Sampling method development and optimization in view of human hand odor analysis by thermal desorption coupled with gas chromatography and mass spectrometry.

Forensic profiling of human odor is challenging and would be useful to support information provided by dogs in courts of justice. Analyses of volatile compounds constitutive of human odor are commonly performed with gas chromatography coupled with mass spectrometry. All developed methods and sampling prototypes have to be easy to use in the field by crime scene investigators. This paper will focus on techniques for human hand odor sampling prior to analysis by a thermodesorption device coupled with gas chromatography and mass spectrometry. Thermodesorption and gas chromatography methods were developed using a sorbent phase spiked with a mixture of 80 compounds representative of human hand odor. Then, the crucial sampling step was performed indirectly with a homemade device based on air suction and trapping on a sorbent. This indirect sampling device was evaluated with the same synthetic mixture for optimization. An innovative polymer sorbent called Sorb-Star® was compared to classic Tenax TA® packed tubes. Sorb-Star® provided similar recovery to Tenax TA® packed tubes and a smaller pooled coefficient of variation (6 vs 13%). Thus, it appeared to be fully suited to the indirect sampling of human hand odor. The developed methods were successfully applied to real samples, the ultimate aim being the comparison of a suspect's sample to a sample collected from a crime scene.

Screening of Breast Cancer from Sweat Samples Analyzed by 2-Dimensional Gas Chromatography-Mass Spectrometry: A Preliminary Study.

Breast cancer (BC) remains one of the most commonly diagnosed malignancies in women. There is increasing interest in the development of non-invasive screening methods. Volatile organic compounds (VOCs) emitted through the metabolism of cancer cells are possible novel cancer biomarkers. This study aims to identify the existence of BC-specific VOCs in the sweat of BC patients. Sweat samples from the breast and hand area were collected from 21 BC participants before and after breast tumor ablation. Thermal desorption coupled with two-dimensional gas chromatography and mass spectrometry was used to analyze VOCs. A total of 761 volatiles from a homemade human odor library were screened on each chromatogram. From those 761 VOCs, a minimum of 77 VOCs were detected within the BC samples. Principal component analysis showed that VOCs differ between the pre- and post-surgery status of the BC patients. The Tree-based Pipeline Optimization Tool identified logistic regression as the best-performing machine learning model. Logistic regression modeling identified VOCs that distinguish the pre-and post-surgery state in BC patients on both the breast and hand area with sensitivities close to 1. Further, Shapley additive explanations and the probe variable method identified the most important and pertinent VOCs distinguishing pre- and post-operative status which are mostly of distinct origin for the hand and breast region. Results suggest the possibility to identify endogenous metabolites linked to BC, hence proposing this innovative pipeline as a stepstone to discovering potential BC biomarkers. Large-scale studies in a multi-centered VOC analysis setting must be carried out to validate obtained findings.

Volatile Organic Compounds Analysis as a Potential Novel Screening Tool for Breast Cancer: A Systematic Review.

Introduction: An early diagnosis is crucial in reducing mortality among people who have breast cancer (BC). There is a shortfall of characteristic early clinical symptoms in BC patients, highlighting the importance of investigating new methods for its early detection. A promising novel approach is the analysis of volatile organic compounds (VOCs) produced and emitted through the metabolism of cancer cells. Methods: The purpose of this systematic review is to outline the published research regarding BC-associated VOCs. For this, headspace analysis of VOCs was explored in patient-derived body fluids, animal model-derived fluids, and BC cell lines to identify BC-specific VOCs. A systematic search in PubMed and Web of Science databases was conducted according to the PRISMA guidelines. Results: Thirty-two studies met the criteria for inclusion in this review. Results highlight that VOC analysis can be promising as a potential novel screening tool. However, results of in vivo, in vitro and case-control studies have delivered inconsistent results leading to a lack of inter-matrix consensus between different VOC sampling methods. Discussion: Discrepant VOC results among BC studies have been obtained, highly due to methodological discrepancies. Therefore, methodological issues leading to disparities have been reviewed and recommendations have been made on the standardisation of VOC collection and analysis methods for BC screening, thereby improving future VOC clinical validation studies.

Evaluation of distance-based approaches for forensic comparison: Application to hand odor evidence.

The issue of distinguishing between the same-source and different-source hypotheses based on various types of traces is a generic problem in forensic science. This problem is often tackled with Bayesian approaches, which are able to provide a likelihood ratio that quantifies the relative strengths of evidence supporting each of the two competing hypotheses. Here, we focus on distance-based approaches, whose robustness and specifically whose capacity to deal with high-dimensional evidence are very different, and need to be evaluated and optimized. A unified framework for direct methods based on estimating the likelihoods of the distance between traces under each of the two competing hypotheses, and indirect methods using logistic regression to discriminate between same-source and different-source distance distributions, is presented. Whilst direct methods are more flexible, indirect methods are more robust and quite natural in machine learning. Moreover, indirect methods also enable the use of a vectorial distance, thus preventing the severe information loss suffered by scalar distance approaches. Direct and indirect methods are compared in terms of sensitivity, specificity, and robustness, with and without dimensionality reduction, with and without feature selection, on the example of hand odor profiles, a novel and challenging type of evidence in the field of forensics. Empirical evaluations on a large panel of 534 subjects and their 1690 odor traces show the significant superiority of the indirect methods, especially without dimensionality reduction, be it with or without feature selection.

Human odor and forensics. Optimization of a comprehensive two-dimensional gas chromatography method based on orthogonality: How not to choose between criteria.

The use of comprehensive two-dimensional gas chromatography coupled with mass spectrometry would be a real asset for the forensic profiling of human hand odor. This paper focuses on the optimization of a comprehensive gas chromatography method using a synthetic mixture of 80 compounds representative of human hand odor composition. In order to rank the candidate column sets, instead of using a unique criterion, we used a chemometric tool called desirability which is based on Derringer functions and enables to consider several criteria simultaneously and hence to get the best compromise. Nine criteria including six orthogonality criteria were used to evaluate the quality and the efficiency of the separation. The desirability analysis lead to a straightforward ranking and an accurate overview of the results in two situations, with an objective of routine analysis and without. In both cases, the DB-1MS×DB-1701 set was found to be best suited for the separation of the considered mixture, however with different gradients.

Human odor and forensics: Towards Bayesian suspect identification using GC × GC-MS characterization of hand odor.

A new method for identifying people by their odor is proposed. In this approach, subjects are characterized by a GC × GC-MS chromatogram of a sample of their hand odor. The method is based on the definition of a distance between odor chromatograms and the application of Bayesian hypothesis testing. Using a calibration panel of subjects for whom several odor chromatograms are available, the densities of the distance between chromatograms of the same person, and between chromatograms of different persons are estimated. Given the distance between a reference and a query chromatogram, the Bayesian framework provides an estimate of the probability that the corresponding two odor samples come from the same person. We tested the method on a panel that is fully independent from the calibration panel, with promising results for forensic applications.

Origin, Analytical Characterization, and Use of Human Odor in Forensics.

Developing a strategy to characterize the odor prints of individuals should be relevant to support identification obtained using dogs in courts of justice. This article proposes an overview of the techniques used for the forensic profiling of human odor. After reviewing the origin of human odor-both genetic and physiological-the different analytical steps from sample collection to statistical data processing are presented. The first challenge is the collection of odor, whether by direct sampling with polymer patches, cotton gauze, etc., or indirect sampling with devices like Scent Transfer Unit. Then, analytical techniques are presented. Analyses are commonly performed with gas chromatography coupled with mass spectrometry. As they yield large amounts of data, advanced statistical tools are needed to provide efficient and reliable data processing, which is essential to give more probative value to information.