Biology subjects

Philpott, M. K.

Publications and source records attributed to Philpott, M. K..

3 recordsLinked to original sources

bioRxiv2023

Comparison of three quantitative approaches for estimating time-since-deposition from autofluorescence and morphological profiles of cell populations from forensic biological samples

Determining when DNA recovered from a crime scene transferred from its biological source, i.e., a samples time-since-deposition (TSD), can provide critical context for biological evidence. Yet, there remains no analytical techniques for TSD that are validated for forensic casework. In this study, we investigate whether morphological and autofluorescence measurements of forensically-relevant cell populations generated with Imaging Flow Cytometry (IFC) can be used to predict the TSD of touch or trace biological samples. To this end, three different prediction frameworks for estimating the number of day(s) for TSD were evaluated: the elastic net, gradient boosting machines (GBM), and generalized linear mixed model (GLMM) LASSO. Additionally, we transformed these continuous predictions into a series of binary classifiers to evaluate the potential utility for forensic casework. Results showed that GBM and GLMM-LASSO showed the highest accuracy, with mean absolute error estimates in a hold-out test set of 29 and 21 days, respectively. Binary classifiers for these models correctly binned 94-96% and 98-99% of the age estimates as over/under 7 or 180 days, respectively. This suggests that predicted TSD using IFC measurements coupled to one or, possibly, a combination binary classification decision rules, may provide probative information for trace biological samples encountered during forensic casework.

molecular biology↗

bioRxiv2023

Differentiation of vaginal cells from epidermal cells using morphological and autofluorescence properties: Implications for sexual assault casework involving digital penetration

Analysis of DNA mixtures from sexual assault evidence is an ongoing challenge for DNA casework laboratories. There is a significant need for new techniques that can provide information as to the source of DNA, particularly for sexual assault samples that do not involve semen. The goal of this study was to develop a new biological signature system that provides additional probative value to samples comprised of mixtures of epidermal and vaginal cells, as may be observed in cases involving digital penetration. Signatures were based on morphological and autofluorescence properties of individual cells collected through Imaging Flow Cytometry (IFC). Comparisons to reference cell populations from vaginal tissue and epidermal cells collected from hands showed strong multivariate differences across >80 cellular measurements. These differences were used to build a predictive framework for classifying unknown cell populations as originating from epithelial cells associated with digital penetration or epidermal tissue. As part of the classification scheme, posterior probabilities of specific tissue group membership were calculated for each cell, along with multivariate similarity to that tissue type. We tested this approach on cell populations from reference tissue as well as mock casework samples involving digital penetration. Many more cells classifying as non-epidermal tissue were detected in digital penetration samples than control hand swabbings. Minimum interpretation thresholds were developed to minimize false positives; these thresholds were also effective when screening licked hands, indicating the potential utility of this method for a variety of biological mixture types and depositional events relevant to forensic casework. Results showed that samples collected subsequent to digital penetration possessed markedly higher numbers of cells classifying as vaginal tissue as well as higher posterior probabilities for vaginal tissue ([≥] 0.90) compared to cell populations collected from hands without prior contact with vaginal tissue. Additionally, digital penetration cell populations may be resolved from saliva cell populations and other non-target tissue types.

cell biology↗

bioRxiv2018

Rapid Identification of Epithelial Cell Types in Forensic Samples Using Intrinsic Fluorescence and Morphological Signatures

Establishing the tissue source of epithelial cells within a biological sample is an important capability for forensic laboratories. In this study we used Imaging Flow Cytometry (IFC) to analyze individual cells recovered from buccal, contact epithelial, and vaginal samples that had been dried between 24 hours and more than eight weeks. Measurements capturing the size, shape, and fluorescent properties of cells were collected in an automated manner and then used to build a multivariate statistical framework for differentiating cells based on tissue type. Results showed that cell populations from the three tissue types could be differentiated using a Discriminant Function plot of IFC measurements. Epidermal cells were distinguished from vaginal and buccal cells with an average classification accuracy of ~94%. Ultimately, cellular measurements such as these, which can be obtained non-destructively, may provide probative information for many types of biological samples and complement results from standard genetic profiling techniques.

cell biology↗