Bloodstain Metabolite Markers: Discovery and Validation for Estimating Age of Bloodstain within 7 Days

Raman Spectroscopy for the Time since Deposition Estimation of a Menstrual Bloodstain

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.

Alkaline Phosphatase for Estimating the Time since Deposition of Blood Fingerprints by Scanning Electrochemical Microscopy

Blood is one of the most frequent and valuable traces encountered at crime scenes, where knowing the time since deposition (TSD) of bloodstains tremendously assists forensic experts to screen out crime-related evidence and aids in the reconstruction of the event sequence. Although increasing proof-of-concept methodologies for investigating the TSD of bloodstains have been reported, there is still no accepted strategy in forensic practice as the aging mechanism involves complex components, leading to the inaccuracy of the estimation results. Herein, an endogenous biomarker of alkaline phosphatase (ALP) was chosen to investigate the TSD by scanning electrochemical microscopy (SECM). Results demonstrate that the ALP activity acquired via SECM lateral scan assay exhibited a clear decrease over time, and a similar trend was observed on both poly(vinylidene fluoride) (PVDF) membrane and glass, with the aging kinetics on PVDF membrane being faster than glass. By means of quantitatively calculating the flux of generated p-aminophenol (PAP), we established the aging curve and realized the TSD estimation of blood fingerprints (BFPs) that was unable to be distinguished via optical measurements. Intriguingly, the as-obtained estimation accuracy ranged from 74.6 to 93.7%, proving the possibility of using an ALP biomarker and SECM. More appealingly, the predicted TSDs were capable of accurately differentiating the deposition sequence of overlapping BFPs, which was hardly achieved by optical means. Therefore, this proof-of-concept strategy demonstrates the value of SECM as a forensic tool and opens possibilities for revealing multidimensional information about crime.

Untargeted Metabolomics Profiling for Determination of the Time since Deposition of Biofluids in a Forensic Context: A Proof-of-Concept for Urine, Saliva, and Semen in Addition to Blood

In a criminal trial, the reconstruction of a crime is one of the fundamental steps of the prosecution process. Common questions, such as what happened, where and how it happened, and who made it happen, need to be solved. Biological evidence at crime scenes can be crucial in the determination of these fundamental questions. One of the more challenging riddles to solve is the when? A trace left at a crime scene can prove a person's presence at the crime scene. Knowledge about when it was deposited there, the time since deposition (TsD), would allow linking the person in space and time to the site. This could fortify allegations against a suspect or discharge accusations if proven to be outside of the temporal boundaries where a suspected crime had occurred. Determining the TsD has yet to become routine forensic casework, despite recent research efforts, especially for blood traces. However, next to blood, other biological traces are also commonly encountered in crime scenes. We here present a study to profile the metabolomes of artificially aged dried body fluid spots of blood, semen, saliva, and urine over 4 weeks by liquid chromatography high-resolution mass spectrometry and data-dependent acquisition. All four body fluids (BFs) exhibited diverse time-dependent changes, and a large number of molecular features (MF) were associated with TsD. Still, significant differences between the BFs were observed, limiting universal interpretability independent of the BF and facilitating a need to further study time-dependent changes of different BFs individually toward the goal of TsD estimation.

Effect of environmental conditions on bloodstain metabolite analysis

Establishing a correlation between environmental variables and chemical change can significantly improve the quality of research in multiple fields. Among various environmental variables, temperature and humidity are closely related to the rate of chemical reactions. This study aimed to confirm changes in metabolite markers that were previously discovered in other temperature and humidity environment conditions and to confirm the possibility that they could act as markers. After blood collection from the subjects and bloodstain preparation, the quantitative values of the bloodstain metabolites were confirmed (when the age of the bloodstain was within a month) under eight environmental conditions (4 °C/30%, 4 °C/60%, 25 °C/30%, 25 °C/60%, 25 °C/90%, 40 °C/30%, 40 °C/60%, and 40 °C/90%). Age-of-bloodstain estimation models were constructed to confirm the applicability of bloodstain metabolites as markers for bloodstain age in various environments. The average concentration of metabolite markers exhibited a decreasing trend with the age of the bloodstain, which transformed into an increasing trend from day 7 onwards. In terms of temperature and humidity, 25 °C and 90%, respectively, showed the most dissimilar metabolite change pattern compared to other conditions. The age-of-bloodstain estimation models developed here have an R-square value of up to 0.92 for each condition and an R-square value of 0.71 when all environmental conditions were combined. The findings herein highlight the immense potential of blood metabolites for field application, confirming the possibility of predicting metabolite changes from the rates of their chemical reactions and validating the importance of metabolites as age-of-bloodstain markers under various environmental conditions.

Discovery and validation of acetyl-L-carnitine in serum for diagnosis of major depressive disorder and remission status through metabolomic approach

Major depressive disorder (MDD) is one of the most common psychiatric disorders that accompany psychophysiological and mood changes. However, the pathophysiology-based disease mechanism of MDD is not yet fully understood, and diagnosis is also conducted through interviews with clinicians and patients. Diagnosis and treatment of MDD are limited due to the absence of biomarkers underlying the pathophysiological mechanisms of MDD. Although various attempts have been made to discover metabolite biomarkers for the diagnosis and treatment response of MDD, problems with sample size and consistency of results have limited clinical application. In addition, it was reported that future biomarker studies must consider exposure to antidepressants, which is the main cause of heterogeneity in depression subgroups. Therefore, the purpose of this study is to discover and validate biomarkers for the diagnosis of depression in consideration of exposure to drug treatment including antidepressants that contribute to the heterogeneity of the MDD subgroup. In the biomarker discovery and validation set, the disease group consisted of a mixture of patients exposed and unexposed to drug treatment including antidepressants for the treatment of MDD. The serum metabolites that differed between the MDD patients and the control group were profiled using mass spectrometry. The validation set including the remission group was used to verify the effectiveness as a biomarker for the diagnosis of depression and determination of remission status. The presence of different metabolites between the two groups was confirmed through serum metabolite profiling between the MDD patient group and the control group. Finally, Acetylcarnitine was selected as a biomarker. In validation, acetylcarnitine was significantly decreased in MDD and was distinguished from remission status. This study confirmed that the discovered acetylcarnitine has potential as a biomarker for diagnosing depression and determining remission status, regardless of exposure to drug treatment including antidepressants.