Procedure for the Quantitative Determination of Mixtures of Nucleic Acid Components Based on Multivariate Spectrophotometric Acid−Base Titrations

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).

Application of Rank Annihilation Factor Analysis for Antibacterial Drugs Determination by Means of pH Gradual Change-UV Spectral Data

The main objective of this study was to develop a simple and efficient spectrophotometric technique combined with chemometrics for the simultaneous determination of sulfamethoxazole (SMX) and trimethoprim (TMP) in drug formulations. Specifically, we sought: (i) to evaluate the potential use of rank annihilation factor analysis (RAFA) to pH gradual change spectrophotometric data in order to provide sufficient accuracy and model robustness; and (ii) to determine SMX and TMP concentration in drug formulations without tedious pre-treatments such as derivatization or extraction techniques which are time-consuming and require hazardous solvents. In the proposed method, the spectra of the sample solutions at different pH values were recorded and the pH-spectra bilinear data matrix was generated. On these data, RAFA was then applied to estimate the concentrations of SMX and TMP in synthetic and real samples. Applying RAFA showed that the two drugs could be determined simultaneously with concentration ratios of SMX to TMP varying from 1:30 to 30:1 in the mixed samples (concentration range is 1-30 µg mL^-1 for both components). The limits of detection were 0.25 and 0.38 µg mL^-1 for SMX and TMP, respectively. The proposed method was successfully applied to the simultaneous determination of SMX and TMP in some synthetic, pharmaceutical formulation and biological fluid samples. In addition, the means of the estimated RSD (%) were 1.71 and 2.18 for SMX and TMP, respectively, in synthetic mixtures. The accuracy of the proposed method was confirmed by spiked recovery test on biological samples with satisfactory results (90.50-109.80%).

Quantitative analysis by resolving variation matrices of pH-Spectrophotometric titration data using Self-Modeling Curve Resolution

A new method is proposed for resolving pH-spectrophotometric titration data to determine mixtures of monoprotic acids. The method uses variation matrices to circumvent the rank deficiency problem of such data by shifting to another target, namely the reaction space. Self-modeling curve resolution is used to resolve variation matrices of pH-spectrophotometric titration data for acid mixtures. The variation matrix is obtained by subtracting the zero-point spectrum (e.g., acidic spectrum) from each spectrum at each pH value. Mean-centering window evolving factor analysis is used to identify the local reaction map. Reaction spectra can be estimated using selective regions of the local reaction map, from which reaction extent vectors can be obtained by alternating least-squares optimization. It was shown that quantitative analysis can be performed by augmentation of the variation matrix of the unknown and standard samples and comparison of obtained reaction extent curves. The applicability of the proposed method was evaluated using model data for binary and ternary mixtures of monoprotic acids. pH-spectrophotometric titration data for real binary mixtures of tartrazine/sunset yellow were also investigated using the proposed method and their concentration were determined in a real sample.

Soft-modeling based spectrofluorimetric study of simultaneous equilibria

A two-way soft resolution method will fail when applied to a simultaneous equilibria system due to rank deficiency in its concentration profiles. Increasing the dimensionality of measurements from two-way to three-way data can be used to overcome this problem. Simultaneous dissociation of two weak acids is considered as a model for simultaneous equilibria. Three-way data obtained from excitation-emission spectrofluorimetric monitoring of a pH-metric titration is analyzed using a proper combination of well-known soft-modeling methods. Multivariate curve resolution-alternating least squares is used for calculating the excitation and emission spectral profiles of involved species and rank annihilation factor analysis for obtaining the contribution of each species in measured excitation-emission matrices at different pHs. The results of simulated and real simultaneous acids dissociation equilibria showed that the proposed combined method performs well even in situation when the equilibrium constants are close to each other. The applicability of method for study of an acidic dissociation is also shown.

Use of gas chromatography–mass spectrometry combined with resolution methods to characterize the essential oil components of Iranian cumin and caraway

Gas chromatography-mass spectrometry combined with iterative and non-iterative resolution methods was used to characterize the essential oil components of Iranian cumin and caraway. Orthogonal projection resolution (OPR) as a non-iterative and distance-selection-multivariate curve resolution-alternative least squares (DS-MCR-ALS) as an iterative method were used as auxiliary means to the analysis in the case of overlapping peaks. A total of 19 and 39 components were identified by direct similarity searches for cumin and caraway oils, respectively. These numbers were extended to 49 and 98 components, respectively with the help of chemometric techniques. Major constituents in cumin are gamma-terpinene (15.82%), 2-methyl-3-phenyl-propanal (32.27%) and myrtenal (11.64%) and in caraway are gamma-terpinene (24.40%), 2-methyl-3-phenyl-propanal (13.20%) and 2, 4(10)-thujadien (14.02%). In spite of different cultivation conditions, there are 28 components which are common between the two seeds.

Local factor analysis of rank-deficient reaction systems

The analysis of spectral measurement data sets using local factor analysis (LFA) requires the rank of the sub-matrix under study to be equal to the number of absorbing species present in the associated sub-system. However, because of mass balance or kinetic constraints, LFA will fail if local rank deficiency occurs. A local rank deficiency sub-system may be present in a global full-rank reaction system or a rank-deficient one. In this paper, the problems occurring when using window target-testing factor analysis (WTTFA), one type of the LFA methods, in a local rank-deficient situation are shown. A new augmented WTTFA (AWTTFA) is then proposed for the correct use of WTTFA when rank deficiency occurs. Principles of this new method have been demonstrated by a simulated kinetic system and an industrial batch data set.

Determination of ebrotidine metabolites in overlapping peaks from capillary zone electrophoresis using chemometric methods

This paper illustrates the possibilities of chemometric methods in the resolution and quantification of various compounds in overlapping peaks from capillary electrophoresis. Ebrotidine and most of its metabolites were efficiently separated by capillary zone electrophoresis (CZE) in a fused-silica capillary. However, the procedure was not suitable for the physical separation of the three less ionizable metabolites, which comigrated and overlapped with the electroosmotic flow signal. Multivariate curve resolution based on an alternating least squares procedure was used for their mathematical resolution. For such a purpose, data obtained in the CZE system with a diode array detector, which consisted of UV spectra registered over time, were analyzed. The ebrotidine metabolites were successfully resolved and quantified in synthetic mixtures and urine samples.

Resolution of overlapped peaks of amino acid derivatives in capillary electrophoresis using multivariate curve resolution based on alternating least squares

The application of chemometric techniques to the resolution of overlapped peaks in capillary electrophoresis (CE) is described. When a physical separation can not be completely accomplished, chemometrics might still resolve the determination of the analytes mathematically. CE with diode array detection can provide a large amount of data consisting of spectra registered over time. In this study, the capillary electrophoretic separation of 1,2-naphthoquinone-4-sulfonate derivatives of amino acids is studied. Most of the common amino acid derivatives can be separated at 30 kV in a fused-silica capillary by using a 40 mM sodium tetraborate + isopropanol (3:1 v/v) solution as background electrolyte. However, peaks of certain derivatives (Phe, His, Leu and Ile) still overlap. A multivariate curve resolution method based on an alternating least squares optimization procedure is used for the resolution of the overlapped electrophoretic peaks. The method takes advantage of spectral and electrophoretic differences of analytes to recover their pure electrophoretic and spectral profiles. In addition, each analyte in the mixture can be quantified using the corresponding standards.