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Lu X, Zhang Z, Gao R, Wang H, Xiao J. Recent progress in the chemical attribution of chemical warfare agents and highly toxic organophosphorus pesticides. Forensic Toxicol 2021. [DOI: 10.1007/s11419-021-00578-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Höjer Holmgren K, Mörén L, Ahlinder L, Larsson A, Wiktelius D, Norlin R, Åstot C. Route Determination of Sulfur Mustard Using Nontargeted Chemical Attribution Signature Screening. Anal Chem 2021; 93:4850-4858. [PMID: 33709707 PMCID: PMC8041246 DOI: 10.1021/acs.analchem.0c04555] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
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Route determination
of sulfur mustard was accomplished through
comprehensive nontargeted screening of chemical attribution signatures.
Sulfur mustard samples prepared via 11 different synthetic routes
were analyzed using gas chromatography/high-resolution mass spectrometry.
A large number of compounds were detected, and multivariate data analysis
of the mass spectrometric results enabled the discovery of route-specific
signature profiles. The performance of two supervised machine learning
algorithms for retrospective synthetic route attribution, orthogonal
partial least squares discriminant analysis (OPLS-DA) and random forest
(RF), were compared using external test sets. Complete classification
accuracy was achieved for test set samples (2/2 and 9/9) by using
classification models to resolve the one-step routes starting from
ethylene and the thiodiglycol chlorination methods used in the two-step
routes. Retrospective determination of initial thiodiglycol synthesis
methods in sulfur mustard samples, following chlorination, was more
difficult. Nevertheless, the large number of markers detected using
the nontargeted methodology enabled correct assignment of 5/9 test
set samples using OPLS-DA and 8/9 using RF. RF was also used to construct
an 11-class model with a total classification accuracy of 10/11. The
developed methods were further evaluated by classifying sulfur mustard
spiked into soil and textile matrix samples. Due to matrix effects
and the low spiking level (0.05% w/w), route determination was more
challenging in these cases. Nevertheless, acceptable classification
performance was achieved during external test set validation: chlorination
methods were correctly classified for 12/18 and 11/15 in spiked soil
and textile samples, respectively.
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Affiliation(s)
- Karin Höjer Holmgren
- Department of CBRN Defence & Security, The Swedish Defence Research Agency (FOI), Cementvägen 20, Umeå SE-901 82, Sweden
| | - Lina Mörén
- Department of CBRN Defence & Security, The Swedish Defence Research Agency (FOI), Cementvägen 20, Umeå SE-901 82, Sweden
| | - Linnea Ahlinder
- Department of CBRN Defence & Security, The Swedish Defence Research Agency (FOI), Cementvägen 20, Umeå SE-901 82, Sweden
| | - Andreas Larsson
- Department of CBRN Defence & Security, The Swedish Defence Research Agency (FOI), Cementvägen 20, Umeå SE-901 82, Sweden
| | - Daniel Wiktelius
- Department of CBRN Defence & Security, The Swedish Defence Research Agency (FOI), Cementvägen 20, Umeå SE-901 82, Sweden
| | - Rikard Norlin
- Department of CBRN Defence & Security, The Swedish Defence Research Agency (FOI), Cementvägen 20, Umeå SE-901 82, Sweden
| | - Crister Åstot
- Department of CBRN Defence & Security, The Swedish Defence Research Agency (FOI), Cementvägen 20, Umeå SE-901 82, Sweden
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Holmgren KH, Valdez CA, Magnusson R, Vu AK, Lindberg S, Williams AM, Alcaraz A, Åstot C, Hok S, Norlin R. Part 1: Tracing Russian VX to its synthetic routes by multivariate statistics of chemical attribution signatures. Talanta 2018; 186:586-596. [PMID: 29784407 DOI: 10.1016/j.talanta.2018.02.104] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2017] [Revised: 02/07/2018] [Accepted: 02/26/2018] [Indexed: 11/25/2022]
Abstract
Chemical attribution signatures (CAS) associated with different synthetic routes used for the production of Russian VX (VR) were identified. The goal of the study was to retrospectively determine the production method employed for an unknown VR sample. Six different production methods were evaluated, carefully chosen to include established synthetic routes used in the past for large scale production of the agent, routes involving general phosphorus-sulfur chemistry pathways leading to the agent, and routes whose main characteristic is their innate simplicity in execution. Two laboratories worked in parallel and synthesized a total of 37 batches of VR via the six synthetic routes following predefined synthesis protocols. The chemical composition of impurities and byproducts in each route was analyzed by GC/MS-EI and 49 potential CAS were recognized as important markers in distinguishing these routes using Principal Component Analysis (PCA). The 49 potential CAS included expected species based on knowledge of reaction conditions and pathways but also several novel compounds that were fully identified and characterized by a combined analysis that included MS-CI, MS-EI and HR-MS. The CAS profiles of the calibration set were then analyzed using partial least squares discriminant analysis (PLS-DA) and a cross validated model was constructed. The model allowed the correct classification of an external test set without any misclassifications, demonstrating the utility of this methodology for attributing VR samples to a particular production method. This work is part one of a three-part series in this Forensic VSI issue of a Sweden-United States collaborative effort towards the understanding of the CAS of VR in diverse batches and matrices. This part focuses on the CAS in synthesized batches of crude VR and in the following two parts of the series the influence of food matrices on the CAS profiles are investigated.
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Affiliation(s)
- Karin Höjer Holmgren
- The Swedish Defence Research Agency, FOI CBRN Defence and Security, SE-901 82 Umeå, Sweden
| | - Carlos A Valdez
- Forensic Science Center, Lawrence Livermore National Laboratory, 7000 East Avenue L-091, Livermore, California 94550, United States
| | - Roger Magnusson
- The Swedish Defence Research Agency, FOI CBRN Defence and Security, SE-901 82 Umeå, Sweden
| | - Alexander K Vu
- Forensic Science Center, Lawrence Livermore National Laboratory, 7000 East Avenue L-091, Livermore, California 94550, United States
| | - Sandra Lindberg
- The Swedish Defence Research Agency, FOI CBRN Defence and Security, SE-901 82 Umeå, Sweden
| | - Audrey M Williams
- Forensic Science Center, Lawrence Livermore National Laboratory, 7000 East Avenue L-091, Livermore, California 94550, United States
| | - Armando Alcaraz
- Forensic Science Center, Lawrence Livermore National Laboratory, 7000 East Avenue L-091, Livermore, California 94550, United States
| | - Crister Åstot
- The Swedish Defence Research Agency, FOI CBRN Defence and Security, SE-901 82 Umeå, Sweden
| | - Saphon Hok
- Forensic Science Center, Lawrence Livermore National Laboratory, 7000 East Avenue L-091, Livermore, California 94550, United States.
| | - Rikard Norlin
- The Swedish Defence Research Agency, FOI CBRN Defence and Security, SE-901 82 Umeå, Sweden.
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Mirjankar NS, Fraga CG, Carman AJ, Moran JJ. Source Attribution of Cyanides Using Anionic Impurity Profiling, Stable Isotope Ratios, Trace Elemental Analysis and Chemometrics. Anal Chem 2016; 88:1827-34. [DOI: 10.1021/acs.analchem.5b04126] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Nikhil S. Mirjankar
- Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, Washington 99352, United States
| | - Carlos G. Fraga
- Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, Washington 99352, United States
| | - April J. Carman
- Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, Washington 99352, United States
| | - James J. Moran
- Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, Washington 99352, United States
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