Direct Analysis In Real Time-high Resolution Mass Spectrometry Research Articles

Utilizing Derivatizing Agents for the Differentiation of Cannabinoid Isomers in Complex Food, Beverage and Personal-care Product Matrices by Ambient Ionization Mass Spectrometry

Recent legalization and decriminalization of marijuana at the state level has not only contributed to a rise in the recreational use of Cannabis sativa, also known simply as Cannabis, but also to an increase in the range of matrices into which cannabinoids are infused. Traditional methods for analyzing these products, which are typically chromatography-based, are often matrix-dependent and demand time-consuming and resource-intensive sample preparation protocols that are highly nuanced and not readily applicable to multiple matrix types. Furthermore, the differentiation of cannabinoids can be troublesome without implementing lengthy run times to achieve resolution of chromatographic peaks. With complex samples such as edibles, beverages, personal-care products, and plant materials, a method that can be more universally applied to rapidly detect and differentiate between cannabinoids is highly desirable. In this study, foods and personal care products under the categories of sweets, spreads, condiments/toppings, beverages, oils, and commercial body products were spiked with cannabinoids including Δ9-tetrahydrocannabinol (THC), cannabidiol (CBD), cannabicitran (CBT), and cannabigerol (CBG). Chemical derivatization of the samples with N-methyl-N-(trimethylsilyl)trifluoroacetamide (MSTFA) followed by direct analysis in real time – high-resolution mass spectrometry (DART-HRMS) analysis readily revealed the presence of cannabinoids in the products despite the matrix complexity (i.e., the contributions from matrix-derived peaks did not interfere with the differentiation of cannabinoids). When analyzed under ambient soft ionization conditions, CBT, THC and CBD are indistinguishable because they are isomers with a molecular formula of C21H30O2 and a protonated monoisotopic mass of 315.2324. However, due to the different number of hydroxyl (-OH) groups (zero in CBT, one in THC, and two in CBD) that engage with the derivatizing agent, the cannabinoids are differentiated based on the mass disparities of the protonated adducts formed (m/z 315.2324, 387.2719 and 459.3119 for CBT, THC, and CBD, respectively), and which are readily revealed by DART-HRMS. This approach circumvents some of the challenges currently encountered by forensic laboratories in the analysis of highly complex and diverse cannabinoid-infused matrices. The results show proof-of-concept for an approach that can aid in the differentiation of cannabinoid isomers by DART-HRMS that accommodates high matrix diversity and complexity, and demonstrates the potential for the approach to be integrated into current workflows for the forensic analysis of Cannabis-related materials and evidence.

Investigating the capability of UA-DLLME and DART-HRMS in the analysis of benzodiazepines in whole human blood

Benzodiazepine (BZD) misuse has increased in the last decade, making its occurrence in criminal cases more commonplace. The detection of BZD in complex biological samples is challenging since they are usually found in small concentrations, requiring the development of sensitive and fast-to-execute methods. In this study, the application of direct analysis in real time – high-resolution mass spectrometry (DART-HRMS) was evaluated in the detection of 10 benzodiazepines (diazepam, oxazepam, chlordiazepoxide, temazepam, alprazolam, flunitrazepam, bromazepam, clonazepam, lorazepam, and midazolam) in ante and postmortem blood samples. Moreover, an ultrasound-assisted dispersive liquid–liquid microextraction (UA-DLLME) approach was developed by full factorial design as a clean-up step before the DART-HRMS analysis. DART-HRMS was capable of qualitative detection of all evaluated BZD in raw antemortem blood samples at concentrations as low as 10 µg mL−1. The UA-DLLME DART-HRMS approach was linear for the 10 BZD in the range of 1 to 10 µg mL−1, with recoveries ranging from 78.5 to 119.5 %, a precision lower than 36 % at 1 µg mL−1, and limits of detection varying between 0.25 and 0.50 µg mL−1. Moreover, the UA-DLLME DART-HRMS method was efficiently applied to postmortem blood samples from criminal cases, enabling the detection of BZD. The developed method facilitated the analysis of 10 BZD in ante and postmortem blood samples, offering a quick sample extraction that linked to the DART-HRMS can be used as a fast and reliable triage method for regulatory screening purposes and could be readily integrated into routine forensic analysis workflows in a high throughput manner.

Automatic MDSPE Combined with DART-HRMS for the Rapid Quantitation of 21 Synthetic Cathinones in Urine.

A new, rapid, and automated method for the quantitation of 21 synthetic cathinones in urine was established using magnetic dispersive solid-phase extraction (MDSPE) in combination with direct analysis in real time-high-resolution mass spectrometry (DART-HRMS). Sample preparation and quantitation were verified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Methcathinone-D3, α-PVP-D8, and proadifen (SKF525A) were used as internal standards. Magnetic HLB extractant and NaH2PO4/NaOH buffer (0.2 M, pH 7) were used in automatic MDSPE. All 21 synthetic cathinones could be detected and analyzed by DART-HRMS in under 1 min. It was proven that the linearities of 21 synthetic cathinones were suitable (R2 > 0.99) in the concentration ranges of 0.5-100 ng/mL or 1-100 ng/mL. The precision and accuracy values were all within ±15%, and the samples were stable under various conditions. The average time of each sample from preprocessing to completion of detection was approximately 2 min, allowing for rapid sample analysis. The relative error (RE) of the concentrations obtained by DART-HRMS and LC-MS/MS were within ±13.61%, and the linear coefficient (R) was 0.9964. The results of DART-HRMS and LC-MS/MS provided equivalent values at the 95% confidence level. In summary, a simple, fast, and convenient quantitation method via DART-HRMS was established. This application can be utilized to reduce backlogs and promote rapid case processing.

Analysis of feed additives by DART mass spectrometry: method optimisation and applications for product traceability in the European Union focusing on coccidiostats and carotenoids

In this study, direct analysis in real time high resolution mass spectrometry (DART-HRMS) was used to investigate the accurate characterisation of feed additive formulations containing coccidiostats or carotenoids. The study demonstrates the efficacy of DART-HRMS in identifying the active substances in these formulations and distinguishing between feed additives with the same active substance. The protocol for this method involves two simple steps that are extracting samples with organic solvents and measuring the extracts with DART-HRMS. The study also employs various statistical tools, including a factorial design approach, to optimise the DART-HRMS settings, and multivariate statistics, to establish classification models for feed additive formulations using nominal mass spectra. Our study demonstrates the potential of DART-HRMS in ensuring the correct identification of feed additives containing various coccidiostats or carotenoids and proposes this tool as an additional means for compliance checks with EU regulations.

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.

DART-HRMS allows the detection of toxic alkaloids in animal autopsy specimens and guides the selection of confirmatory methods in accidental plant poisoning

BackgroundIn cases of suspected animal poisonings or intoxications, there is the need for high-throughput, rapid and accurate analytical tools capable of giving rapid answers and, thus, speeding up the early stages of investigations. Conventional analyses are very precise, but do not meet the need for rapid answers capable of orienting the decisions and the choice of appropriate countermeasures. In this context, the use of ambient mass spectrometry (AMS) screening methods in toxicology laboratories could satisfy the requests of forensic toxicology veterinarians in a timely manner. ResultsAs a proof of principle, direct analysis in real time high resolution mass spectrometry (DART-HRMS) was applied to a veterinary forensic case in which 12 of a group of 27 sheep and goats died with an acute neurological onset. Because of evidence in the rumen contents, the veterinarians hypothesized an accidental intoxication after ingestion of vegetable materials.The DART-HRMS results showed abundant signals of the alkaloids calycanthine, folicanthidine and calycanthidine, both in the rumen content and at the liver level. The DART-HRMS phytochemical fingerprinting of detached Chimonanthus praecox seeds was also compared with those acquired from the autopsy specimens. Liver, rumen content and seed extracts were then subjected to LC-HRMS/MS analysis to gather additional insights and confirm the putative assignment of calycanthine anticipated by DART-HRMS.HPLC-HRMS/MS confirmed the presence of calycanthine in both rumen contents and liver specimens and allowed its quantification, ranging from 21.3 to 46.9 mg kg−1 in the latter. This is the first report detailing the quantification of calycanthine in liver after a deadly intoxication event. Significance and noveltyOur study illustrates the potential of DART-HRMS to offer a rapid and complementary alternative to guide the selection of confirmatory chromatography-MSn strategies in the analysis of autopsy specimens from animals with suspected alkaloid intoxication. This method offers the consequent saving of time and resources over those needed for other methods.

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

BackgroundHemp 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.MethodThe 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.ResultsWhen 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.DiscussionThe 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.

Introducing "DoPP": A Graphical User-Friendly Application for the Rapid Species Identification of Psychoactive Plant Materials and Quantification of Psychoactive Small Molecules Using DART-MS Data.

The widespread abuse of "legal high" psychoactive plants continues to be of global concern because of their negative impacts on public health and safety. In forensic science, a major challenge in controlling these substances is the paucity of methods to rapidly identify them. We report the development of the Database of Psychoactive Plants (DoPP), a new user-friendly tool featuring an architecture for the identification of plant unknowns, and the necessary regression statistics for the development and validation of psychoactive compound quantification. The application relies on the knowledge that terrestrial plants exhibit species-specific chemical signatures that can be revealed by direct analysis in real time─high-resolution mass spectrometry (DART-HRMS). Subsequent automated machine learning processing of libraries of these spectra enables rapid discrimination and species identification. The chemical signature database includes 57 available plant species. The rapid acquisition of mass spectra and the ability to sample the materials in their native form enabled the generation of the vast amounts of spectral replicates required for database construction. For the identification of sample unknowns, a data analysis workflow was developed and implemented using the DoPP tool. It utilizes a hierarchical classification tree that integrates three machine learning methods, namely, random forest, k-nearest neighbors, and support vector machine, all of which were fused using posterior probabilities. The results show accuracies of 98 and 99% for 10-fold cross-validation and external validation, respectively, which make the classification model suitable for identity prediction of real samples.

Optimized Solid-Phase Mesh-Enhanced Sorption from Headspace (SPMESH) for Rapid Sub-ng/kg Measurements of 3-Isobutyl-2-methoxypyrazine (IBMP) in Grapes.

Parallel extraction of headspace volatiles from multiwell plates using sorbent sheets (HS-SPMESH) followed by direct analysis in real-time high-resolution mass spectrometry (DART-HRMS) can be used as a rapid alternative to solid-phase micro-extraction (SPME) gas-chromatography mass-spectrometry (GC-MS) for trace level volatile analyses. However, an earlier validation study of SPMESH-DART-MS using 3-isobutyl-2-methoxypyrazine (IBMP) in grape juice showed poor correlation between SPMESH-DART-MS and a gold standard SPME-GC-MS around the compound’s odor detection threshold (<10 ng/kg) in grape juice, and lacked sufficient sensitivity to detect IBMP at this concentration in grape homogenate. In this work, we report on the development and validation of an improved SPMESH extraction approach that lowers the limit of detection (LOD < 0.5 ng/kg), and regulates crosstalk between wells (<0.5%) over a calibration range of 0.5–100 ng/kg. The optimized SPMESH-DART-MS method was validated using Cabernet Sauvignon and Merlot grape samples harvested from commercial vineyards in the central valley of California (n = 302) and achieved good correlation and agreement with SPME-GC-MS (R2 = 0.84) over the native range of IBMP (<0.5–20 ng/kg). Coupling of SPMESH to a lower resolution triple quadrupole (QqQ)-MS via a new JumpShot-HTS DART source also achieved low ng/kg detection limits, and throughput was improved through positioning stage optimizations which reduced time spent on intra-well SPMESH areas.

Rapid, novel screening of toxicants in poison baits, and autopsy specimens by ambient mass spectrometry.

Animal poisoning and dissemination of baits in the environment have public health and ethological implications, which can be followed by criminal sanctions for those responsible. The reference methods for the analysis of suspect baits and autopsy specimens are founded on chromatographic-based techniques. They are extremely robust and sensitive, but also very expensive and laborious. For this reason, we developed an ambient mass spectrometry (AMS) method able to screen for 40 toxicants including carbamates, organophosphate and chlorinated pesticides, coumarins, metaldehyde, and strychnine. Spiked samples were firstly purified and extracted by dispersive solid phase extraction (QuEChERS) and then analyzed by direct analysis in real time high-resolution mass spectrometry (DART-HRMS). To verify the performance of this new approach, 115 authentic baits (n = 59) and necropsy specimens (gastrointestinal content and liver, n = 56) were assessed by the official reference methods and combined QuEChERS-DART-HRMS. The agreement between the results allowed evaluation of the performances of the new screening method for a variety of analytes and calculation of the resultant statistical indicators (the new method had overall accuracy 89.57%, sensitivity of 88.24%, and a specificity of 91.49%). Taking into account only the baits, 96.61% of overall accuracy was achieved with 57/59 samples correctly identified (statistical sensitivity 97.50%, statistical specificity 94.74%). Successful identification of the bitter compound, denatonium benzoate, in all the samples that contained rodenticides (28/28) was also achieved. We believe initial screening of suspect poison baits could guide the choice of reference confirmatory methods, reduce the load in official laboratories, and help the early stages of investigations into cases of animal poisoning.

Authentication of Edible Insects' Powders by the Combination of DART-HRMS Signatures: The First Application of Ambient Mass Spectrometry to Screening of Novel Food.

This feasibility study reports the use of direct analysis in real-time high-resolution mass spectrometry (DART-HRMS) in profiling the powders from edible insects, as well as the potential for the identification of different insect species by classification modeling. The basis of this study is the revolution that has occurred in the field of analytical chemistry, with the improved capability of ambient mass spectrometry to authenticate food matrices. In this study, we applied DART-HRMS, coupled with mid-level data fusion and a learning method, to discriminate between Acheta domesticus (house cricket), Tenebrio molitor (yellow mealworm), Locusta migratoria (migratory locust), and Bombyx mori (silk moth). A distinct metabolic fingerprint was observed for each edible insect species, while the Bombyx mori fingerprint was characterized by highly abundant linolenic acid and quinic acid; palmitic and oleic acids are the statistically predominant fatty acids in black soldier fly (Hermetia illucens). Our chemometrics also revealed that the amino acid proline is a discriminant molecule in Tenebrio molitor, whereas palmitic and linoleic acids are the most informative molecular features of the house cricket (Acheta domesticus). Good separation between the four different insect species was achieved, and cross-validation gave 100% correct identification for all training samples. The performance of the random forest classifier was examined on a test set and produced excellent results, in terms of overall accuracy, sensitivity, and specificity. These results demonstrate the reliability of the DART-HRMS as a screening method in a future quality control scenario to detect complete substitution of insect powders.

Ambient mass spectrometry for rapid authentication of milk from Alpine or lowland forage.

Metabolomics approaches, such as direct analysis in real time-high resolution mass spectrometry (DART-HRMS), allow characterising many polar and non-polar compounds useful as authentication biomarkers of dairy chains. By using both a partial least squares discriminant analysis (PLS-DA) and a linear discriminant analysis (LDA), this study aimed to assess the capability of DART-HRMS, coupled with a low-level data fusion, discriminate among milk samples from lowland (silages vs. hay) and Alpine (grazing; APS) systems and identify the most informative biomarkers associated with the main dietary forage. As confirmed also by the LDA performed against the test set, DART-HRMS analysis provided an accurate discrimination of Alpine samples; meanwhile, there was a limited capacity to correctly recognise silage- vs. hay-milks. Supervised multivariate statistics followed by metabolomics hierarchical cluster analysis allowed extrapolating the most significant metabolites. Lowland milk was characterised by a pool of energetic compounds, ketoacid derivates, amines and organic acids. Seven informative DART-HRMS molecular features, mainly monoacylglycerols, could strongly explain the metabolomic variation of Alpine grazing milk and contributed to its classification. The misclassification between the two lowland groups confirmed that the intensive dairy systems would be characterised by a small variation in milk composition.

New strategies for the differentiation of fresh and frozen/thawed fish: A rapid and accurate non-targeted method by ambient mass spectrometry and data fusion (part A)

Ambient mass spectrometry (AMS) was applied for the first time to differentiate fresh and frozen/thawed Dicentrarchus labrax (European sea bass). One hundred and twenty samples were submitted to two extraction procedures and analyzed in positive and negative ion modes by direct analysis in real time-high resolution mass spectrometry (DART-HRMS). The four DART-HRMS datasets were concatenated with a low-level data fusion approach, and the resultant unique block of data was submitted to multivariate statistical analysis to tease out the most informative m/z values capable of codifying fresh and defrosted D. labrax . The statistical significance (p-value) and fold change (FC) of these informative signals were then evaluated with univariate analyses and tentatively assigned. The 25 features were then used to build a support vector machine (SVM) model capable of classifying D. labrax samples according to whether they were fresh or previously frozen. The SVM model has accuracy, sensitivity and specificity of 100%, both in training and test set. The SVM model was used to successfully classify an independent set of twenty fresh and frozen/thawed Salmo salar (Atlantic salmon). The concentrations of the most significant molecular features were quantified by gas-chromatography-mass spectrometry. • (+/−)DART-HRMS of polar and non-polar extracts of sea bass was performed. • The four DART-HRMS datasets were concatenated by low-level data fusion. • PLS-DA was performed on the training set to extrapolate the informative signals. • SVM classification model was constructed with the selected signals. • The built-in SVM model was validated with on hold-out subset with high accuracy.

Quantification of hordenine in a complex plant matrix by direct analysis in real time-high-resolution mass spectrometry: Application to the "plant of concern" Sceletium tortuosum.

Recently, there has been an increase in the recreational abuse of several psychoactive plants, resulting in the United Nations Office on Drugs and Crime creating a list of "plants of concern." One such material is Sceletium tortuosum and products derived from it. Regulation of these materials is challenging because of their innocuous appearance, the cumbersome sample preparation steps required to render the material into a form amenable to analysis by conventional techniques, the requirement for nuanced sample analysis protocols, and lengthy analysis times. It is demonstrated here that direct analysis in real time-high-resolution mass spectrometry (DART-HRMS) can be used to not only identify S.tortuosum material based on the detection of characteristic biomarkers including hordenine and several mesembrine alkaloids, but also quantify the amount of hordenine present. Using hordenine-d6 as an internal standard, a protocol, validated according to US Food and Drug Administration (FDA) Guidelines for the Development and Validation of Bioanalytical Methods, was devised for the quantification of the psychoactive component hordenine. The method was then applied to the quantification of hordenine in six commercially available products derived from the foliage and stems of S.tortuosum. By this method, the lower limit of quantification (LLOQ) was found to be 1μg/ml. Observed hordenine concentrations ranged from 0.02738 to 1.071 mg of hordenine per gram of plant material. The developed technique provides an effective and quick means for the detection and quantification of hordenine in S.tortuosum, which can be extended to analysis of other hordenine-containing products.

DART-HRMS as a triage approach for the rapid analysis of cannabinoid-infused edible matrices, personal-care products and Cannabis sativa hemp plant material

Forensic laboratories use traditional methods such LC-MS and GC–MS for determining if evidence is derived from Cannabis sativa or infused with cannabinoids. These approaches require sample pretreatment steps to render samples into a form suitable for analysis by these techniques, which can be time-consuming and resource-intensive, particularly for complex matrices such as edibles. Furthermore, there is no universal method for the analysis and quantification of cannabinoids in edibles, which is in part due to the ever-evolving range of products into which cannabinoids are infused. In this study, the ambient ionization technique direct analysis in real time – high-resolution mass spectrometry (DART-HRMS) was used for the rapid detection of cannabinoids in complex matrices. A variety of cannabinoid-infused samples were analyzed, including hemp (the non-psychoactive variety of C. sativa), commercial personal-care products, edible certified reference materials (CRMs), and edibles prepared in-house using cannabinoid analytical standards (i.e., THC and CBD). The absence or presence of cannabinoids within these samples, which are challenging to analyze by traditional methods, was determined within a matter of seconds by simply presenting bulk material to the DART gas stream for analysis. With no sample pretreatment or lengthy data processing, this approach provides a method that complements confirmatory testing for the rapid triage of complex plant materials, personal-care products, and edible matrices for cannabinoids prior to launching confirmatory tests, saving crime laboratories time and resources. This method accommodates a broad range of materials, and it is demonstrated that cannabinoids can be readily detected regardless of the matrix type.

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.

A longevity study to determine appropriate storage conditions for sexual lubricants using spectroscopic and spectrometric techniques

There has been an increase in the number of reported cases in which assailants have used a condom or sexual lubricant. Sexual predators understand that DNA from seminal fluid is one of the main forms of evidence used to connect a suspect to a victim or crime scene; therefore, the use of condoms in sexual assault cases has increased. This dilemma has led to research into other types of trace evidence (e.g., sexual lubricants). The study presented herein was performed to determine the optimal storage time length and conditions appropriate for storing trace lubricant residue. This research project used Fourier transform infrared spectroscopy (FTIR), direct analysis in real time-high resolution mass spectrometry (DART-HRMS), and gas chromatography-mass spectrometry (GC-MS) techniques to analyze the stored swabs containing sexual lubricants at 8 timepoints over 18 months. Blank, personal lubricant, and condom swabs were stored under several environmental conditions. Swab storage allowed for the determination of whether lubricants degraded, thus adversely affecting the ability to recognize the classification patterns. Resulting spectra from each instrument can be used to identify environmental degradation of lubricant samples and generate investigative leads. Pearson Correlation Coefficients and time plots of the chemical components were used to determine if chemical breakdown occurred for each lubricant and if the pattern changed significantly. Results showed that the strongest correlations occur between the initial timepoint (T 0) and one month (T1m), with correlations decreasing consistently up to eighteen months (T18m). The best storage conditions were determined to be 22 °C at both 16% and 50% humidity. The ability to understand the effects of environment and time to the analysis of sexual lubricants may offer helpful information when analyzing sexual assault kits.

Oregano authentication by mid-level data fusion of chemical fingerprint signatures acquired by ambient mass spectrometry

Economically motivated adulteration (EMA) of herbs and spices is very frequent and a major cause of concern to consumers, manufacturers and legislators. Rapid, non-targeted methods capable of distinguishing authentic herbs from those mixed with low cost materials are desirable. To this aim, ambient mass spectrometry (AMS) was applied to authenticate dried oregano leaves. Authentic and adulterated oregano samples were submitted to two extraction procedures and analysed in positive and negative ion modes by direct analysis in real time-high resolution mass spectrometry (DART-HRMS). Mid-level data fusion of the four blocks of DART-HRMS data was performed, and the resultant unique dataset was submitted to supervised statistical analysis to ascertain the signals that discriminate authentic from adulterated oregano. The fourteen most informative signals of authenticity were tentatively assigned and validated by support vector machine (SVM). In the final model, accuracy, sensitivity and specificity of >90% were obtained. Independent authentic and adulterated oregano samples were used to validate the discriminative m/z values and evaluate the classification capability of the model. To the best of our knowledge this is the first application of AMS coupled to mid-level data fusion for oregano authentication.

Detection and Quantification of Psychoactive N,N-Dimethyltryptamine in Ayahuasca Brews by Ambient Ionization High-Resolution Mass Spectrometry.

The United Nations Office on Drugs and Crime designated twenty psychoactive botanical species as “plants of concern” because of their increased recreational abuse. Four of these are used to prepare ayahuasca brews. The complexity of the plant matrices, as well as the beverage itself, make the identification and quantification of the Schedule I component, N,N-dimethyltryptamine (DMT), a time-consuming and resource-intensive endeavor when performed using conventional approaches previously reported. Reported here is the development of a rapid validated method for the quantification of DMT in ayahuasca by direct analysis in real time-high-resolution mass spectrometry (DART-HRMS). This ambient ionization approach also enables identification of ayahuasca through detection of the secondary metabolites associated with its plant constituents. Analysis of six ayahuasca brews created using different combinations of DMT/harmala alkaloid-containing plants resulted in beverages with DMT levels of 45.7–230.5 mg/L. The detected amounts were consistent with previously reported values determined by conventional approaches.