuracy was confirmed by the recoveries ranged from 91.9% to 110.2% and the root-mean-square-error of predictions (RMSEPs) less than 1.1μg/mL. The results indicated that the chromatographic method with the aid of ATLD is efficient, sensitive and cost-effective and can realize the resolution and accurate quantification of flavonoids even in the presence of interferences, thus providing an alternative method for accurate quantification of analytes especially when the complete separation is not easily accomplished. The method was successfully applied to propolis capsules samples and the satisfactory results were obtained.

Second-order advantage obtained from standard addition first-order instrumental data and multivariate curve resolution-alternating least squares. Calculation of the feasible bands of results

In order to achieve the second-order advantage, second-order data per sample is usually required, e.g., kinetic-spectrophotometric data. In this study, instead of monitoring the time evolution of spectra (and collecting the kinetic-spectrophotometric data) replicate spectra are used to build a virtual second order data. This data matrix (replicate mode×λ) is rank deficient. Augmentation of these data with standard addition data [or standard sample(s)] will break the rank deficiency, making the quantification of the analyte of interest possible. The MCR-ALS algorithm was applied for the resolution and quantitation of the analyte in both simulated and experimental data sets. In order to evaluate the rotational ambiguity in the retrieved solutions, the MCR-BANDS algorithm was employed. It has been shown that the reliability of the quantitative results significantly depends on the amount of spectral overlap in the spectral region of occurrence of the compound of interest and the remaining constituent(s).

Quantitative study of state switching in proteins using a single probe combined with trilinear decomposition

Excitation–Emission Matrix fluorescence (EEM) signals from the state switching of α-chymotrypsin can be resolved and investigated quantitatively by trilinear decomposition.