Non-destructive age estimation of biological fluid stains: An integrated analytical strategy based on near-infrared hyperspectral imaging and multivariate regression
Graphical abstract
Introduction
The recent advancements in DNA extraction and amplification awarded to biological evidences a crucial role in the forensic investigation. Their detection within the crime scene consistently provide the identification of a suspect or a victim, but also allows to exonerate innocent individuals and gather further knowledge to reconstruct the crime action (for example, by pattern analysis). Another part of information that biological traces may reveal is the alleged time frame when a crime was committed [1]. This estimation substantially contributes to the activity level proposition assessment as it is proposed by the “hierarchy of propositions” theory [2]. For these reasons, a procedure that allows to correlate the time of air exposure of a biological trace with its progressive degradation, is likely to provide considerable advantage in the resolution of violent criminal events. For estimation of the age of a bloodstain, several techniques have been investigated. Recent review by Bremmer [3] and Zadora [4] looked over the methods applied to this purpose, including high-performance liquid chromatography, electron paramagnetic resonance, atomic force microscopy, RNA degradation measurements, infrared and Raman spectrocopies. However, none of these methods is implemented in the forensic practice yet, because they are subjected to a variety of potential bias sources [5], require complex sample preparations and need to be performed in a laboratory setting [6]. An even more limited number of analytical techniques have been described for the age estimation of other biological traces [7,8].
The sole availability of latent traces, often in minimal amount, together with the presence of contaminants [9] and fluid mixtures, frequently makes the biological trace detection remarkably complex [10]. While it is requested that the suspected biological evidences are promptly detected and identified, traditional body fluid identification and analysis unfortunately present severe limitations, essentially due to the critical and/or degraded conditions in which these evidences are often found [3]. Moreover, their detection with traditional tests involves further degradation or even destruction of the sample [11]. In particular, the use of chemical reagents makes the process of latent trace visualization destructive, preventing the repetition of the analysis possibly requested. On the other hand, the DNA profiling performed on a minimal amount of biological fluids requires its careful preservation. Indeed, both sample contamination by the use of presumptive chemical tests and degradation by confirmatory analysis represent substantial threats when only minimal/latent traces are available [12]. All these issues push research toward the development of new techniques allowing to detect minute biological traces in a selective and non-destructive way, possibly using miniaturized and portable devices, enabling in-field activity.
The significant progress in the laser technology and the development of innovative detectors have greatly improved the spectroscopic methods for molecular characterization [11]. In this regard, infrared (IR) radiation between 1000 and 2500 nm (referred to as the near infrared – NIR – region) represents a very powerful tool for forensic sciences, especially when it is combined with hyperspectral imaging techniques (HSI-NIR). In particular, Edelman and coworkers provided the first suggestion of hyperspectral imaging application in forensics [13]. Later on, the suitability of NIR-HSI to identify the location of semen [14], vaginal fluid, and urine stains was practically demonstrated [15]. The inherent investigation of the spatial dimension allowed by HSI-NIR makes it highly valuable in the analysis of heterogeneous surfaces. In detail, the HSI-NIR data are organized in a four-dimensional matrix, often called “hypercube”, in which the x and y dimensions account for the spatial domain, while the z dimension represents the spectral one (reflectance values for each wavelength). The hypercube data processing using appropriate chemometric techniques allows the analyst to gain information on both the chemical nature of the substances present at the investigated surface and their location on it.
Recently, an analytical protocol based on HSI-NIR data was developed for the screening of various common substrates to highlight and identify various biological traces in the potential context of a crime scene [16]. In this study, a straightforward and reliable data processing for the extraction of the chemical information embodied within the spectra was proposed. This approach was based on calculating a normalized difference image (NDI), which provides a monolayer grayscale image maximizing the difference between the stain and the supporting material [17].
In the present study, such an analytical protocol was applied to biological evidences enabling the evaluation of trace degradation processes, like oxidation or carboxylation, related to the period of air exposure. The application of multivariate regression to the acquired NIR spectra provided an estimate of the exposure period, corresponding to the time elapsed from the moment the crime was committed, based on the degradation level of the biological trace.
The choice of robust and straightforward chemometric techniques for data processing pursues the same aim. In the legal field, the traces should ideally be analysed and interpreted at the crime scene, in the original context, with no chance of external contamination. In contrast, the analytical procedures currently used to highlight and detect the biological traces exploit chemical and/or optical methods, both involving significant contact with the sample [18]. Hyperspectral imaging is particularly interesting within this context, as it is suited for non-contact identification of evidence, minimizing the risk of trace contamination and destruction. Further advantages associated with the spectroscopic techniques include the speed of analysis, absence of solvents and samples pre-treatments, ability to discriminate and identify several biological fluids. All these aspects make the HSI-NIR technique particularly appropriate and promising to pursue the goal of biological traces characterization.
Section snippets
Experimental protocol
According to the scheme reported in Fig. 1, two tissues with different hydrophilic vs. hydrophobic properties, namely black cotton and black polyester fabrics, were selected to investigate potentially distinct interactions occurring between the biological fluids and the supporting materials depending on their nature and chemical features.
Three biological fluids were investigated, including blood, urine, and semen, as they represent the biological evidences most frequently found in crime scenes.
Biological traces on glass
Prior to the development of regression models, to model the characteristic evolution of each biological traces during the exposure time in the spectral region of interest, the absorption patterns of dehydrated fluids on glass were assessed with the aim of confirming the distinctive wavelengths for each trace under study. The most informative wavelengths, confirmed in such a way, are reported in a previous study [16]. In more detail, for blood, the band centred at 2280 nm was selected,
Conclusions
Several techniques have been explored during the last century to address the age determination of biological fluid stains. However, most of these studies were addressed to the aging of blood traces, leaving little room for the aging study of other biological matrices, such as dehydrated urine and seminal fluid, both being frequently found in the context of violent crimes. For the first time, this study systematically investigated the aging of various biological fluids – including blood, semen,
Credit author statement
Cristina Manis: Investigation, Visualization, Writing – original draft. Cristina Malegori: Conceptualization, Methodology, Formal analysis, Writing – original draft. Eugenio Alladio: Investigation, Resources, Writing – original draft. Marco Vincenti: Conceptualization, Project administration, Writing – review & editing. Paolo Garofano: Resources, Supervision. Filippo Barni: Validation, Resources, Writing – review & editing. Andrea Berti: Validation, Resources, Writing – review & editing. Paolo
Funding
Financial support provided by Università degli Studi di Genova (Research Project Curiosity Driven 2020: “3Depth – From 2D to 3D hyperspectral imaging exploiting the penetration depth of near-infrared radiation”, CUP: D34G20000100005) is gratefully acknowledged.
Declaration of competing interest
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Paolo Oliveri reports financial support was provided by University of Genova.
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