Random Forest Processing of Direct Analysis in Real-Time Mass Spectrometric Data Enables Species Identification of Psychoactive Plants from Their Headspace Chemical Signatures

Mass Spectrometric Interrogation of Earwax: Toward the Detection of Ménière's Disease

Many diseases remain difficult to identify because the occurrence of characteristic biomarkers within traditional matrices such as blood and urine remain unknown. Disease diagnosis could, therefore, benefit from the analysis of readily accessible, non-traditional matrices that have a high chemical content and contain distinguishing biomarkers. One such matrix is cerumen (i.e., earwax), whose chemical complexity can pose challenges when analyzed by conventional methods. A combination of cerumen chemical profiles analyzed by gas chromatography-mass spectrometry (GC-MS) and direct analysis in real time-high-resolution mass spectrometry (DART-HRMS) were investigated to ascertain the possible presence of the rare otolaryngological disorder Ménière's disease. This illness is currently identified via "diagnosis by exclusion" in which the disease is distinguished from others with overlapping symptoms by the process of elimination. GC-MS revealed a chemical profile difference between those with and without a Ménière's disease diagnosis by a visually apparent diminution of the compounds present in the Ménière's disease samples. DART-HRMS revealed that the two classes could be differentiated using three fatty acids: cis-9-hexadecenoic acid, cis-10-heptadecenoic acid, and cis-9-octadecenoic acid. These compounds were subsequently quantified by GC-MS and overall, the amounts of these fatty acids were decreased in Ménière's disease patients. The average levels for non-Ménière's disease samples were 7.89 μg/mg for cis-9-hexadecenoic acid, 0.87 μg/mg for cis-10-heptadecenoic acid, and 4.94 μg/mg for cis-9-octadecenoic acid. The average levels for Ménière's disease samples were 1.70 μg/mg for cis-9-hexadecenoic acid, 0.13 μg/mg for cis-10-heptadecenoic acid, and 2.07 μg/mg for cis-9-octadecenoic acid. The confidence levels for cis-9-hexadecenoic acid, cis-10-heptadecenoic acid, and cis-9-octadecenoic acid were 98.7%, 99.9%, and 95.4%, respectively. The results suggest that assessment of the concentrations of these fatty acids could be a useful clinical tool for the more rapid and accurate detection of Ménière's disease.

Combined ambient ionization mass spectrometric and chemometric approach for the differentiation of hemp and marijuana varieties of Cannabis sativa

BACKGROUND

Hemp and marijuana are the two major varieties of Cannabis sativa. While both contain Δ⁹-tetrahydrocannabinol (THC), the primary psychoactive component of C. sativa, they differ in the amount of THC that they contain. Presently, U.S. federal laws stipulate that C. sativa containing greater than 0.3% THC is classified as marijuana, while plant material that contains less than or equal to 0.3% THC is hemp. Current methods to determine THC content are chromatography-based, which requires extensive sample preparation to render the materials into extracts suitable for sample injection, for complete separation and differentiation of THC from all other analytes present. This can create problems for forensic laboratories due to the increased workload associated with the need to analyze and quantify THC in all C. sativa materials.

METHOD

The work presented herein combines direct analysis in real time-high-resolution mass spectrometry (DART-HRMS) and advanced chemometrics to differentiate hemp and marijuana plant materials. Samples were obtained from several sources (e.g., commercial vendors, DEA-registered suppliers, and the recreational Cannabis market). DART-HRMS enabled the interrogation of plant materials with no sample pretreatment. Advanced multivariate data analysis approaches, including random forest and principal component analysis (PCA), were used to optimally differentiate these two varieties with a high level of accuracy.

RESULTS

When PCA was applied to the hemp and marijuana data, distinct clustering that enabled their differentiation was observed. Furthermore, within the marijuana class, subclusters between recreational and DEA-supplied marijuana samples were observed. A separate investigation using the silhouette width index to determine the optimal number of clusters for the marijuana and hemp data revealed this number to be two. Internal validation of the model using random forest demonstrated an accuracy of 98%, while external validation samples were classified with 100% accuracy.

DISCUSSION

The results show that the developed approach would significantly aid in the analysis and differentiation of C. sativa plant materials prior to launching painstaking confirmatory testing using chromatography. However, to maintain and/or enhance the accuracy of the prediction model and keep it from becoming outdated, it will be necessary to continue to expand it to include mass spectral data representative of emerging hemp and marijuana strains/cultivars.

Rapid Detection and Quantification of Hallucinogenic Salvinorin A in Commercial Salvia divinorum Products by DART-HRMS

In recent years, national laboratories have identified several plant-derived materials as concerns to public health because of their psychoactive effects, potential for abuse, and the lack of federal regulation of their use. One of these is Salvia divinorum (aka Salvia), which has received focused attention due to its increasing recreational use and the ease by which it can be acquired. Traditional chromatographic approaches for the detection of the major psychoactive component of Salvia (i.e., salvinorin A) typically require time-consuming sample pretreatment prior to identifying the presence of salvinorin A in plant material unknowns. In this study, direct analysis in real time-high-resolution mass spectrometry (DART-HRMS) was used to rapidly screen for Salvia plant material. This approach facilitated the analysis of bulk material in its native form, thereby bypassing sample pretreatment steps. In addition, a validated DART-HRMS method was developed for the quantification of salvinorin A in commercial Salvia products (e.g., raw plant materials, enhanced leaf extracts). In this regard, cholesterol was found to be a suitable internal standard. The average salvinorin A content in raw Salvia leaves was determined to be 1.54 mg/g, while the salvinorin A quantified in enhanced Salvia leaf extracts was between 13.0 and 53.2 mg/g.

Plasma-based ambient mass spectrometry: Recent progress and applications

Ambient mass spectrometry (AMS) has grown as a group of advanced analytical techniques that allow for the direct sampling and ionization of the analytes in different statuses from their native environment without or with minimum sample pretreatments. As a significant category of AMS, plasma-based AMS has gained a lot of attention due to its features that allow rapid, real-time, high-throughput, in vivo, and in situ analysis in various fields, including bioanalysis, pharmaceuticals, forensics, food safety, and mass spectrometry imaging. Tens of new methods have been developed since the introduction of the first plasma-based AMS technique direct analysis in real-time. This review first provides a comprehensive overview of the established plasma-based AMS techniques from their ion source configurations, mechanisms, and developments. Then, the progress of the representative applications in various scientific fields in the past 4 years (January 2017 to January 2021) has been summarized. Finally, we discuss the current challenges and propose the future directions of plasma-based AMS from our perspective.

Application of direct analysis in real-time mass spectrometry (DART-MS) in forensic science: a comprehensive review

Background

As the rate of crime is constantly increasing, the workload on the forensic analyst also piles up. The availability of a limited number of seized samples makes it crucial to directly analyze the sample, thereby preventing wastage in the prior steps of sample preparation. Due to such needs, the forensic community is consistently working on broadening the usage of direct analysis in real-time mass spectrometry (DART-MS). DART-MS is a relatively new technique for rapid mass spectral analysis. Its use for chemical analysis credits its ability to analyze the sample at atmospheric pressure.

Main body

This article gives insight into the ionization mechanisms, data analysis tools, and the use of hyphenated techniques like thermal-desorption-DART-MS, infrared-thermal-desorption-DART-MS, Joule-heating thermal-desorption-DART-MS, etc. This review summarizes the applications of DART-MS in the field of Forensic Science reported from 2005 to 2021. The applications include analysis of drugs, warfare agents, gun-shot residues, ink differentiation, and other forensically relevant samples. The paper also presents the relation between the type of DART-MS technique and the ionization mode used for a particular class of compounds.

Conclusion

The review follows that the high-resolution mass-spectrometers or low-resolution mass-spectrometers systems in the positive or negative mode were highly dependent on the type of analyte under investigation. Drugs, inks, dyes, and paints were mainly analyzed using the positive ionization mode in the HRMS technique. The examinations of fire accelerants predominantly used the positive ionization mode in the LRMS technique. Moreover, the limit of detection values obtained from the qualitative screening of street drugs were of ppb level, indicating high sensitivity of DART-MS. Considering the work done in the past years, there are potential future research needs of this technology, especially in forensic science.

Graphical Abstract

Oh D. Determination of Methanol in Commercialized Alcohol-based Hand Sanitizing and Other Similar Products using Headspace GC-MS

Background:

Demand for alcohol-based products, including gel- and aqueous-type hand sanitizers, room sprays, and mouthwashes, has sharply increased during the ongoing COVID-19 pandemic because of their microbicidal properties. However, toxic methanol can be found from intentional addition of methanol by manufacturers and invariable production during the manufacture alcohol (ethanol). Although the FDA has recommended that such products should contain less than 630 ppm of methanol, it is only a temporary measure established specifically to regulate such products during the current COVID-19 pandemic and hence is not strictly regulated.

Objective:

This study aims to detect and quantify the level of methanol in alcohol-based products. However, some manufacturers unethically add methanol in their products and promote them as methanol-free. Besides, they do not provide proficiency and toxicity test results. Therefore, these kinds of products need to be analyzed to determine if they are acceptable to use.

Method:

This study qualitatively and quantitatively investigates the amount of methanol in commercial alcohol-based products using a newly developed headspace gas chromatography/mass spectrometry method. Moreover, alcohol beverages which contain methanol were analyzed to be compared with the levels of methanol in alcohol-based products and determine if their methanol levels are acceptable.

Results:

Methanol concentrations in gel-type hand sanitizers (517 ppm) and mouthwashes (202 ppm) were similar to those in white wine (429 ppm) and beer (256 ppm), respectively, while that of aqueous-type hand sanitizers (1139 ppm) is 1.5 times more than that of red wine (751 ppm).

Conclusion:

Methanol levels in most of the alcohol-based products did not exceed the FDA-recommended limit.

Coral Genus Differentiation Based on Direct Analysis in Real Time-High Resolution Mass Spectrometry-Derived Chemical Fingerprints

Coral reefs are one of the most biologically diverse ecosystems, and the accurate identification of the species is essential for diversity assessment and conservation. Current genus determination approaches are time-consuming and resource-intensive and can be highly subjective. To explore the hypothesis that the small-molecule profiles of coral are genus-specific and can be used as a rapid tool to catalogue and distinguish between coral genera, the small-molecule chemical fingerprints of the species Acanthastrea echinata, Catalaphyllia jardinei, Duncanopsammia axifuga, Echinopora lamellosa, Euphyllia divisa, Euphyllia paraancora, Euphyllia paradivisa, Galaxea fascicularis, Herpolitha limax, Montipora confusa, Monitpora digitata, Montipora setosa, Pachyseris rugosa, Pavona cactus, Plerogyra sinuosa, Pocillopora acuta, Seriatopora hystrix, Sinularia dura, Turbinaria peltata, Turbinaria reniformis, Xenia elongata, and Xenia umbellata were generated using direct analysis in real time-high resolution mass spectrometry (DART-HRMS). It is demonstrated here that the mass spectrum-derived small-molecule profiles for coral of different genera are distinct. Multivariate statistical analysis processing of the DART-HRMS data enabled rapid genus-level differentiation based on the chemical composition of the coral. Coral samples were analyzed with no sample preparation required, making the approach rapid and efficient. The resulting spectra were subjected to kernel discriminant analysis (KDA), which furnished accurate genus differentiation of the coral. Leave-one-out cross-validation (LOOCV) was carried out to determine the classification accuracy of each model and confirm that this approach can be used for coral genus attribution with prediction accuracies ranging from 86.67 to 97.33%. The advantages and application of the statistical analysis to DART-HRMS-derived coral chemical signatures for genus-level differentiation are discussed.

Forensic applications of DART-MS: A review of recent literature

The need for rapid chemical analyses and new analytical tools in forensic laboratories continues to grow due to case backlogs, difficult-to-analyze cases, and identification of previously unseen materials such as new psychoactive substances. To adapt to these needs, the forensics community has been pursuing the use of ambient ionization mass spectrometry, and more specifically direct analysis in real time mass spectrometry (DART-MS), for a wide range of applications. From the inception of DART-MS forensic applications have been researched with demonstrations ranging from drugs of abuse to inorganic gunshot residue to printer inks to insect identification. This article presents a review of research demonstrating the use of DART-MS for forensically relevant samples over the past five years. To provide more context, background on the technique, sampling approaches, and data analysis methods are presented along with a discussion on the potential future and research needs of the technology.

Pharmacokinetics and Pharmacodynamics of Salvinorin A and Salvia divinorum: Clinical and Forensic Aspects

Salvia divinorum Epling and Játiva is a perennial mint from the Lamiaceae family, endemic to Mexico, predominantly from the state of Oaxaca. Due to its psychoactive properties, S. divinorum had been used for centuries by Mazatecans for divinatory, religious, and medicinal purposes. In recent years, its use for recreational purposes, especially among adolescents and young adults, has progressively increased. The main bioactive compound underlying the hallucinogenic effects, salvinorin A, is a non-nitrogenous diterpenoid with high affinity and selectivity for the κ-opioid receptor. The aim of this work is to comprehensively review and discuss the toxicokinetics and toxicodynamics of S. divinorum and salvinorin A, highlighting their psychological, physiological, and toxic effects. Potential therapeutic applications and forensic aspects are also covered in this review. The leaves of S. divinorum can be chewed, drunk as an infusion, smoked, or vaporised. Absorption of salvinorin A occurs through the oral mucosa or the respiratory tract, being rapidly broken down in the gastrointestinal system to its major inactive metabolite, salvinorin B, when swallowed. Salvinorin A is rapidly distributed, with accumulation in the brain, and quickly eliminated. Its pharmacokinetic parameters parallel well with the short-lived psychoactive and physiological effects. No reports on toxicity or serious adverse outcomes were found. A variety of therapeutic applications have been proposed for S. divinorum which includes the treatment of chronic pain, gastrointestinal and mood disorders, neurological diseases, and treatment of drug dependence. Notwithstanding, there is still limited knowledge regarding the pharmacology and toxicology features of S. divinorum and salvinorin A, and this is needed due to its widespread use. Additionally, the clinical acceptance of salvinorin A has been hampered, especially due to the psychotropic side effects and misuse, turning the scientific community to the development of analogues with better pharmacological profiles.

Detection of trace drugs of abuse in baby formula using solid-phase microextraction direct analysis in real-time mass spectrometry (SPME-DART-MS)

The intentional or unintentional adulteration of baby formula with drugs of abuse is one of the many increasingly complex samples forensic chemists may have to analyze. This sample type presents a challenge because of a complex matrix that can mask the detection of trace drug residues. To enable screening of baby formula for trace levels of drugs, the use of solid-phase microextraction (SPME) coupled with direct analysis in real-time mass spectrometry (DART-MS) was investigated. A suite of five drugs was used as adulterants and spiked into baby formula. Samples were then extracted using SPME fibers which were analyzed by DART-MS. Development of a proof-of-concept method was completed by investigating the effects of the DART gas stream temperature and the linear speed of the sample holder. Optimal values of 350°C and 0.2 mm/s were found. Once the method was established, representative responses and sensitivities for the five drugs were measured and found to be in the range of single ng/mL to hundreds ng/mL. Additional studies found that the presence of the baby formula matrix increased analyte signal (relative to methanolic solutions) by greater than 200%. Comparison of the SPME-DART-MS method to a traditional DART-MS method for trace drug detection found at least a factor of 13 improvement in signal for the drugs investigated. This work demonstrates that SPME-DART-MS is a viable technique for the screening of complex matrices, such as baby formula, for trace drug residues and that development of a comprehensive method is warranted.

Research on target feature extraction and location positioning with machine learning algorithm

The accurate positioning of target is an important link in robot technology. Based on machine learning algorithm, this study firstly analyzed the location positioning principle of binocular vision of robot, then extracted features of the target using speeded-up robust features (SURF) method, positioned the location using Back Propagation Neural Networks (BPNN) method, and tested the method through experiments. The experimental results showed that the feature extraction of SURF method was fast, about 0.2 s, and was less affected by noise. It was found from the positioning results that the output position of the BPNN method was basically consistent with the actual position, and errors in X, Y and Z directions were very small, which could meet the positioning needs of the robot. The experimental results verify the effectiveness of machine learning method and provide some theoretical support for its further promotion and application in practice.