Forensic Science Data sponsored by the National Institute of Justice
PI Name: Rabi A. Musah, State University of New York at Albany
Study Summary: The accelerated legalization of marijuana has contributed to the rise in popularity of edible marijuana products (edibles) and raises several public health concerns including risk of consumption by children, delayed activation time, intensity of psychoactive effects, and variation of laws from one state to another regarding serving size, labeling, and packaging of marijuana products. There are several challenges that these products impose on the forensic science community, including the difficulty in detection and quantification of tetrahydrocannabinol (THC) in complex matrices that contain hundreds of other constituents, such as edibles and unrefined plant materials. This project developed novel, efficient and validated approaches by which crime labs can recover and quantify THC in complex matrices such as edibles and plant materials, and differentiate it from CBD and other phytocannabinoids using direct analysis in real time – high-resolution mass spectrometry.
NIJ Grant #: 2019-DU-BX-0026
Description of End Product: Datasets in the form of fully published work and accompanying supporting data
Note: This cite includes additional studies funded by NIJ
Study Title: A Dental Anthropological Databank for Use in the Statistical Estimation of Ancestry and Sex in Forensic Anthropology
PI Names: Marin Pilloud, University of Nevada, Reno; G. Richard Scott, University of Nevada, Reno
Study Summary: This research created a large dataset of dental data to improve estimations of sex assigned at birth and ancestry/population affinity in forensic anthropology. Data were collected from a global sample on dental metrics and dental morphology. The project also created a database in which data could be collected and a manual describing data collection and database use. These modern contribute to the the web-based application rASUDAS that can be used to estimate population of an unknown individual.
NIJ Grant #: 2017-DN-BX-0143
Description of End Product: A database and a web-based application
Study Title: Application of the Human Virome to Touched Objects and Hair Shafts
PI Name: Michael Adamowicz, University of Nebraska
Study Summary: This proposal is designed to address the ongoing need to create forensically relevant linkages between persons, places, and objects by developing the heretofore untapped potential of the human viral microbiome (virome). The human virome is a source of rich genetic diversity that needs to be examined to determine if it is stable, transferable, and provides a sufficient power of discrimination to be used as an alternative to traditional human forensic deoxyribonucleic acid (DNA) tests when such tests are infeasible. The human bacterial microbiome is already being examined as an alternative method for human identification in forensically relevant cases. The human virome offers some advantages as the viral genomes are even smaller than those of bacteria, and thus are potentially more physically stable, have a variety of morphologies (double- and single-stranded) increasing the possible number of discriminating markers, and is present throughout the human body, including the skin and body fluids, making it transferable. License and code also available.
NIJ Grant #: 2019-75-CX-0017
Description of End Product: Data, Curated Databases, Software
Study Title: Development of an Interactive Database of Contemporary Material Properties for Computer Fire Modeling
PI Names: Craig Weinschenk, UL Fire Safety Research Institute; Mark McKinnon, UL Fire Safety Research Institute; Nicholas Dow, UL Fire Safety Research Institute; Daniel Madrzykowski, UL Fire Safety Research Institute
Study Summary: This study provides standard fire test data, thermo-physical properties, and model inputs for over 70 materials that are commonly encountered in the built environment. The database website provides complete transparency on the procedures used to prepare materials for testing as well as the experimental protocol used to test the material samples. In addition, the current industry best practices and recommendations on analysis of the raw data and guidance on how the data may be used to effectively simulate burning of materials with common computational models and heuristics is provided. With these data and the provided guidance, fire investigators and fire model practitioners may represent solid materials into fire models and analyses that they previously could not include while also enjoying higher confidence in the simulations and results of these analyses than prior to publication of this research and database. The website was designed to allow investigators and practitioners with any level of education and understanding of heat transfer, thermodynamics, and data structures to easily access and understand the data and properties.
NIJ Grant #: 2019-DU-BX-0018
Description of End Product: Interactive Database, Data Archive
PI Names: Daniel Kosmas, Rensselaer Polytechnic Institute; John Mitchell, Rensselaer Polytechnic Institute
Study Summary: The purpose of this project is to develop novel prescriptive analytics to assist criminal justice practitioners in the decision-making process in disrupting human trafficking networks, as well as develop a network generator that will simulate human trafficking networks. These analytics will be based on network interdiction problems, a class of mathematical problems that have been successfully applied to the disruption of nuclear smuggling and drug trafficking networks. Current limitations on applying network interdiction problems to disrupting human trafficking is the uncertainty in the network structure and that traffickers will react to any disruption efforts to mitigate their losses. We improved upon network interdiction models by incorporating how traffickers might react in response to disruption efforts. These models were tested on synthetic but realistic network data on domestic sex trafficking networks.
NIJ Grant #: 2020-R2-CX-0022
Description of End Product: Datasets used in published works supported by the fellowship that are formatted for use with AMPL.
Study Title: Bio-inspired Material-integrated Magnetic Beads for Differential Extraction of Sperm in Forensic Applications
PI Name: Utkan Demirci, Stanford University
Study Summary: The goal of this study was to further develop a specific surface chemistry to modify magnetic beads with a unique sperm capture reagent. To further develop an integrated system with bio-inspired material integrated beads to capture and quantitate the number of sperm in a forensic sample and to develop specific protocols for forensic applications with the system. As a secondary goal developmental validation of the system including sensitivity, precision and accuracy, reproducibility, stability studies and correlation with currently used methods, resulting in commercialization suitable next generation system to accelerate the differential extraction process for forensic investigations.
NIJ Grant #: 2019-NE-BX-0003
Description of End Product: The archived data includes two publications and one intellectual property disclosure filing
Second Publication: A Confirmatory Test for Sperm in Sexual Assault Samples Using a Microfluidic-integrated Cell Phone Imaging System
PI Name: Liguo Song, Western Illinois University
Study Summary: As medicinal and recreational cannabis markets continue to grow, global demands for cannabis testing keep rising. The cannabis industry must ensure product quality, regulatory compliance and safety. There is an urgent need for validated methods to measure the total THC concentration in various products of cannabis by crime laboratories. This study sought to validate a LC-DAD-ESI/MS/MS method and resulted in four peer-reviewed articles: 1) Development of a validated method for rapid quantification of up to sixteen cannabinoids using ultra-high-performance liquid chromatography diode-array detector with optional electrospray ionization time-of-flight mass spectrometry detection; 2) Potency testing of up to twenty cannabinoids by liquid chromatography diode array detector with optional electrospray ionization time-of-flight mass spectrometry; 3) Potency testing of up to sixteen cannabinoids in hemp-infused edibles using liquid chromatography diode array detector with optional confirmation of identity by electrospray ionization time-of-flight mass spectrometry; and 4)A liquid chromatography electrospray ionization tandem mass spectrometry method for quantification of up to eighteen cannabinoids in hemp-derived products.
NIJ Grant #: 2020-DQ-BX-0021
Description of End Product: Datasets and peer-reviewed journal articles
Study Title: Inter-laboratory Variation in Interpretation of DNA Mixtures Study: DNAmix 2021
PI Names: R. Austin Hicklin (Director, Forensic Science Group, Noblis); Jonathan Davoren (Director of Core Facility and Applied Research, Bode Technology)
Study Summary: DNAmix 2021 was a large-scale study conducted to evaluate the extent of consistency and variation among forensic laboratories in the interpretation of DNA mixtures, and to assess the effects of various potential sources of variability. The study was composed of four phases. The Policies and Procedures Questionnaire assessed laboratory policies and procedures relevant to DNA mixture interpretation. The Casework Scenario Questionnaire assessed the nature of mixture casework, and analysis procedures or decisions that may vary depending upon the case scenario. In the Number of Contributors Subtest participants were given electropherogram data and asked to provide assessments of suitability and number of contributors. In the Interpretation, Comparison, and Statistical Analysis Subtest participants were given electropherogram data with DNA profiles of potential contributors, and were asked to provide interpretations and statistical analyses. A total of 179 participants from 87 different laboratories participated in the study.
NIJ Grant #: 2020-R2-CX-0049
Description of End Product: Electropherograms (EPGs) for the 29 mixtures used (PDF images)
Study Title: Enhanced Mixture Interpretation with Long-read DNA Sequencing
PI Names: Jianye Ge, UNT Health Science Center; August Woerner, UNT Health Science Center
Study Summary: This project is the first to evaluate a construct called a macrohaplotype. Macrohaplotypes target Combined DNA Index System Short Tandem Repeats (CODIS STRs) and large swathes of DNA surrounding them. The database produced and additional information provided show great promise for deconvolving and otherwise interpreting complex DNA mixtures.
NIJ Grant #: 15PNIJ-21-GG-04159-RESS
Description of End Product: Macrohaplotype database, which can be used for forensic match and DNA mixture statistics. We have also added several bioinformatic tools; these include TRcaller and USAT (which can be used to evaluate and visualize STRs used alignment methods, respectively), as well as MacroHapCaller (which can be used to characterize macrohaplotypes from long read sequencing data) and MacrohapSimulator (which can be used to simulate the PCR and sequencing process of macrohaplotypes in both single-source and DNA mixture scenarios).
Study Title: Coping with Close Non-Matches in Latent Print Comparisons (re-) Training
PI Name: Heidi Eldridge, RTI International
Study Summary: RTI International and the University of Lausanne partnered to create an International Close Non-Match Library (ICNML). This project aimed at measuring the current state of latent print examiners' understanding of close non-matches, developing training tools to help latent print examiners cope with close non-matches, and building the library itself, which will contain both known ground truth same source and close non-match different source pairings and is an invaluable tool for training, testing, and research. Using a partnership model to leverage an international network of public and private agencies and members of academia representing some of the top experts in the field, an ICNML of ~1,000 cases were prepared offering a repository of relevant and realistic marks and prints of known ground truth from ~100 donors. This ICNML includes ~3,000 non-mated pairs of varying difficulty that are potential close non-matches as well as 3 sets of known same-source exemplars for each latent mark contained therein (~5,500 marks representing ~1,000 unique areas). These potential close non-matches were evaluated by latent fingerprint experts to certify whether they are, in fact, close non-matches via two mechanisms: the partners who originally locate the different source pairs with an AFIS will indicate whether they consider each pair to be a close non-match or not; and an experimental phase will task volunteer participants with comparing a sub-set of the same source and different source pairs in the ICNML. Those which are judged to be different source were posed a follow-up question, asking participants whether the pair was a close non-match. Finally, an experiment was conducted to measure how well red flags for close non-matches identified by an expert panel actually predict those marks which are likely to produce a close non-match.
NIJ Grant #: 2018-DU-BX-0227
Description of End Product: Dataset and database, final project report
Study Title: A Paradigm Shift in Forensic Toxicology: The Development and Validation of Two Automated Sample Preparation Techniques for the Comprehensive Screening of Biological Matrices Using High Resolution Mass Spectrometry
PI Name: Rebecca Wagner, Virginia Department of Forensic Science
Study Summary: The goal of this research project is to develop and validate two fully automated sample preparation techniques for the qualitative analysis of whole blood and additional biological matrices in accordance with the guidelines promulgated by SWGTOX. The objectives for this project are: 1) develop, validate, and compare tubular and 96-well plate fully automated SPE sample preparation techniques to an existing manual sample preparation technique for comprehensive screening of antemortem and postmortem biological samples using LC-qTOF, and 2) compare LC-qTOF screening results with current qualitative screening protocols including blood alcohol stop testing limits, ELISA results, and GC-MS screening results. The tubular method will be a transfer of an existing manual SPE methodology to an automated process while the 96-well plate configuration will be a scaled down approach of the larger scale tubular automated process. The two methods will be compared to the existing manual SPE procedure as well as to each other for efficiency, specificity, and cost-effectiveness to enable Virginia and laboratories across the country to evaluate benefits of implementation. The methods will also be evaluated against conventional multi-step screening procedures including ELISA and GC-MS screening as well as stop testing protocols that currently exist in many laboratories.
NIJ Grant #: 2018-DU-BX-0168
Description of End Product: Instrumental data, large datasets, reports, and final project report. Contact the PI for access to the data (becky.wagner@dfs.virginia.gov)
Study Title: Solving Cases of Sudden Unexpected Natural Death in the Young through Comprehensive Postmortem Genetic Testing
PI Name: Yingying Tang, Molecular Genetics Laboratory Office of Chief Medical Examiner
Study Summary: The primary goals of this project are twofold. First, we aim to identify and test a large number of SUND cases and provide answers to the medical examiners and the families. Second, we aim to evaluate the utility of molecular testing in postmortem investigations and to inform forensic practice standards and guidelines.
NIJ Grant #: 2018-DU-BX-0204
Description of End Product: Peer-reviewed journal publications
- Molecular Genetic Characterization of Sudden Deaths Due to Thoracic Aortic Dissection or Rupture
- Cardiac Genetic Test Yields and Genotype-Phenotype Correlations from Large Cohort Investigated by Medical Examiner’s Office
Study Title: Deep Learning Methods for Post Mortem Interval Estimation
PI Name: Audris Mockus, University of Tennessee, Knoxville
Study Summary: The aim is to support the development of the techniques and tools that help forensic anthropologists and law enforcement with a sound empirical basis to make the decisions concerning approaches to determine postmortem interval (PMI). This will be accomplished by curating a large and context-rich dataset documenting the evolution of human decomposition and by developing and evaluating a collection of approaches including a generalized version of Accumulated Degree Days (gADD) and deep learning networks to estimate the state of the decomposition and PMI.
NIJ Grant #: 15PNIJ-21-GG-04161-SLFO
Description of End Product: Software, configuration, and deep-learning models resulting from research on automatic determination of PMI and stages of decay
Study Title: An Object-Centric Approach for Image Analysis to Combat Human Trafficking
PI Name: Robert Pless, George Washington University
Study Summary: This research project explored algorithms to facilitate investigational searches of the form: "In what hotel was this image taken". To support this we collected a large number of images from online sources and also through an iPhone app that we improved over the course of this project. We maintain a server to support the National Center for Missing and Exploited Children that operates this search in an ongoing manner. The primary research data produced under this project is a collection of images organized to support research on large scale hotel classification. This was the subject of a publication in the AAAI conference, and two different, highly popular Kaggle contests. Files for the 2021 and 2022 contests are available through Kaggle.
NIJ Grant #: 2018-75-CX-0038
Description of End Product: Scripts and image files
Study Title: Adolescent Behavior Cognitive Development - Social Development Sub-Study
PI Name: Lia Ahonen, University of Pittsburgh
Study Summary: Adolescent Behavior and Cognition Development Study - Social Development (ABCD-SD) is a prospective study on adolescent delinquency and victimization. ABCD-SD is a sub-study of the Adolescent Behavior and Cognition Development Study, utilizing the extensive ABCD data on cognitive and brain development while adding measures on delinquency and victimization risks and outcomes for participants at 5 of the 21 ABCD sites (n=2,426 at baseline). The aim of ABCD-SD is to advance the understanding of the influences of variations of and maturational delays in cognitive and brain development, substance use exposure, and pre-exposure phenotypes on delinquency trajectories and responses to victimization. This knowledge is crucial to informing policymakers and prevention science to decrease the number of juveniles in the juvenile or criminal justice system.
NIJ Grant #: 2017-MU-CX-0044
Description of End Product: Restricted data embedded in the larger ABCD data release
Study Title: Learning from Our Casework: The Forensic Anthropology Database for Assessing Methods Accuracy
PI Names: Cris Hughes, University of Illinois Urbana-Champaign; Chelsey Juarez, California State University, Fresno
Study Summary: The forensic anthropology database for assessing methods accuracy (FADAMA) is a free online forensic case database for documenting forensic anthropology methods and case outcomes. It serves the broader forensic anthropology community of practitioners, researchers and students. The main purpose of this database is to create avenues for forensic anthropology methods development and improvement by providing detailed data on method use, method outcomes, and individual and cumulative method accuracy. To this end, FADAMA is a repository for forensic anthropologists with past and/or present positively identified cases. All data submitted by practitioners is then amalgamated into a single database, which can be easily searched and downloaded for research purposes by FADAMA users.
NIJ Grant #: 2018-DU-BX-0213
Description of End Product: Restricted, living database accessible by request
Study Title: Evaluation of Nuclear DNA from Rootless Hairs for Forensic Purposes
PI Name: Richard Green, University of California, Santa Cruz
Study Summary: Whole genome sequencing data from single hairs and saliva from 50 human donors. Illumina GSA array data from saliva DNA from the same donors.
NIJ Grant #: 2020-DQ-BX-0014
Description of End Product: DNA and genotype array data accessible by request
Study Title: Linking Internal Organ Microbiome and Metabolome Composition to Cause of Death in Medicolegal Investigations
PI Name: Jack A. Gilbert, University of California, San Diego
Study Summary: The goal of this study was to apply a 16S rRNA barcoding approach to investigate variation among different organs, as well as the extent to which microbial associations among different body organs in human cadavers can be used to predict forensically important determinations, such as cause and time of death. We assessed microbiota of organ tissues including brain, heart, liver, spleen, prostate, and uterus collected at autopsy from criminal casework of 40 Italian cadavers with times of death ranging from 24 to 432 h. Both the uterus and prostate had a significantly higher alpha diversity compared to other anatomical sites, and exhibited a significantly different microbial community composition from non-reproductive organs, which we found to be dominated by the bacterial orders MLE1-12, Saprospirales, and Burkholderiales. In contrast, reproductive organs were dominated by Clostridiales, Lactobacillales, and showed a marked decrease in relative abundance of MLE1-12. We conclude that distinct community profiles of reproductive versus non-reproductive organs may help guide the application of forensic microbiology tools to investigations of human cadavers.
NIJ Grant #: 2017-MU-MU-4042
Description of End Product: Genetic sequence data for microbes
PI Name: David Alan Stoney, Stoney Forensic, Inc
Study Summary: This study collected data to determine if very small particles trapped in the adhesive along the exposed edges of duct tape rolls contains sufficient numbers and variety of small particles, acquired post-manufacture, to allow comparisons and measurable discrimination among tape segments from different rolls, and to allow meaningful, quantitative associations among tape segments from the same roll.
NIJ Grant #: 2020-MU-CX-0018
Description of End Product: Spreadsheets with SEM/EDS quantitative elemental analysis data for each of the particles in the specimens and related controls.
Study Title: Improving Results from Touch DNA Evidence with Optimized Direct Polymerase Chain Reaction (PCR) Methods, 2020-2022
PI Names: Abigail S. Bathrick, Bode Technology; Anna C. Salmonsen, Bode Technology; Jonathan M. Davoren, Bode Technology
Study Summary: Direct polymerase chain reaction (PCR) is a DNA processing method in which a sample is added directly to an amplification reaction without prior purification or quantification and has been identified as a method that may improve genotyping data obtained from low-yield touch DNA samples. The goal of the project was to generate data in support of a re-evaluation of the Federal Bureau of Investigation's (FBI) Quality Assurance Standard (QAS) 9.4 and the 2018 Forensic Science Technology Working Group (TWG) operational requirements.
The project was performed in two phases. Phase I examined the direct PCR-compatible collection methods in conjunction with mock touch DNA evidence samples on a variety of substrates. Phase II examined direct PCR of touch DNA samples that were stored at room temperature for up to six months after collection and samples that were re-sampled after initial processing. Direct PCR was performed using GlobalFiler and PowerPlex Fusion 6C amplification methods that were already validated for standard casework processing.
NIJ Grant #: 2019-DU-BX-0009
Description of End Product: Excel and CSV datasets and the technical summary for the project.
Study Title: Novel Ambient Oxidation Trends in Fingerprint Aging Discovered by Kendrick Mass Defect Analysis
PI Name: Young Jin Lee, Iowa State University
Study Summary: A Kendrick mass defect (KMD) plot is an efficient way to disperse complex high-resolution mass spectral data in a visually informative two-dimensional format which allows for the rapid assignment of compound classes that differ by heteroatom content and/or unsaturation. We apply KMD plot analysis for the first time to sebaceous fingerprints aged for 0-7 days to characterize lipid degradation processes analyzed by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). In addition to the ambient ozonolysis of fingerprint lipids, we observed unique spectral features associated with epoxides and medium chain fatty acid degradation products that are correlated with fingerprint age. We propose an ambient epoxidation mechanism via peroxyl radical intermediate, and the prevalence of omega-10 fatty acyl chains in fingerprint lipids to explain the features observed by the KMD plot analysis. Our hypotheses are supported by the aging experiment performed in a sparse ozone condition and on-surface Paternò-Büchi reaction. A comprehensive understanding of fingerprint degradation processes, afforded by the KMD plots, provides crucial insights for considering which ions to monitor and which to avoid, when creating a robust model for time since deposition of fingerprints.
NIJ Grant #: 2019-DU-BX-0134
Description of End Product: Mass spectrometry data set used in Kendrick Mass Defect analysis available in the Supporting Information section of the publication
Study Title: Positive Identification Using Frontal Sinus Comparisons: Developing Empirically-based Guidelines
PI Name: Lauren N. Butaric, Des Moines University
Study Summary: The goal of this project is to provide medicolegal practitioners with a set of guidelines and important considerations for frontal sinus identification that will be developed based on a comprehensive analysis of previously published identification methods, including factors that may affect the accuracy of those methods (e.g., intra/inter observer reliability, image modality, sinus size/complexity, individual's age). Ultimately results indicate that visual assessment remains one of the most efficient, accurate, and reliable methods when utilizing the frontal sinus for positive identification.
There are 7 datasets associated with this study, each with their own DOI:
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FS_Ontogeny_Coded_Data: Dataset contains age of stabilization data for frontal sinus traits of 146 individuals.
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FS_EFA_Outline_Data: Outline data related to the Elliptical Fourier Analysis (EFA) method which includes a collection of scaled coefficients for all tracings that underwent EFA.
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FS_TD_Outline Data: Outline data related to the Total Difference method.
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FS_VisualAssess_Data: Survey responses regarding reliability of visual assessments when utilizing the frontal sinus for positive identification purposes.
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FS_Ontogeny_Outline_Data: Data associated with Elliptical Fourier Analyses coefficients, specifically regarding the outline data related to frontal sinus ontogeny.
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FS_Orientation_Outline_Data: Resulting normalized coefficients of Elliptical Fourier Analyses on frontal sinus outline data related to varying cranial orientation.
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FS_ImageMode_Coded_Data: String codes derived from frontal sinus traits following previously published methods related to the effect of varying image modality for forensic identification purposes.
NIJ Grant #: 2020-75-CX-0013
Description of End Product: Seven CSV and .txt datasets containing stabilization data, outline data, visual assessments and coded image modality data.
Study Title: AI Enabled Community Supervision for Criminal Justice Services
PI Names: Marcus Rogers, Purdue University; Umit Karabiyik, Purdue University; Sudhir Aggarwal, Florida State University; Carrie Pettus, Florida State University; Tathagata Mukherjee, University of Alabama in Huntsville; Haeyong Chung, University of Alabama in Huntsville
Study Summary: This project aimed to revolutionize the reentry process for justice-involved individuals (JII) by harnessing the power of artificial intelligence (AI) and advanced technologies. The centerpiece of the endeavor is the AI-based Support and Monitoring System, or AI-SMS, a cutting-edge platform designed to assist JII and their dedicated caseworkers in their journey to reintegrate seamlessly into the community. While the primary focus is on JII, the researchers recognize the critical role played by caseworkers-clinically trained individuals who facilitate the reentry process from a community perspective.
AI-SMS was conceived to be a multifaceted tool that provides case workers with early warning indicators of risky behavior and equips JII with the means and strategies to mitigate these risks, aligning with best practices in hybrid supervision. At its core, the system is committed to delivering personalized resources and opportunities to JII, complementing the support offered by caseworkers.
NIJ Grant #: 2019-75-CX-K001
Description of End Product: Software and code
Study Title: A Black Box Study of the Accuracy and Reproducibility of Tire Evidence Examiners' Conclusions
PI Name: William Chapman, Noblis
Study Summary: Tire impression evidence can be a valuable tool during a crime scene investigation - it can link vehicles to scenes or secondary locations, and reveal information about the series of events surrounding a crime. The interpretation of tire impression evidence relies on the expertise of forensic tire examiners; however, until this study was conducted there had not been any published research empirically evaluating the decisions reported by practicing forensic tire examiners. This study constitutes the first formal black box study of tire impression evidence examiners; the results are an empirical evaluation of the accuracy and reproducibility of 238 tire comparison decisions reported by 17 examiners. The results of this study provide key information about the practice of tire impression examination to laboratory managers, practitioners, and the legal system that can help to facilitate improvements in standardization, training, and practice.
NIJ Grant #: 2020-DQ-BX-0026
Description of End Product: De-identified participant data, comparison set images as provided to participants
Study Title: Expert Algorithm for Substance Identification (EASI)
PI Name: Glen P. Jackson, West Virginia University
Study Summary: This study aimed to develop an Expert Algorithm for Substance Identification (EASI) that will both improve the confidence of drug identifications from mass spectra and enable reliable inter-laboratory identifications without the need to acquire contemporaneous spectra of standards. The data included 303 replicates of cocaine and 10 replicates of cocaine compounds (diastereomers), and showed the variance observed in operational crime labs over the course of several months for different drug standards.
NIJ Grant #: 15PNIJ-21-GG-04179-COAP
Description of End Product: Excel database consisting of 20 extracted ion abundances from 1019 mass spectra and 303 replicates of cocaine.
Study Title: Comparative Evaluation of Genotyping Technologies for Investigative Genetic Genealogy in Sexual Assault Casework
PI Name: Jonathan Davoren, Bode Technology
Study Summary: Investigative Genetic Genealogy (IGG) offers a capability to identify investigative leads when the Combined DNA Index System (CODIS) searching is unproductive. IGG can provide time efficient methods for removing perpetrators of serial violent crimes, such as rape and murder from the community, thereby increasing public safety. However, use of IGG has preceded establishment of best practices. Development of best practices must start with a systematic evaluation of the laboratory technologies currently used to generate high-density single nucleotide polymorphism (SNP) genotypes. This study evaluated the three technologies currently available for developing high-density SNP genotypes from human DNA samples and compared their abilities to generate profiles from challenging forensic samples related to sexual assault casework across two separate phases to assess. More specifically, this project sought to investigate how low-template DNA (e.g., around 1-2 ng inputs) and highly degraded DNA would affect the quality, accuracy, and reproducibility of high-density SNP genotypes and ultimately affect the performance of IGG to identify potential relatives in the GEDmatch PRO database, a dedicated portal designed to support police and forensic teams with investigative comparisons to GEDmatch data.
NIJ Grant #: 15PNIJ-21-GG-04143-MUMU
Description of End Product: Genotyping quality metrics Excel datasets for each technology evaluated
Study Title: Measurement of Heat Transfer and Fire Damage Patterns on Walls for Fire Model Validation
PI Name: Matthew J. DiDomizio, Fire Safety Research Institute
Study Summary: Fire investigators and researchers leverage fire models to predict fire growth and fire pattern development. These fire models incorporate simplifying assumptions in their representation of heat transfer through walls, but the impact of these assumptions on model predictions of fire exposures and fire damage patterns is not well understood. Experiments were conducted in which freestanding walls were subjected to exposure from controlled fire sources, including gas burners, liquid fuels, and furnishings. Experiments were conducted at the Bureau of Alcohol, Tobacco, Firearms and Explosives - Fire Research Laboratory (ATF-FRL) in Maryland. The experiments addressed three validation spaces: field heat flux from a fire to a wall, heat transfer through fire-exposed walls, and fire damage patterns arising on fire-exposed walls.
NIJ Grant #: 15PNIJ-21-GG-04167-RESS
Description of End Product: Experimental dataset, photographs, and videos for fire researchers and fire model developers to validate models that predict heat transfer to fire-exposed walls, as well as fire damage patterns occurring on fire-exposed walls.
Study Title: Enhanced Ignitable Liquid and Substrate Database Functionality for Improved Casework and Research
PI Names: Michael E. Sigman, University of Central Florida; Mary Williams, University of Central Florida; Larry Tang, University of Central Florida
Study Summary: The Ignitable Liquids Reference Collection (ILRC) and Substrate databases contain separate compilations of data from reference materials that is intended for use by forensic analysts to conduct fire debris analysis. The ILRC, Substrate, and Fire Debris databases were redesigned and made available on a single website to enhance usability in casework and research. This project also investigated the construction of digital fire debris data by mixing ignitable liquid and substrate(s) digital data. Total ion chromatograms and total ion spectra of in silico fire debris were created from data in the Ignitable Liquids Reference Collection and Substrate databases. In silico mixing provides the ability to develop large data sets for machine learning.
NIJ Grant #: 15PNIJ-22-GG-04421-SLFO
Description of End Product: Fire debris datasets and database containing sample information, total ion chromatograms, and total ion spectra
Study Title: Front-End Differentiation of Contributor Cell Populations and Estimation of DNA Content Using Novel Cellular Signatures
PI Name: Christopher Ehrhardt, Virginia Commonwealth University
Study Summary: The objective of this project is to develop a new method for screening trace biological samples for the number of contributors and DNA content based on the presence and relative abundance of key protein and hormone targets within cell populations. There is a critical need for presumptive techniques that could provide valuable information and enable more effective triaging of casework samples, particularly touch samples. To address this, we developed a novel workflow for analyzing biological evidence samples that (1) estimates on the number of contributors in a mixture based upon flow cytometry histogram profiles, (2) estimates the human-specific DNA content in the sample based upon fluorescent signal intensities, and (3) differentiates cell populations in the mixture based contributor-specific attributes. The primary advantage of using this approach with our novel signatures is that all aspects of the proposed workflow are inherently non-destructive. This is ideal for touch evidence samples since these are typically compromised and low in template quantity.
The aims and scope of this project specifically address three operational requirements identified by the 2019 Forensic Technology Working Group: (1) Biological evidence screening tools that can address number and proportion of contributors, (2) ability to differentiate and selectively analyze DNA and/or cells from multiple donors or multiple tissue/cell types contributing to mixtures, with minimal or no sample loss, and (3) comprehensive, systematic, well-controlled studies that provide both foundational knowledge and practical data about "touch evidence" DNA transfer and persistence in the real world.
NIJ Grant #: 2020-DQ-BX-0023
Description of End Product: Supplemental Electropherogram Data and Morphological and Autofluorescence Dataset for 'Touch' Epidermal Cell Populations
Study Title: Evaluation of the Occurrence and Associative Value of Non-Identifiable Fingermarks on Unfired Ammunition in Handguns for Evidence Supporting Proof of Criminal Possession, Use and Intent
PI Name: David Alan Stoney, Stoney Forensic, Inc
Study Summary: The overall goal of this project was to answer the question of how often non-identifiable fingermarks occur on naturally loaded handgun ammunition and what range of associative values can be expected. This is a potential new source of evidence, as current forensic science practices set these fingermarks aside, leaving them unexamined. The project was successful, with highly significant findings showing that non-identifiable fingermarks with strong associative value are found frequently on loaded handgun ammunition. Utilization of this new source of evidence will require adjustment of long-standing forensic examination practices and balancing the level of effort required with the utility of the resulting associations. To do this one important follow-on step is replacing the labor-intensive research laboratory methods applied in this project with more efficient technologies available in forensic laboratories.
The project produced datasets that include images of 415 non-identifiable fingermarks in .tif format, and corresponding images with annotation of fingermark minutiae in .jpg format. The accompanying spreadsheets contain summary information for each of 1263 rounds of ammunition (number of identifiable and non-identifiable fingermarks found, the number of annotated minutiae for the marks, the handgun type - semi-automatic vs. revolver - and the caliber class), as well as the results from each of the handguns sampled.
NIJ Grant #: 15PNIJ-21-GG-04192-RESS
Description of End Product: Images of Non-Identifiable Fingermarks in .tif format, and corresponding images with annotation of fingermark minutiae in .jpg format. The accompanying spreadsheets contain summary information for each of 1263 rounds of ammunition, (number of identifiable and non-identifiable fingermarks found, the number of annotated minutiae for the marks, the handgun type (semi-automatic vs. revolver) and the caliber class) as well as the results from each of the handguns sampled.
PI Name: Christine Moore, 9-Delta Analytical LLC
Study Summary: This project was intended to develop a visually-read, rapid testing device for identifying the presence of fentanyl and/or synthetic opioids in oral fluids and environmentally-friendly laboratory confirmation methods for quantitation of the drugs in oral fluid using liquid chromatography with tandem mass spectral detection (LC-MS/MS). The testing device was developed by nform, a subrecipient of the National Institute of Justice award, and 9-Delta Analytical developed the confirmatory laboratory procedures. These research and development activities are one of many critical steps in addressing the ongoing opioid crisis in the United States.
NIJ Grant #: 15PNIJ-23-GG-04233-RESS
Description of End Product: Time and collection volume for oral fluid samples; Immunoassay cross-reactivity data; Device results; Drug recovery from the pad; Validation parameters for LCMSMS methods; SOFT posters
Study Title: Automatic Acquisition and Identification of Footwear Class Characteristics
PI Name: Susan Vanderplas, University of Nebraska-Lincoln
Study Summary: Most footwear evidence in the United States is evaluated on the basis of class characteristics, without regard for individualizing information. Unfortunately, it is very difficult to assess the strength of a class characteristic match due to lack of data about the frequency of class characteristics within a population. This project addresses the lack of data through the development of equipment and software which can automate the data collection process. The data include images taken with the prototype shoe scanner on a college campus located in Ames, Iowa.
NIJ Grant #: 2019-MU-MU-4096
Description of End Product: Datasets containing images taken with a prototype shoe scanner and the project’s final report.
Study Title: Identification of Minor Dye Components of Fibers via Integrating Cavity-Enhanced Raman Spectroscopy
PI Name: Hergen Eilers, Washington State University
Study Summary: The goal of this project is to evaluate integrating-cavity-enhanced Raman spectroscopy (ICERS) to measure anti-Stokes Raman spectra for the characterization of dyed fibers. ICERS has been developed for the ultrasensitive identification and characterization of materials, and enhancements of five orders of magnitude have been demonstrated. Using ICERS to measure anti-Stokes Raman spectra eliminates the fluorescence background, while the cavity design amplifies the anti-Stokes Raman signal. The combination of the two makes it possible to detect, identify, and characterize minor dye components without interference from fluorescence. Such an approach is expected to reveal more minor dye components which could help narrow down the source of the fiber in question.
NIJ Grant #: 2018-DU-BX-0178
Description of End Product: Several figures and tables from the project's final report containing summarized fabric analysis results.
Study Title: Validation of a Confirmatory Proteomic Mass Spectrometry Body Fluid Assay for Use in Publicly Funded Forensic Laboratories
PI Name: Donald Siegel, New York City Office of Chief Medical Examiner
Study Summary: The goal of this work was to validate the New York City Office of Chief Medical Examiner confirmatory, protein-based body fluid assay for blood, saliva and semen. The assay employs a multiple reaction monitoring mass spectrometry method, and evaluated 1) Assay Performance, 2) Informatic Analysis of Peptide Marker Strength, 3) the Value of Additionally Collected Mass Spectrometry Data, and 4) a Data Quality Management System. The assay has been accredited by the American National Standards Institute's National Accreditation Board (ANAB) and approved by the New York State Commission on Forensic Science.
NIJ Grant #: 15PNIJ-21-GG-02712-SLFO
Description of End Product: Mass spectrometry datasets. Email the PI via the New York City Office of Chief Medical Examiner's contact page to request access to the data.
PI Names: Lauryn DeGreeff, Florida International University; Braden Giordano, U.S. Naval Research Laboratory
Study Summary: The goal of the research is to develop a highly sensitive method of non-contact field detection of two drug classes - designer benzodiazepines and synthetic opioids - by focusing on the detection of vaporous surrogate compounds that are representative of the majority of the drug class. The pre-concentration process of the vaporous surrogates using a novel Silicon Nanowire system that is functionalized to increase detection sensitivity is outlined. Additionally, a sampling method for the identification of drug surrogates in confiscated material was developed.
NIJ Grant #: 15PNIJ-22-GG-04418-RESS
Description of End Product: Downloadable zip file containing Headspace gas chromatography/mass spectrometry (GC/MS) benzodiazepines data, thermal desorption-GC/MS data, and Quartz Crystal Microbalance data. It's recommended that the link be opened in a new browser window.