Forensic Science, Medicine and Pathology最新文献

A diagnosis of atherosclerotic cardiovascular disease is critical importance in forensic medicine, particularly because severe atherosclerosis is known to be associated with a high risk of sudden death. In South Korea, the assessment of coronary atherosclerosis during autopsy largely depends on the forensic pathologist's visual measurements, which may limit diagnostic accuracy. The objective of this study was to develop a deep learning algorithm for rapid and precise assessment of coronary atherosclerosis and to identify factors influencing the model's prediction of atherosclerosis severity. A total of 3,717 digital photographs were retrospectively extracted from a database of 1,920 forensic autopsies, with one image each selected for the left anterior descending coronary artery and the right coronary artery. The deep learning algorithm developed in this study demonstrated a high level of agreement (0.988, 95% CI: 0.985-0.990) and absolute agreement (0.986, 95% CI: 0.978-0.991) between predicted and ground truth atherosclerosis values on the test set. The model demonstrated strong overall performance on the test set, achieving a weighted F1-score of 0.904. However, the class-wise F1-scores were 0.957 for mild, 0.785 for moderate, and 0.876 for severe grades, indicating that performance was lowest for the moderate grade. Additionally, decomposition, stent implantation, and thrombi did not have a statistically significant impact on coronary atherosclerosis assessment except for calcification. Although enhancing model performance for moderate grades remains a challenge, this study's findings demonstrate the potential of artificial intelligence as a practical tool for assessing coronary atherosclerosis in autopsy photographs.

Age estimation is crucial in forensic sciences for victim identification, migration studies, and bioarchaeology. In subadults, it is based on maturational changes, while in adults, it relies on degenerative processes, reducing accuracy. Traditional methods, such as anthropological and dental approaches, are widely used, but recent advances in biochemical and molecular biology (BMB) have introduced epigenetic and biochemical analyses. Given the variability in biological aging, it is essential to evaluate and compare these methods for more precise and reproducible results. This article is a scoping review analyzing the accuracy of anthropological, dental, and BMB methods for estimating age in living individuals, cadavers, and adult skeletal remains. A scoping review following PRISMA-ScR guidelines was conducted in PubMed, Scopus, and WOS, covering studies from 2015 to 2024. Articles applying regression models for age estimation and reporting error metrics were included, while reviews and studies without precision data were excluded. Anthropological methods analyze degenerative changes in bone structures, such as the pubic symphysis and acetabulum, with error margins of 4-25 years. Forensic dentistry uses pulp-to-tooth ratios and secondary dentin deposition, yielding mean errors of 2.5-12.5 years. BMB methods, such as DNA methylation, telomere shortening, and aspartic acid racemization, offer accuracies of ± 3 to ± 10 years but require specialized equipment. Artificial intelligence enhances reproducibility, although standardization challenges remain. Age estimation in adults, particularly those over 40, remains challenging. Validating traditional methods, integrating AI, and applying multivariate molecular models can improve accuracy. A multidisciplinary approach is essential for forensic applications.

Sudden cardiac death due to an isolated right ventricular thromboembolism is an uncommon cause of death. In the reported case, a healthy, asymptomatic young male with no past medical history outside of obesity and his age was found unresponsive by a family member who suspected him to be sleeping. Examination of the heart at autopsy revealed a large serpiginous, organized and obstructive blood clot compromising most of the right ventricle with no other cardiac abnormalities and without any evidence of a pulmonary embolism. The patient was found to not have any history of substance abuse, genetic predispositions, kidney disease, or COVID-19 infection which has all been linked to ventricular thrombi.

This is a case report of a postmortem dismemberment (removal of the head) of a 44-year-old man (the perpetrator was 39-years-old) who died of natural causes (massive pneumonia). The case was neither a defensive nor an offensive mutilation but could be properly termed a "communication" dismemberment. The assumption that a victim of dismemberment is always a victim of homicide is not true in this case. To our knowledge, this is one of the very rare cases in which a perpetrator who has nothing to do with the death dismembered a body. Gerchow's question about whether there has ever been a case in which someone who had nothing to do with the death dismembered a body can be answered with a "yes."

Estimating the postmortem interval (PMI) is a crucial aspect of forensic death-related investigations. However, determining the time of death remains one of the biggest challenges in forensic medicine. This study aims to assess the potential of protein analysis as a vital tool and histopathological examination to evaluate the PMI. Fifty male rats were randomly distributed into five groups of 10. These rats were kept at room temperature (22 °C) with a relative humidity of 15% during the period between the time of death and organ removal. The kidneys and Livers were extracted at 0-, 24-, 48-, 72-, and 96-hour intervals. The β-catenin immunohistochemical analysis showed no immunoreactivity in either organ at 0 h, which increased to severe immunoreactivity at 96 h after death. Additionally, flow cytometry demonstrated a decline in liver and kidney Bcl-2 expression at 96 h, at 17.5% and 12.8%, respectively, as the postmortem period increased. Moreover, a histopathological examination of the Liver and kidney showed progressively greater degradation over time as the PMI increased, resulting in the loss of normal Liver and kidney architecture at 96 h. These findings suggest the potential use of specific proteins' autolytic alterations as definite diagnostic parameters for the PMI. Autolytic processes have a delayed onset and show a significant increase in progression rate at each time interval. Different organs suffer different rates of autolysis in correlation to their structure and enzymatic content. Further studies are required to evaluate the definite roles of β-catenin and Bcl-2 expression as predictive tools for future applications in humans based on extensive experimental studies.

The wave of migration that is observed worldwide, and especially the one in the Mediterranean region is contributing significantly to the contemporary humanitarian crisis. Shipwrecks are one of the most characteristic ways in which the migratory wave leads to mass casualties. Forensic practitioners nowadays are called upon to establish the cause of death, but also to identify victims of mass disasters, whose features may be significantly altered due to the extreme conditions in which they are found. On November 1st, 2022, a shipwreck of a boat full of immigrants, transiting from Turkey to Italy occurred at the southern region of Karystos, a coastal city located in Evoia island, Greece. The management of this case by our Department, involving multiple fatalities, including all relevant aspects (identification procedures, post-mortem examination) is presented. A brief review of the relevant literature is also included, with the aim of drawing conclusions on how a forensic department's workload might be affected by relevant incidents. Classical tools of conventional disaster victim identification protocols (e.g. fingerprint collection, dental examination, DNA profiling, etc.), may prove to be non-efficient as is such cases ante-mortem data are very difficult to obtain. International collaboration (Police, Diplomatic Corps) is a critical factor to increase the speed and the efficiency of the whole identification procedure. In the future, planning of a new protocol, adapted to Migrant-related cases, that will include more ante-mortem data (e.g. photographic material, social network or mobile phone data), may prove to help in such cases. It should be stressed that adoption of a universal identification protocol, along with training of all relevant personnel, are crucial steps to achieve increased readiness and handling-speed for future cases.

In recent years, bear attacks in Slovakia have increased, including two fatal attacks. The first fatality involved a 63-year-old man who was attacked by a brown bear while hiking with his family. He sustained grievous injuries to the left thigh and died at the scene shortly after the attack. In the second case, a 58-year-old man was found dead near a walking trail, and recent bear prints were found nearby. The man sustained various blunt and sharp injuries to the head and right upper extremity, strongly suggesting a bear attack. The cause of death was severance of the cervical spinal cord. Both victims presented with similar topographical and patterned injuries, which were consistent with biting and clawing. Sets of similar penetrating wounds arranged in rectangular patterns were also found on both victims. Differentiating such injuries from homicidal or self-inflicted wounds is of pivotal medico-legal importance. This paper provides a detailed analysis, visualization and assessment of wound morphology following fatal bear attacks.

Hyperspectral imaging (HSI) analyzes the reflected light spectrum of an object, providing insights into its material composition. In this experimental, prospective study, standardized hematomas were created in subjects and observed over 21 days using a portable hyperspectral camera, aiming to correlate changes in the reflected light spectrum with hematoma age and enable an objective method for age determination of hematomas. In 25 young and healthy subjects, a hematoma was induced by injecting 3 ml of autologous blood on the volar side of the forearm. The hematomas were documented over a 7-day period in 24-hour intervals and then for an additional 14 days in 48-hour intervals using a portable HSI camera covering the wavelength range from 400 nm to 1000 nm. The datasets from the hematomas were normalized using the spectrum of unaffected skin. Lasso regression models were trained on the normalized data to identify age-dependent changes in the reflection spectra and to make age predictions for hematomas of unknown age. The different regression models were compared based on their predictive accuracy and then evaluated against the actual hematoma age. The best age prediction model based on HSI recordings achieved a mean prediction error of 3.35 days over a 21-day observation period.Expanding the data set and methodology, as well as combining them with other techniques and testing on naturally occurring hematomas of various sizes and locations, are necessary steps to transfer this method into practical application.