Simultaneous spectrophotometric determination of cobalt,copper and nickel using 1-(2-thiazolylazo)-2-naphthol by chemometrics methods

The simultaneous determination of cobalt, copper and nickel using 1-（2-thiazolylazo）-2-naphthol （first figure of this article） by spectrophotometric method is a difficult problem in analytical chemistry, due to spectral interferences. By multivariate calibration methods, such as partial least squares （PLS） regression, it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. Orthogonal signal correction （OSC） is a preprocessing technique used for removing the information unrelated to the target variables based on constrained principal component analysis. OSC is a suitable preprocessing method for PLS calibration of mixtures without loss of prediction capacity using spectrophotometric method. In this study, the calibration model is based on absorption spectra in the 550-750-nm range for 21 different mixtures of cobalt, copper and nickel. Calibration matrices were formed from samples containing 0.05-1.05, 0.05-1.30 and 0.05-0.80 μg·mL^-1 for cobalt, copper and nickel, respectively. The root mean square error of prediction （RMSEP） for cobalt, copper and nickel with OSC and without OSC were 0.007, 0.008, 0.011 and 0.031,0.037, 0.032 μg· mL^-1, respectively. This procedure allows the simultaneous determination of cobalt, copper and nickel in synthetic and real samples and good reliability of the determination was proved.

Determination of trace amounts of morphine in human plasma by anodic adsorptive stripping differential pulse voltammetry

New adsorptive anodic differential pulse stripping voltammetry method for the direct determination of morphine at trace levels in human plasma of addicts is proposed.The procedure involves an adsorptive accumulation of morphine on a HMDE,followed by oxidation of adsorbed morphine by voltammetry scan using differential pulse modulation.The optimum conditions for the analysis of morphine are pH 10.5,Eacc of -100 mV（vs.Ag/AgCl）,and tacc of 120 s.The peak current is proportional to the concentration of morphine,and a Linear calibration graph is obtained at 0.01-3.10μg mL^-1.A relative standard deviation of 1.06%（n=5）was obtained,and the limit of detection was 3 ng mL^-1.The capabiLity of the method for the analysis of real samples was evaluated by the determination of morphine in spiked human plasma and addicts human plasma with satisfactory results.

Determination of captopril in pharmaceutical preparation and biological fluids using two- and three-way chemometrics methods

Spectrophotometric method has been developed for the direct quantitative determination of captopril in pharmaceutical preparation and biological fluids （human plasma and urine） samples. The method was accomplished based on parallel factor analysis （PARAFAC） and partial least squares （PLS）. The study was carried out in the pH range from 2.0 to 12.8 and with a concentration from 0.70 to 61.50μg mL^-1 of captopril. Multivariate calibration models such as PLS at various pH and PARAFAC were elaborated from ultraviolet spectra deconvolution and captopril determination. The best models for this system were obtained with PARAFAC and PLS at pH 2.0. The applications of the method for determination of real samples were evaluated by analysis of captopril in pharmaceutical preparations and biological fluids with satisfactory results. The accuracy of the method, evaluated through the RMSEE was 0.5801 for captopril with best calibration curve by PARAFAC and 0.6168 for captopril with PLS at pH 2.0 model.

Quantitative structure-property relationship study of the solubility of thiazolidine-4-carboxylic acid derivatives using ab initio and genetic algorithm-partial least squares

A quantitative structure-activity relationships （QSAR） study is suggested for the prediction of solubility of some thiazolidine-4- carboxylic acid derivatives in aqueous solution. Ab initio theory was used to calculate some quantum chemical descriptors including electrostatic potentials and local charges at each atom, HOMO and LUMO energies, etc. Modeling of the solubility of thiazolidine- 4-carboxylic acid derivatives as a function of molecular structures was established by means of the partial least squares （PLS）. The subset of descriptors, which resulted in the low prediction error, was selected by genetic algorithm. This model was applied for the prediction of the solubility of some thiazolidine-4-carboxylic acid derivatives, which were not in the modeling procedure. The relative errors of prediction lower that -4% was obtained by using GA-PLS method. The resulted model showed high prediction ability with RMSEP of 3.8836 and 2.9500 for PLS and GA-PLS models, respectively.

Spectrophotometric Simultaneous Determination of Zinc(II), Manganese(II) and Iron(II) in Pharmaceutical Preparations Using OSC-PLS

This work reports the spectrophotometric simultaneous determination of zinc（Ⅱ）, manganese（Ⅱ） and iron（Ⅱ） in pharmaceutical preparation, using orthogonal signal correctionpartial least squares （OSC-PLS）. All the factors affecting on the sensitivity were optimized and the linear dynamic range for determination of these metals was found. The PLS modeling was used for the multivariate calibration of the spectrophotometric data. The OSC was used for preprocessing of data matrices and the prediction results of model. The experimental calibration matrix was designed by measuring the absorbance over the range 450-570 nm for 21 samples of 0.05-1.05, 0.10-1.10 and 0.05-1.05μg·mL^-1 of zinc（Ⅱ）, manganese（Ⅱ） and iron（Ⅱ）, respectively. The RMSEP for zinc（Ⅱ）, manganese（Ⅱ） and iron（Ⅱ） using OSC-PLS were 0.0164, 0.0132, 0.0146, respectively. The proposed method was successfully applied the determination of zinc（Ⅱ）, manganese（Ⅱ） and iron（Ⅱ） in pharmaceutical preparations.

Multiwavelength spectrophotometric determination of acidity constants of 1-(2-thiazolylazo)-2-naphthol in methanol-water mixtures

The acid-base properties of 1-（2-thiazolylazo）-2-naphthol （TAN） in mixtures of methanol-water at 25℃ and an ionic strength of 0.1 mol/L are studied by a multi-wavelength spectrophotometfic method. The acidity constants of all related equilibria are estimated using the whole spectral fitting of the collected data to an established factor analysis model. DATAN program was used for determination of acidity constants. The corresponding pKa values in methanol-water mixtures were determined. There is a linear relationship between acidity constants and the mole fraction of methanol in the solvent mixtures.

Pattern discovery of long non-coding RNAs associated with the herbal treatments in breast and prostate cancers

Background:Accumulating evidence shows that long non-coding RNAs(lncRNAs)play critical roles in cancer progression.The possible association between lncRNAs and herbal medicine is yet to be known.This study aims to identify medicinal herbs associated with lncRNAs by RNA-seq data for breast and prostate cancer.Methods:To develop the optimal approach for identifying cancer-related lncRNAs,we implemented two steps:(1)applying protein–protein interaction(PPI),Gene Ontology(GO),and pathway analyses,and(2)applying attribute weighting and finding the efficient classification model of the machine learning approach.Results:In the first step,GO terms and pathway analyses on differential co-expressed mRNAs revealed that lncRNAs were widely co-expressed with metabolic process genes.We identified two hub lncRNA-mRNA networks that implicate lncRNAs associated with breast and prostate cancer.In the second step,we implemented various machine learning-based prediction systems(Decision Tree,Random Forest,Deep Learning,and Gradient-Boosted Tree)on the non-transformed and Z-standardized differential co-expressed lncRNAs.Based on five-fold cross-validation,we obtained high accuracy(91.11%),high sensitivity(88.33%),and high specificity(93.33%)in Deep Learning which reinforces the biomarker power of identified lncRNAs in this study.As data originally came from different cell lines at different durations of herbal treatment intervention,we applied seven attribute weighting algorithms to check the effects of variables on identifying lncRNAs.Attribute weighting results showed that the cell line and time had little or no effect on the selected lncRNAs list.Besides,we identified one known lncRNAs,downregulated RNA in cancer(DRAIC),as an essential feature.Conclusions:This study will provide further insights to investigate the potential therapeutic and prognostic targets for prostate cancer(PC)and breast cancer(BC)in common.