Presence Of Unknown Interferences Research Articles

Green Approach for Simultaneous Quantitative Analysis of Fluoroquinolones in the Environment using Three-Dimensional Fluorescence Coupled with Second-Order Calibration Method.

In this study, a straightforward and quick analytical technique based on the self-weighted alternating trilinear decomposition (SWATLD) algorithm in conjunction with excitation-emission matrix (EEM) fluorescence for the simultaneous determination of the antibiotics levofloxacin (LVFX) and ciprofloxacin (CIP) in environmental waters and sediments was developed. This approach completely utilizes the "second-order advantage" and inherits the great sensitivity of classic fluorescence. It replaces or improves the conventional "physical/chemical separation" with "mathematical separation", enabling direct and quick quantification of the target analytes even in the presence of unknown interferences, greatly streamlining sample preparation procedures, consuming less solvent, and speeding up analysis time, and allows successful and environmentally friendly solution of overlapping fluorescence spectra of multiple components in complicated environmental matrices without cumbersome pretreatment steps and complex and expensive instrumentation. The limits of detection varied between 0.34 and 0.67 ng mL- 1, and the average spiking recoveries of LVFX and CIP in water and sediment ranged from 97.6 to 107.7% with relative standard deviations lower than 6.6%. The developed method shows the reliability of the technology and the ability to quickly detect trace antibiotics in lake water even in the presence of unidentified interferents.

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.

PARAFACM: A second-order calibration algorithm for handling data with missing values

In the process of collecting chemical data, missing values often occur due to some reasons. The missing values will destroy the multi-linear structure of the data, thus making the traditional multi-way calibration algorithm unable. Therefore, this work proposed a novel second-order calibration algorithm, PARAFAC for missing values (PARAFACM), which can directly handle the three-way data array with missing values. This proposed algorithm combines the idea of regarding multivariate linear regression as a set of individual univariate linear regressions with the iterative least squares principle. PARAFACM is open source and available from Supplementary materials. The proposed algorithm, as well as the previous three algorithms, including weighted PARAFAC (WPARAFAC), Incomplete Data PARAFAC (INDAFAC), and PARAFAC with single imputation (PARAFACSI), were used to handle the three-way simulation data array with three missing situations (random missing points, random missing channels, and scattering removal) at different missing ratios and noise levels. The comparison results show that the proposed algorithm is more universal when dealing with three missing situations and has a faster iteration speed. Moreover, its overall performance is better than the other algorithms when dealing with different missing ratios and noise levels. In addition, the proposed algorithm was also used to decompose the semi-simulated HPLC-DAD data array with missing time channels and the real EEM data array with scattering removal, and obtained satisfactory quantitative results. In general, the proposed algorithm can efficiently and accurately handle a variety of three-way data arrays with missing values, and extract the qualitative and quantitative information of components of interest in the presence of unknown interferences.

A chemometric comparison of different models in fluorescence analysis of dabigatran etexilate and dabigatran.

In this paper, a simple, rapid, low-cost and potential method was established for the simultaneous quantitative analysis of dabigatran etexilate (DABE) and dabigatran (DAB) in spiked biological fluids. It combined excitation-emission matrix fluorescence (EEMF) with different second-order calibration methods, including the self-weighted alternating normalized residue fitting (SWANRF) algorithm based on trilinear decomposition model, the multivariate curve resolution - alternating least-squares (MCR-ALS) based on bilinear decomposition model and the unfolded partial least-square coupled with residual bilinearization (U-PLS/RBL) based on latent variables model. The proposed method showed "second-order advantage", that is, satisfactory quantitative results were successfully obtained even in the presence of unknown interferences and serious spectral overlap. The recoveries of DABE and DAB in spiked biological fluids were 91.7%-101.7% for SWANRF, 95.9%-117.8% for MCR-ALS, 83.0%-109.6% for U-PLS/RBL, respectively. Figures of merit and other statistical parameters were also calculated to assess the performance of the proposed method. Moreover, the modeling procedures and characteristics of three different models in EEMF analysis were discussed and compared.

Analysis of Carcinogenic Polycyclic Aromatic Hydrocarbons in the Complex Background of the Petroleum Fluorescence Using Multivariate Curve Resolution Alternating Least Square and Total Synchronous Fluorescence Spectroscopic Technique.

Multivariate curve resolution alternating least square (MCR-ALS) analysis allows the simultaneous retrieval of pure concentration and spectral profiles for each of the analysed chemical components from the composite spectrum even in the presence of unknown interferences. Total synchronous fluorescence spectroscopy (TSFS), a multidimensional fluorescence technique that describes the variation of synchronous fluorescence profile acquired as a function of increasing offset, has become a useful analytical technique. Suitably arranged TSFS data set can be easily processed using MCR-ALS and thereby a simple and sensitive analytical tool could be developed. The present work successfully used the combination of the MCR-ALS and TSFS to analyse the three carcinogenic and mutagenic polycyclic aromatic hydrocarbons (PAHs) namely Benzo[a]Pyrene, Chrysene and Pyrene in the presence of complex fluorescence background originated from petroleum product. MCR-ALS assisted TSFS can be used for the routine analyses of these carcinogenic PAHs to ensure the quality of water and other samples belonging to different part of the ecosystem.

Novel Three-Dimensional Resolution of a pH and Ultraviolet-Visible Absorption Spectral Dataset for the Determination of Desloratadine in a Pharmaceutical Product and Its Acid Dissociation Constant

Three-way data analysis (or multi-way data analysis) of higher-order records is required to develop new and potential resolution methods to reveal multiple latent information or hidden features from multicomponent systems in presence of unknown interferences. This article presents a new application of parallel factor analysis (PARAFAC), which is one of the multiway analysis techniques, to quantify desloratadine in sirup and to simultaneously determine its acid dissociation constant (pKa) in the presence of spectral interferences without using complex and expensive instrumental methods. The three-dimensional pH-absorbance dataset, which was obtained as a function of wavelength, pH and concentration, was decomposed using the PARAFAC algorithm to obtain the estimated spectral, pH and relative concentration profiles of acid-base pair of desloratadine and sirup excipients. The quantity of the drug in sirup formulation was calculated from the estimated relative concentration profile, which was one of the three modes. At the same time, the acid dissociation constant of desloratadine was determined using the estimated pH profile of the acid and base species in their equilibrium. The applicability of the PARAFAC method was confirmed by the analysis of validation samples. In the practical application of the PARAFAC method to real samples, successful results were reported for the quality control of a sirup formulation containing desloratadine and for the estimation of desloratadine’s pKa value. The PARAFAC assay results were compared to results obtained by ultra-performance liquid chromatography (UPLC).

A novel quadrilinear decomposition method for four-way data arrays analysis based on algorithms combination strategy: Comparison and application

Recently, there has been growing interest in the decomposition of multilinear component models in the field of multi-way calibration. In this work, a novel quadrilinear decomposition method, i.e. four-way algorithm combination method (FACM), is proposed for four-way calibration. The FACM skillfully integrates the alternating quadrilinear decomposition (AQLD) algorithm with the four-way parallel factor analysis (FPARAFAC) algorithm and gives full play to their advantages. The performance of the FACM and the existing five algorithms are compared by using two simulated data sets. Moreover, a published four-way data array and a new four-way data array, which record a series of fluorescence spectra information of biomarkers in biological samples, are investigated by the proposed method respectively. The results demonstrate that the novel method can accurately and effectively extract the qualitative and quantitative information of analytes of interest even in the presence of unknown interferents and varying background. Besides, the FACM has attractive properties, such as very fast convergence, insensitive to initial values and excess number of components, and suitable for high noise level as well as severely collinear data. In addition, the proposed method can also be extended to combine other iterative algorithms, providing a feasible idea for the exploration and development of new algorithms.

Hyperbolic subtraction method: Determination of the concentration of an analyte in the presence of an unknown interferent via spectral data.

A theoretical model to determine the concentration of an analyte in the presence of unknown interferents using spectral-type data is described. The method involves absorbance measurements at three wavelengths and the calculation of specific absorbances yielding a hyperbolic relationship between absorbance ratios and analyte concentrations. The concentration of the analyte of known spectrum can be determined in the presence of an interferent or mixture of interferents of unknown concentration(s) and spectra can be determined combining data for different sets of wavelengths. Application to indigo and isatin solutions in DMSO related to the so-called Maya blue problem is reported as an illustrative application example.

High-throughput chemometrically assisted flow-injection method for the simultaneous determination of multi-antiretrovirals in water

This work is focused on the simultaneous determination of different nucleosides (lamivudine, abacavir, zidovudine) and non-nucleoside (nevirapine, efavirenz) reverse transcriptase inhibitors (antiretrovirals) in river, tap and well water by pH-gradient flow-injection analysis with diode-array detection (FIA-DAD) and further multivariate curve resolution-alternating least square (MCR-ALS) processing. Previous to the development of the analytical method with quantitative purpose, the acid-base characterization was conducted for all the analytes by determination of the experimental pKa. The pKa values, obtained by UV spectrometric titration coupled to MCR-ALS data modeling, were in agreement with those found in the literature, and, interestingly, a non-reported pKa of 12.27 was identified for nevirapine. Eventually, the analytical method was developed and its performance on the quantitation of the antiretrovirals was evaluated through its application to validation and environmental samples. The recovery studies showed values between 85 and 115% with relative errors of prediction below 10%. The figures of merit were satisfactory for all the studied drugs, with limits of detection between 25 and 40 μg L−1. Therefore, the proposed method, which is based on the generation of high-throughput data, is a simple and suitable alternative to determine the concentration of antiretroviral drugs in complex matrices, without pre-concentration or extraction steps. Additionally, MCR-ALS demonstrated to be a useful tool for solving mixtures of analytes with high spectral overlapping, in the presence of unknown interferences.

New approach to H-point standard addition method for detection and elimination of unspecific interferences in samples with unknown matrix

A novel method for correction of unknown unspecific (additive) interferences was developed in sequential injection analysis (SIA) using a Lab on Valve module (LOV) with spectrophotometric detection. The method implements a novel idea to calibrate by the standard addition method in several different chemical conditions created in such a way to measure different signal for an analyte and unchanged signal for interferents causing additive effect. This approach, being an enhancement of the H-point standard addition method (HPSAM), enables to quantify unbiased concentration of an analyte in the presence of unknown interferences. The method was tested on the example of the determination of ascorbic acid in soft drinks and juices basing on reduction of Fe(III) to Fe(II) and reaction of the latter with o-phenanthroline to the ferroin complex absorbing at 512.0nm. The analytical utility of the method has been verified and confirmed by the spectrophotometric determination of total acidity in rose and red wines in the presence of bromothymol blue absorbing at 616.0nm. Calibration solutions were prepared automatically in the designed flow system. Ascorbic acid was determined with LOD of 1.4mgL−1 and LOQ of 4.2mgL−1 within linear working range up to 80mgL−1, while in case of the determination of total acidity the values of 4.2, 11.8 and 100, respectively, were obtained. A sample was consumed in volumes of 400 and 1000µL in both cases. The analyses are simple, “green”, and non-expensive. The developed method is readily applicable to analysis of real samples of complex unknown matrices and adaptable to different analytical 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.

A systematic study on the effect of noise and shift on multivariate figures of merit of second-order calibration algorithms

In the present study, multivariate analytical figures of merit (AFOM) for three well-known second-order calibration algorithms, parallel factor analysis (PARAFAC), PARAFAC2 and multivariate curve resolution-alternating least squares (MCR-ALS), were investigated in simulated hyphenated chromatographic systems including different artifacts (e.g., noise and peak shifts). Different two- and three-component systems with interferences were simulated. Resolved profiles from the target components were used to build calibration curves and to calculate the multivariate AFOMs, sensitivity (SEN), analytical sensitivity (γ), selectivity (SEL) and limit of detection (LOD). The obtained AFOMs for different simulated data sets using different algorithms were used to compare the performance of the algorithms and their calibration ability. Furthermore, phenanthrene and anthracene were analyzed by GC-MS in a mixture of polycyclic aromatic hydrocarbons (PAHs) to confirm the applicability of multivariate AFOMs in real samples. It is concluded that the MCR-ALS method provided the best resolution performance among the tested methods and that more reliable AFOMs were obtained with this method for the studied chromatographic systems with various levels of noise, elution time shifts and presence of unknown interferences.

Area correlation constraint for the MCR−ALS quantification of cholesterol using EEM fluorescence data: A new approach

This work demonstrates the use of a new additional constraint for the Multivariate Curve Resolution−Alternating Least Squares (MCR−ALS) algorithm called “area correlation constraint”, introduced to build calibration models for Excitation Emission Matrix (EEM) data. We propose the application of area correlation constraint MCR−ALS for the quantification of cholesterol using a simulated data set and an experimental data system (cholesterol in a ternary mixture). This new constraint includes pseudo-univariate local regressions using the area of resolved profiles against reference values during the alternating least squares optimization, to provide directly accurate quantifications of a specific analyte in concentration units. In the two datasets investigated in this work, the new constraint retrieved correctly the analyte and interference spectral profiles and performed accurate estimations of cholesterol concentrations in test samples. This the first study using the proposed area constraint using EEM measurements. This new constraint approach emerges as a new possibility to be tested in general cases of second-order multivariate calibration data in the presence of unknown interferents or in more involved higher order calibration cases.

Maximizing the Sum Rate in Cellular Networks Using Multiconvex Optimization

In this paper, we propose a novel algorithm to maximize the sum-rate in interference-limited scenarios where each user decodes its own message with the presence of unknown interferences and noise. The problem of adapting the transmit and receive filters of the users to maximize the sum-rate with a transmit power constraint is nonconvex. Our novel approach is to formulate the sum-rate maximization problem as an equivalent multiconvex optimization problem by adding two sets of auxiliary variables. An iterative algorithm, which alternatingly adjusts the system variables and the auxiliary variables is proposed to solve the multiconvex optimization problem and we show that the algorithm converges to a stationary point. The proposed algorithm is applied to a downlink cellular scenario consisting of several cells each of which contains a base station serving several mobile stations. We examine the two cases, with or without several half-duplex amplify-and-forward relays assisting the transmission. A sum power constraint at the base stations and at the relays are assumed. The applicability of our approach to the individual power constraints case is also shown. Finally, we show that the proposed multiconvex formulation of the sum-rate maximization problem is applicable to many other wireless systems in which the estimated data symbols are multiaffine functions of the system variables.

Second order advantage obtained by spectroelectrochemistry along with novel carbon nanotube modified mesh electrode: Application for determination of acetaminophen in Novafen samples

A matrix-augmentation multivariate curve resolution–alternating least-squares (MA-MCR–ALS) has been conducted on the spectroelectrochemical data of acetaminophen oxidation in order to quantify acetaminophen in Novafen capsule in the presence of unknown interferences. The experiments were carried out using new cheap mesh electrode, namely carbon nanotube modified mesh electrode (CNMME) as optically transparent thin layer electrode (OTTLE). For each sample, a second order spectroelectrochemical data was obtained and MA-MCR–ALS method was applied to analyze these data. Unlike full trilinear models such as PARAFAC, MCR–ALS is flexible in applying trilinearity constraint for each component, a fact which makes it manage deviations from trilinearity of data effectively. This method was employed in both spectral and kinetic augmentation mode of data under examining different trilinear components. However, spectral augmentation was the only setting which allows MA-MCR–ALS to solve the analytical problem achieving the second order advantage. Therefore, here the results of the augmentation in this mode have been described. In order to obtain the best analytical figures of merit in the analysis, different constraints were investigated. The results indicated the accuracy of the proposed method.

Application of bilinear least squares/residual bilinearization in bulk liquid membrane system for simultaneous multicomponent quantification of two synthetic dyes

For the first time, this research reports a new application of bulk liquid membrane (BLM) with second-order calibration based on the bilinear least squares/residual bilinearization (BLLS/RBL) algorithm, as a novel method for simultaneous removal and quantification of allura red (AR) and sunset yellow (SY) as model compounds in soft drinks and food samples. Due to severe spectral overlapping between the AR and SY and strong colinearities present in the data set, common second-order multivariate calibration methods, such as parallel factor analysis (PARAFAC) and multivariate curve resolution-alternating least-squares (MCR-ALS), could not be successfully applied to the presently studied samples. At first, the basic experimental parameters affecting the transport of the target dyes were investigated and optimized. Then under the optimum conditions, we have explored an alternative use of BLLS/RBL methodology, which can work adequately with strongly overlapping spectra and colinearities problems. Satisfactory results were obtained for analysis of target analytes. The proposed method was validated by comparison with a reference method based on high-performance liquid chromatography-ultra violet detection (HPLC-UV) and no significant differences were found between the reference values and the ones obtained with the proposed method. Such a chemometrics-based protocol may be a very promising tool for more analytical applications in real samples monitoring, due to its advantages of easy sample pretreatment, accuracy, sufficient spectral resolution and concentration prediction even in the presence of unknown interferences.

Second-order data obtained by beta-cyclodextrin complexes: A novel approach for multicomponent analysis with three-way multivariate calibration methods

This research reports the first application of β-cyclodextrin (β-CD) complexes as a new method for generation of three way data, combined with second-order calibration methods for quantification of a binary mixture of caffeic (CA) and vanillic (VA) acids, as model compounds in fruit juices samples. At first, the basic experimental parameters affecting the formation of inclusion complexes between target analytes and β-CD were investigated and optimized. Then under the optimum conditions, parallel factor analysis (PARAFAC) and bilinear least squares/residual bilinearization (BLLS/RBL) were applied for deconvolution of trilinear data to get spectral and concentration profiles of CA and VA as a function of β-CD concentrations. Due to severe concentration profile overlapping between CA and VA in β-CD concentration dimension, PARAFAC could not be successfully applied to the studied samples. So, BLLS/RBL performed better than PARAFAC. The resolution of the model compounds was possible due to differences in the spectral absorbance changes of the β-CD complexes signals of the investigated analytes, opening a new approach for second-order data generation. The proposed method was validated by comparison with a reference method based on high-performance liquid chromatography photodiode array detection (HPLC-PDA), and no significant differences were found between the reference values and the ones obtained with the proposed method. Such a chemometrics-based protocol may be a very promising tool for more analytical applications in real samples monitoring, due to its advantages of simplicity, rapidity, accuracy, sufficient spectral resolution and concentration prediction even in the presence of unknown interferents.

HPLC-DAD data coupled with second-order calibration method applied to food analysis: Simultaneous determination of six benzoylurea insecticides in various fruit samples by selecting time region of chromatogram

This work presents a novel application of second-order calibration based on self-weighted alternating trilinear decomposition (SWATLD) algorithm for analyzing the HPLC-DAD data. The proposed method makes it possible to simultaneously determine teflubenzuron, hexaflumuron, flufenoxuron, chlorfluazuron, diflubenzuron and benzoylurea in different fruit samples, i.e. pear, apple and banana, in the selected time region of chromatogram. The concentration, elution time and spectral information of these benzoylurea insecticides are selectively extracted from complex matrices even in the presence of unknown interferences. The root-mean-square error of prediction (RMSEP) and figures of merit, including sensitivity (SEN), selectivity (SEL) and limit of detection (LOD) are employed to access the performance of the method. The LODs obtained for these insecticides are within the range 0.017-0.26 ppm in pears, 0.039-0.33 ppm in apples, 0.041-0.44 ppm in bananas, respectively. Such a chemometrics-based protocol holds great potential to be extended as a promising alternative for more practical applications in food safety and quality monitoring.

Characterization of sildenafil citrate tablets of different sources by near infrared chemical imaging and chemometric tools

The chemical imaging technique by near infrared spectroscopy was applied for characterization of formulations in tablets of sildenafil citrate of six different sources. Five formulations were provided by Brazilian Federal Police and correspond to several trademarks of prohibited marketing and one was an authentic sample of Viagra. In a first step of the study, multivariate curve resolution was properly chosen for the estimation of the distribution map of concentration of the active ingredient in tablets of different sources, where the chemical composition of all excipients constituents was not truly known. In such cases, it is very difficult to establish an appropriate calibration technique, so that only the information of sildenafil is considered independently of the excipients. This determination was possible only by reaching the second-order advantage, where the analyte quantification can be performed in the presence of unknown interferences. In a second step, the normalized histograms of images from active ingredient were grouped according to their similarities by hierarchical cluster analysis. Finally it was possible to recognize the patterns of distribution maps of concentration of sildenafil citrate, distinguishing the true formulation of Viagra. This concept can be used to improve the knowledge of industrial products and processes, as well as, for characterization of counterfeit drugs.

Simultaneous determination of tyrosine and dopamine in urine samples using excitation–emission matrix fluorescence coupled with second-order calibration

Abstract A “green” and quick analytical method for complex compounds was developed for simultaneous determination of tyrosine (Tyr) and dopamine (DA) in urine samples in this paper. The three-way responsive data recorded by excitation–emission matrix fluorescence (EEM) spectrometer was analyzed using second-order calibration methods based on both parallel factor analysis (PARAFAC) and self-weighted alternating trilinear decomposition (SWATLD) algorithms. The EEM spectra of the analytes were overlapped with the background in urine samples. However the second-order advantage of both PARAFAC and SWATLD methods was exploited, even in the presence of unknown interferences and the satisfactory results can be obtained. Furthermore, the linear ranges of Tyr and DA were determined to be 0.042–6.42 μg/mL and 0.18–4.43 μg/mL, respectively, and the accuracies of both methods were validated by the analytical figures of merit (FOM).