Background: Accurate estimation of the postmortem interval (PMI) is critical in forensic death investigations. Traditional signs of death—algor mortis, livor mortis, and rigor mortis—are generally reliable only within the first two to three days after death, with their accuracy decreasing as decomposition progresses. This paper presents a systematic review conducted in accordance with PRISMA guidelines, aiming to evaluate and compare current methods for estimating the PMI. Specifically, the study identifies both traditional and modern techniques, analyzes their advantages, limitations, and applicable timeframes, critically synthesizes the literature, and highlights the importance of combining multiple approaches to improve accuracy. Methods: A systematic search was conducted in the PubMed, Scopus, and Web of Science databases, following the PRISMA guidelines. The review included original articles and reviews that evaluated PMI estimation methods (through thanatological signs, entomology, microbial succession, molecular, imaging, and omics approaches). Extracted data included study design, methodology, PMI range, and accuracy information. Out of the 1245 identified records, 50 studies met the inclusion criteria for qualitative synthesis. Results: Emerging methods, such as molecular markers, microbial succession, omics technologies, and advanced imaging show improved accuracy across extended postmortem intervals. RNA degradation methods demonstrated higher accuracy within the first 72 h, while entomology and microbial analysis are more applicable during intermediate and late decomposition stages. Although no single method is universally reliable, combining traditional and modern approaches tailored to case-specific factors improves overall PMI estimation accuracy. Conclusions: This study supports the use of an integrative, multidisciplinary, and evidence-based approach to improve time-since-death estimation. Such a strategy enhances forensic outcomes by enabling more precise PMI estimates in complex or delayed cases, increasing legal reliability, and supporting court-admissible expert testimony based on validated, multi-method protocols.

Background and Objectives: Periodontitis is a common chronic inflammatory disease and a leading cause of tooth loss worldwide. Traditional diagnostic methods, such as probing and radiographic assessment, are retrospective and fail to detect ongoing disease activity. In recent years, salivary biomarkers and oral microbiome profiling have emerged as promising tools for earlier detection and precision-based management. The aim of this review is to synthesize current evidence on salivary and microbiome-derived biomarkers in periodontitis and to evaluate their translational potential in diagnostics and therapy. Materials and Methods: A narrative review was performed using PubMed, Scopus, and Web of Science to identify studies published between 2020 and 2025. Search terms included periodontitis, salivary biomarkers, oral microbiome, dysbiosis, and precision therapy. Priority was given to systematic reviews, meta-analyses, and translational studies that addressed diagnostic or therapeutic applications. Eligible publications included English-language original studies and reviews reporting on the diagnostic or therapeutic relevance of salivary or microbiome biomarkers in periodontitis. Results: Salivary biomarkers such as cytokines, matrix metalloproteinases (MMPs), oxidative stress markers, microRNAs, and extracellular vesicles (EVs) show consistent associations with disease activity and treatment outcomes. Oral microbiome studies reveal that both classical pathogens and community-level dysbiosis contribute to disease risk. Translational advances include chairside immunoassays, biosensors, lab-on-a-chip devices, and artificial intelligence (AI)-driven analyses. Biomarker-guided therapies—such as microbiome modulation, natural bioactive compounds, host-response modulation, and smart biomaterials—are being evaluated with increasing frequency in translational studies. Conclusions: By integrating salivary and microbiome biomarkers with novel diagnostic technologies and emerging therapies, this review complements existing systematic evidence and offers a translational roadmap toward precision periodontology.

Background: In sudden cardiac deaths (SCD), visceral adipose tissue has begun to manifest interest as a standalone cardiovascular risk factor. Studies have shown that epicardial adipose tissue can be seen as a viable marker of coronary atherosclerosis. This study aimed to evaluate, from a forensic perspective, the correlation between body mass index (BMI), heart weight, coronary and valvular atherosclerosis, left ventricular morphology, and the thickness of the epicardial adipose tissue (EAT) in sudden cardiac deaths, establishing an increased thickness of EAT as a novel risk factor. Methods: This is a retrospective case–control descriptive study that included 80 deaths that were autopsied, 40 sudden cardiac deaths, and 40 control cases who hanged themselves and had unknown pathologies prior to their death. In all the autopsies performed, the thickness of the epicardial adipose tissue was measured in two regions of the left coronary artery, and the left ventricular morphology, macro/microscopically quantified coronary and valvular atherosclerosis, and weight of the heart were evaluated. Results: This study revealed a higher age in the SCD group (58.82 ± 9.67 vs. 53.4 ± 13.00; p = 0.03), as well as a higher incidence in females (p = 0.03). In terms of heart and coronary artery characteristics, there were higher values of BMI (p = 0.0009), heart weight (p < 0.0001), EAT of the left circumflex artery (LCx) (p < 0.0001), and EAT of the left anterior descending artery (LAD) (p < 0.0001). In the multivariate analysis, a high baseline value of BMI (OR: 4.05; p = 0.004), heart weight (OR: 5.47; p < 0.001), EAT LCx (OR: 23.72; p < 0.001), and EAT LAD (OR: 21.07; p < 0.001) were strong independent predictors of SCD. Moreover, age over 55 years (OR: 2.53; p = 0.045), type Vb plaque (OR: 17.19; p < 0.001), mild valvular atherosclerosis (OR: 4.88; p = 0.002), and moderate left ventricle dilatation (OR: 16.71; p = 0.008) all act as predictors of SCD. Conclusions: The data of this research revealed that higher baseline values of BMI, heart weight, EAT LCx, and EAT LAD highly predict SCD. Furthermore, age above 55 years, type Vb plaque, mild valvular atherosclerosis, and left ventricle dilatation were all risk factors for SCD.

Background/Objectives: Forensic dental determination plays a central role in human identification, age estimation, and trauma analysis in medico-legal contexts. Traditional approaches—including clinical examination, odontometric analysis, and radiographic comparison—remain essential but are constrained by examiner subjectivity, population variability, and reduced applicability in fragmented or degraded remains. Recent advances in cone-beam computed tomography (CBCT), three-dimensional surface scanning, intraoral imaging, and artificial intelligence (AI) offer promising opportunities to enhance accuracy, reproducibility, and integration with multidisciplinary forensic evidence. The aim of this review is to synthesize conventional and emerging approaches in forensic odontology, critically evaluate their strengths and limitations, and highlight areas requiring validation. Methods: A structured literature search was performed in PubMed, Scopus, Web of Science, and Google Scholar for studies published between 2015 and 2025. Search terms combined forensic odontology, dental identification, CBCT, 3D scanning, intraoral imaging, and AI methodologies. From 108 records identified, 81 peer-reviewed articles met eligibility criteria and were included for analysis. Results: Digital methods such as CBCT, 3D scanning, and intraoral imaging demonstrated improved diagnostic consistency compared with conventional techniques. AI-driven tools—including automated age and sex estimation, bite mark analysis, and restorative pattern recognition—showed potential to enhance objectivity and efficiency, particularly in disaster victim identification. Persistent challenges include methodological heterogeneity, limited dataset diversity, ethical concerns, and issues of legal admissibility. Conclusions: Digital and AI-based approaches should complement, not replace, the expertise of forensic odontologists. Standardization, validation across diverse populations, ethical safeguards, and supportive legal frameworks are necessary to ensure global reliability and medico-legal applicability.

Background: Sudden cardiac death (SCD) is a major public health concern worldwide, affecting all age and social groups. Methods: In this retrospective study, of the 8265 autopsies performed in the Institute of Legal Medicine, 1618 cases of SCD were included. The aim of this study is to identify demographic characteristics, etiological factors, epidemiological characteristics and risk factors that lead to SCD. Results: The highest incidence of SCD was in age group 40–69 years (65.0%), 71.6% of this age group being men. Of the total number, 32.1% (520) occurred in the emergency room. The most common cause of sudden death is represented by coronary atherosclerotic disease, reported in 89.8% (1453) of cases, tricoronary lesions being found in 60% (870) of cases. Etiological factors of SCD encountered during autopsies were acute myocardial infarction in 13.9% (225), dilated cardiomyopathy 43.9% (710), cardiac hypertrophy 579 (36.07%), pericarditis 1.9% (30), myocarditis 1.73% (28) and adipositas cordis 5% (81). Along with epicardial fat and BMI, alcohol consumption was recorded in 17.9% (290), this being a potential trigger. Conclusions: Based on forensic autopsy and histological findings, a wide variety of factors are involved in the etiopathogenesis of SCD, some of which can be eliminated through preventive measures implemented early.

Background: Sudden cardiac death (SCD) is a significant global public health issue and the leading cause of death worldwide. Its etiopathogenesis is complex and multilayered, involving dynamic factors interacting with a preexistent cardiovascular pathology, frequently unknown, and resulting in cardiac rhythm disorders and cardiac arrest; Methods: This study conducted a retrospective descriptive analysis over a one-year period, identifying 321 autopsy cases of sudden deaths from the Institute of Legal Medicine in Mures County, Romania, in 2019. From the 321 sudden death cases, 189 autopsy reports were selected for analysis based on inclusion and exclusion; Results: The autopsies had a mean age of 61.16 years and included 140 males and 49 females. No significant differences were found between the silent myocardial infarction (SMI) and no-SMI groups regarding demographic data. The SMI group exhibited higher thickness of LV (left ventricle), IV (interventricular septum), EAT LCx (epicardial adipose tissue at left circumflex artery), EAT LAD (epicardial adipose tissue at left anterior descending artery), heart weight, and BMI (body mass index). The left coronary artery showed a higher incidence of type V plaques, while the right coronary artery showed higher incidences of type V and type VI plaque. The SMI group also exhibited a higher incidence of moderate and severe valvular atherosclerosis, severe left ventricle dilatation, and a lower incidence of mild left ventricle dilatation. In addition, the SMI group showed a higher presence of contraction band necrosis on histological examination. Multivariate analysis revealed that type V and type VI plaques for the right and left coronary arteries, moderate and severe valvular atherosclerosis, severe left ventricle dilatation, heart weight, EAT LCx, EAT LAD, LV thickness, IV thickness, BMI, and the presence of contraction band necrosis are all independent predictors of SMI; Conclusions: The findings suggest that SCD is a complex condition, and its etiopathogenesis involves dynamic factors interacting with pre-existing cardiovascular pathology. The risk factors of SCD are similar to those of ischemic heart disease. The findings of this study could guide clinicians in identifying patients at risk of SCD and implementing preventive measures.