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Spiked pad study at 50 0 C to show discriminators of groups are indicative of chemical component Complex Mixture Study Figure 9 Headspace analysis of four.

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Presentation on theme: "Spiked pad study at 50 0 C to show discriminators of groups are indicative of chemical component Complex Mixture Study Figure 9 Headspace analysis of four."— Presentation transcript:

1 Spiked pad study at 50 0 C to show discriminators of groups are indicative of chemical component Complex Mixture Study Figure 9 Headspace analysis of four different colognes. The scores plot shows that these complex mixtures had enough variability to be differentiated. The dendrogram for this data set (not shown) also showed how replicates of the same cologne clustered together and were different than the other colognes. Human scent arises from a variety of sources:  Secretions from the apocrine, eccrine and sebaceous glands  Bacteria “feeding” on these secretions  Cellular debris  Topical applications (sunscreen, cologne,etc.) An individual’s chemical profile will be comprised of volatile and semi-volatile compounds and within this profile will be his/her “odorome” which will be a combination of malodorous and pleasant odor components (Figure 2).  Many components of the VSVCP will contain N,S,O functional groups (5-6)  Will be amenable to ionization by gas phase proton/ electron transfer reactions in atmospheric pressure chemical ionization (APCI) “Odorome” can be affected by (7-13):  Diet  Health  Age  Heredity  Race Multivariate statistical analysis techniques are ideally suited for analysis of complex mixtures and classifying samples into categories:  Deal with data on two or more variables measured on a set of objects  Developed to explore the interdependence of variables  Can empirically discover groups with similar spectra (hierarchical cluster analysis, HCA)  Can summarize variation in highly multivariant spectra (principle component analysis, PCA)  Can develop classification rules for predefined groups (discriminant analysis, DA)  Transforms original, intercorrelated variables into anew set of uncorrelated variables  Identifies main data characteristics from interrelated variables  Summarizes multivariate variability efficiently in fewer dimensions Purpose: Show statistical differences using multivariate analysis between unused scent pads and spiked pads, or pads used to sample items or individuals. Method: Process data obtained with a thermal desorption atmospheric pressure chemical ionization source coupled to a PE Sciex 365 mass spectrometer using Pirouette, a multivariate data analysis program. Results: Statistical differences observed between unused pads from different boxes and between unused pads and pads used to sample head space of single component and complex mixtures (colognes) using multivariate analysis. Trained canines are used in search and rescue operations as well as to track fugitives, missing persons, and for scent identification line-ups. Using scent as forensic evidence assumes that each individual has a unique odor, that the unique odor is stable over time and that a dog can differentiate between odors of different people. Several empirical studies have been performed to determine how well dogs can differentiate odors between people (1-4), yet very little scientific data has been published with respect to the actual identity of chemical components canines are targeting/smelling. Scent evidence can be found on any item a suspect has touched, worn, or eliminated. Clothing and weapons are easily collected as evidence, but for objects that cannot be removed from the crime scene, a Scent Transfer Unit™ (STU) shown in Figure 1 was developed to collect the scent evidence onto a gauze pad which can be stored until needed. The gauze pad would then be given to a canine who may follow a suspect’s path from a crime scene, place a suspect at a particular scene, match a suspect to a weapon, or identify a suspect in a line-up. By using thermal desorption atmospheric pressure chemical ionization mass spectrometry (TD/APCI-MS), we can analyze scent pads rapidly, without suffering loss of analyte often encountered with extraction steps in GC/MS. In addition, using multivariate analysis on the acquired data will show how reproducible the scent profiles acquired with the STU are, as well as determine important discriminators in identifying individuals or groups. 1. Schoon, G.A.A. J. Forensic Sci. 1998, 43, Schoon, G.A.A. Appl. Anim. Behav. Sci. 1996, 49, Schoon, G.A.A.; De Bruin, J.C. Forensic Sci. Int. 1994, 69, Brisbin, Jr., I.L.; Austad, S.N. Anim. Behav. 1991, 42, Bernier, U.R.; Booth, M.M.; Yost, R.A. Anal. Chem. 1999, 71, Zeng, X.; Leyden, J.J.; Lawley, H.J.; Sawano, K.; Nohara, I; Preti G. J. Chem. Ecol. 1991, 17, Nicolaides, N. Science, 1974, 186, Green, S.C.; Stewart, M.E.; Downing, D.T. J. Invest. Dermatol. 1984, 83, Smith, K.; Thompson, G.F.; Koster, H.D. Science, 1969, 166, Haze, S.; Gozu, Y.; Nakamura, S.; Kohno, Y.; Sawano, K.; Ohta, H.; Yamazaki, K. J. Invest. Dermatol. 2001, 116, Mitchell, S.C.; Smith, R.L. Drug Metabolism and Disposition, 2001, 29, Schaefer, M.L.; Young, D.A.; Restrepo, D. J. Neurosci. 2001,21, Schaefer, M.L.; Yamazaki, K; Osada, K.; Restrepo, D.; Beauchamp, G.K. J. Neurosci 2002, 22, Figure 1 Photograph of the STU device with a sterile gauze (Johnson and Johnson) used to collect scent evidence. Experiments performed with a thermal desorption atmospheric pressure chemical ionization source coupled to a PE Sciex 365 mass spectrometer (MDS Sciex, Concord, Ontario, Canada). System optimized for detection of likely odor compounds in both positive and negative ion modes. “Scent” samples collected on sterile gauze pads (or scent pads, Johnson & Johnson) using the STU.  Neat compounds – headspace analysis  Humans – Will be collecting samples from population including homogeneous groups of individuals (e.g. 40 yr old Caucasian males) and subpopulation for race, gender, and age variations.  Sample from various locations on body Scent pads are placed in thermal desorption unit (Figure 3) and mass spectra recorded from m/z 30 to m/z 500 Import data into Pirouette (Lite Explore v3.11)  Identify similar groups  Identify important discriminators (m/z) for each group Identify “most discriminating” components in scent profile  Tandem mass spectrometry  GC/MS of extracted or thermally desorbed scent pads Pads from different boxes show variability as well as significant background ions.  Less background ions in negative ion mode Complex mixtures (colognes) can be differentiated using Pirouette, a multivariate analysis program. Variability can be determined (PCA scores plot) and the source(s) of the variability identified (PCA loading plot).  Sampled headspace of isovaleric acid clustered with pads spiked with isovaleric acid;major discriminators included m/z 101 and 203, (M-H) - and (2M-H) -, respectively.  Sampled headspace of 2-nonenal clustered on the basis of m/z 141 (protonated molecule of 2- nonenal)(not shown). Further optimize thermal desorption and APCI interface conditions for odorome model compounds. Explore alternative pads to reduce background. Refine statistical analysis procedures using existing data sets. Begin human sampling:  Sampling duration  Sampling areas, articles  Apply discriminant analysis to data sets  Male and female  Young and old  Caucasian, Asian, etc. SAR acknowledges support through Oak Ridge Institute for Science and Education, Oak Ridge, TN in conjunction with the Federal Bureau of Investigation Counter-terrorism Forensic Science Research Unit (FBI-CTFSRU). Research sponsored by the Federal Bureau of Investigation through the Work for Others Office, U.S. Department of Energy, under contract No. DE-AC05- 00OR22725 with Oak Ridge National Laboratory, managed and operated by UT-Battelle, LLC. Authors thank Dr. Dennis Wolf at ORNL for helpful discussions regarding multivariate analysis. Authors thank John Luke at MSA for loan of thermal desorption equipment. Authors thank Larry Harris for loan of STU device. API 365 MS was provided through a Cooperative Research and Development Agreement with MDS Sciex (CRADA ORNL ). Figure 2 Illustration of human scent composition. Many components of the VSVCP and most odor compounds will contain some functional group, such as N, S, and O. Optimization of TD/APCI-MS to obtain predominantly molecular ion species Desorption Of Sterile Gauze Pads Figure 6 Temperature studies on unused pads (positive ion mode) show slight variations in thermally desorbed components between boxes of pads with same lot numbers and boxes with different lot numbers. Figure 4 Mass spectra of the headspace analysis of isovaleric acid and 2- nonenal in positive ion mode under identical conditions. Some fragmentation is observed and more “odorous” compounds must be characterized in both positive and negative ion before the “best” conditions for each mode are finalized. Figure 5 Comparison in positive and negative ion mode of a scent pad used to sample a glass slide spotted with isovaleric acid (Desorption temperature at 40 o C). Chemical noise from the pad overshadows the protonated molecule at m/z 103. Less chemical noise in negative ion mode shows strong (M-H) - at m/z 101. Figure 7 Scores plot on left shows several clusters. One associated with background air (yellow cluster on bottom) and one with unused pads (lower right cluster). The orange cluster in the bottom left represents pads spiked with heptanoic acid and the clusters at the top represent isovaleric acid spiked onto pads (blue) and pads used to sample a chamber with isovaleric acid (yellow). The loading plot on the right shows that the principle discriminators for the clusters are indeed the molecular species for isovaleric acid (top cluster) and heptanoic acid (bottom left). Figure 8 The resulting dendrogram from the HCA analysis of this data set shows that the pads spiked with isovaleric acid (sp#) and the pads used to sample the chamber of isovaleric acid (smp#) are more similar to one another than either the heptanoic acid spiked pads or unused pads. Figure 3 Scent pad being placed into thermal desorption unit. Rapid Mass Spectral Acquisition and Statistical Analysis for Determination of Scent Discriminators Keiji G. Asano 1, Gary J. Van Berkel 1, Scott A. Ramsey 2, and Brian A. Eckenrode 3 1 Oak Ridge National Laboratory, Oak Ridge, TN, 2 Michigan State University, East Lansing, MI, 3 Federal Bureau of Investigation, Quantico, VA RESULTS AND DISCUSSION MULTIVARIATE ANALYSISHUMAN SCENT EXPERIMENTAL REFERENCES BACKGROUND OVERVIEW SUMMARY FUTURE WORK ACKNOWLEDGEMENTS


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