Forensic chemistry plays a crucial role in aiding law enforcement investigations by applying analytical techniques for the analysis of evidence. While bloodstains are frequently encountered at crime scenes, distinguishing between peripheral and menstrual bloodstains presents a challenge. This is due to their similar appearance post-drying. Raman spectroscopy has emerged as a promising technique capable of discriminating between the two types of bloodstains, offering invaluable probative information. Moreover, estimating the time since deposition (TSD) of bloodstains aids in crime scene reconstruction and prioritizing what evidence to collect. Despite extensive research focusing on TSD estimations, primarily in peripheral bloodstains, a crucial gap exists in determining the TSD of menstrual bloodstains. This study demonstrates how Raman spectroscopy effectively analyzes biological samples like menstrual blood, showing similar aging patterns to those of peripheral blood and provides proof-of-concept models for determining the TSD of menstrual blood. While this work shows promising results for creating a universal model for bloodstain age determination, further testing with more donors needs to be conducted before the implementation of this method into forensic practice.

Saliva is a common biological examination material at crime scenes and has high application value in forensic case investigations. It can reflect the suspect\'s time of crime at the scene and provide evidence of the suspect\'s criminal facts. Even though many researchers have proposed their experimental protocols for estimating the time since deposition (TsD) of saliva, there is still a relative lack of research on the use of microorganisms to estimate TsD. In the current study, the succession change of microbial community in saliva with different TsD values was explored to discern the microbial markers related to TsD of saliva. We gathered saliva samples from six unrelated healthy Han individuals living in Guizhou, China and exposed these samples to indoor conditions at six time points (0, 1, 3, 7, 15, and 28 days). Temporal changes of microbial compositions in these samples were investigated by 16S rRNA sequencing (V3-V4 regions). By assessing temporal variation patterns of microbial abundance at the genus level, four bacteria (Brucella, Prevotella, Pseudomonas, and Fusobacterium) were observed to show good time dependence in these samples. In addition, the hierarchical clustering and principal co-ordinates analysis results revealed that these saliva samples could be classified into t-short (≤7 days) and t-long (>7 days) groups. In the end, the random forest model was developed to predict the TsD of these samples. For the model, the root mean square error, R2, and mean absolute error between predicted and actual TsD values were 1.5213, 0.9851, and 1.1969, respectively. To sum up, we identified TsD-related microbial markers in saliva samples, which could be viewed as valuable markers for inferring the TsD of saliva.

In forensics, it is important to determine the time since deposition (TSD) of bloodstains, one of the most common types of biological evidence in criminal cases. However, no effective TSD inference methods have been established despite extensive attempts in forensic science. Our study investigated the changes in the blood transcriptome over time, and we found that degradation could be divided into four stages (days 0-2, 4-14, 21-56, and 84-168) at 4 °C. A random forest prediction model based on these transcriptional changes was trained on experimental samples and tested in separate test samples. This model was able to successfully predict TSD (area under the curve [AUC] = 0.995, precision = 1, and recall = 1). Thus, this proof-of-concept pilot study has practical significance for assessing physical evidence. Meanwhile, 11 upregulated and 13 downregulated transcripts were identified as potential time-marker transcripts, laying a foundation for further development of TSD analysis methods in forensic science and crime scene investigation.

Various body fluids such as blood, semen, vaginal secretions, and saliva are frequently encountered at crime scene. In cases of sexual assault, semen stains are one of the most reliable evidence of biological origin. In this study, our objective was to develop a method for estimating the time since deposition of semen stains on five different fabric types using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) Spectroscopy, with a focus on a time frame of up to 8 weeks. Semen samples from six different volunteers were dripped onto five distinct fabric materials, and ATR-FTIR measurements were obtained at 17 different time points. Principal component analysis (PCA) and partial least squares (PLS) methods were employed to differentiate semen stains on various fabric samples and estimate the age of semen stains. Models constructed using PCA and PLSR achieved high R2 values and low root-mean-square error (RMSE). While the performance varies depending on fabric types, it was observed that age estimation of semen stains can be made within following intervals: 0.39-0.76 days for 0-7 day range, 2.59-3.38 days for the 1-8 week range, and 3.98-8.1 days for the 0-56 day range. This study demonstrates the effectiveness of using ATR-FTIR spectroscopy in combination with chemometrics to estimate the age of human semen stains on various fabric types based on time-dependent spectral changes.

The analysis of genetic material may be the only way to identify an unknown person or solve a criminal case. Often, the conditions in which the genetic material was found determine the choice of the analytical method. Hence, it is extremely important to understand the influence of various factors, both external and internal, on genetic material. The review presents information on DNA and RNA persistence, depending on the chemical and physical factors affecting the genetic material integrity. One of the factors taken into account is the time elapsing to genetic material recovery. Temperature can both preserve the genetic material or lead to its rapid degradation. Radiation, aquatic environments, and various types of chemical and physical factors also affect the genetic material quality. The substances used during the forensic process, i.e., for biological trace visualization or maceration, are also discussed. Proper analysis of genetic material degradation can help determine the post-mortem interval (PMI) or time since deposition (TsD), which may play a key role in criminal cases.

An accurate method to estimate the age of a stain or the time since deposition (TsD) would represent an important tool in police investigations for evaluating the true relevance of a stain. In this study, two laboratories reproduced an mRNA-based method for TsD estimation published by another group. The qPCR-based assay includes four transcripts (B2M, LGALS2, CLC, and S100A12) and showed preferential degradation of the 5\' end over the 3\' end. In this study, the blood-specific marker ALAS2 was added to examine whether it would show the same degradation pattern. Based on our qPCR data several elastic net models with different penalty combinations were created, using training data from the two laboratories separately and combined. Each model was then used to estimate the age of bloodstains from two independent test sets each laboratory had prepared. The elastic net model built on both datasets with training samples up to 320 days old displayed the best prediction performance across all test samples (MAD=18.9 days). There was a substantial difference in the prediction performance for the two laboratories: Restricting TsD to up to 100 days for test data, one laboratory obtained an MAD of 2.0 days when trained on its own data, whereas the other laboratory obtained an MAD of 15 days.

Further steps toward understanding the time-related information contained within bloodstains found at the crime scene are rightly considered a top priority in forensic science. Contrary to widely held assumptions, the reason for the delayed exploitation of bloodstains dating methods in practice is not the lack of suitable analytical techniques for monitoring degradation processes. The problem lies in the variability of the environmental and circumstantial conditions, playing a vital role in the degradation kinetics of blood deposits. The present article demonstrates the possibility of breaking with current approaches based on absolute age estimations to finally answer time-centered questions in real forensic scenarios. The proposed novel framework for situating forensic traces in time is based on the likelihood ratio assessment of the (dis)similarity between the evidence decomposition and sets of reference materials obtained through supervised aging. In such a strategy, every dating procedure is constructed on a case-by-case basis to fit examined blood traces, thereby limiting the adverse influence of external factors on the validity of age estimations and providing a way for future crime scene implementation.

Interest in the human microbiome has grown in recent years because of increasing applications to biomedicine and forensic science. However, the potential for dating evidence at a crime scene based upon time-dependent changes in microbial signatures has not been established, despite a relatively straightforward scientific process for isolating the microbiome. We hypothesize that modifications in microbial diversity, abundance, and succession can provide estimates of the time a surface was touched for investigative purposes. In this proof-of-concept research, the sequencing and analysis of the 16 S rRNA gene from microbes present in fresh and aged latent fingerprints deposited by three donors with pre- and post-washed hands is reported. The stability of major microbial phyla is confirmed while the dynamics of less abundant groups is described up to 21 days post-deposition. Most importantly, a phylum is suggested as the source for possible biological markers to date fingerprints: Deinococcus-Thermus.

Being able to attest when a bloodstain was deposited at a crime scene can be invaluable to a prosecution process, and methods to provide that information have long been desired. Determining the Time since Deposition (TsD) of a trace would allow placing a subject both in space and time to the crime scene-or prove that a trace left by that person was unrelated to it because it was deposited before or after the time the crime had occurred. To this day, no method for TsD determination has made its way into routine forensic casework, mainly because of the numerous challenges that await when trying to understand and account for all the influencing and confounding factors that affect the aging process (such as, e.g., temperature, UV-light exposure, or humidity). Here, we present an untargeted metabolomics-based study using liquid chromatography high-resolution mass spectrometry (LC-HR-MS) and data-dependent acquisition to analyze blood samples aged under two distinctly different storage conditions over 48 weeks. Global differences in age- and storage-dependent changes in blood metabolomes were described, and TsD-classification strategies based on qualitative and quantitative assessment of molecular features (MFs) have been proposed. Based on the selected criteria to best predict the TsD, the dipeptide Phenylalanylalanine (PheAla) can be considered as a promising candidate for TsD prediction. In essence, changes in the blood metabolome dynamics showed a strong association with increasing TsD, but significant differences depending on storage conditioning were observed, facilitating the need to study further the influence of individual influencing factors on TsD determination.

As an effective supplement to the current forensic DNA typing and one of the research hotpots in forensic science, the in-depth mining and characterization of biological evidence can provide rich and reliable clues for case investigation. In this study, the time-dependent variations of transcriptome were confirmed in in vitro blood samples within 0-168 days and a random forest model was established to realize the classification of blood samples with different TSD (time since deposition). Meanwhile, significant differences were observed in the transcripts of blood samples with different smoking habits and genders within a certain time period. HLA-DRB1, HLA-DQB1 and HLA-DQA2 were identified as markers for smoking habit identification, while the transcripts for RPS4Y1 and EIF1AY from the non-recombining region of the Y chromosome (NRY) were identified as markers for male sex identification. Thus, this study provides a theoretical foundation and experimental strategy for establishing a transcriptome-based method for characterizing blood sample retention time and donor characteristics in the field of forensic investigation.
案件现场生物物证信息深度挖掘与刻画，可以为案件侦查、涉案人员查找提供丰富可靠线索，是当前法医DNA检验的有效补充，也是国内外法庭科学的研究热点之一。本研究以血液样本为研究对象，证实了0~168天内离体血液样本转录组变化的时间相关性，并建立随机森林模型实现不同离体时间血液样本分类。同时，进一步证实相同离体时间段内，不同吸烟习惯和不同性别供体来源的血液样本转录本具有显著差异，HLA-DRB1、HLA-DQB1和HLA-DQA2可以作为供体吸烟习惯判别标志，Y染色体非重组区(non-recombining Y, NRY)的转录本RPS4Y1和EIF1AY可以作为供体性别特征判别标志。本研究为法庭科学领域建立基于转录组分析的血液样本遗留时间和供体特征刻画方法提供了理论基础和实验依据。.