The Ability of Narcotic Detection Canines to Detect Illegal Synthetic Cathinones (Bath Salts)

Twelve certified narcotic detection canines were tested for their ability to detect confiscated illegal synthetic cathinones (bath salts). These canine teams were randomly assigned to two different groups and each group imprinted on one of two types of bath salts, ethylone and alpha-pyrrolidinovalerophenone (α-PVP), over the period of 1 month; while simultaneously documenting the imprinting procedure. The newly imprinted canines were validated by field testing and found to not only detect the imprinted bath salt to which they were trained, but they were able to detect other bath salts. The imprinting procedure and results are the first scientifically validated studies on the ability of canines to detect these harmful and illegal substances. Analytical headspace analysis using Solid Phase Microextraction (SPME) on several ethylone and α-PVP samples revealed compounds common in both. These compounds can be used to create a safe and reliable synthetic cathinone mimic training aid for canine teams

Vampires in the village Žrnovo on the island of Korčula: following an archival document from the 18th century

Središnja tema rada usmjerena je na raščlambu spisa pohranjenog u Državnom arhivu u Mlecima (fond: Capi del Consiglio de’ Dieci: Lettere di Rettori e di altre cariche) koji se odnosi na događaj iz 1748. godine u korčulanskom selu Žrnovo, kada su mještani – vjerujući da su se pojavili vampiri – oskvrnuli nekoliko mjesnih grobova. U radu se podrobno iznose osnovni podaci iz spisa te rečeni događaj analizira u širem društvenom kontekstu i prate se lokalna vjerovanja.The main interest of this essay is the analysis of the document from the State Archive in Venice (file: Capi del Consiglio de’ Dieci: Lettere di Rettori e di altre cariche) which is connected with the episode from 1748 when the inhabitants of the village Žrnove on the island of Korčula in Croatia opened tombs on the local cemetery in the fear of the vampires treating. This essay try to show some social circumstances connected with this event as well as a local vernacular tradition concerning superstitions

The utilization of chiral ion mobility spectrometry for the detection of enantiomeric mixtures and thermally labile compounds

This dissertation utilized electrospray ion mobility mass spectrometry (ESI-IMS-MS) to develop methods necessary for the separation of chiral compounds of forensic interest. The compounds separated included ephedrines and pseudoephedrines, that occur as impurities in confiscated amphetamine type substances (ATS) in an effort to determine the origin of these substances. The ESI-IMS-MS technique proved to be faster and more cost effective than traditional chromatographic methods currently used to conduct chiral separations such as gas and liquid chromatography. Both mass spectrometric and computational analysis revealed the separation mechanism of these chiral interactions allowing for further development to separate other chiral compounds by IMS. Successful separation of chiral compounds was achieved utilizing a variety of modifiers injected into the IMS drift tube. It was found that the modifiers themselves did not need to be chiral in nature and that achiral modifiers were sufficient in performing the required separations. The ESI-IMS-MS technique was also used to detect thermally labile compounds which are commonly found in explosive substances. The methods developed provided mass spectrometric identification of the type of ionic species being detected from explosive analytes as well as the appropriate solvent that enhances detection of these analytes in either the negative or positive ion mode. An application of the developed technique was applied to the analysis of a variety of low explosive smokeless powder samples. It was found that the developed ESI-IMS-MS technique not only detected the components of the smokeless powders, but also provided data that allowed the classification of the analyzed smokeless powders by manufacturer or make

Measuring Odor Transport of Narcotic Substances Using DART-MS

The employment of canines in matters of law enforcement is due to their heightened olfactory senses, which helps in evaluating the presence of illicit substances. However, there have been instances where canines are signaling the presence of narcotics when they are not there. This study aimed to analyze how active odorants transport from one area to another. Direct Analysis in Real-Time coupled to a high-resolution mass spectrometer (DART-MS) was used to analyze, in real-time, the volatile organic compounds (VOCs) of two narcotic substances: cocaine and methamphetamine. This study found that the transfer of VOCs from these narcotics does occur. Methyl benzoate was detected at 39.3 ± 3.2 s after exposure from 3 meters away, whereas benzaldehyde was detected at 43.3 ± 0.6 s from the same distance. The guidelines used for canine certification should be revisited to account for these results to lower or eliminate unconfirmed alerts by canines

Method development for an untargeted HS-SPME-GC–MS analysis of terpenes and cannabinoids for the geographical sourcing of Marijuana

Despite growing decriminalization of Cannabis sativa (i.e., marijuana) possession throughout the United States of America, there remains to be an ongoing interest in the detection of unlawfully possessed and transported marijuana. This issue has resulted in an increasing interest regarding the generalization and specification related to the canine detection of marijuana. More specifically, canine trainers have expressed concerns on whether canines can generalize on the odor of marijuana regardless of the origin of their training materials. This research aims to differentiate multiple marijuana headspace samples from three regions in the USA based solely on the volatile organic compounds (VOCs) found in their odor profiles. In this study, a heated headspace solid phase micro-extraction (SPME) technique was optimized and implemented for the collection of both volatile terpenes and cannabinoids from marijuana. The headspace samples were analyzed using two full-scan, untargeted, optimized methods on a gas chromatograph coupled to a mass spectrometer (GC–MS), and a variety of chemometric tools were applied to the data to enable differentiation and potential classification between sample populations. Principal component analysis and sparse partial least squares discriminant analysis (sPLS-DA) employed in this study have demonstrated a disparity between marijuana varieties based on geography using the VOCs extracted from their odor profiles. With this research, it is intended to determine some fundamental differences between Cannabis of different geographical origins and set a foundation for the development and advancement of instrumental applications for other non-contact marijuana detection techniques in support of the improvement of illicit substance detection technology

Investigating the Use of SARS-CoV-2 (COVID-19) Odor Expression as a Non-Invasive Diagnostic Tool—Pilot Study

Since the beginning of the COVID-19 pandemic, there has been enormous interest in the development of measures that would allow for the swift detection of the disease. The rapid screening and preliminary diagnosis of SARS-CoV-2 infection allow for the instant identification of possibly infected individuals and the subsequent mitigation of the disease spread. Herein, the detection of SARS-CoV-2-infected individuals was explored using noninvasive sampling and low-preparatory-work analytical instrumentation. Hand odor samples were obtained from SARS-CoV-2-positive and -negative individuals. The volatile organic compounds (VOCs) were extracted from the collected hand odor samples using solid phase microextraction (SPME) and analyzed using gas chromatography coupled with mass spectrometry (GC-MS). Sparse partial least squares discriminant analysis (sPLS-DA) was used to develop predictive models using the suspected variant sample subsets. The developed sPLS-DA models performed moderately (75.8% (±0.4) accuracy, 81.8% sensitivity, 69.7% specificity) at distinguishing between SARS-CoV-2-positive and negative -individuals based on the VOC signatures alone. Potential markers for distinguishing between infection statuses were preliminarily acquired using this multivariate data analysis. This work highlights the potential of using odor signatures as a diagnostic tool and sets the groundwork for the optimization of other rapid screening sensors such as e-noses or detection canines

Predicting SARS-CoV-2 Variant Using Non-Invasive Hand Odor Analysis: A Pilot Study

The adaptable nature of the SARS-CoV-2 virus has led to the emergence of multiple viral variants of concern. This research builds upon a previous demonstration of sampling human hand odor to distinguish SARS-CoV-2 infection status in order to incorporate considerations of the disease variants. This study demonstrates the ability of human odor expression to be implemented as a non-invasive medium for the differentiation of SARS-CoV-2 variants. Volatile organic compounds (VOCs) were extracted from SARS-CoV-2-positive samples using solid phase microextraction (SPME) coupled with gas chromatography–mass spectrometry (GC–MS). Sparse partial least squares discriminant analysis (sPLS-DA) modeling revealed that supervised machine learning could be used to predict the variant identity of a sample using VOC expression alone. The class discrimination of Delta and Omicron BA.5 variant samples was performed with 95.2% (±0.4) accuracy. Omicron BA.2 and Omicron BA.5 variants were correctly classified with 78.5% (±0.8) accuracy. Lastly, Delta and Omicron BA.2 samples were assigned with 71.2% (±1.0) accuracy. This work builds upon the framework of non-invasive techniques producing diagnostics through the analysis of human odor expression, all in support of public health monitoring

The Use of Biological Sensors and Instrumental Analysis to Discriminate COVID-19 Odor Signatures

The spread of SARS-CoV-2, which causes the disease COVID-19, is difficult to control as some positive individuals, capable of transmitting the disease, can be asymptomatic. Thus, it remains critical to generate noninvasive, inexpensive COVID-19 screening systems. Two such methods include detection canines and analytical instrumentation, both of which detect volatile organic compounds associated with SARS-CoV-2. In this study, the performance of trained detection dogs is compared to a noninvasive headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) approach to identifying COVID-19 positive individuals. Five dogs were trained to detect the odor signature associated with COVID-19. They varied in performance, with the two highest-performing dogs averaging 88% sensitivity and 95% specificity over five double-blind tests. The three lowest-performing dogs averaged 46% sensitivity and 87% specificity. The optimized linear discriminant analysis (LDA) model, developed using HS-SPME-GC-MS, displayed a 100% true positive rate and a 100% true negative rate using leave-one-out cross-validation. However, the non-optimized LDA model displayed difficulty in categorizing animal hair-contaminated samples, while animal hair did not impact the dogs’ performance. In conclusion, the HS-SPME-GC-MS approach for noninvasive COVID-19 detection more accurately discriminated between COVID-19 positive and COVID-19 negative samples; however, dogs performed better than the computational model when non-ideal samples were presented