Second-order Standard Addition Research Articles

Mercury (II) sensing using a simple turn-on fluorescent graphene oxide based aptasensor in serum and water samples

A simple, highly sensitive, and selective fluorometric aptasensing platform based on aptamer and graphene oxide (GO) is proposed for the determination of mercury (II) ion (Hg2+). In the designed assay, two aptamer probes, a carboxy-fluorescein (FAM) labeled aptamer (aptamer A) and its complementary (aptamer B) with partial complement containing several mismatches and GO as the quencher were used. In the absence of Hg2+, both A and B aptamers were adsorbed on the surface of GO by π-π-stacking, leading to fluorescence quenching of FAM due to fluorescence resonance energy transfer (FRET). Upon exposure to Hg2+, the A and B aptamer strands bind Hg2+ and form T-Hg2+-T complexes, leading to the formation of a stable double-stranded aptamer. The double-stranded aptamer is detached from the GO surface, resulting in the recovery of FAM fluorescence. The fluorescence intensity (FI) of the developed sensor was correlated with the Hg2+ concentration under optimized experimental conditions in two wide linear ranges, even in the presence of 10 divalent cations as interferences. The linear ranges were obtained from 200.0 to 900.0 fM and 5.0 to 33.0 pM, a limit of detection (LOD) of 106.0 fM, and a limit of quantification (LOQ) of 321.3 fM. The concentration of Hg2+ was determined in five real samples containing three water and two serum samples, using spiking and standard addition methods and the results were compared with the spiked amounts and atomic absorption (AAS) as standard method respectively, with acceptable recoveries. Furthermore, in the standard addition method, to overcome the effects of matrix influence of real samples in quantitative predictions, the excitation-emission matrix (EEM) data for samples was simultaneously analyzed by multivariate curve resolution with alternating least squares (MCR-ALS) as a second-order standard addition method (SOSAM).

Identification and quantification of ciprofloxacin, enrofloxacin and difloxacin residues in milk using excitation-emission fluorescence and second-order standard addition methods

In the presence of non-modeled components and analyte-matrix interaction in real samples, a combination of second-order multivariate calibration and standard addition is desired to achieve accurate results via second-order advantage. Enrofloxacin (ENR), Difloxacin (DIF), and Ciprofloxacin (CIP) are Fluoroquinolones widely considered antibiotic residues in milk. Excitation-emission fluorescence spectra of these antibiotics at pH = 9.1 provide second-order data for identifying and quantifying them in a mixture using second-order calibration modeling.Rank annihilation factor analysis (RAFA) and multivariate curve resolution-alternating least squares (MCR-ALS) with trilinearity constraints are applied to determine the CIP, ENR, and DIF residues in synthetic mixtures and milk using second-order excitation-emission fluorescence spectroscopy. In both methods, the trilinearity constraint guarantees a unique true solution to the spectral profiles of analytes. The combination of second-order standard addition and higher-order calibration modeling with RAFA and MCR-ALS supports the second-order advantage in milk analysis.

Development of a second-order standard addition fluorescence method for the direct determination of riboflavin in human urine samples without previous clean up and separation steps

A new strategy for the determination of riboflavin (RF, or vitamin B2) in human urine samples has been developed, combining excitation-emission fluorescence matrix (EEFM) data in standard addition mode and second-order chemometric analysis. The method is simple, fast and eco-friendly because it complies with the green analytical chemistry principles, avoiding the need of previous clean up and separation steps that consume high amounts of organic solvents. Successful results were obtained by different chemometric algorithms, namely parallel factor analysis (PARAFAC), unfolded partial least-squares/residual bilinearization (U-PLS/RBL) and multidimensional partial least-squares/residual bilinearization (N-PLS/RBL), all in the modified standard addition. These algorithms allowed us to achieve selectivity in a system, which requires standard addition and shows a significant background spectral overlapping with the studied vitamin. The quality of the proposed strategy was evidenced on the basis of the analytical recoveries from urine samples spiked with RF. The detection limits achieved in urine samples are encouraging compared to those obtained using chromatographic approaches. The relative prediction errors were lower than 5.6%.

A combined theoretical and experimental study for the chiral discrimination of naproxen enantiomers by molecular modeling and second-order standard addition method

In the present study, excitation–emission matrix (EEM) fluorescence data of guest–host complexes between naproxen enantiomers and β-cyclodextrin were used to develop a second-order calibration method that was subsequently used to determine the enantiomeric composition of samples of naproxen. The chiral discrimination of naproxen enantiomers was realized via their difference in interaction with the chiral cavity of β-cyclodextrin due to their difference in stereochemical structure. The strategy combined the use of a self-weighted alternating normalized residue fitting (SWANRF) algorithm, for extraction of the pure analyte signal, with the standard addition strategy, for determination of naproxen enantiomers in the presence of a matrix effect caused by the proteins present in human urine. Feasible results were obtained in a molar fraction range from 60.0 to 85.0% of S-naproxen, providing absolute errors lowers than 7.50%. Finally, molecular modeling was performed to determine the chiral recognition on a molecular level, and the difference in the interaction energies and the patterns of molecular interactions were discussed. The results were in good agreement with experimental data.

A second-order standard addition method based on the data treatment by calculation of variation matrix of kinetic systems analyzed by MCR-ALS

A new method is proposed to resolve the kinetic-spectrophotometric data of multicomponent mixtures and determination of analyte(s) in the presence of unknown matrix. The method uses variation matrix data by shifting to another target, namely the reaction space. The variation matrix is obtained by subtracting the zero-point spectrum (e.g., first spectrum) from each spectrum at each time. This space shifting decreases the rank numbers to the numbers of reactions. Self-modeling curve resolution is used to resolve the variation matrices of kinetic-spectrophotometric data for mixtures of analytes. In addition, second-order standard addition method is used to remove the matrix effect(s) when analyze unknown samples. This means that, quantitative analysis can be performed by augmentation of the variation matrix of the unknown samples and standard added samples and, then, plotting standard addition calibration curve. The applicability of the proposed method is evaluated using model and real data for mixtures of analytes.

Direct determination of trans-resveratrol in human plasma by spectrofluorimetry and second-order standard addition

Trans-resveratrol (RVT) is an antioxidant found in red grapes and their derivatives, which has been related to the reduction of cardiovascular diseases and cancer incidence. This work developed a new spectrofluorimetric–chemometric method for the direct determination of RVT in human plasma. For each measurement, excitation–emission matrices were obtained from 280 to 360 nm (excitation) and from 380 to 550 nm (emission). The strategy adopted in this work combined data treatment with parallel factor analysis (PARAFAC), for extracting the pure analyte signal, using the standard addition method, which permits determinations in the presence of a strong matrix effect caused by plasma analyte–protein binding. Plasma samples were diluted 10 times and, for each, four standard additions of RVT were performed, in triplicate. A specific PARAFAC model was built for the three replicates of each sample, from three-way arrays formed by five measurements (initial sample plus four additions), 17 excitation wavelengths and 86 emission wavelengths. The best models were selected with four factors and accounted for more than 99.90% of the data variance. The loadings obtained were related to RVT and three interferences. The scores related to the analyte were used for linear regressions and all standard addition curves presented correlation coefficients equal or greater than 0.99. Good results were obtained in the concentration range from 0.10 to 5.00 μg mL −1, with recoveries between 94.0 and 110.0%. The proposed method was also validated through the estimates of several figures of merit: sensitivity, analytical sensitivity, selectivity, precision, and limits of detection and quantitation.

A novel second-order standard addition analytical method based on data processing with multidimensional partial least-squares and residual bilinearization

In the presence of analyte–background interactions and a significant background signal, both second-order multivariate calibration and standard addition are required for successful analyte quantitation achieving the second-order advantage. This report discusses a modified second-order standard addition method, in which the test data matrix is subtracted from the standard addition matrices, and quantitation proceeds via the classical external calibration procedure. It is shown that this novel data processing method allows one to apply not only parallel factor analysis (PARAFAC) and multivariate curve resolution-alternating least-squares (MCR-ALS), but also the recently introduced and more flexible partial least-squares (PLS) models coupled to residual bilinearization (RBL). In particular, the multidimensional variant N-PLS/RBL is shown to produce the best analytical results. The comparison is carried out with the aid of a set of simulated data, as well as two experimental data sets: one aimed at the determination of salicylate in human serum in the presence of naproxen as an additional interferent, and the second one devoted to the analysis of danofloxacin in human serum in the presence of salicylate.

Determination of propranolol enantiomers in plasma and urine by spectrofluorimetry and second-order standard addition method

The determination of propranolol enantiomers in human plasma and urine by spectrofluorimetry and a second-order standard addition method is described. The methodology is based on chiral recognition of propranolol by formation of an inclusion complex with β-cyclodextrin, a chiral auxiliary, in the presence of 1-butanol. The adopted strategy combines the use of PARAFAC, for extraction of the pure analyte signal, with the standard addition method, for determinations in the presence of an individual matrix effect caused by the quenching action of the proteins present in the plasma and urine. A specific PARAFAC model was built for each sample, in triplicate, and the scores were related to (R)-propranolol mole fraction using a linear regression in the standard addition method. Using a propranolol with concentration of 260 ng mL −1, good results were obtained for determinations in the mole fraction range from 50 to 80% of (R)-propranolol, providing absolute errors between 0.4 and 3.6% for plasma and between 0.9 and 6.0% for urine.

Determination of pesticides in honey using excitation–emission matrix fluorescence coupled with second-order calibration and second-order standard addition methods

The present paper presents a novel method for simultaneous determination of the three pesticides, carbaryl, carbendazim and 1-naphthol in honey. The excitation–emission matrix fluorescence data from calibration and prediction samples composed a three-way data array and then were analyzed using the second-order calibration method based on the self-weighted alternating trilinear decomposition (SWATLD). The second-order advantage of the SWATLD-based second-order calibration method was exploited, which makes it possible that calibration can be performed even in the presence of unknown interferences. The method was applied to determine the pesticides in the complex matrix of the honey sample. After the calibration step the recoveries of carbendazim and 1-naphthol were satisfactory. The quantification of carbaryl using the second-order standard addition method (SOSAM) based on SWATLD and the high-performance liquid chromatography–tandem mass spectrometry (HPLC–MS) were performed to validate the concentration of carbaryl in honey samples.

Enhanced spectrofluorimetric determination of aflatoxin B1 in wheat by second-order standard addition method

Determination of aflatoxin B1 (AFB1) in wheat has been accomplished by enhanced spectrofluorimetry in combination with second-order standard addition method (EF-SOSAM). The adopted strategy combined the use of parallel factor analysis (PARAFAC) for extraction of the pure analyte signal and the standard addition method, for a determination in the presence of matrix effect caused by wheat matrix. The method is based on the enhanced fluorescence of AFB1 by β-cyclodextrin in 10% (w/w) methanol–water solution. After sample treatment and without any extended cleanup steps and derivatization process, four standard additions were performed for each sample. A specific PARAFAC model was built from three-way arrays formed by excitation–emission spectra and 5 measurements (sample plus 4 additions). The scores related to AFB1 were used for a linear regression in the standard addition method. Two naturally contaminated wheat and spiked wheat samples containing AFB1 in the range 0–18 μg kg −1 were analyzed by EF-SOSAM and compared with HPLC results. EF-SOSAM analysis of spiked wheat samples gave a good correlation with spiked values ( R 2 > 0.990). The limit of detection of method was 0.9 μg kg −1 for the determination of AFB1 in wheat samples.

Second-order standard addition for deconvolution and quantification of fatty acids of fish oil using GC–MS

In the present work two second-order calibration methods, generalized rank annihilation method (GRAM) and multivariate curve resolution-alternating least square (MCR-ALS) have been applied on standard addition data matrices obtained by gas chromatography–mass spectrometry (GC–MS) to characterize and quantify four unsaturated fatty acids cis-9-hexadecenoic acid (C16:1ω7c), cis-9-octadecenoic acid (C18:1ω9c), cis-11-eicosenoic acid (C20:1ω9) and cis-13-docosenoic acid (C22:1ω9) in fish oil considering matrix interferences. With these methods, the area does not need to be directly measured and predictions are more accurate. Because of non-trilinear conditions of GC–MS data matrices, at first MCR-ALS and GRAM have been used on uncorrected data matrices. In comparison to MCR-ALS, biased and imprecise concentrations (%R.S.D. = 27.3) were obtained using GRAM without correcting the retention time-shift. As trilinearity is the essential requirement for implementing GRAM, the data need to be corrected. Multivariate rank alignment objectively corrects the run-to-run retention time variations between sample GC–MS data matrix and a standard addition GC–MS data matrix. Then, two second-order algorithms have been compared with each other. The above algorithms provided similar mean predictions, pure concentrations and spectral profiles. The results validated using standard mass spectra of target compounds. In addition, some of the quantification results were compared with the concentration values obtained using the selected mass chromatograms. As in the case of strong peak-overlap and the matrix effect, the classical univariate method of determination of the area of the peaks of the analytes will fail, the “second-order advantage” has solved this problem successfully.

Determination of the capability of detection of a hyphenated method: application to spectroelectrochemistry

A procedure to evaluate the capability of detection of a second-order analytical technique to determine an analyte in presence of an interferent has been proposed taking into account α and β errors in a similar way as ISO norms indicate for the univariate analytical methods. The potentiality of spectroelectrochemistry as a quantitative three-way technique of analysis has been analysed. Trilinearity of spectroelectrochemical data has been studied since it is a necessary condition to apply the trilinear decomposition (TLD) method. As an example, the voltabsorptometric determination of o-tolidine in presence of high concentration of ferrocyanide was chosen to test the applicability of the proposed method. In the same way, the capability of discrimination has been determined. In addition, a second-order standard addition method (SOSAM) has been applied to calculate the concentration of the analyte of interest in the presence of this interferent, avoiding the need to previously identify and determine the quantity of the interferent.

Second-Order Standard Addition Method Based on Alternating Trilinear Decomposition

In this study, a second-order standard addition method based on alternating trilinear decomposition (ATLD-SOSAM) was developed. It was applied to second-order HPLC-DAD data and compared to methods employing direct trilinear decomposition (DTLD) and PARAFAC. The results show that ATLD-SOSAM is slightly superior to both DTLD-SOSAM and PARAFAC-SOSAM.

A second‐order standard addition method with application to calibration of a kinetics–spectroscopic sensor for quantitation of trichloroethylene

AbstractPresented here is an algorithm for analysis of second order data by the method of standard additions. The method of standard additions is applicable when matrix effects make traditional calibration unreliable. The algorithm employs a generalized eigenproblem to mathematically separate the instrument response of the analyte from the instrument response of any interfering species. A scheme for determining the eigenvectors (and hence the concentration estimate) that uniquely correspond to the analyte of interest is given. These eigenvectors can readily be distinguished from any eigenvector that corresponds to the spectrum of the interferents or both the interferents and analyte. The stability of the estimated analyte concentration is verified by Monte Carlo simulations. The algorithm is applied to the analysis of trichloroethylene in samples that have matrix effects caused by an interaction with chloroform.