Cyanazine herbicide monitoring as a hazardous substance by a DNA nanostructure biosensor

Cyanazine is a beneficial herbicide in the triazines group that inhibits photosynthesis in plants and monitoring of this herbicide is so important for study agriculture products. The present researches have been focused on monitoring of cyanazine by a straightforward and fast electrochemical strategy. Herein, to monitor the cyanazine level, Pt and Pd doped CdO nanoparticle decorated SWCNTs composite (Pt-Pd-CdO/SWCNTs) has been synthesized as a conductive mediator and characterized by EDS, SEM and TEM techniques. The Pt-Pd-CdO/SWCNTs and ds-DNA have been used for modification of the gold electrode (GE). Moreover, the oxidation signal of guanine relative to ds-DNA at the surface of Pt-Pd-CdO/SWCNTs/ds-DNA/GE has been considered as an bioelectroanalytical issue to monitoring cyanazine for the first time. Electrochemical impedance spectroscopic (EIS) signals have confirmed that the inclusion of Pt-Pd-CdO/SWCNTs at the surface of the GE has lowered charge-transfer resistance by ca.1.54 times and created a highly conductive state for monitoring of cyanazine in nanomolar concentration. On the other hand, differential pulse voltammograms (DPV) of Pt-Pd-CdO/SWCNTs/ds-DNA/GE have indicated a linear dynamic range of 4.0 nM-70 µM with a detection limit of 0.8 nM to the monitoring of cyanazine. In addition, the molecular docking study has emphasized that cyanazine herbicide is capable of binding to ds-DNA preferably at the guanine-cytosine rich sequences, and confirmed experimental results. In the final step, Pt-Pd-CdO/SWCNTs/ds-DNA/GE has been successfully utilized for the monitoring of cyanazine herbicide in food and water samples.

The Use of Computational Methods for the Development of Molecularly Imprinted Polymers

Recent years have witnessed a dramatic increase in the use of theoretical and computational approaches in the study and development of molecular imprinting systems. These tools are being used to either improve understanding of the mechanisms underlying the function of molecular imprinting systems or for the design of new systems. Here, we present an overview of the literature describing the application of theoretical and computational techniques to the different stages of the molecular imprinting process (pre-polymerization mixture, polymerization process and ligand-molecularly imprinted polymer rebinding), along with an analysis of trends within and the current status of this aspect of the molecular imprinting field.

Mycophenolate mofetil sensor based on molecularly imprinted polymer/multi-walled carbon nanotubes modified carbon paste electrode

Using square wave voltammetry, a carbon paste electrode modified by molecularly imprinted polymer (MIP) as a recognition element of mycophenolate mofetil (MMF) and multi-walled carbon nanotubes was used for MMF monitoring To investigate the electrode during modification, electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) were utilized. After optimization of the effective parameters, the anodic peak current of MMF was utilized for dynamic range study which was linear in 9.9 nM-87 μM range. The detection limit of the sensor was 7.0 nM. The capture ability of MIP to target was compared with that of non-imprinted polymer (NIP). The practical application of the sensor in biological fluid samples analysis demonstrates its selectivity, sensitivity, and stability.

Determination of hydrogen sulfide and hydrogen peroxide in complex samples of milk and urine by spectroscopic standard addition data and chemometrics methods

Spectroscopic data of standard additions were collected and used to calculate the spectrum of the unknown interferent(s) based on the net analyte signal.

Simultaneously detection of calcium and magnesium in various samples by calmagite and chemometrics data processing

The current study describes results of the application of radial basis function-partial least squares (RBF-PLS), partial robust M-regression (PRM), singular value decomposition (SVD), evolving factor analysis (EFA), multivariate curve resolution with alternating least squares (MCR-ALS) and rank annihilation factor analysis (RAFA) methods for the purposes of simultaneous determination of trace amounts calcium (Ca(2+)) and magnesium (Mg(2+)) and exploratory analysis based on their colored complexes formation with 1-(1-hydroxy-4-methyl-2-phenylazo)-2-naphthol-4-sulfonic acid (calmagite) as chromomeric reagent. The complex formation Ca(2+) and Mg(2+) with calmagite was investigated under pH10.20. The performance of RBF-PLS model in detection of minerals was compared with PRM as a linear model. The pure concentration and spectral profiles were obtained using MCR-ALS. EFA and SVD were used to distinguish the number species. The stability constants of the complexes were derived using RAFA. Finally, RBF-PLS was utilized for simultaneous determination of minerals in pharmaceutical formulation and various vegetable samples.

Simultaneous UV-Vis spectrophotometric quantification of ternary basic dye mixtures by partial least squares and artificial neural networks

One of the main difficulties in quantification of dyes in industrial wastewaters is the fact that dyes are usually in complex mixtures rather than being pure. Here we report the development of two rapid and powerful methods, partial least squares (PLS-1) and artificial neural network (ANN), for spectral resolution of a highly overlapping ternary dye system in the presence of interferences. To this end, Crystal Violet (CV), Malachite Green (MG) and Methylene Blue (MB) were selected as three model dyes whose UV-Vis absorption spectra highly overlap each other. After calibration, both prediction models were validated through testing with an independent spectra-concentration dataset, in which high correlation coefficients (R²) of 0.998, 0.999 and 0.999 were obtained by PLS-1 and 0.997, 0.999 and 0.999 were obtained by ANN for CV, MG and MB, respectively. Having shown a relative error of prediction of less than 3% for all the dyes tested, both PLS-1 and ANN models were found to be highly accurate in simultaneous determination of dyes in pure aqueous samples. Using net-analyte signal concept, the quantitative determination of dyes spiked in seawater samples was carried out successfully by PLS-1 with satisfactory recoveries (90-101%).