Detection and confirmation of fentanyls in high clay-content soil by electron ionization gas chromatography-mass spectrometry

Detection of illicit drugs in the environment, particularly in soils, often suggests the present or past location of a clandestine production center for these substances. Thus, development of efficient methods for the analysis and detection of these chemicals is of paramount importance in the field of chemical forensics. In this work, a method involving the extraction and retrospective confirmation of fentanyl, acetylfentanyl, thiofentanyl, and acetylthiofentanyl using trichloroethoxycarbonylation chemistry in a high clay-content soil is presented. The soil was spiked separately with each fentanyl at two concentrations (1 and 10 μg/g) and their extraction accomplished using ethyl acetate and aqueous NH₄OH (pH ~ 11.4) with extraction recoveries ranging from ~56% to 82% for the high-concentration (10 μg/g) samples while ranging from ~68% to 83% for the low-concentration (1 μg/g) samples. After their extraction, residues containing each fentanyl were reacted with 2,2,2-trichloroethoxycarbonyl chloride (Troc-Cl) to generate two unique and predictable products from each opioid that can be used to retrospectively confirm their presence and identity using EI-GC-MS. The method's limit of detection (MDL/LOD) for Troc-norfentanyl and Troc-noracetylfentanyl were estimated to be 29.4 and 31.8 ng/mL in the organic extracts. In addition, the method's limit of quantitation for Troc-norfentanyl and Troc-noracetylfentanyl were determined to be 88.2 and 95.5 ng/mL, respectively. Collectively, the results presented herein strengthen the use of chloroformate chemistry as an additional chemical tool to confirm the presence of these highly toxic and lethal substances in the environment.     

Changes in methamphetamine impurity profiles induced by tert-butoxycarbonylation

Analysis of impurities in methamphetamine (MA) can be used to characterize MA seizures, investigate the relationship among MA seizures, and provide information on their synthetic routes. Recently, chemically derivatized MA, such as tert-butoxycarbonyl (t-Boc) MA, has been seized and attracted attention because routine forensic analysis methods may fail to correctly identify them. Chemical derivatization is a simple method for protection and deprotection of a compound, and protection of MA using t-Boc can be used to mask the MA. Although t-Boc derivatization might alter the impurity profile of MA, the actual changes in the impurity profile have not been investigated. In this study, changes in the MA impurity profile with tert-butoxycarbonylation were explored. MA and some typical impurities were derivatized using di-tert-butyl dicarbonate and water. Analysis of the impurities in five MA samples by gas chromatography showed that peaks both appeared and disappeared for the deprotected MA compared with the original MA. However, typical impurities important for characterizing MA seizures were conserved after derivatization and deprotection. Most of the new peaks were speculated to be contaminants introduced during derivatization and deprotection. A peak giving a mass spectrum similar to that of t-Boc MA was detected in the chromatograms of t-Boc MA and deprotected MA. Although the origin of this peak was not determined, it might be a marker for the MA involving tert-butoxycarbonylation. These results indicate that tert-butoxycarbonylation can alter the MA impurity profile; therefore, care is needed when interpreting results for derivatized MA.     

Relevance analysis using revision identifier in MS word

Electronic documents often contain personal or confidential information, which can be used as valuable evidence in criminal investigations. In the digital investigation, special techniques are required for grouping and screening electronic documents, because it is challenging to analyze relationships between numerous documents in storage devices manually. To this end, although techniques such as keyword search, similarity search, topic modeling, metadata analysis, and document clustering are continually being studied, there are still limitations for revealing the relevance of documents. Specifically, metadata used in previous research are not always values present in the documents, and clustering methods with specific keywords may be incomplete because text‐based contents (including metadata) can be easily modified or deleted by users. In this work, we propose a novel method to efficiently group Microsoft Office Word 2007+ (MS Word) files by using revision identifier (RSID). Through a thorough understanding of the RSID, examiners can predict organizations to which a specific user belongs, and further, it is likely to discover unexpected interpersonal relationships. An experiment with a public dataset (GovDocs) provides that it is possible to categorize documents more effectively by combining our proposal with previously studied methods. Furthermore, we introduce a new document tracking method to understand the editing history and movement of a file, and then demonstrate its usefulness through an experiment with documents from a real case.     

A forensic examination of four popular cross‐platform file‐sharing apps with Wi‐Fi P2P

File‐sharing apps with Wi‐Fi hotspot or Wi‐Fi Direct functions become more popular. They can work on multiple platforms and allow users to transfer files in a concealed manner. However, when criminals use these apps in illegal activities, it becomes an important issue for investigators to find digital evidence on multiple platforms. At present, there are few studies on this topic, and most of them are limited to the single platform problem. In this paper, we propose a forensic examination method for four popular cross‐platform file‐sharing apps with Wi‐Fi hotspot and Wi‐Fi Direct functions: Zapya, SHAREit, Xender, and Feem. We use 22 static and live forensic tools for 11 platforms to acquire, analyze, and classify the forensic artifacts. In our experiments, we find many useful forensic artifacts and classify them into six categories. The experimental results can support law enforcement investigations of digital evidence and provide information for future studies on other cross‐platform file‐sharing apps.     

Validation of the 4‐aminophenol color test for the differentiation of marijuana‐type and hemp‐type cannabis

The analysis of cannabis plant material submitted to seized‐drug laboratories was significantly affected by the signing of the Agricultural Improvement Act of 2018, which defined hemp and removed it from the definition of marijuana in the Controlled Substances Act. As a result, field law enforcement personnel and forensic laboratories now are in need of implementing new protocols that can distinguish between marijuana‐type and hemp‐type cannabis. Colorimetric tests provide a cost‐effective and efficient manner to presumptively identify materials prior to submission to a laboratory for analysis. This work presents the validation of the 4‐aminophenol (4‐AP) color test and demonstrates its utility for discriminating between marijuana‐type and hemp‐type cannabis (i.e., typification). Validation studies included the testing of numerous cannabinoid reference materials, household herbs, previously characterized cannabis plant samples, and real‐case samples. The 4‐AP test reliably produces a pink result when the level of Δ⁹‐tetrahydrocannabinol (THC) is approximately three times lower than the level of cannabidiol (CBD). A blue result is generated when the level of THC is approximately three times higher than that of CBD. Inconclusive results are observed when the levels of THC and CBD are within a factor of three from each other, demonstrating the limitations of the test under those scenarios.     

Understanding research methods,limitations, and applications of drug data collected by the National Forensic Laboratory Information System (NFLIS-Drug)

The National Forensic Laboratory Information System (NFLIS) is a drug surveillance program of the US Drug Enforcement Administration that systematically collects data on drugs that are seized by law enforcement and submitted to and analyzed by the Nation's forensic laboratories (NFLIS-Drug). NFLIS-Drug data are increasingly used in predictive modeling and drug surveillance to examine drug availability patterns. Given the complexity of the data and data collection, there are some common methodological pitfalls that we highlight with the aim of helping researchers avoid these concerns. The analysis done for this Technical Note is based on a review of the scientific literature that includes 428 unique, refereed article citations in 182 distinct journals published between January 1, 2005, and April 30, 2021. Each article was analyzed according to how NFLIS-Drug data were mentioned and whether NFLIS-Drug data were included. A sample of 37 articles was studied in-depth, and data issues were summarized. Using examples from the literature, this Technical Note highlights eight broad concerns that have important implications for the proper applications, interpretations, and limitations of NFLIS-Drug data with suggestions for improving research methods and accurate reporting of forensic drug data. NFLIS-Drug data are timely and provide key information to inform drug use trends across the United States; however, our present analysis shows that NFLIS-Drug data are misunderstood and represented in the literature. In addition to highlighting these issues, DEA has created several resources to assist NFLIS data users and researchers, which are summarized in the discussion.     

Racial and ethnic differences in the risk factors associated with bully victimization

Bullying victimization has been recognized as a social issue facing a large proportion of America’s children and adolescents. Although important contributions to the knowledge base have been made regarding risk factors for bullying, little is known about whether a relationship between the potential victim’s race/ethnicity and their likelihood of bully victimization exists. Further, whether the factors that place persons at risk for bullying victimization are invariant across groups is unknown. The present study attempts to fill these voids in the literature by using a national sample and incorporating a more comprehensive list of predictors compared to what has been used in previous studies. Results indicate that risk factors for bullying are largely invariant across race and ethnicity.     

The discovery of acquaintance rape: the salience of methodological innovation and rigor

Over the past 20 years, research has uncovered the many types of sexual victimizations women experience. Findings regarding the victim-offender relationship in such incidents have undoubtedly been among the most striking. Particularly salient is the revelation that the sexual abuse of and violence against women-including rape-most often are perpetrated not by a stranger but by someone known to the victim. Without the innovation and implementation of victimization surveys with behaviorally specific questions, this knowledge may have remained unknown. Instead, armed with such knowledge, prevention and education efforts can be fashioned to address sexual victimizations committed by someone known to the victim. In this article, we address these issues related to key developments in sexual victimization research.