Choosing between GC–FTIR and GC–MS spectra for an efficient intelligent identification of illicit amphetamines

Separation and determination of estrogen in the water environment by high performance liquid chromatography-fourier transform infrared spectroscopy

The components for connecting high-performance liquid chromatography (HPLC) with Fourier-transform infrared spectroscopy (FTIR) were investigated to determine estrogen in the water environment, including heating for atomization, solvent removal, sample deposition, drive control, spectrum collection, chip swap, cleaning and drying. Results showed that when the atomization temperature was increased to 388 K, the interference of mobile phase components (methanol, H2O, acetonitrile, and NaH2PO4) were completely removed in the IR measurement of estrogen, with 0.999 of similarity between IR spectra obtained after separation and corresponding to the standard IR spectra. In experiments with varying HPLC injection volumes, high similarity for IR spectra was obtained at 20 ul injection volume at 0.01 mg/L BPA while a useful IR spectrum for 10 ng/L BPA was obtained at 80 ul injection volume. In addition, estrogen concentrations in the natural water samples were calculated semi-quantitatively from the peak intensities of IR spectrum in the mid-infrared region.

Superoxide Ion: Generation and Chemical Implications

Superoxide ion (O2(•-)) is of great significance as a radical species implicated in diverse chemical and biological systems. However, the chemistry knowledge of O2(•-) is rather scarce. In addition, numerous studies on O2(•-) were conducted within the latter half of the 20th century. Therefore, the current advancement in technology and instrumentation will certainly provide better insights into mechanisms and products of O2(•-) reactions and thus will result in new findings. This review emphasizes the state-of-the-art research on O2(•-) so as to enable researchers to venture into future research. It comprises the main characteristics of O2(•-) followed by generation methods. The reaction types of O2(•-) are reviewed, and its potential applications including the destruction of hazardous chemicals, synthesis of organic compounds, and many other applications are highlighted. The O2(•-) environmental chemistry is also discussed. The detection methods of O2(•-) are categorized and elaborated. Special attention is given to the feasibility of using ionic liquids as media for O2(•-), addressing the latest progress of generation and applications. The effect of electrodes on the O2(•-) electrochemical generation is reviewed. Finally, some remarks and future perspectives are concluded.

Global Clustering Quality Coefficient Assessing the Efficiency of PCA Class Assignment

An essential factor influencing the efficiency of the predictive models built with principal component analysis (PCA) is the quality of the data clustering revealed by the score plots. The sensitivity and selectivity of the class assignment are strongly influenced by the relative position of the clusters and by their dispersion. We are proposing a set of indicators inspired from analytical geometry that may be used for an objective quantitative assessment of the data clustering quality as well as a global clustering quality coefficient (GCQC) that is a measure of the overall predictive power of the PCA models. The use of these indicators for evaluating the efficiency of the PCA class assignment is illustrated by a comparative study performed for the identification of the preprocessing function that is generating the most efficient PCA system screening for amphetamines based on their GC-FTIR spectra. The GCQC ranking of the tested feature weights is explained based on estimated density distributions and validated by using quadratic discriminant analysis (QDA).

Principal component analysis coupled with artificial neural networks--a combined technique classifying small molecular structures using a concatenated spectral database

In this paper we present several expert systems that predict the class identity of the modeled compounds, based on a preprocessed spectral database. The expert systems were built using Artificial Neural Networks (ANN) and are designed to predict if an unknown compound has the toxicological activity of amphetamines (stimulant and hallucinogen), or whether it is a nonamphetamine. In attempts to circumvent the laws controlling drugs of abuse, new chemical structures are very frequently introduced on the black market. They are obtained by slightly modifying the controlled molecular structures by adding or changing substituents at various positions on the banned molecules. As a result, no substance similar to those forming a prohibited class may be used nowadays, even if it has not been specifically listed. Therefore, reliable, fast and accessible systems capable of modeling and then identifying similarities at molecular level, are highly needed for epidemiological, clinical, and forensic purposes. In order to obtain the expert systems, we have preprocessed a concatenated spectral database, representing the GC-FTIR (gas chromatography-Fourier transform infrared spectrometry) and GC-MS (gas chromatography-mass spectrometry) spectra of 103 forensic compounds. The database was used as input for a Principal Component Analysis (PCA). The scores of the forensic compounds on the main principal components (PCs) were then used as inputs for the ANN systems. We have built eight PC-ANN systems (principal component analysis coupled with artificial neural network) with a different number of input variables: 15 PCs, 16 PCs, 17 PCs, 18 PCs, 19 PCs, 20 PCs, 21 PCs and 22 PCs. The best expert system was found to be the ANN network built with 18 PCs, which accounts for an explained variance of 77%. This expert system has the best sensitivity (a rate of classification C = 100% and a rate of true positives TP = 100%), as well as a good selectivity (a rate of true negatives TN = 92.77%). A comparative analysis of the validation results of all expert systems is presented, and the input variables with the highest discrimination power are discussed.