Innovations in latent fingerprint analysis for forensic applications with matrix assisted laser desorption/ionization mass spectrometry imaging

This dissertation presents work that aims to address the current limitations of latent fingerprint analysis in the forensic science field and discuss innovative new ways that matrix assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) could be used to develop techniques that would alleviate some of the current issues. The first chapter consists of a general introduction to MALDI-MSI and presents a general workflow for a MALDI-MSI experiment. The sixth and final chapter summarizes the work presented in this dissertation and provides a future outlook. The second chapter discusses the compatibility of MALDI-MSI and one of the most common forensic development techniques for latent fingerprints, cyanoacrylate fuming. An array of endogenous and exogenous compounds were studied to determine if there were any changes in structure (reactions with cyanoacrylate) or signal due to the fuming process. None of the compounds exhibited any structural changes and most had comparable signal intensity with or without cyanoacrylate fuming. One class of compounds, however, quaternary ammonium derivatives (present in many hygiene products) had significantly suppressed signal after fuming. The third chapter studies the cyanoacrylate fuming mechanism in more depth based on evidence from the mass spectra in the compatibility study. Specifically, several peaks were identified that were determined to be unique to the spectra of fingerprints that had been cyanoacrylate fumed. The peaks were identified by exact mass and MS/MS and were found to be dimers and trimers of ethyl cyanoacrylate. In addition, some further studies were done to determine which endogenous compounds are responsible for the adherence of the cyanoacrylate polymer to the fingerprint ridges. It was determined that the most polymer formation happens on fatty acids and amino acids, which must play an important role in the fuming process. The fourth chapter outlines how endogenous fingerprint compounds diffuse from the fingerprint ridges over time. The initial idea was to model the diffusion of a triacylglycerol (TG) in an attempt to determine the time since deposition or age of the fingerprint. It was thought that a TG would diffuse more slowly than fatty acids (FAs), which had been researched previously by another group, and would allow for aging over a longer time period. However, it was determined that the surface interactions between fingerprint compounds and the sample substrate played a larger role in the diffusion rate than the molecular weight of the compounds. For example, the more hydrophobic TG only diffused slower than the FA on a hydrophobic surface. The fifth chapter discusses using variability in the TG profile to determine differences in diet, exercise, and whether or not an individual has diabetes. As TGs play a role in many health conditions, including obesity and diabetes, differences could be reflected in the TG profile of a latent fingerprint. 79 total participants (16 with diabetes) were recruited to determine if the TG profile was impacted by diabetes. General trends showed the possibility that diabetics, particularly type 2 diabetics, could have higher levels of saturated TGs; however, no significant conclusions could be drawn due to diet and exercise differences obscuring some of the effects. Diet and exercise effects were tested with subsets of the original data set with clear diet and exercise habits. The exercise study included 8 male (4 that exercise regularly and 4 that do not) and 8 female participants (5 that exercise regularly and 3 that do not). Male participants that exercised regularly had a much lower relative abundance of completely saturated TGs compared to those that do not exercise. The same effect did not occur with the female participants. The study on diet consisted of 5 vegetarians, 3 low carbohydrate/ketogenic, and 4 people without any diet restrictions. The vegetarians had very high relative amounts of saturated TGs compared to either of the diets, whereas the ketogenic diet was comparable to the control

A Characterization of Human Burial Signatures using Spectroscopy and LIDAR

This study is an analysis of terrestrial remote sensing data sets collected at the University of Tennessee’s Anthropology Research Facility (ARF). The objective is to characterize human burial signatures using spectroscopy and laser scanning technologies. The development of remote human burial detection methodologies depends on basic research to establish signatures that inform forensic investigations. This dissertation provides recommendations for future research on remote sensing of human burials, and for investigators who wish to apply these technologies to case work. Data used in this study include terrestrial spectra, aerial hyperspectral imagery, satellite multispectral imagery, terrestrial light detection and ranging (LIDAR), and aerial LIDAR. In February 2013, ten individuals donated through the Forensic Anthropology Center body donation program were buried in three differently sized graves at the ARF. The graves contain one, three, and six bodies, respectively. An empty experimental control grave was also created. Terrestrial data collections were made from two-days pre-burial to 21-months post-burial. Aerial data were collected from 19 to 27-months post-burial. Satellite imagery was collected from six-months pre-burial to 23-months post-burial. Analytical emphasis is placed on the terrestrial data sets, which are of the highest spatial and spectral fidelity. Results of terrestrial data analysis reveal separable spectral and topographic signatures between the disturbed locations and surrounding undisturbed area. Aerial and satellite data were used to attempt validation of terrestrial data analysis findings, but findings were inconclusive. This study demonstrates that live vegetation spectral samples can be correctly classified as disturbed or undisturbed groups at rates from 52.0 – 78.3% using statistically-based classification models. Additionally, this study documents localized elevation change at burial surfaces as a result of initial digging activity, subsequent soil settling and subsurface decomposition. The findings of this research are significant to both researchers and practitioners. It is the first study to compare live vegetation spectra associated with human burials and is the first to document burial elevation change using LIDAR. This work contributes to a collective understanding of human burial signatures that can be used together or with other geophysical methods to assist in locating unmarked human burials

Interrogation of Ion-Neutral Complexes by Trapped Ion Mobility-Mass Spectrometry and Theoretical Calculations

In the present study, the fundamentals of molecular ion trapping and the application of trapped ion mobility spectrometry coupled to mass spectrometry (TIMS-MS) to the separation and identification of molecular components in complex mixtures are shown. In particular, ion-neutral complexes lifetimes, relative stability, binding energies and candidate structures are described for common explosives during TIMS-MS, as well as the effect of the micro-environment, during complex sample analysis. A novel TIMS-MS workflow was developed for the detection of both inorganic residues (IGSR; inorganic gunshot residues) and organic residues (OGSR) of firearm discharge residue from skin swabs, capable of high specificity and short analysis time (few min) from a small sample size (µL). The TIMS-MS workflow provided fast, post-ionization, high resolution mobility (RIMS ~ 150–250) and mass separations (RMS ~ 20–40k) with isotopic pattern recognition. In addition, for the first time, liquid chromatography, trapped ion mobility spectrometry and mass spectrometry are combined for fast separation, identification and quantitation of labile juvenile hormones (JHs) with increased sensitivity and confidence levels. In particular, the use of the parent ion and in-source diagnostic fragment ions in a LC-TIMS-MS workflow was developed, complemented with novel extraction and labeled standards for the detection and quantitation of JHs in biological samples

Revealing chemical evidence from fingerprints through matrix-assisted laser desorption/ionization - mass spectrometry imaging

This dissertation presents my efforts to advance the application of matrix-assisted laser desorption/ionization - mass spectrometry imaging (MALDI-MSI) to the chemical analysis of latent fingerprints. The first chapter contains a general introduction to MALDI-MSI, with a focus on the application to fingerprint analysis. The final chapter summarizes the presented work and future directions for the research. The second chapter presents the feasibility of using carbon fingerprint development powder (CFP) as an existing MALDI matrix. This study compared the ionization efficiency of CFP and other commonly used MALDI matrices. The data revealed that CFP is comparable or better than the currently utilized MALDI matrices for latent fingerprint analysis. MALDI-MSI was performed on fingerprints dusted with CFP and lifted with forensic lifting tape, demonstrating that more realistic samples can also be analyzed using MALDI-MSI. Most importantly, it was shown that MALDI-MSI does not destroy the fingerprint during analysis and the fingerprint can be preserved as forensic evidence. The third chapter investigated the use of titanium oxide development powder (TiO2) as a MALDI matrix and elaborates on the impact of adding additional matrices to the signal-to-noise (S/N) ratio of fingerprint compounds. It was demonstrated that TiO2 worked efficiently as an existing MALDI matrix and did not require the use of a high-resolution mass spectrometer. Additional matrices on top of the TiO2 showed limited success and caused a decrease in intensity for some compounds. However, additional matrix did allow the analysis of TiO2 developed fingerprints in negative mode. Importantly this work emphasized the need for knowledge of traditional matrix applicability in fingerprint analysis. In the fourth chapter, the potential for using MALDI-MSI to develop lifestyle profiles of unknown individuals is presented. Prior work studying exogenous fingerprint compounds focused on illicit substances. In this work, compounds related to consumer products, foods, and beverages could be detected in fingerprint residue using MALDI-MSI. These specific compounds could be used for brand or subtype determination of a particular source, such as subtype of citrus fruit. Each set of compounds detected tells a portion of an individual\u27s lifestyle. In the fifth chapter, the mechanism of degradation of unsaturated triacylglycerols (TGs) in fingerprints aged under ambient environment conditions was investigated. MALDI-MSI was used to explore TG profiles of fresh and aged latent fingerprints. With time, the unsaturated TGs underwent ambient ozonolysis resulting in a decrease in the abundance of unsaturated TGs that was relatively reproducible in an individual. In addition, two sets of peaks emerged with time, and were determined to be degradation peaks of unsaturated TGs due to ambient ozonolysis. The decrease of unsaturated TGs can be monitored to establish the time since deposition, or age, of latent fingerprints

Bayesian hierarchical modeling for the forensic evaluation of handwritten documents

The analysis of handwritten evidence has been used widely in courts in the United States since the 1930s (Osborn, 1946). Traditional evaluations are conducted by trained forensic examiners. More recently, there has been a movement toward objective and probability-based evaluation of evidence, and a variety of governing bodies have made explicit calls for research to support the scientific underpinnings of the field (National Research Council, 2009; President\u27s Council of Advisors on Science and Technology (US), 2016; National Institutes of Standards and Technology). This body of work makes contributions to help satisfy those needs for the evaluation of handwritten documents. We develop a framework to evaluate a questioned writing sample against a finite set of genuine writing samples from known sources. Our approach is fully automated, reducing the opportunity for cognitive biases to enter the analysis pipeline through regular examiner intervention. Our methods are able to handle all writing styles together, and result in estimated probabilities of writership based on parametric modeling. We contribute open-source datasets, code, and algorithms. A document is prepared for the evaluation processed by first being scanned and stored as an image file. The image is processed and the text within is decomposed into a sequence of disjoint graphical structures. The graphs serve as the smallest unit of writing we will consider, and features extracted from them are used as data for modeling. Chapter 2 describes the image processing steps and introduces a distance measure for the graphs. The distance measure is used in a K-means clustering algorithm (Forgy, 1965; Lloyd, 1982; Gan and Ng, 2017), which results in a clustering template with 40 exemplar structures. The primary feature we extract from each graph is a cluster assignment. We do so by comparing each graph to the template and making assignments based on the exemplar to which each graph is most similar in structure. The cluster assignment feature is used for a writer identification exercise using a Bayesian hierarchical model on a small set of 27 writers. In Chapter 3 we incorporate new data sources and a larger number of writers in the clustering algorithm to produce an updated template. A mixture component is added to the hierarchical model and we explore the relationship between a writer\u27s estimated mixing parameter and their writing style. In Chapter 4 we expand the hierarchical model to include other graph-based features, in addition to cluster assignments. We incorporate an angular feature with support on the polar coordinate system into the hierarchical modeling framework using a circular probability density function. The new model is applied and tested in three applications

2020 SDSU Data Science Symposium Program

https://openprairie.sdstate.edu/ds_symposium_programs/1002/thumbnail.jp

Advances in Forensic Genetics

The book has 25 articles about the status and new directions in forensic genetics. Approximately half of the articles are invited reviews, and the remaining articles deal with new forensic genetic methods. The articles cover aspects such as sampling DNA evidence at the scene of a crime; DNA transfer when handling evidence material and how to avoid DNA contamination of items, laboratory, etc.; identification of body fluids and tissues with RNA; forensic microbiome analysis with molecular biology methods as a supplement to the examination of human DNA; forensic DNA phenotyping for predicting visible traits such as eye, hair, and skin colour; new ancestry informative DNA markers for estimating ethnic origin; new genetic genealogy methods for identifying distant relatives that cannot be identified with conventional forensic DNA typing; sensitive DNA methods, including single-cell DNA analysis and other highly specialised and sensitive methods to examine ancient DNA from unidentified victims of war; forensic animal genetics; genetics of visible traits in dogs; statistical tools for interpreting forensic DNA analyses, including the most used IT tools for forensic STR-typing and DNA sequencing; haploid markers (Y-chromosome and mitochondria DNA); inference of ethnic origin; a comprehensive logical framework for the interpretation of forensic genetic DNA data; and an overview of the ethical aspects of modern forensic genetics

Enhancing the forensic comparison process of common trace materials through the development of practical and systematic methods

An ongoing advancement in forensic trace evidence has driven the development of new and objective methods for comparing various materials. While many standard guides have been published for use in trace laboratories, different areas require a more comprehensive understanding of error rates and an urgent need for harmonizing methods of examination and interpretation. Two critical areas are the forensic examination of physical fits and the comparison of spectral data, which depend highly on the examiner’s judgment. The long-term goal of this study is to advance and modernize the comparative process of physical fit examinations and spectral interpretation. This goal is fulfilled through several avenues: 1) improvement of quantitative-based methods for various trace materials, 2) scrutiny of the methods through interlaboratory exercises, and 3) addressing fundamental aspects of the discipline using large experimental datasets, computational algorithms, and statistical analysis. A substantial new body of knowledge has been established by analyzing population sets of nearly 4,000 items representative of casework evidence. First, this research identifies material-specific relevant features for duct tapes and automotive polymers. Then, this study develops reporting templates to facilitate thorough and systematic documentation of an analyst’s decision-making process and minimize risks of bias. It also establishes criteria for utilizing a quantitative edge similarity score (ESS) for tapes and automotive polymers that yield relatively high accuracy (85% to 100%) and, notably, no false positives. Finally, the practicality and performance of the ESS method for duct tape physical fits are evaluated by forensic practitioners through two interlaboratory exercises. Across these studies, accuracy using the ESS method ranges between 95-99%, and again no false positives are reported. The practitioners’ feedback demonstrates the method’s potential to assist in training and improve peer verifications. This research also develops and trains computational algorithms to support analysts making decisions on sample comparisons. The automated algorithms in this research show the potential to provide objective and probabilistic support for determining a physical fit and demonstrate comparative accuracy to the analyst. Furthermore, additional models are developed to extract feature edge information from the systematic comparison templates of tapes and textiles to provide insight into the relative importance of each comparison feature. A decision tree model is developed to assist physical fit examinations of duct tapes and textiles and demonstrates comparative performance to the trained analysts. The computational tools also evaluate the suitability of partial sample comparisons that simulate situations where portions of the item are lost or damaged. Finally, an objective approach to interpreting complex spectral data is presented. A comparison metric consisting of spectral angle contrast ratios (SCAR) is used as a model to assess more than 94 different-source and 20 same-source electrical tape backings. The SCAR metric results in a discrimination power of 96% and demonstrates the capacity to capture information on the variability between different-source samples and the variability within same-source samples. Application of the random-forest model allows for the automatic detection of primary differences between samples. The developed threshold could assist analysts with making decisions on the spectral comparison of chemically similar samples. This research provides the forensic science community with novel approaches to comparing materials commonly seen in forensic laboratories. The outcomes of this study are anticipated to offer forensic practitioners new and accessible tools for incorporation into current workflows to facilitate systematic and objective analysis and interpretation of forensic materials and support analysts’ opinions