Defense Date

2023

Document Type

Directed Research Project

First Advisor

Dr. Christopher Ehrhardt

Second Advisor

Dr. Susan Greenspoon

Third Advisor

Katherine Philpott J.D.

Abstract

In forensic casework the identification of body fluids at a crime scene can frequently play an important role in reconstructing the events that occurred. There are several bodily fluid identification methods to characterize unknown stains recovered as evidence. However, there has not been a reliable method for detecting the presence vaginal cells and/or differentiate it from other forensically relevant tissue types that may be recovered from a crime scene. The detection of vaginal fluid is important for forensic casework due to the abundance of sexual assault kits that are not only backlogged but continue to be submitted to the lab every day. This is particularly a challenge in sexual assault cases where samples may be a mixture of vaginal cells with epidermal cells and/or saliva cells. To address this, we tested a new approach for identifying vaginal cells within mixture samples based on Imaging Flow Cytometry (IFC) profiling which can occur on the front-end of a DNA profiling workflow. During IFC, the morphology and autofluorescence profile is characterized in a high throughput and non-destructive fashion, which provides discriminating signatures for cell populations based on their intrinsic biochemical differences which varies across source tissue. First, samples throughout the menstrual cycle were analyzed to assess the variation of this cell type as it applies to the IFC measurements being taken. Menstrual samples showed some variation across the sampling period but were ultimately still distinguishable from epidermal and saliva cell populations. Next, we tested whether vaginal cell signatures could be used to identify contributor cell populations in mock casework samples consisting of mixtures of (1) vaginal and penile epidermal cells and (2) vaginal and saliva cells. Based on morphological and autofluorescence signatures of each cell type, vaginal cells were detected in overwhelming majority of mixture samples. This approach offers a new method with potential to improve the identification, differentiation, and confirmation of vaginal cells and fluid in forensically relevant samples, as well as serve as a predictive tool for the quantity and quality of DNA from specific contributors in a biological mixture.

Rights

© The Author(s)

Is Part Of

VCU Master of Science in Forensic Science Directed Research Projects

Date of Submission

5-4-2023

Available for download on Friday, May 03, 2024

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