Search Results (48)

The 1992 cold case homicide of “Ina Jane Doe” illustrates how an interdisciplinary team worked to identify the decedent using a combined approach of skeletal re-analysis, updated forensic art informed by anthropologists’ input, archival research, and forensic investigative genetic genealogy. The original forensic art for “Ina Jane Doe” showed an over-pathologization of skeletal features and an inaccurate hairstyle; however, the case gained notoriety on internet true crime forums leading to speculation about the decedent’s intellectual capacity and physical appearance. The “Ina Jane Doe” case demonstrates the importance of advocating for skeletal re-analysis as more robust methods and technologies emerge in forensic science, as well as the impact of sustained public interest in cold cases. In this case, continuous public interest and online speculation led to anthropologists constructing a team of experts to correct and revise narratives about the decedent. Forensic anthropologists’ role in cold cases may include offering skeletal re-analysis, recognizing and correcting errors in the original estimations of the biological profile, searching for missing person matches, and/or working collaboratively with subject matter experts in forensic art, odontology and forensic investigative genetic genealogy. Full article

Background/Objectives: Oral squamous cell carcinoma (OSCC) often presents at an advanced stage; therefore, the early detection of precursor lesions is crucial. However, the risk assessment of precursor lesions such as oral epithelial dysplasia (OED) remains challenging because of the subjectivity of histopathological grading. We aimed to identify molecular markers that enhance the diagnostic accuracy and prognostic stratification of OSCC and explore the differences in the molecular characterization of OED and OSCC using a few selected markers. Methods: A two-step diagnostic workflow was applied: (1) FISH evaluation of EGFR amplification and CDKN2A deletion to distinguish OED from OSCC and identify EGFR-dependent tumors, and (2) HRAS immunohistochemistry performed exclusively in EGFR-negative OSCCs to stratify EGFR-independent cases. Fluorescence in situ hybridization (FISH) was used to assess seven EGFR/cell cycle-related genes (CCND1, CDKN2A, EGFR, PIK3CA, PTEN, TP53, and 1p36 locus) in 117 formalin-fixed paraffin-embedded samples (66 OED and 51 OSCC) and 10 normal mucosa samples. HRAS expression was evaluated using immunohistochemistry (IHC) in 36 EGFR amplification-negative OSCCs samples. Results:EGFR amplification was frequent in OSCC, whereas CDKN2A deletion was common in OED. The EGFR-amplified/ CDKN2A-intact profile showed high specificity for OSCC and improved diagnostic performance (area under the curve = 0.77) when combined with the Ki-67 labeling index. It also predicted poor disease-free survival (hazard ratio [HR] = 5.08, p = 0.016) and overall survival (HR = 6.10, p = 0.047). Among EGFR-negative OSCCs, HRAS overexpression was associated with advanced-stage disease and a poor prognosis (HR = 6.15, p = 0.043). Conclusions:EGFR amplification was frequent in OSCC, and CDKN2A deletion was prevalent in OED, supporting their use as molecular markers for differential diagnoses. FISH for EGFR/CDKN2A and HRAS IHC can stratify OSCC by diagnosis and prognosis, enabling practical molecular subclassification, including EGFR-negative cases. Full article

Background and objectives: This study aimed to investigate the effects of familial Mediterranean fever (FMF)—a chronic inflammatory disease—on dental maturation regarding dental development using three dental age estimation methods. Methods: The orthopantomograms of 78 children diagnosed with FMF were compared with those of 78 systemically healthy control children. Demirjian, Willems, and Cameriere’s methods were used to estimate the dental age from seven teeth in the left mandible on the orthopantomograms. The data were analyzed using R statistical software. Results: The mean difference between dental age (DA) and chronological age (CA) using the Demirjian method was 0.646 in the control group and 0.753 in the FMF group (p = 0.595). For the Willems method, the mean DA versus CA difference was 0.283 in the control group and 0.322 in the FMF group (p = 0.835). Regarding the Cameriere method, the mean difference between DA and CA was −0.399 for the control group and −0.435 for the FMF group (p = 0.863), indicating no significant differences. At the ±1-year threshold, the Willems method showed the highest accuracy (69.87%), followed by the Cameriere method (66.67%), whereas the Demirjian method had the lowest accuracy (54.49%). These results suggest that the Willems method provides a more reliable estimate of chronological age within a ±1-year margin compared with the other two methods. Conclusions: Of the dental age estimators, the Willems method gave the closest age estimates. The Demirjian method overestimated the chronological age in both healthy children and children with FMF. For Turkish children receiving regular colchicine therapy, dental maturation was unaffected by FMF, suggesting that effective inflammatory control might preserve odontogenesis. Full article

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. Full article

Artificial Intelligence, especially Convolutional Neural Networks (CNN), is gaining importance in health sciences, including forensic odontology. This study aimed to systematically analyze elements for automated dental status registration on OPGs using CNNs, on different image segments and resolutions. A dataset of 1400 manually annotated digital OPGs was divided into train, test, and validation sets (75%–12.5%–12.5%). Pre-trained and from-scratch models were developed and evaluated on images from full OPGs to individual and segmented teeth and sizes from 256 px to 1820 px. Performance was measured by Sørensen–Dice coefficient for segmentation and mean average precision (mAP) for detection. For segmentation, the UNet Big model was the most successful, using segmented or individual images, achieving 89.14% for crown and 84.90% for fillings, and UNet with 79.09% for root canal fillings. Caries presented a significant challenge, with the UNet model achieving the highest score of 64.68%. In detection, YOLOv5x6, trained from scratch, achieved the highest mAP of 98.02% on 1820 px images. Larger image resolutions and individual tooth inputs significantly improved performance. This study confirms the success of CNN models in specific tasks on OPGs. Image quality and input (individual tooth, resolutions above 640 px) critically influenced model competence. Further research with from-scratch models, higher resolutions, and smaller image segments is recommended. Full article

Background: The phenomenon of pink teeth represents a notable observation in forensic science, although its interpretation remains complex and not directly attributable to a specific cause of death. Methods: This systematic review provides an updated and comprehensive overview of the morphological and histological mechanisms associated with this finding, with a focus on hemoglobin diffusion and pigment accumulation during putrefaction rather than on detailed biochemical pathways. Results: Environmental conditions, especially high humidity and moderate temperatures, are identified as key facilitators. The synthesis of the available evidence, including case reports, observational series, and experimental studies, confirms that pink discoloration is primarily linked to postmortem hemoglobin diffusion following erythrocyte breakdown and release of heme groups into dentinal structures. This process occurs more frequently under conditions that preserve hemoglobin and facilitate its migration into dental tissues. Importantly, pink teeth have been documented across a wide spectrum of postmortem scenarios, such as hanging, drowning, carbon monoxide poisoning, and prolonged exposure to humid environments, indicating that their presence is neither pathognomonic nor exclusively associated with a specific cause of death. Assessment methods include semi-quantitative visual scoring systems (e.g., SPTC and SPTR), spectrophotometric assays, and histochemical analyses for hemoglobin derivatives. Recent advances in digital forensics, particularly micro-computed tomography and artificial intelligence–based segmentation, may further support the objective evaluation of chromatic dental changes. Conclusions: This review underscores the need for standardized approaches to the identification, classification, and analysis, both qualitative and quantitative, of pink teeth in medico-legal practice. Although not diagnostic in isolation, their systematic study enhances our understanding of decomposition processes and contributes supplementary interpretive data in forensic investigations. Full article

Objective: This study aimed to evaluate the photobiomodulatory (PBM) effects of low-power light-emitting diode (LED) irradiation on cultured human umbilical vein endothelial cells (HUVECs), focusing on changes in cellular metabolic activity and morphology. Materials and Methods: HUVECs were cultured and divided into three groups: control (no irradiation), red LED (655 nm), and blue LED (455 nm). Cells were irradiated once with a total energy dose of 4 J over 60 s. Cellular metabolic activity was assessed at 0, 1, 3, and 6 h post-irradiation using the WST-8 assay. Morphological changes were examined 3 h post-irradiation using rhodamine–phalloidin staining and confocal laser scanning microscopy. Results: Red LED irradiation significantly enhanced metabolic activity immediately and at 3 h post-irradiation compared to the control group. Blue LED irradiation showed a non-significant trend toward increased metabolic activity at 1 and 3 h. Morphometric analysis revealed increases in cell area, perimeter, and Feret diameter in both LED-irradiated groups, with more pronounced changes observed in the red LED group. Conclusions: Low-power red LED light (655 nm) effectively promotes metabolic activation and induces morphological changes in vascular endothelial cells, suggesting its potential application in angiogenesis and wound healing. Due to its safety and accessibility, LED-based PBM may serve as a promising therapeutic modality for soft tissue regeneration in both clinical and home-care settings. Full article

Background: It is important to accurately determine the legal age at which a person is considered and treated as an adult; in many countries, it is 18. With the increasing migration flow to European countries, accurate age estimation methods must be implemented. In this study, the third molar maturity (I_3m) index and mandible condyle cortication stage were tested to distinguish adult from non-adult Latvian individuals using dental panoramic radiographs. Methods: This study included 716 selected dental panoramic radiographs of patients between the ages of 14 and 22. The lower-left third molar apical root parts were analyzed, and the I_3m index was calculated. In addition, the condyle cortication stage was evaluated. Results: All logistic regression models achieved statistically significant results (p < 0.001). The accuracy was high for all groups (males: 0.90, females: 0.87, both genders: 0.89), and the sensitivity was lower than the specificity, particularly for females (sensitivity: 0.55). The I_3m index appears to be a strong predictor across all models, while the mandibular condyle cortication stage plays a more nuanced role, depending on sex and the stage of condyle maturation. A higher I_3m index value (greater than the cut-off of 0.095 in males) indicates a higher likelihood of being classified as a non-adult male for this model; however, in females, a cut-off point higher than 0.150 indicated a higher likelihood of being classified as a non-adult female. The new proposed cut-off values need to be tested on a new sample. Conclusions: The I_3m index is a reliable age estimation tool, and a modified cut-off value could be determined for each gender in Latvian individuals. The condyle cortication stage is a weak tool for chronological age estimation in dental panoramic radiographs. Full article

Immunohistochemically, ameloblastomas often express CD56; however, novel neuroendocrine markers such as synaptophysin (SYP), insulinoma-associated protein 1 (INSM1), and chromogranin A (CgA) remain unexplored. We analyzed 36 ameloblastoma specimens for CD56, SYP, CgA, and clusterin (CLU) and examined limited samples for INSM1 expression by performing immunohistochemistry, transmission electron microscopy, and reverse transcriptase-polymerase chain reaction. Our findings indicate that the limited cells were positive for CD56, SYP, CgA, INSM1, and CLU expression in 72% (26/36), 14% (5/36), 0% (0/40), 80% (4/5), and 22% (8/36) of the cases, respectively. CD56 expression correlated with older age, but not with subtype, SYP, and CLU expression. However, SYP-positive cases were exclusively found in CD56- and CLU-positive cases, and SYP and CLU expression were significantly correlated. Selected cases had dense-core granules and NCAM1 and SYP mRNA expression. This study is the first to suggest neuroendocrine differentiation in ameloblastomas, as indicated by SYP and INSM1 immunoexpression and the presence of dense-core granules, which are consistent with the recent World Health Organization classification of Head and Neck Tumors guidelines. SYP-positive and CgA-negative phenotypes may characterize neuroendocrine differentiation in ameloblastoma. Although the underlying molecular mechanism remains unclear, CLU expression may be associated with neuroendocrine differentiation. Full article

Background/Objectives: Dental age estimation is a vital component of forensic science, helping to determine the identity and actual age of an individual. However, its effectiveness is challenged by methodological variability and biological differences between individuals. Therefore, to overcome the drawbacks such as the dependence on manual measurements, requiring a lot of time and effort, and the difficulty of routine clinical application due to large sample sizes, we aimed to automatically estimate tooth age from panoramic radiographs (OPGs) using artificial intelligence (AI) algorithms. Methods: Two-Dimensional Deep Convolutional Neural Network (2D-DCNN) and One-Dimensional Deep Convolutional Neural Network (1D-DCNN) techniques were used to extract features from panoramic radiographs and patient records. To perform age estimation using feature information, Genetic algorithm (GA) and Random Forest algorithm (RF) were modified, combined, and defined as Modified Genetic–Random Forest Algorithm (MG-RF). The performance of the system used in our study was analyzed based on the MSE, MAE, RMSE, and R² values calculated during the implementation of the code. Results: As a result of the applied algorithms, the MSE value was 0.00027, MAE value was 0.0079, RMSE was 0.0888, and R² score was 0.999. Conclusions: The findings of our study indicate that the AI-based system employed herein is an effective tool for age detection. Consequently, we propose that this technology could be utilized in forensic sciences in the future. Full article

Artificial intelligence (AI) is an area of computer science that focuses on designing machines or systems that can perform operations that would typically need human intelligence. AI is a rapidly developing technology that has grabbed the interest of researchers from all across the globe in the healthcare industry. Advancements in machine learning and data analysis have revolutionized oral health diagnosis, treatment, and management, making it a transformative force in healthcare, particularly in dentistry. Particularly in dentistry, AI is becoming increasingly prevalent as it contributes to the diagnosis of oro-facial diseases, offers treatment modalities, and manages practice in the dental operatory. All dental disciplines, including oral medicine, operative dentistry, pediatric dentistry, periodontology, orthodontics, oral and maxillofacial surgery, prosthodontics, and forensic odontology, have adopted AI. The majority of AI applications in dentistry are for diagnoses based on radiographic or optical images, while other tasks are less applicable due to constraints such as data availability, uniformity, and computational power. Evidence-based dentistry is considered the gold standard for decision making by dental professionals, while AI machine learning models learn from human expertise. Dentistry AI and technology systems can provide numerous benefits, such as improved diagnosis accuracy and increased administrative task efficiency. Dental practices are already implementing various AI applications, such as imaging and diagnosis, treatment planning, robotics and automation, augmented and virtual reality, data analysis and predictive analytics, and administrative support. The dentistry field has extensively used artificial intelligence to assist less-skilled practitioners in reaching a more precise diagnosis. These AI models effectively recognize and classify patients with various oro-facial problems into different risk categories, both individually and on a group basis. The objective of this descriptive review is to review the most recent developments of AI in the field of dentistry. Full article

Forensic Odontology is a critical field within forensic science, with significant importance in legal contexts and the identification of victims in mass disasters or cases of abuse. This article focuses on the efforts made by the European University Cyprus (EUC) School of Dentistry to raise awareness among dental students regarding legal and forensic dentistry practices. Through voluntary visits to the Anthropological Laboratory of the Committee on Missing Persons (CMP) in Cyprus, students gain firsthand experience and insights into anthropological analysis for identifying missing individuals. These visits provide students with practical application opportunities, emphasizing record-keeping practices, oral tissue morphology analysis, and unique aspects of restorative work during identification processes. Feedback from participating students highlights the value of experiential learning in increasing awareness about forensic odontology’s importance and relevance in real-world scenarios. The initiatives undertaken by the EUC School of Dentistry contribute to enhancing legal and forensic dentistry awareness among future dental professionals in Cyprus. Full article

Recently, there has been a growing interest in using DNA methylation analysis for age estimation. Despite this growing interest, there is a scarcity of research on the potential of DNA methylation as a biomarker for age estimation in Indonesia. This study aims to investigate the applicability of ELOVL2, PRKG2, and EDARADD genes for forensic identification in the 11–20 age group among Indonesians. This research utilizes 43 archived blood samples from healthy individuals who underwent blood tests at the Gatot Soebroto Army Hospital (RSPAD) in Central Jakarta, Indonesia. The methylation-specific PCR (MSP) technique assessed the DNA methylation level. The key findings of this study include (1) a strong positive correlation between methylation levels in the ELOVL2 gene and age; (2) a strong negative correlation between methylation levels in PRKG2 and EDARADD genes with age; (3) the development of three linear regression formulas for age prediction; and (4) mean absolute error (MAE) values derived from this research, which are ±0.48 for ELOVL2 gene regression formula, ±0.58 for PRKG2 gene regression formula, and ±0.72 for EDARADD gene regression formula. In summary, this study explores the potential of DNA methylation analysis for age estimation in Indonesia, focusing on ELOVL2, PRKG2, and EDARADD genes in the 11–20 age group. The findings underscore the applicability of DNA methylation analysis in forensic identification and age estimation, paving the way for future research in this field. Full article

Post-mortem interval (PMI) estimation remains one of the major challenges in forensic practice, especially for late PMIs beyond 7–10 days after the death of the subject. In 2022, an innovative method to investigate the occurrence of mutations induced by the death of a subject in the DNA of post-mortem dental pulps at different PMIs was developed, applying a next-generation sequencing (NGS) analysis. The present study aims to apply the same method of analysis to a small sample of teeth belonging to the same subject and analyzed at different PMIs/accumulated degree days (ADDs), and of teeth extracted from different subjects but analyzed at the same PMI/ADD to verify the repeatability of the results obtained in relation to the time elapsed since death. A total of 10 teeth were collected from 6 patients (3 males and 3 females) with PMI varying from 8 to 35 days, and ADD from 157.4 to 753.8. We found 1754 mutations in 56 genes, with more than 700 mutations having a prevalence > 5% and more than 300 variants considered of interest for the purposes of the study. Mutations that were not present at lower PMIs but manifested in later PMIs in pulps belonging to the same subject demonstrate that they can only have been acquired by the subject after death and according to the time elapsed since death. In total, 67 somatic mutations in 29 out of the 56 genes of the used panel occurred in a fashion that allows an association with specific PMI/ADD ranges (within 8 days, between 17 and 28, and beyond 30 days after death). The results suggest that temperature and humidity could influence the rate of DNA degeneration in dental pulps, thus PMI should be estimated in ADD more than days. The preliminary validation supports the hypothesis that the innovative method could be a useful tool for estimating the post-mortem interval even beyond the first week after death, but further analyses are needed to customize a specific genetic panel for forensic investigations and verify the influence of degenerative processes of soft tissues surrounding dental elements on DNA degeneration of pulps. Full article

Dental anthropology provides a deep insight into biological, ecological and cultural aspects associated with human individuality, behaviour and living conditions and the environment. Our study uses a correlation analysis to test the metric relationships between tooth sizes and jaw dimensions and juxtaposes them with biological sex and stature. A sample of n = 100 dental casts was used to record metric dental data including the mesio-distal and bucco-lingual tooth crown diameters and nine upper and lower jaw dimensions. All crown diameters were highly correlated with both stature and biological sex, with the canines exhibiting the highest correlation. The majority of jaw dimensions exhibited similar correlations. Our results suggest that the differences between the sexes in most crown diameters and some jaw dimensions may be related to the stature of the individuals measured. Two groups of closely correlating features emerged among the jaw dimensions, differing in their degree of correlation with crown diameters and with sex. The results and insights obtained are highly relevant for evolutionary biology, dentistry, craniofacial research, bioarchaeology and forensic odontology. Full article