Search Results (139)

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

The secondary use of electronic health records is essential for developing artificial intelligence-based clinical decision support systems. However, even after direct identifiers are removed, de-identified electronic health records remain vulnerable to re-identification, membership inference attacks, and model extraction attacks. This study examined the balance between privacy protection and model utility by evaluating de-identification strategies and differentially private learning in large-scale electronic health records. De-identified records from a tertiary medical center were analyzed and compared with three strategies—baseline generalization, enhanced generalization, and enhanced generalization with suppression—together with differentially private stochastic gradient descent. Privacy risks were assessed through k-anonymity distributions, membership inference attacks, and model extraction attacks. Model performance was evaluated using standard predictive metrics, and privacy budgets were estimated for differentially private stochastic gradient descent. Enhanced generalization with suppression consistently improved k-anonymity distributions by reducing small, high-risk classes. Membership inference attacks remained at the chance level under all conditions, indicating that patient participation could not be inferred. Model extraction attacks closely replicated victim model outputs under baseline training but were substantially curtailed once differentially private stochastic gradient descent was applied. Notably, privacy-preserving learning maintained clinically relevant performance while mitigating privacy risks. Combining suppression with differentially private stochastic gradient descent reduced re-identification risk and markedly limited model extraction while sustaining predictive accuracy. These findings provide empirical evidence that a privacy–utility balance is achievable in clinical applications. Full article

Background: Individuals who are victimized and exploited by the heinous crimes of human trafficking (HT) access healthcare during their exploitation, yet gaps in education on HT content exist in prelicensure nursing programs. This study explored the impact of an HT simulation on nursing students’ preparedness in the identification of victims as well as their perceptions of the impact of this educational intervention on future practices. Methods: A quasi-experimental design with a qualitative component was used. A convenience sample of 120 nursing students were recruited. The participants completed a pretest survey, viewed a preparatory education video, and participated in the simulation followed by a debriefing, a 20-min video, and posttest survey. Results: More than 3/4 of the participants reported no previous exposure to this content. A paired sample t-test showed efficacy (p < 0.001) with a Cohen’s d > 0.8, illustrating an increase in knowledge gained. The qualitative data yielded four themes: eye-opening, educational and informative, increased awareness, and preparedness. Conclusions: Nurses are well-positioned to identify, treat, and respond to victims of HT. The findings underscore the critical need to incorporate comprehensive HT content into prelicensure nursing curricula. Through integration of an HT simulation, future nurses can be better prepared to address this pervasive issue, ultimately improving victim outcomes and ensuring progress towards UN Sustainable Development Goal 5 of Gender Equality and Goal 16 of Peace, Justice, and Strong Institutions. In addition, addressing this topic in prelicensure nursing education ensures that future nurses are not only clinically competent but also morally and emotionally prepared to handle the complexities of HT in their professional roles. Full article

Background/Objectives: When a relationship ends due to abuse, a favorable attitude toward reconciliation may become a risk factor. The objective of this study was to develop and validate an instrument to measure the attitude toward returning to an ex-partner. Methods: A pilot study was conducted to evaluate the dimensionality and psychometric quality of the items. The main study involved 55 women who had been victims of gender violence. Results: Following item analysis and assessments of reliability (α = 0.93) and validity, a unidimensional 16-item scale was developed. The instrument, named the “Attitude Toward Returning to an Ex-partner Scale” (ATRES), allows for the identification of predispositions to return to a relationship in which serious abuse has occurred. Moreover, the findings revealed that a heightened perception of danger, along with forgiveness directed toward oneself, the other person, and the situation, was associated with a less favorable attitude toward reconciliation. Conversely, high religiosity predisposed individuals to rekindle the relationship. Conclusions: The scale could serve to facilitate interventions, mainly in situations where restoring the relationship can be a risk. The assessment of the predisposition to forgive the ex-partner—namely, the individual who perpetrated the abuse—as well as the victim’s attitude toward re-engaging in the relationship, constitute important considerations for preventing revictimization. The ATRES is the first self-report measure designed to assist researchers and professionals in the precise assessment of specific beliefs and myths underlying the reinstatement of a relationship. Full article

Background/Objectives: Research has shown that those who experience childhood sexual abuse (CSA) are at increased risk of subsequent sexual revictimization. Multiple sexual victimizations can lead to higher rates of depression, anxiety, trauma, and suicidality. Prior research has yielded varying definitions of revictimization, including only accounting for revictimization that occurred in adulthood or multiple CSA episodes by the same perpetrator, or it has broadly assessed maltreatment without a specific focus on CSA. This study examined mental health outcomes in survivors of CSA who experienced sexual revictimization in childhood from a different perpetrator, comparing their mental health outcomes (i.e., depression, suicidal ideation, post-traumatic stress disorder (PSTD), hopelessness, guilt, and shame) to those who reported CSA by one perpetrator. Methods: Adult survivors of CSA (n = 627) completed an online survey describing their CSA experience, whether they experienced CSA by one or multiple perpetrators in childhood, and a series of mental health questionnaires. Results: Almost half of the sample reported CSA by more than one perpetrator in childhood (n = 267; 42.58%). Survivors who reported multiple CSA perpetrators reported significantly higher levels of depression, suicidal thoughts, PTSD, hopelessness, shame, and some facets of guilt in adulthood compared to those who reported CSA by a single perpetrator. Conclusions: Experiencing CSA by multiple perpetrators in childhood may lead to more negative mental health outcomes in adulthood. The findings emphasize the importance of early identification and intervention for individuals who experienced CSA. Full article

This study explores the emergent dynamics of knowledge sovereignty within organisations following data breach incidents. Using qualitative analysis based on Benoit’s image restoration theory, this study shows that employees do more than relay official messages—they actively shape information governance after a cyberattack. Employees adapt Benoit’s response strategies (denial, evasion of responsibility, reducing offensiveness, corrective action, and mortification) based on how authentic they perceive the organisation’s response, their identification with the company, and their sense of fairness in crisis management. This investigation substantively extends extant crisis communication theory by showing how knowledge sovereignty is shaped through negotiation, as employees manage their dual role as breach victims and organisational representatives. The findings suggest that employees are key actors in post-breach information governance, and that their authentic engagement is critical to organisational recovery after cybersecurity incidents. Full article

This review paper presents a comprehensive overview of DNA preservation in hard tissues (bones and teeth) for applications in forensic and archaeogenetic analyses. It presents bone structure, DNA location in bones and teeth, and extensive information about postmortem DNA location and preservation. Aged bones are a challenging biological material for DNA isolation due to their low DNA content, degraded DNA, and the potential presence of PCR inhibitors. In addition, the binding of DNA to the mineral matrix necessitates the inclusion of a demineralization process in extraction, and its contribution to the resulting increase in both DNA quality and quantity is explained. Guidelines and recommendations on bone sample selection to obtain higher DNA yields are discussed in terms of past, recent, and possible future recommendations. Interskeletal and intraskeletal differences in DNA yield are also explained. Recent studies have shown that current recommendations for the genetic identification of skeletal remains, including femurs, tibias, and teeth, may not be the most effective sampling approach. Moreover, when mass disasters and mass graves with commingled skeletal remains are considered, there is a greater possibility that the recommended set of skeletal elements will not be available for sampling and subsequent genetic testing. This review highlights interskeletal and intraskeletal variability in DNA yield, with a focus on studies conducted on poorly preserved skeletal remains, including both postwar (1945) victims from Slovenia and ancient human skeletons. Special emphasis is placed on anatomical differences and potential mechanisms influencing DNA preservation, as demonstrated in research on both modern and historical skeletons. Finally, the petrous part of the temporal bone and tooth cementum were reviewed in greater detail because they have been recognized as an optimal sampling type in both ancient DNA studies and routine forensic case analyses. Our experiences with the Second World War and archaeological petrous bones are discussed and compared to those of other bone types. Full article

This review presents an in-depth analysis of the synergistic role of molecular biology in advancing forensic entomology. The study discusses how insects associated with decomposing bodies provide critical data for estimating the post-mortem interval (PMI), and how molecular techniques improve species identification and trace analysis. The manuscript examines DNA-based methods such as RAPD, RFLP, and mitochondrial sequencing, along with innovative applications like gene expression profiling and entomotoxicology analysis. Additionally, it presents real case studies illustrating how molecular data from insects can be used not only to estimate PMI but also to identify victims or suspects through human DNA retrieved from insect tissues. These advances confirm the fundamental role of molecular biology in strengthening the reliability and applicability of forensic entomology in legal contexts. Full article

Purpose: Suicide is a leading cause of death among children and adolescents worldwide. This study examined the prevalence and characteristics of suicides among children and adolescents (aged ≤ 19 years) over a 13-year period in the broader area of Athens, Greece. Key aspects analyzed included victim demographics, circumstances surrounding the incidents, and methods employed. Methods: A retrospective analysis was conducted on autopsy cases performed at the Department of Forensic Medicine and Toxicology, National and Kapodistrian University of Athens, from 1 January 2011, to 31 December 2023. Results: Out of 5819 autopsies conducted between 2011 and 2023, 371 were classified as suicides. Among these, 12 cases (representing 3.2% of suicides) involved children and adolescents aged ≤ 19 years and met the study’s inclusion criteria for detailed forensic analysis. The average age of the victims was 17.7 ± 2.1 years (range: 14–19), with males representing 58.3% of cases. Hanging was the most common method of suicide (9 cases, 75.0%), followed by firearm use, falls from height, and hydrogen sulfide inhalation (one case each). Death occurred in the home in 10 cases (83.3%), with 6 specifically taking place in the bedroom. Scars indicative of prior self-harming behavior were present in two cases (16.7%), while suicide notes were found in three cases (25.0%). Toxicological analysis revealed alcohol and cannabis use in one case, cannabis alone in one case, and alcohol alone in two cases. Four victims (33.3%) had a documented psychiatric diagnosis, with two of them under antidepressant treatment at the time of death. Conclusions: This study highlights the forensic value of autopsy-based investigations in unveiling hidden patterns of adolescent suicidality and informs targeted prevention strategies. Integrating medico-legal findings into public health responses may enhance early identification and intervention in vulnerable youth populations. Full article

At crime scenes, apart from the detection of blood, it may be important to determine whether a person was alive at the time of blood deposition. Based on the rapid onset of fibrinolysis after death, this pathway could be considered to identify potential biomarkers for postmortem blood. Fibrinolysis is the natural process that breaks down blood clots after healing a vascular injury. One of its products, D-dimer, could be a potential biomarker for postmortem blood. SERATEC^® (SERATEC^® GmbH, Göttingen, Germany) has developed the PMB immunochromatographic assay to simultaneously detect human hemoglobin and D-dimer. The main goals of this study were to assess the possibility of using this test to detect postmortem blood, evaluate D-dimer levels in antemortem, menstrual, and postmortem blood, and assess the ability to obtain STR profiles from postmortem blood. Except for one degraded sample, all postmortem blood samples reacted positively for the presence of D-dimer using the SERATEC^® PMB test. All antemortem blood samples from living individuals showed negative results for D-dimer detection, except for one liquid sample with a weak positive result, probably due to pre-existing health conditions. Menstrual blood samples gave variable results for D-dimer. The DIMERTEST^® Latex assay was used for semi-quantitative measurement of D-dimer concentrations, with postmortem and menstrual blood yielding higher D-dimer concentrations compared to antemortem blood. Full STR profiles were developed for all postmortem samples tested except for one degraded sample, pointing to the possibility of not only detecting postmortem blood at the crime scene but also the potential identification of the victim. Full article

The complexity for law enforcement and child protection agencies has been exacerbated by the proliferation of child sexual exploitation channels, facilitated by digital platforms and social media. Generative AI’s ability to analyze large datasets, recognize patterns, and generate new content makes it one of the potential solutions for detecting suspicious behavior and indicators of child sexual exploitation. This paper discusses the potential of generative AI to aid in the fight against pedophilic crimes by reviewing current research, methodologies, and challenges, as well as future directions and ethical concerns. Although the potential benefits are significant, applying AI to such a sensitive area presents numerous challenges, including privacy concerns, algorithmic bias, and potential misuse, which must be addressed carefully. Full article

The decision to remove a bullet from a gunshot victim depends on its location and associated medical risks, with surgical extraction often not indicated. Radiological imaging plays a vital role in assessing gunshot wounds and locating bullets, and it is essential in both clinical and forensic contexts. This narrative review examines the use of computed tomography (CT) for virtual bullet analysis, providing insights into shape, design, fragmentation, and material composition. Traditional 2D X-ray imaging, though commonly used, has limitations in accurately assessing caliber and position due to magnification and its 2D nature. In contrast, CT scans generate 3D reconstructions for detailed and precise examination, overcoming challenges such as metal artifacts with techniques such as extended Hounsfield unit (HU) reconstructions. These methods enhance the visualization of metal objects, allowing for better analyses of lodged bullets. Dual-energy CT further differentiates materials, such as lead and copper, using HU value differences at two energy levels. These advancements enable the virtual classification, shape analysis, and material identification of bullets in forensic investigations, even when the bullet remains in the body. As CT technology progresses, its forensic applications are expected to improve, providing more accurate and comprehensive differentiations of bullet types in future cases. Full article

Background/Objectives: Identification of human remains is of utmost importance for criminal investigations and providing closure to the families. The reconstruction of a biological profile of the individual will narrow down the list of candidates for identification. From another perspective, facial approximations performed by a forensic artist can provide investigative leads, with the identity being confirmed by primary or secondary methods of identification. In recent years, DNA analysis has evolved, trying to create a portrait of the perpetrator/victim based on External Visible Characteristics (EVCs), the color of the eyes, hair, and skin and Biogeographical ancestry (BGA), called DNA phenotyping. Despite these advances, currently, there are no studies integrating the biological profile performed by forensic anthropologists, the facial approximation created by forensic artists and EVCs determined by DNA. The goal of this work was to integrate these three investigative leads to enhance the possibility of human identification. Methods: Five donated remains from Mercyhurst were studied through these approaches: reconstruction of biological profile, facial approximation and estimation of EVCs based on previous studies. Results: Our results indicated the feasibility of integrating this biological profile and EVCs data into the facial approximation developed by the forensic artist, aiming to an enhance portrait of the remains. In a second phase of this project, the accuracy of the integrated facial approximation will be assessed. Conclusions: This study pointed out the importance of an interdisciplinary approach towards the identification of human remains, as well as the combination of current methods with new technologies. Full article

This study examines multi-lexical data sources, utilizing an extracted dataset from an open-source corpus and the Global Terrorism Datasets (GTDs), to predict lexical patterns that are directly linked to terrorism. This is essential as specific patterns within a textual context can facilitate the identification of terrorism-related content. The research methodology focuses on generating a corpus from various published works and extracting texts pertinent to “terrorism”. Afterwards, we extract additional lexical contexts of GTDs that directly relate to terrorism. The integration of multi-lexical data sources generates lexical patterns linked to terrorism. Machine learning models were used to train the dataset. We conducted two primary experiments and analyzed the results. The analysis of data obtained from open sources reveals that while the Extra Trees model achieved the highest accuracy at 94.31%, the XGBoost model demonstrated superior overall performance with a higher recall (81.32%) and F1-Score (83.06%) after tuning, indicating a better balance between sensitivity and precision. Similarly, on the GTD dataset, XGBoost consistently outperformed other models in recall and the F1-score, making it a more suitable candidate for tasks where minimizing false negatives is critical. This implies that we can establish a specific co-occurrence and context within the terrorism dataset from multiple lexical data sources in effectively identifying certain multi-lexical patterns such as “Suicide Attack/Casualty”, “Civilians/Victims”, and “Hostage Taking/Abduction” across various applications or contexts. This will facilitate the development of a framework for understanding the lexical patterns associated with terrorism. Full article

Background/Objectives: Kinship inference is commonly adopted in various forensic applications, but previous studies have often lacked precision. Methods: In this study, a new method for the nomenclature of kinship types, i.e., kinship chain (KC), was proposed, and then, six types of identity by state (IBS) scores were calculated for simulated and real families using four types of markers. Finally, several Bayesian network (BN)-based classifiers were constructed to investigate the efficiency of the kinship inference. Results: A total of 7, 22, 58, and 3 KCs were obtained for common first-, second-, and third-degree relatives and unrelated pairs, respectively. High accuracies could be achieved in distinguishing between related and unrelated pairs after combining the four types of genetic markers, with an accuracy of >99.99% for all 7 KCs of first-degree relationships and ~99% for 14 out of 22 KCs of second-degree relatives. When comparing relationships of the same degree, the accuracies were 99.28%, 42.31%, and 15.82% for first-, second-, and third-degree relationships, respectively. When it came to differentiating unspecific relationships, the overall accuracy was over 80%. All the results were validated on real family data. Conclusions: With the new nomenclature method of kinship types and the combination of autosomal and non-autosomal genetic markers, kinship inference can be realized with high accuracy and precision, which will be helpful in complex forensic cases, such as the identification of mass disaster victims. Full article