International Journal of Legal Medicine最新文献

MicroRNAs (miRNAs) have emerged as promising biomarkers for the identification of forensically significant body fluids, aiding crime scene reconstruction and the identification of biological material donors. However, despite their potential, inter-study discrepancies and lack of reproducibility have limited their forensic application, particularly in body fluid identification. A major challenge lies in the variability introduced by different nucleic acid extraction methods. This study aimed to evaluate the co-extraction performance and miRNA detection efficiency of three commonly used nucleic acid extraction kits (AccuPrep Genomic DNA Extraction Kit, QIAamp DNA Mini Kit, and miRNeasy Tissue/Cells Advanced Micro Kit) across five saliva input volumes (400 µL, 200 µL, 100 µL, 50 µL, and 25 µL). To assess yield, purity, robustness (CV%), and sensitivity, two quantification platforms were used, followed by a two-step reverse transcription quantitative polymerase chain reaction (RT-qPCR) protocol to evaluate the impact of extraction methods on miRNA expression. Our results demonstrate that both the extraction procedure and the quantity of input material significantly influences nucleic acid recovery. Additionally, we observe variations in miRNA levels depending on the extraction method used. Surprisingly, the kit designed specifically for miRNA extraction yielded relatively poor miRNA recovery. In contrast, the DNA extraction kit (AccuPrep Genomic DNA Extraction Kit) produced the highest nucleic acid yield with moderate purity and showed the lowest Cq values for miRNA targets, indicating better miRNA detection. These findings underscore the importance of the choice of extraction kit, as it can significantly influence both the yield and quality of nucleic acids detected, and the extension, accuracy and reliability of miRNA-based forensic analyses.

Body fluid/tissue identification (BFID) is a fundamental forensic task for determining the origin of biological evidence such as blood, saliva, and semen. While traditional BFID methods rely on enzymatic, immunological, or spectroscopic methods, the emergence of RNA profiling has expanded its capabilities to not only identify body fluid/tissue but also, to some extent, assign them to specific contributors. This review focuses on three fundamental biological characteristics of RNA molecules that underpin their applications: specificity, stability, and polymorphism (length, sequence, and expression variations). Furthermore, research progress in RNA-based fluid/tissue analysis is discussed, highlighting the applications of these properties and addressing the remaining challenges. This article provides a comprehensive overview of the principles and current state of RNA analysis for forensic body fluid/tissue identification and contributor assignment.

Sudden cardiac death is a leading cause of death in the 40-65 age group in industrialized countries. In approximately 70-80% of cases, it is attributable to atherosclerotic degeneration of the coronary circulation. This experimental study aims to evaluate the suitability of ultrasound for the morpho-functional characterization of the coronary circulation in ex situ hearts. The coronaries of six human hearts were cannulated with a vascular catheter, and an aqueous contrast medium was injected using an electric pump. The cannulated vessel underwent ultrasound scanning (US) for both morphological and functional study using US and color Doppler. Subsequently, a cardiopathological examination of each heart was performed. US and color Doppler allowed the characterization of the coronary vessels, the morphology of atherosclerotic plaques, the degree of vascular stenosis, and related dysfunctional, reduced or turbulent flow. Subsequent cardio-pathological examination confirmed the US findings. Preliminary results indicate coronary US as a promising diagnostic technique in cardio-pathology, as a preliminary screening test for subsequent targeted investigations, since it enables the pathologist to assess the dysfunctional implications of atherosclerotic disease on coronary flow. Future perspectives include extending the studied sample and comparing post-mortem US with other techniques commonly used for the study of coronary pathology.

Motorcycle crashes result in the deaths of hundreds of motorcyclists annually in Australia and Great Britain. To assist with investigations into the circumstances of such events, forensic practitioners may be asked to infer the context in which hard and soft tissue injuries were produced. At present, limited research exists relating to skeletal fracture patterns in motorcycle crash fatalities for forensic practitioners to compare their cases with. Therefore, this study evaluated fracture patterns across the whole-body of 200 deceased adult motorcycle riders and pillion passengers whilst considering the influence of contextual variables. Cases were obtained from the Victorian Institute of Forensic Medicine, Australia, and the East Midlands Forensic Pathology Unit, England, United Kingdom, between 2012 and 2020. Intrinsic and extrinsic variable data was gathered from medico-legal reports, while skeletal trauma data was recorded using post-mortem computed tomography scans. Descriptive statistics, modified Poisson regression and negative binomial regression were undertaken to investigate fracture patterning, including the effect of the different contextual variables. The study found skeletal trauma to be common, and often extensive, in deceased motorcyclists, with fracturing of the thorax (95%), lower limbs (69%), upper limbs (65%), and skull (64%) being particularly frequent. The variables shown to affect fracture patterning and the number of bones fractured comprised age, helmet use, impact type and object, speed and ejection status. This research may aid forensic practitioners in their investigations by facilitating an enhanced understanding of fracture patterning and causation in fatal motorcycle crashes.

Objectives: To assess the performance of automatic rib fracture detection of an existing deep learning (DL) model, nnDetection, on a postmortem (PM) CT scan dataset, and to identify the main factors of domain shift between clinical and PM CT imaging.

Background: Rib fracture detection and classification in forensic investigations is a time-consuming yet crucial task that can contribute to determine the cause of death. DL models are a promising tool, as recent research shows that radiologists using DL models can detect rib fractures in clinical CT scans at higher sensitivity and in shorter time.

Methods: A dataset of 50 PMCT scans (24% women; age: mean 61, range 19 - 96 years) was retrospectively collected and annotated, and used to train a first instance of the model, nnDetPM. Another instance of the model, nnDetClin, was trained on data from another dataset, RibFrac, consisting of 660 clinical CT scans (36% women; age: mean 55, range 21 - 94 years).

Results: On the PM testing set, nnDetPM achieved an average sensitivity of 70.2% and an average precision (at 0.1 intersection over union) of 78.1%, whereas nnDetClin fell far behind at 19.8% average sensitivity and 25.5% average precision, indicating a substantial impact of the domain shift from clinical to PM CT data. Further inspection of the results showed that the main factors of this domain shift were the position of the arms and the presence of medical ware in the image acquisition area of the PMCT scans.

Conclusion: The performance of nnDetPM, with an average sensitivity of 70.2%, was notable and comparable to that of radiologists. However, more advanced techniques must be explored to decide if DL models can overcome the domain shift factors.

Intoxication cases involving new psychoactive substances (NPS) are known to provide various challenges for forensic toxicological case interpretation, starting with the identification of previously unknown substances. Furthermore, the pharmacological characteristics of these substances, including potency and metabolic processes, remain largely unstudied. In this particular medico-legal case, a 20-year-old man consumed clonazafone and fluoro-etonitazene, which were examined in blood by targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS). Additionally, a urine screening was conducted using LC-high-resolution mass spectrometry (HRMS) to investigate the metabolism of these substances, particularly clonazafone. Clonazafone was (semi-)quantified in urine (39 ng/mL), muscle tissue (3.0 ng/g), and stomach content (76'000 ng/mL), but could not be detected in peripheral blood, heart blood, and vitreous humor (lower limit of quantification: 0.1 ng/mL). Additionally, clonazepam (1.5 ng/mL) and its metabolite 7-amino-clonazepam (140 ng/mL), as well as amphetamine (110 ng/mL) and the designer-opioid fluoro-etonitazene (3.3 ng/mL) were found in blood. Within the HR screening, desglycylclonazafone, the intermediate of clonazafone that can be further converted into clonazepam, was detected in the stomach content and urine. Screening in urine has also revealed several metabolites of clonazafone. The cause of death was assumed to be a mixed drug intoxication with fluoro-etonitazene, clonazepam, and amphetamine.