Multivariate regression modelling for gender prediction using volatile organic compounds from hand odor profiles via HS-SPME-GC-MS.

The efficacy of using human volatile organic compounds (VOCs) as a form of forensic evidence has been well demonstrated with canines for crime scene response, suspect identification, and location checking. Although the use of human scent evidence in the field is well established, the laboratory evaluation of human VOC profiles has been limited. This study used Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) to analyze human hand odor samples collected from 60 individuals (30 Females and 30 Males). The human volatiles collected from the palm surfaces of each subject were interpreted for classification and prediction of gender. The volatile organic compound (VOC) signatures from subjects' hand odor profiles were evaluated with supervised dimensional reduction techniques: Partial Least Squares-Discriminant Analysis (PLS-DA), Orthogonal-Projections to Latent Structures Discriminant Analysis (OPLS-DA), and Linear Discriminant Analysis (LDA). The PLS-DA 2D model demonstrated clustering amongst male and female subjects. The addition of a third component to the PLS-DA model revealed clustering and minimal separation of male and female subjects in the 3D PLS-DA model. The OPLS-DA model displayed discrimination and clustering amongst gender groups with leave one out cross validation (LOOCV) and 95% confidence regions surrounding clustered groups without overlap. The LDA had a 96.67% accuracy rate for female and male subjects. The culminating knowledge establishes a working model for the prediction of donor class characteristics using human scent hand odor profiles.

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.

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.

The influence of intra-personal variations in human hand odor on the determination of sample donor.

A dual effort investigation was conducted to study (a) the naturally occurring variation in same-donor human hand odor samples over time and (b) the accuracy in associating same-donor human hand odor samples. Hand odor samples were collected from 8 donors throughout 5 sampling sessions; samples were collected in triplicate and analyzed by HS-SPME-GC-MS at each sampling session. The resulting human hand odor profiles were analyzed to investigate (a) the variability of human hand odor profiles as a function of time and (b) the ability to determine the source origin of human hand odor samples, determining samples to be from the same source or different sources. The researchers observed greater variation in 2-dimensional human scent profile patterning schemes among inter-day, inter-subject samples and less variation in inter-day, intra-subject samples. Although intra-subject samples revealed less variation than inter-subject samples, there was still notable variability among inter-day, intra-subject human scent profiles, with an observed time dependency. Two proof of concept models for the source determination of human hand odor samples were developed with maximum performance measuring TPR = 0.817/ FPR = 0.308 and TPR = 1.000/ FPR = 0.206 for models one and two, respectively. The study quantified same-donor human hand odor profile variation over time displayed within a larger goal of determining sample source origin.

Preliminary accuracy of COVID-19 odor detection by canines and HS-SPME-GC-MS using exhaled breath samples.

The novel coronavirus SARS-CoV-2, since its initial outbreak in Wuhan, China has led to a worldwide pandemic and has shut down nations. As with any outbreak, there is a general strategy of detection, containment, treatment and/or cure. The authors would argue that rapid and efficient detection is critical and required to successful management of a disease. The current study explores and successfully demonstrates the use of canines to detect COVID-19 disease in exhaled breath. The intended use was to detect the odor of COVID-19 on contaminated surfaces inferring recent deposition of infectious material from a COVID-19 positive individual. Using masks obtained from hospitalized patients that tested positive for COVID-19 disease, four canines were trained and evaluated for their ability to detect the disease. All four canines obtained an accuracy >90% and positive predictive values ranging from ~73 to 93% after just one month of training.

Controlled Odor Mimic Permeation Systems for Olfactory Training and Field Testing.

The Controlled Odor Mimic Permeation System (COMPS) was developed to provide a convenient field testing method of odor delivery at controlled and reproducible rates. COMPS are composed of an odorant of interest on an absorbent material sealed inside of a permeable polymer bag. The permeable layer allows for a constant release of the odorant over a given amount of time. The permeable bag is further stored in a secondary, impermeable bag. The double-containment procedure allows for equilibration of the odorant from the permeable bag but within the impermeable outer layer, resulting in an instant and reproducible source of odorant vapor upon removal from the outer packaging. COMPS are used in both olfactory testing for experimental scenarios and for olfactory detection training, such as with detection canines. COMPS can be used to contain a wide range of odorants (e.g., narcotics powders) and provide a controlled release of the associated odorants. Odor availability from COMPS is expressed in terms of permeation rate (i.e., the rate of the odorant vapor released from a COMPS per unit time) and is typically measured by gravimetric means. The permeation rate for a given mass or volume of odorant can be adjusted as needed by varying the bag thickness, surface area, and/or polymer type. The available odor concentration from a COMPS can also be measured by headspace analysis techniques such as solid phase microextraction with gas chromatography/mass spectrometry (SPME-GC/MS).

Generalization and Discrimination of Molecularly Similar Odorants in Detection Canines and the Influence of Training.

Operationally-deployed canine detectors are often trained on one or a limited number of materials representing a single target odor, and training frequently occurs using materials of a high purity grade in controlled scenarios with minimal other background odors. Conversely, in the field, canine detectors are expected to generalize and identify variations of the target odor, while discriminating from similar extraneous or background odors. This exemplifies the balance between generalization and discrimination required for effective canine detectors. This research explored the tendency for detection canines to generalize or discriminate between similar odorants. Two groups of related odorants were used in two separate studies; (1) odorants of similar functional groups with differing carbon chains, and (2) odorants of similar carbon chain length but differing functional groups. Within each odorant set, the effect of training was addressed by incrementally increasing the number of odorants each canine was trained to detect. Initially, discrimination increased with increasing molecular dissimilarity in both odorant groups. After further training on additional related odorants, generalization increased across the set of odorants of the same carbon chain length, but there were no significant changes in either generalization or discrimination across the set of odorants of the same functional group. The results suggest that the canines in this study were more likely to generalize across compounds of the same chain length with differing functional group than across compounds of the same functional group, but differing chain lengths. Furthermore, some variation in performance between individual canines indicated that the tendency to generalize differed with experience, breed, and other factors affecting olfaction.

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.

Advances in the use of odour as forensic evidence through optimizing and standardizing instruments and canines.

This paper explores the advances made in identifying trace amounts of volatile organic compounds (VOCs) that originate from forensic specimens, such as drugs, explosives, live human scent and the scent of death, as well as the probative value for detecting such odours. The ability to locate and identify the VOCs liberated from or left by forensic substances is of increasing importance to criminal investigations as it can indicate the presence of contraband and/or associate an individual to a particular location or object. Although instruments have improved significantly in recent decades-with sensitivities now rivalling that of biological detectors-it is widely recognized that canines are generally still more superior for the detection of odourants due to their speed, versatility, ruggedness and discriminating power. Through advancements in the detection of VOCs, as well as increased standardization efforts for instruments and canines, the reliability of odour as evidence has continuously improved and is likely to continue to do so. Moreover, several legal cases in which this novel form of evidence has been accepted into US courts of law are discussed. As the development and implementation of best practice guidelines for canines and instruments increase, their reliability in detecting VOCs of interest should continue to improve, expanding the use of odour as an acceptable form of forensic evidence.

Separation mechanism of chiral impurities, ephedrine and pseudoephedrine, found in amphetamine-type substances using achiral modifiers in the gas phase.

A new mechanism is proposed that describes the gas-phase separation of chiral molecules found in amphetamine-type substances (ATS) by the use of high-resolution ion mobility spectrometry (IMS). Straight-chain achiral alcohols of increasing carbon chain length, from methanol to n-octanol, are used as drift gas modifiers in IMS to highlight the mechanism proposed for gas-phase separations of these chiral molecules. The results suggest the possibility of using these achiral modifiers to separate the chiral molecules (R,S) and (S,R)-ephedrine and (S,S) and (R,R)-pseudoephedrine which contain an internal hydroxyl group at the first chiral center and an amino group at the other chiral center. Ionization was achieved with an electrospray source, the ions were introduced into an IMS with a resolving power of 80, and the resulting ion clusters were characterized with a coupled quadrupole mass spectrometer detector. A complementary computational study conducted at the density functional B3LYP/6-31g level of theory for the electronic structure of the analyte-modifier clusters was also performed, and showed either "bridged" or "independent" binding. The combined experimental and simulation data support the proposed mechanism for gas-phase chiral separations using achiral modifiers in the gas phase, thus enhancing the potential to conduct fast chiral separations with relative ease and efficiency.