Hydrolysis of uranyl(VI) in acidic and basic aqueous solutions using a noncomplexing organic base: a multivariate spectroscopic and statistical study

In the field of actinide aqueous chemistry, this work aims to resolve some controversy about uranyl(VI) hydroxide species present in basic aqueous solutions. We revisit the Raman, IR, and UV-visible spectra with two new approaches. First, Raman, IR and UV data were recorded systematically from aqueous solutions with the noncomplexing electrolyte (C(2)H(5))(4)NNO(3) at 25 °C and 0.1 MPa ([U(total)] = 0.005-0.105 M) in H(2)O and D(2)O over a wide range of -log mH(D)(+) between 2.92 and 14.50. Second, vibrational spectra (IR and Raman) of basic solutions in H(2)O and D(2)O were analyzed using the Bayesian Positive Source Separation method to estimate pure spectra of individual species. In D(2)O solutions, the new spectroscopic data showed the occurrence of the same species as those in H(2)O. As observed for the wavenumber of the symmetric stretching mode, the wavenumber characteristic of the O═U═O antisymmetric stretching mode decreases as the number of OH(D)(-) ligands increases. These kinds of data, completed by (1) analysis of the signal widths, (2) persistence of the apparent exclusion rule between IR and Raman spectra of the uranyl species stretching modes, and (3) interpretation of the absorption UV-visible spectra, allow discussion of the chemistry, structures, and polynuclearity of uranyl(VI) species. In moderate basic solutions, the presence of two trimers is suggested. In highly basic solutions ([OH(-)] ≈ 3 M), the two monomers UO(2)(OH)(4)(2-) and UO(2)(OH)(5)(3-) are confirmed to be in good agreement with earlier EXAFS and NMR results. The occurrence of the UO(2)(OH)(6)(4-) monomer is also suggested from the more basic solutions investigated.     

A study of trace element contamination in river sediments in Serbia using microwave-assisted aqua regia digestion and multivariate statistical analysis

The aim of this study was the evaluation of the trace element contamination level in sediments of the most important rivers in Serbia and their tributaries. The determination of the aqua regia soluble contents of 12 micro- and macro-elements (Ca, Cd, Co, Cr, Cu, Fe, Mn, Pb, Ni, Zn, Be and V) in sediments was developed by the microwave digestion technique combined with inductively coupled plasma atomic emission spectrometry. Correlation analysis and principal component analysis distinguishes factors of lithogenic and anthropogenic origins. The Fe, Mn, Be and V contents are controlled by a regional lithogenic high background factor, while Cd, Cr, Pb, Ni, Zn and Cu are recognized as tracer of pollution. For Co, mixed sources from both lithogenic and anthropogenic inputs were evidenced.The investigated sediment of the major rivers and their tributaries in Serbia showed high concentrations of metals, especially of Cd, Pb, Cu and Zn, which may cause serious environmental impacts. Rivers which flow into the Danube from its entrance into Serbia significantly influence the chemical load of the water and sediments.The experimental study was conducted using two BCR standard reference materials. The calculated accuracy and precision confirmed the good performance of the adopted procedures.     

Chemometric data analysis of pollutants in wastewater—a case study

In this study, chemometric techniques such as cluster analysis (CA), discriminant analysis (DA), principal component analysis (PCA) and partial least squares (PLS) were used to analyse the wastewater dataset to identify the factors which affect the composition of sewage of domestic origin, spatial and temporal variations, similarity/dissimilarity among the wastewater characteristics of cis- and trans-drains and discriminating variables. Samples collected from 24 wastewater drains in Lucknow city and from three sites on Gomti river in the month of January/February, May, August and November during the period of 5 years (1994-1999) were characterized for 32 parameters. The multivariate techniques successfully described the similarities/dissimilarities among the sewage drains on the basis of their wastewater characteristics and sources signifying the effect of routine domestic/commercial activities in respective drainage areas. Spatial and seasonal variations in wastewater composition were also determined successfully. CA generated six groups of drains on the basis of similar wastewater characteristic. PCA provided information on seasonal influence and compositional differences in sewage generated by domestic and industrial waste dominated drains and showed that drains influenced by mixed industrial effluents have high organic pollution load. DA rendered six variables (TDS, alkalinity, F, TKN, Cd and Cr) discriminating between cis- and trans-drains. PLS-DA showed dominance of Cd, Cr, NO₃, PO₄ and F in cis-drains wastewater. The results suggest that biological-process based STPs could treat wastewater both from the cis- as well as trans-drains, however, prior removal of toxic metals will be required from the cis-drains sewage. Further, seasonal variations in wastewater composition and pollution load could be the guiding factor for determining the STPs design parameters. The information generated would be useful in selection of process type and in designing of the proposed sewage treatment plants (STPs) for safe disposal of wastewater.     

Diagnosis of lung cancer based on metal contents in serum and hair using multivariate statistical methods

The classification of normal and cancer groups with four multivariate methods according to metal contents in serum and hair samples has been discussed in the present paper. Results show that the four multivariate methods, stepwise discrimination analysis, principal components analysis, hierarchical cluster analysis, and stepwise cluster analysis can distinguish the two groups correctly. The independent samples of both normal and cancer groups were tested and can be distinguished correctly by the four methods. Therefore, these methods can be used as an aid for diagnosis of lung cancer according to the metal contents in serum and hair samples.     

Water stability of cobalt doped ZIF-8: a quantitative study using optical analyses

Zeolitic imidazolate frameworks (ZIFs), in particular ZIF-8 (made of Zn²⁺ and 2-methyilimidazolate) and cobalt-doped-ZIF-8, are found important for many energy and environmental applications. It was reported that ZIFs show excellent structural stability in water and thus ideal for aqueous applications. However, recent studies also found some evidence that ZIF-8 undergoes hydrolysis in water. Despite the importance of ZIF's stability in many aqueous applications, the extent of ZIFs' degradation in water is still not yet fully understood. In this study, we report a quantitative study of the water stability of 0–100 at% cobalt-doped ZIF-8, using a new combination of analytical tools. The study demonstrated the importance of analyzing both filtered powders and the filtrate liquid systematically, in particular by using UV–Vis spectroscopy and thermogravimetric analysis. The combination of analytical tools allowed the study on the effects of ZIF concentrations in water, cobalt doping levels, and amounts of ligands in water on the water stability of ZIF samples. The effect of cobalt-doping was investigated by using ZIF particles with identical sizes (200–400 nm), in order to eliminate the effects of particle size on hydrolysis. Unlike other synthesis methods, a mechanochemical ball milling method allowed the production of nano-scale ZIF-8 particles with similar sizes, independent of cobalt-doping levels. The proposed combination of analytical tools including UV–Vis spectroscopy can be applied to the study of the water stability of other MOF materials.     

A case study of the natural attenuation of gas condensate hydrocarbons in soil and groundwater

Applied Biochemistry and Biotechnology - Condensate liquids have been found to contaminate soil and groundwater at two gas production sites in the Denver Basin operated by Amoco Production Co....     

Investigation of chemical diversity in different parts and origins of ethnomedicine Gentiana rigescens Franch using targeted metabolite profiling and multivariate statistical analysis

Gentiana rigescens, an ethnomedicine, is widely cultivated in Yunnan province of China. Although a wide range of metabolites including iridoid glycosides, flavonoids and triterpenoids have been reported in this ethnomedicine, the data on accumulation and distribution of metabolites in certain parts are limited. In this study, targeted metabolic fingerprinting of iridoid glycosides based on liquid chromatography–ultraviolet detection–tandem mass spectrometry (LC‐UV‐MS/MS) was developed to investigate the metabolic similarities and differences in different parts and origins. Thirty‐one compounds, including iridoid glycosides and flavonoids, were detected from targeted metabolite profiling and plausibly assigned to the different parts of G. rigescens. Multivariate statistical analysis was designed to reveal close chemical similarities between all the selected samples and to identify key metabolites characteristic of the standard. The results suggested that accumulation and distribution of metabolites in aerial and underground parts were different. Moreover, root samples tended to be grouped on the basis of the geographical closeness of region. Five metabolites can be considered as potential markers for the classification of underground parts from different regions. These results provided chemical information on the potential pharmaceutical value for further research, making G. rigescens ideal for the rational usage of different parts and exploitation of the source. Copyright © 2015 John Wiley & Sons, Ltd.     

Metabolic characterization of the early stage of hepatic fibrosis in rat using GC‐TOF/MS and multivariate data analyses

The aim of this study was to explore the changes in the urine metabolic spectrum in rats with the early stage of liver fibrosis using gas chromatography–time of flight/mass spectrometry (GC‐TOF/MS), try to search for potential biomarkers and elucidate the probably metabonomic pathogenesis. The early stage of liver fibrosis was established with a single subcutaneous injection of carbon tetrachloride twice each week for 4 weeks continuously. At the end of the experiment, GC‐TOF/MS technology with multivariate statistical approaches such as principal component analysis, partial least squares‐discriminant analysis and orthogonal partial least squares‐discriminant analysis was used to analyze the changes in the metabolic spectrum trajectory and identify potential biomarkers. Twelve potential biomarkers in the model group, such as succinic acid, threonine and lactose, were selected, which indicate that the metabonomic pathogenesis of the early stage of liver fibrosis may be related to disorders of energy metabolism, amino acid metabolism and fatty acid metabolism.     

Probing the structural and electronic factors affecting the adsorption and reactivity of alkenes in acidic zeolites using DFT calculations and multivariate statistical methods

Quantum mechanical (QM) cluster calculations have been performed on a model of ZSM-5 at DFT and MP2 levels. We investigated how the adsorption energies and the energetics of alkoxide intermediate formation of six different alkene substrates, ethene, propene, 1-butene, cis/trans butene, and isobutene, vary in this zeolite model. An analysis of the DFT geometric, electronic, and energetic parameters of the zeolite-substrate complexes, transition states, and alkoxide intermediates is performed using principal components analysis (PCA) and partial least squares (PLS). These deliver an insight into the correlated changes that occur between molecular structure and energy along the reaction coordinate between the physisorbed and chemisorbed species within the zeolite. To the best of our knowledge, this is the first occasion multivariate techniques such as PCA or PLS have been employed to profile the changes in electronics, distances, and angles in QM calculations of catalytic systems such as zeolites. We find the calculated adsorption and the alkoxide intermediate energies correlate strongly with the absolute charge on the substrate and the length of the substrate double bond. The transition states' energies are not affected by the zeolite framework as modeled, which explains why they correlate strongly with the gas-phase substrate protonation energy. Our cluster results show that for ethene, propene, 1-butene, and isobutene, the relative energetics associated with the formation of the alkoxide intermediate in ZSM-5 follow the same trends as calculations where the effects of the framework are included.     

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity: in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique

The accurate identification of T-cell epitopes remains a principal goal of bioinformatics within immunology. As the immunogenicity of peptide epitopes is dependent on their binding to major histocompatibility complex (MHC) molecules, the prediction of binding affinity is a prerequisite to the reliable prediction of epitopes. The iterative self-consistent (ISC) partial-least-squares (PLS)-based additive method is a recently developed bioinformatic approach for predicting class II peptide-MHC binding affinity. The ISC-PLS method overcomes many of the conceptual difficulties inherent in the prediction of class II peptide-MHC affinity, such as the binding of a mixed population of peptide lengths due to the open-ended class II binding site. The method has applications in both the accurate prediction of class II epitopes and the manipulation of affinity for heteroclitic and competitor peptides. The method is applied here to six class II mouse alleles (I-Ab, I-Ad, I-Ak, I-As, I-Ed, and I-Ek) and included peptides up to 25 amino acids in length. A series of regression equations highlighting the quantitative contributions of individual amino acids at each peptide position was established. The initial model for each allele exhibited only moderate predictivity. Once the set of selected peptide subsequences had converged, the final models exhibited a satisfactory predictive power. Convergence was reached between the 4th and 17th iterations, and the leave-one-out cross-validation statistical terms--q2, SEP, and NC--ranged between 0.732 and 0.925, 0.418 and 0.816, and 1 and 6, respectively. The non-cross-validated statistical terms r2 and SEE ranged between 0.98 and 0.995 and 0.089 and 0.180, respectively. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made freely available online (http://www.jenner.ac.uk/MHCPred).     

Non-invasive identification of organic materials in wall paintings by fiber optic reflectance infrared spectroscopy: a statistical multivariate approach

The aim of this study is to develop a method for the non-invasive and in situ identification of organic binders in wall paintings by fiber optic mid-FTIR reflectance spectroscopy. The non-invasive point analysis methodology was set-up working on a wide set of wall painting replicas of known composition and using statistical multivariate methods, in particular principal component analysis (PCA), for the interpretation, understanding, and management of data acquired with reflectance mid-FTIR spectroscopy. Results show that PCA can be helpful in managing and preliminary sorting of the large amount of spectra typically collected during non-invasive measurement campaigns and highlight further avenues for research. The developed PCA model was finally applied to the case of a Renaissance wall painting by Perugino assessing it predictability as compared to the interpretation of the single spectrum.     

Environmental dose assessment using Ecolego: case study of soil from Japan

From the Fukushima incident, a number of radionuclides were released, causing radioactive contamination to the environment. Depending on their own half-lives, the radionuclides, however, will decay over time. During the decay, those radionuclides can be transferred to the ecosystem and, eventually, to humans. As part of the environmental surveillance and restoration program, radiological dose assessments have been carried out in response to the incident to prevent a potentially unacceptable dose to the public. This study focuses on the deposition of certain radionuclides in soil and their transport through the terrestrial food chain. Soil from two sites, Namie and Iitate, where radioactive contamination is evident was used as the source term. The assessment has been conducted using Ecolego, a simulation software used for conducting dose assessments of complex dynamic systems evolving over time especially in the field of radiology. Possible pathways from the soil used as the source term to humans as well as crops, forage, livestock products, and milk, for specific radioactive species have been studied. The dose assessment results of I-131, Cs-134, Cs-137, Sr-89, and Sr-90 in each compartment of the food chain are presented in this literature. The concentrations of the studied radionuclides vary from one medium to another, resulting from the characteristic of the medium itself along with other factors, such as the half-lives and transfer factors. Due to the fact that the concentrations of the radionuclides are affected by the depth of soil, there may be some uncertainty of the dose assessment results from the model.     

Simultaneous determination of 20 bioactive components in Chuanxiong Rhizoma from different production origins in Sichuan province by ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry combined with multivariate statistical analysis

Chuanxiong Rhizoma is a commonly used in traditional Chinese medicine. Chuanxiong Rhizoma is widely distributed in Sichuan province, China, including the cities of Dujiangyan, Pengzhou, Meishan, Qionglai, and Shifang. However, reports on the comparisons of quality of Chuanxiong Rhizoma of different production origins are limited. Therefore, an ultra-HPLC with triple quadrupole MS method was developed for the determination of 20 bioactive components (12 aromatic acids and eight phthalides) in 36 samples from different production origins and further assessed its quality. The contents of these 20 constituents of samples were analyzed by hierarchical cluster analysis and orthogonal partial least squares discrimination analysis; the result indicated that Chuanxiong Rhizoma of different production origins had some differences. Thirteen constituents of quality difference markers were acquired by variable importance for the project. Furthermore, the sum of the contents of these quality difference markers was different from various production origins of Chuanxiong Rhizoma. Meanwhile, Z-ligustilide and senkyunolide A as main constituents of quality difference markers, the rate of various production origins of Chuanxiong Rhizoma was different. This study provides a foundation for the quality assessment of Chuanxiong Rhizoma.     

X-ray scattering and multivariate analysis for classification of organic samples: a comparative study using Rh tube and synchrotron radiation

This work compares the performance of X-ray tube induced and synchrotron induced energy dispersive X-ray fluorescence in generating scattering profiles when organic samples are irradiated. In the first case, this effect produces sharper peaks, well defined in the spectra, whereas synchrotron-induced scatter are seen as broad bands. These effects may be used for classifying simple materials like graphite, coke, activated carbon and carbon nanotubes, all having the same composition but different structures, using multivariate data analysis. In a second sample set, the method was applied to liquid samples of different alcohols (methanol, ethanol, 1-propanol and 2-propanol). Classifications were obtained in both cases independent of the X-ray source (synchrotron radiation or X-ray tube radiation), showing that the use of chemometric tools combined with X-ray spectrometry can efficiently distinguish organic samples by using scattering effects.     

Heck arylation of acrolein acetals using the 9-bromoanthracene: A case of study

The influence of several parameters on the selectivity of the palladium catalysed Heck coupling of 9-bromoanthracene with acrolein acetals was studied. While the ester is the quasi exclusive product when only a base (i.e. NaOAc, K₂CO₃, etc.) is added in the medium, the presence of halide abstracting agent such as thallium or silver salts decreases noticeably the selectivity towards the ester. On the other hand, the addition of n-Bu₄NOAc yields to the formation of the aldehyde with up to 74% selectivity. The presence of water was found to play a significant role not only on the rate but also on the selectivity of the reaction. A comprehensive mechanism is proposed outlining the influence of each additive, particularly on the selectivity of the reaction.     

Assessment of applicability domain for multivariate counter-propagation artificial neural network predictive models by minimum Euclidean distance space analysis: A case study

Alongside the validation, the concept of applicability domain (AD) is probably one of the most important aspects which determine the quality as well as reliability of the established quantitative structure–activity relationship (QSAR) models. To date, a variety of approaches for AD estimation have been devised which can be applied to particular type of QSAR models and their practical utilization is extensively elaborated in the literature. The present study introduces a novel, simple, and effective distance-based method for estimation of the AD in case of developed and validated predictive counter-propagation artificial neural network (CP ANN) models through a proficient exploitation of the Euclidean distance (ED) metric in the structure-representation vector space. The performance of the method was evaluated and explained in a case study by using a pre-built and validated CP ANN model for prediction of the transport activity of the transmembrane protein bilitranslocase for a diverse set of compounds. The method was tested on two more datasets in order to confirm its performance for evaluation of the applicability domain in CP ANN models. The chemical compounds determined as potential outliers, i.e., outside of the CP ANN model AD, were confirmed in a comparative AD assessment by using the leverage approach. Moreover, the method offers a graphical depiction of the AD for fast and simple determination of the extreme points.     

1H NMR: a tool to study the fate of pollutants in the environment

In situ ¹H NMR, directly performed on biological fluids is a very powerful tool to study the fate of pollutants in the environment. The biodegradation of 2-aminobenzothiazole by Rhodococcus rhodochrous was monitored by reverse phase HPLC and by in situ ¹H NMR, methods performed directly on culture media without purification. The xenobiotic was biotransformed into a hydroxylated derivative. The chemical structure of this metabolite was determined by a long-range ¹H–¹⁵N heteronuclear shift correlation without any previous ¹⁵N enrichment of the compound. This approach allowed the assignment of the metabolite structure to 2-amino-6-hydroxybenzothiazole.