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).

Classification and determination of total hardness of water using silver nanoparticles.

Herein a semi-quantitative and quantitative method for rapid determination of water hardness was introduced. The method was based on color change of silver nanoparticles (AgNPs) in the presence of real water samples. Carbon dots were prepared from mulberry in a hydrothermal procedure and used as reductant of silver ion for synthesis of AgNPs. A classification method based on the color change of AgNPs in the presence of different water samples was also founded. The analysis based of the proposed method was cheap and rapid. On site semi-quantitative determination of total hardness of water can be performed by the proposed method. A linear calibration model based on the color analysis of the images of AgNPs in the presence of water samples was constructed. The model was applicable for determination of total hardness of water in the range of 116-248 mg L-1 of calcium carbonate. A variety of real water samples were included in the calibration model. The calibration method can be used to predict total hardness of water in a critical range above the soft water and below the very hard water. The results were compared by the standard titrimetric method based on ethylenediaminetetraacetic acid. Prediction of total hardness of real water samples based on the color model was in most cases below 20%.

A simple equipment and colorimetric method for determination of chloroform in water.

Chlorination is a common and successful method for disinfection of water all around the world, especially in developing countries. However, this process can produce trihalomethanes (THMs) byproducts which are carcinogen. The major THM occurring in this process is chloroform. The purpose of this study was to design a simple equipment for colorimetric determination of chloroform in various water samples. The method is based on the colorimetric reaction of chloroform with resorcinol in strong basic medium on a filter paper. Response surface methodology (RSM) was employed to optimize the determination condition. The reagents were immobilized on filter paper and the color change was followed to quantify chloroform without using any analytical instrument. Detection limit and linear range of the proposed method were 0.007 mg/L and 0.011-1.192 mg/L, respectively for analysis of samples with volume of 2.0 L. The method was successfully applied to determine chloroform in different water samples and compared with GC-MS as a standard method. Employing the designed device, purge, trap and analysis steps were performed in a single run which can reduce the uncertainties originated by excessive steps of the analysis.

Water discrimination based on the kinetic variations of AgNP spectrum.

The assessment of water quality and its classification have considerable importance on public health. This requires monitoring of a wide range of physical, chemical and biological parameters. Here, an array of sensors composed of absorbances in different wavelengths in a kinetic process was used for classification. The data were obtained in the kinetic absorbance variations of silver nanoparticles (AgNPs) in the presence of different mineral waters. Spectral variations with time for each water sample were vectorized, and the matrix composed of these vectors was analyzed using principal component analysis (PCA) and hierarchical cluster analysis (HCA) as unsupervised clustering methods. The distinct clusters of nine different water samples were obtained using PCA and clustering by HCA resulted in an error rate of only 14.8%, which corresponds to misclassification of 4 water samples out of 27. The ability of the method for the discrimination of water samples using AgNP as the sole reagent can be attributed to the high dimensionality of data and the influence of the chemical environment in each water sample on the absorbance variations of AgNPs.

Application of response surface methodology and green carbon dots as reducing agents in speciation of iron.

Herein, for the first time, we used a green synthetic approach, via the hydrothermal treatment of grape and onion without any functionalization, to produce reducing carbon dots (CDs). The method has the advantages of low cost, easy operation and being environmentally friendly. The as-synthesized grape and onion CDs were characterized by UV-Vis spectrophotometry, spectrofluorimetry, FTIR spectroscopy and transmission electron microscopy (TEM). Interestingly, it was found that the synthesized CDs could reduce Fe3+ to Fe2+. Based on this finding, a method based on complexation with 1,10-phenanthroline was introduced for determination of Fe3+ and total iron in water samples. A response surface methodology was employed to explore the factors influencing the response, i.e. concentration of 1,10-phenanthroline and concentration of as-synthesized CDs. The proposed method provides a simple and sensitive colorimetric approach to detect Fe3+ over a wide linear range of 4.6-160 µM with a low detection limit of 0.1 µM. Moreover, for the first time, the reducing strength of CDs was estimated by the well-known Prussian blue assay.

Spectrophotometric determination of nitrite in soil and water using cefixime and central composite design.

The present paper seeks to develop a simple method for the spectrophotometric determination of nitrite in soil and water samples and also measure optimum reaction conditions along with other analytical parameters. The method is based on the diazotization-coupling reaction of nitrite with cefixime and 1-naphthylamine in an acidic solution (Griess reaction). The final product that is an azo dye has an orange color with maximum absorption at 360 nm which Beer's Law is obeyed over the concentration range 0.02-15.00 mg L(-1) of nitrite. Optimal conditions of the variables affecting the reaction were obtained by central composite design (CCD). A detection limit of 4.3×10(-3) mg L(-1) was obtained for determination of nitrite by the proposed method. The proposed method was successfully applied to determine nitrite in soil and water samples. The molar absorptivity of the product of the reaction and RSD in determination of nitrite in real samples are 4.1×10(3) (L mol(-1) cm(-1)) and lower than 10%, respectively.

H-point curve isolation method for determination of catechol in complex unknown mixtures.

In this work, the combination of H-point curve isolation method (HPCIM) and H-point standard additions method (HPSAM) was used for determination of catechol in the presence of phenolic interferents. Spectrophotometric multivariate calibration data constructed by successive standard additions of an analyte in an unknown matrix was used by the method. A cumulative spectrum for interferents in sample was extracted by HPCIM and then HPSAM is used for determination of the catechol concentration by obtained cumulative interferents spectrum. The method was tested with simulated data set. The spectrum obtained from applying HPCIM to the simulated data well agrees with the cumulative spectra of the interferents. The method was applied to the determination of catechol in the presence of highly overlapping interferents in synthetic ternary mixtures using spectrophotometric data. Moreover, the proposed method was successfully used for determination of catechol in real complicated matrices of tea and urine samples. Percent recoveries were between 95.4 and 113.6.

Hard- and soft-modeling approaches for resolution of complex formation of Co2+ and Ni2+ with glycine.

Principal component analysis (PCA) was used to obtain information about the number of components in the complex formation equilibria of Co(2+) and Ni(2+) with glycine (Gly). In order to obtain a clearer insight into these complex formation systems, multivariate curve resolution-alternating least squares (MCR-ALS) was used. Using MCR-ALS as a soft-modeling method, well-defined concentration and spectral profiles were obtained under unimodality, non-negativity, and closure constraints. Based on the obtained results, an equilibrium model was proposed and subsequently, a hard-modeling method was used to resolve the complex formation equilibria completely. Due to the presence of multiple equilibria, the resolution of such systems is very difficult. The Co-Gly system was best described by a model consisting of M(GlyH), M(Gly), M(Gly)(2), M(Gly)(2)H, and M(Gly)(3) (M = Co(2+)) with the overall stability constants determined to be 7.10 ± 0.011, 5.14 ± 0.006, 9.28 ± 0.009, 13.75 ± 0.016, and 11.10 ± 0.010, respectively. On the other hand, the system of Ni-Gly was best fitted by a model containing M(GlyH), M(Gly), M(Gly)(2), M(Gly)(3), and M(Gly)(2)(OH) (M = Ni(2+)) with overall stability constants of 10.95 ± 0.04, 6.41 ± 0.03, 11.31 ± 0.03, 15.39 ± 0.06, and 14.32 ± 0.02, respectively.

A chemometrics approach for simultaneous determination of cyanazine and propazine based on a carbon paste electrode modified by a molecularly imprinted polymer.

In a completely rational and designed approach, simultaneous determination of cyanazine and propazine in environmental and food samples was performed using a molecularly imprinted polymer modified carbon paste electrode (MIP-CPE) and partial least squares. The MIP-CPE designed is based on the theoretical studies functioned as a selective recognition element and pre-concentrator agent for cyanazine and propazine. Fractional factorial and central composite designs were performed to recognize, and subsequently optimize, the variables affecting the cathodic stripping voltammetric currents for the analytes. The important variables were identified to be accumulation potential with optimum values of -0.45 and -0.44 V and pH with optimum values of 2.40 and 2.34 for cyanazine and propazine, respectively. Exploration of the overall optimum conditions for simultaneous determination of cyanazine and propazine resulted in accumulation potential of -0.44 V and pH of 2.4. Dynamic linear ranges of 0.05-9.00 µmol L(-1) and 0.01-1.00 µmol L(-1) and detection limits of 0.010 and 0.001 µmol L(-1) were obtained for cyanazine and propazine, respectively. The results of the application of the proposed method on the simultaneous determination of cyanazine and propazine in foodstuffs and environmental samples were satisfactory.

Principle component analysis (PCA) and second-order global hard-modelling for the complete resolution of transition metal ions complex formation with 1,10-phenantroline.

Second-order global hard-modelling was applied to resolve the complex formation between Co(2+), Ni(2+), and Cd(2+) cations and 1,10-phenantroline. The highly correlated spectral and concentration profiles of the species in these systems and low concentration of some species in the individual collected data matrices prevent the well-resolution of the profiles. Therefore, a collection of six equilibrium data matrices including series of absorption spectra taken with pH changes at different reactant ratios were analyzed. Firstly, a precise principle component analysis (PCA) of different augmented arrangements of the individual data matrices was used to distinguish the number of species involved in the equilibria. Based on the results of PCA, the equilibria included in the data were specified and second-order global hard-modelling of the appropriate arrangement of six collected equilibrium data matrices resulted in well-resolved profiles and equilibrium constants. The protonation constant of the ligand (1,10-phenantroline) and spectral profiles of its protonated and unprotonated forms are the additional information obtained by global analysis. For comparison, multivariate curve resolution-alternating least squares (MCR-ALS) was applied to the same data. The results showed that second-order global hard-modelling is more convenient compared with MCR-ALS especially for systems with completely known model. It can completely resolve the system and the concentration profiles which are closer to correct ones. Moreover, parameters showing the goodness of fit are better with second-order global hard-modelling.

Application of multivariate curve resolution-alternating least squares (MCR-ALS) for secondary structure resolving of proteins.

Fourier transform infrared (FTIR) spectroscopy is the most common spectroscopic technique used for study of protein structure. Initially, band deconvolution techniques were applied to determine the secondary structure of proteins. Recently, several multivariate regression methods have been used to predict the secondary structure of proteins as an alternative to the previous methods. Multivariate curve resolution-alternating least squares (MCR-ALS) was applied on the FTIR spectra of proteins to resolve the fraction and spectral profiles of different structural motifs. Initial estimates of spectral profiles of different protein motifs were built using orthogonal projection approach (OPA). Predicted fractions of alpha-helix and beta-sheet obtained by MCR-ALS technique were compared with those from partial least squares (PLS) modeling which revealed superiority of the former. If we consider the possibility of pure spectra prediction in addition to the prediction of secondary structure from the data set, MCR-ALS can be proposed as a very valuable alternative for qualitative and quantitative study of protein structures.

Application of soft- and hard-modelling approaches to resolution of kinetics of electron donor-acceptor complex formation of 2,3-dichloro-5,6-dicyano-1,4-benzoquinone with imipramine in different solutions.

Kinetics of electron donor-acceptor (EDA) complex formation of imipramine and 2,3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ) was investigated spectrophotometrically in acetonitrile, 1,2-dichloroethane, and chloroform solutions using soft- and hard-modelling approaches. From the results of exploratory analysis of kinetic data and the spectral changes by soft-modelling approaches, evolving factor analysis (EFA) and orthogonal projection approach (OPA), a consecutive two-steps reaction with two intermediates was proposed for the process in acetonitrile and 1,2-dichloroethane media and one with a single intermediate in chloroform solution. Secondly, by applying, multivariate nonlinear least squares hard-modelling approach on the collected experimental kinetic data matrix, the nonlinear parameters (rate constants) as well as the linear parameters (spectral profiles) were obtained by fitting the collected experimental kinetic data matrix to the proposed model. Small values of standard deviation in the resulting parameters and sum of squares of the residuals (ssq) obtained showed the proper selection of the model. Furthermore, the values of lack of fit and percent of explained variance confirmed the correct identified models. Identification of the model with the aid of soft-modelling approaches followed by application of the hard-modelling approaches decreases significantly the rotational ambiguity associated with the obtained concentration and spectral profiles. Variations in the kinetic constants were in complete agreement with the model proposed and the solvent polarities.