Evaluation of gas chromatography-atmospheric pressure chemical ionization tandem mass spectrometry as an alternative to gas chromatography tandem mass spectrometry for the determination of polychlorinated biphenyls and polybrominated diphenyl ethers

First Detection of Food-Derived Agricultural Chemicals Residues in Waste Wool Fibers by Ultrasound-Assisted Extraction-QuEChERS Cleanup-UPLC-MS/MS

Food-derived agricultural chemical residues (FACRs) accumulate gradually in organisms and can damage their nervous system, endocrine system and reproductive system, posing significant harm. Currently, there is little literature on the detection of FACRs in waste wool fibers. In this paper, an ultrasound-assisted extraction-QuEChERS (Quick, Easy, Cheap, Effective, Rugged, Safe) cleanup-UPLC-Ms/Ms method was applied for the qualitative analysis and quantitative determination of trace FACRs in waste wool fibers with 0.2% formic acid-methanol as extraction solvent and multi-selective ion scanning. Using the external standard method, it was shown that the 13 target FACRs showed good linearity in the mass concentration range of 0.1-50 μg/kg. The limits of detection were 1.0- 10.0 μg/kg and the limits of quantification were 4.0-40.0 μg/kg. The recoveries of the 13 target FACRs ranged from 78 to 112.6% at the 5-, 10- and 20-fold detection limit spiked levels, and the intra- or inter-day relative standard deviations were 2.05-6.98% or 1.98-6.99%, respectively. This method satisfied the detection requirements and can be used in applications.

Emerging environmental pollutants hydroxylated polybrominated diphenyl ethers: From analytical methods to toxicology research

Hydroxylated polybrominated diphenyl ethers (OH-PBDEs) are of particular concern due to their ubiquitous distribution and adverse health effects. Significant progress has been made in the characterization of OH-PBDEs by using mass spectrometry (MS). In this review, we summarize applications of MS-based techniques in detection, environmental and biota distribution, and potential health risk effects, hoping to unfold an overall picture on account of current knowledge of OH-PBDEs. The analytical methodologies are discussed from sample pretreatment to MS analysis. The methods including gas chromatography-MS (GC-MS), liquid chromatography-MS (LC-MS), and ion mobility spectrometry-MS (IMS-MS) are discussed. GC-MS is the most frequently adopted method in the analysis of OH-PBDEs due to its excellent chromatographic resolution, high sensitivity, and strong ability for unknown identification. LC-MS has been widely used for its high sensitivity and capability of direct analysis. As a newly developed technique, IMS-MS provides high specificity, which greatly facilitates the identification of isomers. OH-PBDEs pervasively existed in both abiotic and biotic samples, including humans, animals, and environmental matrices. Multiple adverse health effects have been reported, such as thyroid hormone disruption, estrogen effects, and neurotoxicity. The reported potential pathological mechanisms are also reviewed. Additionally, MS-based metabolomics, lipidomics, and proteomics have been shown as promising tools to unveil the molecular mechanisms of the toxicity of OH-PBDEs. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Predictive Modeling for Metabolomics Data

In recent years, mass spectrometry (MS)-based metabolomics has been extensively applied to characterize biochemical mechanisms, and study physiological processes and phenotypic changes associated with disease. Metabolomics has also been important for identifying biomarkers of interest suitable for clinical diagnosis. For the purpose of predictive modeling, in this chapter, we will review various supervised learning algorithms such as random forest (RF), support vector machine (SVM), and partial least squares-discriminant analysis (PLS-DA). In addition, we will also review feature selection methods for identifying the best combination of metabolites for an accurate predictive model. We conclude with best practices for reproducibility by including internal and external replication, reporting metrics to assess performance, and providing guidelines to avoid overfitting and to deal with imbalanced classes. An analysis of an example data will illustrate the use of different machine learning methods and performance metrics.

Multiresidue analysis of 85 persistent organic pollutants in small human serum samples by modified QuEChERS preparation with different ionization sources in mass spectrometry

In this study, a multiresidue analytical method was developed, validated, and applied for quantifying 85 persistent organic pollutants (POPs), including 38 polychlorinated biphenyls (PCBs), 23 polybrominated diphenyl ethers (PBDEs), and 24 organochlorine pesticides (OCPs) from 200 μL of human serum. A modified QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) method was applied to minimize the required sample amount and optimize various conditions including the extraction solvent and the number of extractions. The extraction efficiency was optimized using double extraction with an ethyl acetate/hexane/acetone mixture. Gas chromatography coupled with triple-quadrupole mass spectrometry was used for analysis, and two different ionization sources, electron impact ionization (EI) and atmospheric pressure chemical ionization (APCI), were used to compare their sensitivity. The APCI source employed soft ionization at atmospheric pressure, producing abundant molecular ion formation with minimal fragmentation, in contrast to extensive fragmentation caused by EI. Of the 85 POPs analyzed, 59 target compounds (69.4%) showed lower limits of detection that were two- to fifty-fold lower in APCI than those determined using EI. The developed method was validated for its detection limit (0.5-10 pg/mL for PCBs, 2-20 pg/mL for PBDEs, and 2-40 pg/mL for OCPs), precision (0.8%-34.3% of coefficient of variation), recovery (49.6%-77.1%), matrix effect (46.7%-156.9%), and accuracy (81.2%-113.1% for PCBs, 85.8%-112.2% for PBDEs, and 55.2%-113.9% for OCPs). Its linearity was R² > 0.99 for 84 compounds, and 96% average accuracy (for APCI) was obtained using the National Institute of Standards and Technology (NIST) standard reference materials (NIST 1957 and 1958). These ionization methods were compared by analyzing 25 real human serum samples. The observed species were 1.1-24.6 pg/mL of 28 PCBs, 2.5 pg/mL of BDE-47, and 6.5-195.1 pg/mL of 6 organochlorine pesticides (median concentration for each species), and only 11 compounds were detected with APCI owing to its enhanced sensitivity.

Development of an Atmospheric Pressure Chemical Ionization Interface for GC-MS

A closed atmospheric pressure chemical ionization (APCI) ion source as interface between a gas chromatograph (GC) and a triple quadrupole mass spectrometer (QqQ-MS) was developed. The influence of different ion source conditions, such as humidity, make-up gas flow, and the position of the GC column, were investigated and determined as main factors to increase sensitivity and repeatability of the system. For a performance test under real conditions, the new APCI ion source was used for the determination of plant protection products in commercially available coffee beans from Vietnam. The ionization behavior was investigated and the majority of the analytes were detected as [MH]+, [M]+∙, or as characteristic fragment ions, which have been assigned to ion source fragmentation. The developed GC-MS methods are based on tandem MS (MS/MS) and revealed for the plant protection products limits of detection (LOD) between 1 and 250 pg on column and relative standard derivations for all compounds < 16%. The used ultrasonic solid-liquid extraction yielded recovery rates of approximately 60 to 100%. Residues of herbicide methyl esters, organophosphorus compounds, and organonitrogen compounds have been detected in the analyzed coffee beans.