International Journal of Legal Medicine最新文献

Rapid technological advancements have significantly enhanced DNA analysis. A key innovation is Next-Generation Sequencing (NGS), also known as Massively Parallel Sequencing (MPS), which followed classic Sanger (CS) sequencing. Compared to CS, NGS offers higher sensitivity, resolution, and throughput, making it particularly valuable for mitochondrial DNA (mtDNA) analysis. The high copy number, matrilineal inheritance, and non-recombining nature of mtDNA, especially its hypervariable regions (HV), make it highly relevant in forensic investigations. NGS has introduced streamlined protocols and improved low-level heteroplasmy detection in mtDNA sequencing. However, with any new technology, its informativeness and authenticity must be evaluated against traditional methods. This study compared mitotypes from degraded WWII skeletal remains recovered from a Slovenian mass grave, using the same DNA extraction method to minimize pre-sequencing variability. Femurs were mechanically and chemically cleaned, pulverized, and fully demineralized. DNA was extracted and purified using EZ1 Advanced XL and quantified with an in-house protocol. CS sequencing was performed using BigDye Terminator Kit v1.1 and ABI PRISM™ 3130 Genetic Analyzer, while NGS was conducted with the Precision ID mtDNA Control Region Panel and Ion GeneStudio™ S5 System. Comparison of mitotypes revealed that NGS identified low-level heteroplasmies undetectable by CS, particularly in length heteroplasmy. However, since Ion Torrent™ Suite 5.10.1 is prone to errors, certain NGS variants had to be disregarded.

In this study, 137 pairwise relationships representing four major relationship categories involving 49 Turkish individuals from four families were analyzed to evaluate the potential gain in the statistical power associated with likelihood ratios (LR) when using sequence-based versus length-based genotyping methods over the same STR loci coverage. To this end, the MPS Precision ID GlobalFiler NGS STR panel Kit and CE GlobalFiler™ PCR Amplification Kit were used. MPS-based analysis revealed the presence of 37 STR DNA sequence variations and / or the presence of 26 STR DNA sequence flanking region SNPs compared to the 150 unique alleles obtained with CE-based genotyping. Considering that most kinship LR calculation software do not readily take into consideration STR DNA sequence variants and STR DNA sequence flanking region SNP data that becomes available during MPS-based genotyping, an alphanumeric allele re-coding system was implemented to incorporate such additional STR isoallelic data to the already available allele calls. Over all the four major relationship categories analyzed, a significant increase in the mean combined LR (cLR) was observed when going from CE-based to MPS-based typing, whereby a 78.08 to 7,864,630.60-fold increase was noted. More specifically, in 134 out of the 137 pairwise relationships analyzed, MPS-based cLR values were higher than those calculated using CE-based data. While the mean cLR was >1,000 for three out of the four major relationship categories when using CE, the only exception being the third degree relationships, the mean cLR was >1,000 for all the four major relationship categories when using MPS. Notably, the mean cLR obtained for the third degree relationships was 47.61 with CE and 3,717.31 with MPS. In comparison with CE-based genotyping, when fully taken into account as proposed in the current study, the DNA sequence variation data afforded by MPS-based genotyping led to a statistically significant gain in terms of cLR values obtained. The use of MPS for cLR calculations had the most impact for both the second and third degree relationships, the two complex / distant type analyzed, hence further underscoring the prospects for MPS in kinship analysis. While the current study demonstrated that cLR is likely to increase substantially upon going from CE to MPS genotyping over the same loci coverage for a given case, when the additional DNA sequence variances are also taken into consideration, further increases are expected due to the more diverse type of forensic markers and even wider loci coverages used by MPS kits.

Detecting gunshot residues (GSR) plays a crucial role in forensic science and forensic medicine by providing important insights into the shooting distance, the shooter, as well as the type of weapon and ammunition used. Detection of GSR on dark surfaces is often impossible on site, and traditional methods such as tape-lift techniques with adhesive films or scanning electron microscope tabs might destroy the GSR pattern at the crime scene during their application. Infrared (IR) photography has proven particularly effective in detecting GSR on dark surfaces, enabling the preservation of the GSR pattern before applying destructive methods. This study aimed to examine how the type of ammunition and the presence of bloodstains affect GSR detection and differentiation using IR photography. 15 types of leaded and 5 types of lead-free 9 mm Luger ammunition were fired onto white cotton fabric and dark-blue denim fabric using the same firearm model, with an additional 14 samples being stained with blood. Resulting GSR patterns varied depending on the ammunition type and fewer GSR particles were visible on denim fabric, even in IR photography, compared to white cotton fabric, but still achieving reliable results comparable to the standard tape-lift method. In addition to the known ability of IR photography to detect GSR from leaded ammunition on clean surfaces, our findings demonstrate for the first time that GSR from lead-free ammunition, as well as GSR on blood-contaminated surfaces can be reliably visualized. In conclusion, IR photography provides a robust, easy-to-use and non-destructive tool for GSR detection, with the distinct benefit of allowing immediate on-site visualization of GSR patterns prior to any laboratory processing. With the use of the custom-made Python script (openly accessible on Github), a quantitative evaluation of GSR comparable to the tape-lift method is a further enhancement in this aspect.

Stiffness and plasticity of human tissues are routinely assessed during forensic autopsy and have recently been identified as a promising metric for estimating time since death in animal models. In this study, the biomechanical state of the human liver is investigated concerning pathology, age at death, sex, liver weight, autolysis, and blood congestion. Additionally, its use for biomechanical time since death estimation is evaluated. The storage, loss, and complex shear moduli of 54 human liver parenchyma samples collected during routine forensic autopsies, were determined using a rheometer. All samples were microscopically analyzed for signs of pathology, autolysis, and blood congestion. High-grade fatty liver samples (n = 6) exhibited significantly higher storage moduli, and complex shear moduli compared to healthy (n = 27), low-grade fatty liver (n = 14), and cirrhotic (n = 7) samples (p ≤ 0.02). High-grade fatty liver samples also had significantly higher loss moduli compared to healthy and cirrhotic samples (p ≤ 0.04). The rheological properties of the human liver were unrelated to age at death (p ≥ 0.26), liver weight (p ≥ 0.13), and sex (p ≥ 0.32). Autolysis significantly increased the loss moduli of healthy liver samples (p = 0.01). Blood congestion significantly lowered the loss moduli of healthy (p = 0.03) and fatty (p < 0.01) samples, as well as storage moduli (p = 0.01), and complex shear moduli (p = 0.01) of fatty samples. A significant positive correlation between the post-mortem interval and the loss modulus was observed for healthy samples, if only samples without signs of blood congestion were included (p = 0.02; n = 9). When stored at 4 °C for an average of eight days post-mortem, liver biomechanics was significantly altered by fatty infiltration, autolysis, blood congestion, and the post-mortem interval, while liver weight, age at death, and sex had no relevant impact.

Nowadays, according to the Istanbul Protocol, diagnostic tests are not an essential part of the clinical assessment of a person alleging torture or ill-treatment. In many cases, a medical history and physical examination are sufficient. However, literature evidence suggests a helpful role of diagnostic imaging in the allegation of evidence of torture, especially in the case of musculoskeletal injuries. The purpose of this narrative review is to highlight the role of imaging tests in suspected torture victims, emphasizing the role of these methods in establishing legal evidence of mistreatment. No specific imaging features are described in the literature, however, musculoskeletal imaging allows the detection of previous fractures, bone deformities, and tendon and ligament injuries. These are mainly due to blunt force injuries. MRI is the most helpful imaging tests to allegate evidence of Falaka. Imaging tests, particularly conventional X-rays and CT, are helpful in forensic investigations of when there is suspicion of retained foreign bodies, such as bullets or shrapnel, especially in cases where clinical examination is inconclusive. CT and MRI can show late sequelae of head trauma such as subdural hematomas, hygromas, old intracerebral bleeding, and hydrocephalus. The current literature highlights the importance of subjecting patients to imaging and specialists examinations to document evidence of torture and support the assessment of the degree of consistency with the reported history. These are second-level investigations that must be targeted to specific diagnostic questions and preceded by a thorough examination conducted by experts in the field using standardized methodologies, in line with the recommendations of the Istanbul Protocol. Imaging studies can bridge the gap between clinical examination and the patient's history.

Background: Heatstroke and fever-related deaths pose significant diagnostic challenges in forensic practice due to overlapping clinical manifestations. This study aims to identify specific molecular markers distinguishing these conditions through transcriptomic profiling of liver tissues in mouse models.

Methods: We established mouse models of severe heatstroke (exposure to 42℃ high-temperature environment) and fever (LPS-induced), and collected liver tissues for RNA sequencing. Differentially expressed genes (DEGs) were identified by DESeq2 and analyzed via GO and KEGG enrichment. Five candidate genes (Hspa1a, Hspa1b, Cyp7a1, Arrdc3, and G6pc) were validated by RT-qPCR and Western blotting.

Results: Transcriptome profiling revealed 5,567 DEGs between the two groups, including 142 heatstroke-specific and 254 fever-specific genes. Heatstroke was characterized by significant up-regulation of Hspa1a, Hspa1b, Cyp7a1, Arrdc3, and G6pc, implicating pathways related to protein homeostasis, glucose metabolism, and energy regulation. In contrast, fever predominantly induced immune- and inflammation-related genes such as Gbp2, Lcn2, Gm12250, Zbp1, and Ccrl2. Importantly, RT-qPCR and Western blot assays consistently validated the differential expression of the five key genes (Hspa1a, Hspa1b, Cyp7a1, Arrdc3, and G6pc), confirming their potential as reliable biomarkers for distinguishing heatstroke from fever.

Conclusion: This study provides comparative transcriptomic evidence distinguishing heatstroke from fever. The identified markers, particularly Hspa1a, Hspa1b, Cyp7a1, Arrdc3, and G6pc, may serve as potential forensic indicators for differentiating hyperthermia-related deaths, while also offering new insights into the molecular responses underlying heat stress and fever.

Olze et al. (2010) proposed the use of pulp involution, classified through stages, for dental age estimation by analyzing the lower third molar. However, the absence of this tooth may render the method inapplicable. The aim of this research was to validate the stages of root pulp visibility in the lower second molar for dental age estimation in the Brazilian population. A total of 1,190 orthopantomographs obtained from participants aged between 14.00 and 30.99 years were evaluated. The data were organized and analyzed using Microsoft Excel© (Microsoft Corp., Redmond, WA, USA) and R Studio (R Foundation, Vienna, Austria) software. The prediction of the age of majority achieved an accuracy of 72%. The probability of a person classified in stage 3 being over 18 years old was 100%; for stage 2, it was 95.26%; for stage 1, 82.88%; and for stage 0, 55.9%. Stage 3 was the only one to present a minimum age above 18 years, while stages 0, 1, and 2 had similar minimum and maximum ages. It is suggested that the stages of pulp involution be used for the assessment of age thresholds rather than for age estimation or the determination of a specific age range. It can be concluded that the stages of root pulp visibility in the lower second molar have the potential to be used for predicting the age of majority in Brazil, especially when used in association with other methods. Further studies are necessary in other countries to assess inter-population differences and the method's applicability across different regions.

Age inference is a key focus of forensic work, and traditional dental age inference methods require individuals to have a complete dental arch. However, congenital or acquired tooth loss may lead to random tooth loss in individuals, resulting in bias in age prediction. To address this issue, we validated and modified Bedek's tooth age inference method (a method for inferring the age of a population with missing teeth) for the first time in the Chinese population of children with complete dentition, congenital tooth loss, and acquired tooth loss, and constructed two new machine learning based tooth age inference methods (unilateral mandible and bilateral mandible tooth age estimation models) in this population. The unilateral mandible model was constructed using the remaining five teeth of the left mandible, excluding the lateral incisor and the second premolar of congenital tooth loss, and the first premolars and first molars of the acquired tooth loss, to estimate chronological age (the two most common types of missing teeth in the Chinese population, respectively). However, the actual types of missing teeth in the population are varied, and the information on the location of missing teeth is often replaced by the developmental morphology of the contralateral teeth. In order to augment the predictive information available to model, we further constructed a bilateral mandible model containing 14 individual mandibular teeth by filling in missing values using datawig. In the male agenesis validation group, the MAE values of the best bilateral, unilateral mandible model, and modified Bedek model were 0.641, 0.715, and 0.920, respectively. In females, the MAE values were 0.763, 0.785, and 0.990, respectively. In the male acquired tooth loss validation group, the MAE values of the three models were 0.793, 0.728, and 1.376, respectively. In females, the MAE values were 0.744, 0.779, and 1.094, respectively. Collectively, these novel odontological age-estimation frameworks provide robust, flexible solutions for forensic casework involving partial dentitions. By accommodating variable patterns of congenital and acquired tooth loss without sacrificing predictive precision, they constitute a critical advancement in the forensic identification of unknown or disputed-age individuals.

In forensic practice, accurately estimating post-mortem interval (PMI) is a crucially significant task, as it can provide key clues for cases in forensic medicine. However, it has also been a major challenge since ancient times. Currently, the traditional methods used in forensic medicine to infer PMI mainly include early post-mortem phenomena, corneal opacity, degree of gastric content digestion, and entomological analysis, but are significantly influenced by environmental factors and individual differences, presenting certain defects in terms of precision and applicability. With the advancement of modern molecular biology techniques, the application of gene expression analysis in the area of forensic medicine has gradually become a research hotspot. Moreover, the integration of machine learning algorithms and artificial intelligence (AI) can analyze multi-source data to construct prediction models, thereby improving the correctness of PMI inference and expanding its application scenarios. In this review, we elaborate on the research advancements, mainly in molecular biology or forensic molecular genetics of PMI estimation in forensic medicine. By systematically reviewing the latest research findings of molecular biology in PMI estimation and exploring its future directions, this review also endeavors to offer valuable references for forensic practitioners to improve the reliability of PMI inference in practical forensic potential applications in the future.

Microbial communities are critical drivers of mammalian carcass decomposition in natural ecosystems. Many studies have attempted to establish a microbial clock to estimate the postmortem interval (PMI); however, several obstacles remain to be solved. This study examines how age and insect activity influence microbial dynamics and emphasizes the role of 'rupture' in the decay. Notably, microbial diversity exhibited more pronounced shifts in immature cadavers, while insect activity suppressed overall diversity. Conversely, older age and insect colonization promoted the dominance of the Pseudomonadota phylum. We constructed random forest models (MAE: 0.62-0.95 days, R²: 0.976-0.987) for PMI estimation. These findings provide novel insights into refining PMI estimation in forensic contexts. Future research will further investigate the mechanisms behind these changes. Additionally, it will explore how other factors influence the decay, improving the accuracy and applicability of PMI estimation in various contexts.