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An expedited field analysis method was developed for the determination of polychlorinated biphenyls (PCBs) in soil matrices using a portable gas chromatography-mass spectrometry (GC-MS) instrument. Soil samples of approximately 0.5 g were measured with a portable scale and PCBs were extracted by headspace solid-phase microextraction (SPME) with a 100 µm polydimethylsiloxane (PDMS) fiber. Two milliliters of 0.2 M potassium permanganate and 0.5 mL of 6 M sulfuric acid solution were added to the soil matrices to facilitate the extraction of PCBs. The extraction was performed for 30 min at 100 ℃ in a portable heating block that was powered by a portable generator. The portable GC-MS instrument took less than 6 min per analysis and ran off an internal battery and helium cylinder. Six commercial PCB mixtures, Aroclor 1016, 1221, 1232, 1242, 1248, 1254, and 1260, could be classified based on the GC chromatograms and mass spectra. The detection limit of this method for Aroclor 1260 in soil matrices is approximately 10 ppm, which is sufficient for guiding remediation efforts in contaminated sites. This method was applicable to the on-site analysis of PCBs with a total analysis time of 37 min per sample. However, the total analysis time could be improved to less than 7 min per sample by conducting the rate-limiting extraction step for different samples in parallel., (© The Author(s) 2016.)

Hair analysis is an area of increasing interest in the fields of medical and forensic sciences. Human scalp hair has attractive features in clinical studies because hair can be sampled easily and noninvasively from human subjects, and unlike blood and urine samples, it contains a chronological record of medication use. Keratin protein is the major component of scalp hair shaft material and it is composed of 21 amino acids. The method used herein for the amino acid determination in hair included keratin protein acid hydrolysis using 6 M hydrochloric acid (HCl), followed by amino acids derivatization using N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA), and the determination of derivatized amino acids by gas chromatography/mass spectrometry (GC/MS). Amino acid profiles of scalp hair of 27 Jordanian subjects (15 diabetes mellitus (DM) type 2 patients and 12 control subjects) were analyzed. A fuzzy rule-building expert system (FuRES) classified the amino acid profiles into diabetic and control groups based on multivariate analyses of the abundance of 14 amino acids. The sensitivity and specificity were 100% for diabetes detection using leave-one-individual-out cross-validation. The areas under the receiver operative characteristics (ROC) curves were 1.0, which represents a highly sensitive and specific diabetes test. The nonessential amino acids Gly and Glu, and the essential amino acid Ile were more abundant in the scalp hair of diabetic patients compared to the hair of control subjects. The associations between the abundance of amino acids of human hair and health status may have clinical applications in providing diagnostic indicator or predicting other chronic or acute diseases.

Rationale: To provide a simple one-step derivatization procedure for the analysis of a wide variety of amino acids in human hair by gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS). N,O-Bis(trimethylsilyl)trifluoroacetamide (BSTFA) derivatization is already widely used outside the IRMS community, is applicable to a variety of functional groups, and provides products that are common entries in mass spectral databases, thus simplifying compound identification., Methods: Method optimization and validation were performed on a mixture of ten standard amino acids found abundantly in human hair. The method was then applied to the analysis of scalp hair from six human subjects. The hair was washed, hydrolyzed with 6 M HCl, derivatized using BSTFA in acetonitrile and analyzed using gas chromatography (GC) with concurrent quadrupole and isotope ratio mass spectrometry (IRMS) detectors., Results: The reproducibility for the δ(13)C measurements, including the derivatization procedure and GC/C/IRMS analysis, on a day-to-day comparison was between 0.19‰ and 0.35‰ (SD, N = 12), with an average standard deviation of 0.26‰. Because trimethylsilylation adds 3N carbon atoms (where N = # reactive protons) to each amino acid, the δ(13)C values for amino acid derivatives were corrected using a mass balance correction and the measured kinetic isotope effect (KIE). The KIE values ranged from 0.984 to 1.020., Conclusions: The procedure gave consistent δ(13)C values with precision similar to other derivatization methods for the range of sample sizes studied: 50-1000 µg of each amino acid. The method gave δ(13)C values consistent with the known literature values when applied to the analysis of amino acids in human hair., (Copyright © 2013 John Wiley & Sons, Ltd.)

A fast method that can be used to classify unknown jet fuel types or detect possible property changes in jet fuel physical properties is of paramount interest to national defense and the airline industries. While fast gas chromatography (GC) has been used with conventional mass spectrometry (MS) to study jet fuels, fast GC was combined with fast scanning MS and used to classify jet fuels into lot numbers or origin for the first time by using fuzzy rule-building expert system (FuRES) classifiers. In the process of building classifiers, the data were pretreated with and without wavelet transformation and evaluated with respect to performance. Principal component transformation was used to compress the two-way data images prior to classification. Jet fuel samples were successfully classified with 99.8 ± 0.5% accuracy for both with and without wavelet compression. Ten bootstrapped Latin partitions were used to validate the generalized prediction accuracy. Optimized partial least squares (o-PLS) regression results were used as positively biased references for comparing the FuRES prediction results. The prediction results for the jet fuel samples obtained with these two methods were compared statistically. The projected difference resolution (PDR) method was also used to evaluate the fast GC and fast MS data. Two batches of aliquots of ten new samples were prepared and run independently 4 days apart to evaluate the robustness of the method. The only change in classification parameters was the use of polynomial retention time alignment to correct for drift that occurred during the 4-day span of the two collections. FuRES achieved perfect classifications for four models of uncompressed three-way data. This fast GC/fast MS method furnishes characteristics of high speed, accuracy, and robustness. This mode of measurement may be useful as a monitoring tool to track changes in the chemical composition of fuels that may also lead to property changes., (Copyright © 2010 Elsevier B.V. All rights reserved.)

We present the development of a new, faster analytical method for the determination of fatty acid ethyl esters (FAEEs) in human hair to detect potential alcohol abuse. FAEEs have been established as metabolites of ethanol consumption in humans and are embedded in the hair follicles during hair growth. The developed method has a total analysis time-including washing, extraction, concentration, separation, and detection-of less than 1 hour. Commonly used extraction procedures in the literature for these biomarkers are typically 15 hours. Analysis is performed using gas chromatography-tandem mass spectrometry (GC-MS/MS) with a GC separation time of less than 9 minutes. Using chemical ionization, mass spectrometric detection consists of selected reaction monitoring, which is widely considered to be one of the most selective and sensitive forms of mass spectrometric detection. Employing selected reaction monitoring helps to reduce interferences from the hair matrix, thereby making the method more selective for these biomarkers of interest. Limits of detection for each FAEE range from 0.002 to 0.030 ng/mg in hair. By using this faster extraction method, this research shows that this method could potentially be used to distinguish whether a person is a heavy drinker, moderate drinker, or nondrinker. The ability to rapidly analyze hair samples can be applied to a number of different areas, such as neonatal screening, parole violations, contributing factors in the cause of death, and any other application requiring the establishment of chronic versus acute alcohol abuse.