Simultaneous spectrophotometric determination of Co (II) and Co (III) in acidic medium with partial least squares regression and artificial neural networks

This study aims at the application of two chemometric techniques to visible spectra of acetic acid solutions of Co (II) and Co (III) for simultaneous determination thereof. Spectral data of 145 samples in the range of 400-700 nm were used to build the models. Partial least squares regression models were developed for which latent variables were determined using internal cross-validation with a leave-one-out strategy and 3 and 2 latent variables were selected for Co(II) and Co(III) based on root mean square error of cross-validation. For these models, root mean square errors of prediction were 1.16 and 0.536 mM and coefficients of determination were 0.975 and 0.892 for Co (II) and Co (III). As an alternate method, artificial neural networks consisting of three layers, with 10 neurons in hidden layer, were trained to model spectra and concentrations of cobalt species. Levenberg-Marquardt algorithm with feed-forward back-propagation learning resulted root mean square errors of prediction of 0.316 and 0.346 mM for Co (II) and Co (III) respectively and coefficients of determination were 0.996 and 0.988.

Spectroscopic characteristics of water-extractable organic matter from different green manures1

Water-extractable organic matter (WEOM) plays an important role in many chemical processes and in soil organic matter accumulation. Large amounts of WEOM can be released by green manure when being incorporated into the soil. However, the characteristics of WEOM extracted from different green manures (GMs) are unclear. In this study, WEOM samples were extracted from Chinese milk vetch (Astragalus sinicus L), radish (Raphanus sativus L), ryegrass (Lolium perenne L), hairy vetch (Vicia villosa L), February orchid (Orychophragmus violaceus) and rye (Secale cereale L) and their characteristics were studied by spectroscopic analysis. WEOM generated from legume GMs contained more water-extractable organic carbon (WEOC) than other GMs and Chinese milk vetch was the highest. UV-visible spectroscopy analysis revealed that all the samples were rich in C=C and C=O functional groups. Carboxylic acid, alcohol, phenol, fatty acids, aliphatic aromatic and amide compounds were found by FTIR spectroscopy in these WEOM samples. WEOM derived from Chinese milk vetch contained more carboxylic acid and inorganic sulphates only appeared in WEOM extracted from the radish. The aromaticity index, humification index, and FTIR absorption ratio 1650/2925 and 1650/2850 showed that WEOM extracted from Chinese milk vetch and hairy vetch had a relatively lower aromaticity and humification degree than other GMs. The fluorescence regional integration (FRI) analysis showed that Chinese milk vetch and hairy vetch had a higher portion of protein-like substance fractions than other GMs. We may deduce that WEOM generated from Chinese milk vetch and hairy vetch has higher chemical activity than other GMs.

The Botanical Drug Substance Crofelemer as a Model System for Comparative Characterization of Complex Mixture Drugs

Crofelemer is a botanical polymeric proanthocyanidin that inhibits chloride channel activity and is used clinically for treating HIV-associated secretory diarrhea. Crofelemer lots may exhibit significant physicochemical variation due to the natural source of the raw material. A variety of physical, chemical, and biological assays were used to identify potential critical quality attributes (CQAs) of crofelemer, which may be useful in characterizing differently sourced and processed drug products. Crofelemer drug substance was extracted from tablets of one commercial drug product lot, fractionated, and subjected to accelerated thermal degradation studies to produce derivative lots with variations in chemical and physical composition potentially representative of manufacturing and raw material variation. Liquid chromatography, UV absorbance spectroscopy, mass spectrometry, and nuclear magnetic resonance analysis revealed substantial changes in the composition of derivative lots. A chloride channel inhibition cell-based bioassay suggested that substantial changes in crofelemer composition did not necessarily result in major changes to bioactivity. In 2 companion papers, machine learning and data mining approaches were applied to the analytical and biological data sets presented herein, along with chemical stability data sets derived from forced degradation studies, to develop an integrated mathematical model that can identify CQAs which are most relevant in distinguishing between different populations of crofelemer.

A Study of the Interaction of Bovine Hemoglobin with Synthetic Dyes Using Spectroscopic Techniques and Molecular Docking

Synthetic dyes are a very efficient class of dyes that are ingested or come into contact with the skin from numerous sources (cosmetics, textiles, leather, paper, and drugs). An important component of their safety profile is the interactions that they form after they enter the body. Hemoglobin is a functionally important protein that can form multiple interactions with soluble compounds present in the blood, and hence forms an important aspect of the toxicological or safety profile of the dyes. Here we study the interaction between bovine hemoglobin and organic dyes using UV-Vis absorbance and fluorescence spectroscopy. Molecular modeling was used to visualize the binding site and partners of the dye molecules, within the hemoglobin molecule. We find that all four dyes studied form sufficiently strong interactions with hemoglobin to allow for the formation of potentially toxic interactions. Molecular modeling showed that all four dyes bind within the central cavity of the hemoglobin molecule. However, binding partners could not be identified as multiple binding conformations with very similar energies were possible for each dye.