Search Results (896)

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

Accurate post-mortem diagnosis of sepsis remains a critical challenge in forensic pathology, as conventional morphological findings often lack specificity. Circulating microRNAs (miRNAs) have been proposed as stable molecular biomarkers, yet their diagnostic value in cadaveric samples is still unclear. This exploratory study investigated the expression of three candidate miRNAs (miR-122-5p, miR-125b-5p, and miR-27a-3p) in post-mortem peripheral whole blood to assess their association with sepsis-related death versus non-infective controls. Out of 58 cases, 45 met quality-control criteria (26 sepsis-related deaths and 19 controls). miRNA expression was quantified by qRT-PCR, normalized to miR-320, and analyzed using ΔCt values. Group differences were evaluated using linear regression models with adjustment for age, sex, and post-mortem interval, with Benjamini–Hochberg correction for multiple testing. In adjusted models, miR-125b-5p and miR-27a-3p showed evidence of association with sepsis status, whereas miR-122-5p did not. These results support the feasibility of miRNA quantification in post-mortem samples and motivate validation in larger, independent cohorts and within multimodal post-mortem diagnostic frameworks. Full article

The flourishing of the Internet of Things (IoT) has not only improved our lives in smart homes and healthcare but also made us more susceptible to cyberattacks. Legacy intrusion detection systems are simply overwhelmed by the scale and diversity of IoT traffic, which is why there is a need for more intelligent forensic solutions. In this paper, we present a statistical technique, the Averaging Detection Method (ADM), for detecting attack traffic. Furthermore, the five deep learning models SimpleRNN, LSTM, GRU, BLSTM, and BGRU are compared for malicious traffic detection in IoT network forensics. A smart home dataset with a simulated DoS attack was used for performance analysis of accuracy, precision, recall, F1-score, and training time. The results indicate that all models achieve high accuracy, above 97%. BiGRU achieves the best performance, 99% accuracy, precision, recall, and F1-score, at the cost of high training time. GRU achieves perfect precision and recall (100%) with faster training, which can be considered for resource-constrained scenarios. SimpleRNN trains faster with comparable accuracy, while LSTMs and their bidirectional counterparts are better at capturing long-term dependencies but are computationally more expensive. In summary, deep learning, especially BiGRU and GRU, holds great promise for boosting IoT forensic investigation by enabling real-time DoS detection and reliable evidence collection. Meanwhile, the proposed ADM is simpler and more efficient at classifying DoS traffic than deep learning models. Full article

Background/Objectives: Many studies in the literature are increasingly focusing on how genes influence the development of individual behaviors and personality traits through genome sequencing. Most research indicates that complex behaviors and their characteristics are influenced by multiple genes, highlighting the crucial role of genetic studies in this field. Behavioral genetics, as a scientific discipline, investigates how genetic factors shape individuals’ behaviors and personality traits. The concepts of violence and aggression, observable in various contexts, have been extensively studied, with a particular focus on the underlying causes of these behaviors. In sports, where physical strength plays a significant role, regulations designed to prevent violent behaviors and aggressive attitudes contribute to the establishment of appropriate behavior patterns and discipline. Methods: This study aims to identify correlations between polymorphisms found in athletes and their responses to questionnaires, focusing on candidate genes known to influence personality and behavior traits, such as catechol-O-methyltransferase (COMT), serotonin transporter (5-HTT), monoamine oxidase (MAO-A), and serotonin 1A transporter (5-HT1A). A total of twenty licensed athletes participated in the study. Participants completed three standardized instruments: the Sportsmanship Behavior Scale (27 items), the Sports Emotion Scale (22 items), and the Anger-Control Scale (34 items). Following the acquisition of informed consent, buccal swab samples were collected for single nucleotide polymorphism (SNP) analysis targeting the COMT, MAO-A, 5- HT1A, and 5-HTT genes. Subsequent to sample collection and questionnaire administration, statistical analyses were conducted to evaluate the relationships among behavioral measures and genetic variants. Results: Overall, the findings point to gene-specific patterns in 5-HTT, MAO-A, and COMT, while no clear pattern emerged for 5-HT1A. Conclusions: Ultimately, this study provides an early exploration of aggression-related genetic patterns within the context of forensic sciences, highlighting preliminary trends and potential associations that may inform the design of future research. Full article

In the Republic of Korea, fire outbreaks caused by electrical devices are one of the most frequent accidents, causing severe damage to human lives and infrastructure. The metropolitan police, The National Institute of Scientific Investigation, and the National Fire Research Institute conduct fire root-cause inspections to determine whether these fires are external or internal infrastructure fires. However, obtaining results is a complex process. In addition, the situation has been hampered by the lack of sufficient digital forensics and relevant programs. Apart from electrical devices, multi-sockets are among the main fire instigators. In this study, we aim to verify the feasibility of utilizing YOLO-based deep-learning object detection models for fire-cause inspection systems for multi-sockets. Particularly, we have created a novel image dataset of multi-socket fire causes with 3300 images categorized into the three classes of socket, both burnt-in and burnt-out. This data was used to train various models, including YOLOv4-csp, YOLOv5n, YOLOR-csp, YOLOv6, and YOLOv7-Tiny. In addition, we have proposed an improved YOLOv5n-SE by adding a squeeze-and-excitation network (SE) into the backbone of the conventional YOLOv5 network and deploying it into a two-stage detector framework with a first stage of socket detection and a second stage of burnt-in/burnt-out classification. From the experiment, the performance of these models was evaluated, revealing that our work outperforms other models, with an accuracy of 91.3% mAP@0.5. Also, the improved YOLOv5-SE model was deployed in a web browser application. Full article

Background/Objectives: Immunohistochemistry (IHC) is a critical diagnostic tool in forensic pathology, enabling molecular-level assessment of wound vitality, post-mortem interval, and cause of death. However, IHC interpretation is subject to variability due to its reliance on human expertise. This study investigates whether artificial intelligence (AI), specifically a generative model, can assist in the diagnostic evaluation of IHC slides and replicate expert-level scoring, thereby improving consistency and reproducibility. Methods: A total of 225 high-resolution IHC images were classified into five immunoreactivity categories. The AI model (ChatGPT-4V) was trained on 150 labeled images and tested blindly on 75 unseen slides. Performance was assessed using confusion matrices, per-class precision/recall/F1, overall accuracy, Cohen’s κ (unweighted and weighted), and binary metrics (sensitivity, specificity, MCC). Results: Overall accuracy was 81.3% (95% CI: 71.1–88.5%), with substantial agreement (κ = 0.767 unweighted; 0.805 linear-weighted; 0.848 quadratic-weighted). Binary classification achieved a sensitivity of 98.3%, specificity of 93.3%, MCC of 0.92. Accuracy was highest in extreme categories (− and +++, 93.3%), while intermediate classes (+ and ++) showed reduced performance (error rates up to 33%). Evaluation was rapid and consistent but lacked interpretative reasoning and struggled with borderline cases. Conclusions: AI-assisted diagnostic evaluation of IHC slides demonstrates promising accuracy and consistency, particularly in well-defined staining patterns. While not a replacement for human expertise, AI can serve as a valuable adjunct in forensic pathology, supporting rapid and standardized assessments. Ethical and legal considerations must guide its implementation in medico-legal contexts. Full article

Sodium hydroxide (NaOH) and hydrochloric acid (HCl) are household chemicals used to disfigure victims in forensic contexts due to their high availability and apparent effects, which alter both the structural integrity and composition of skeletal elements. NaOH dissolves soft tissues and produces violent, exothermic reactions but, ostensibly, fails to alter the structure and color of bones and teeth. HCl is considered one of the most destructive chemical agents utilized, causing rapid demineralization of hard tissues. Current works focus on total dissolution times, rather than on discrete changes and the potential for personal identification. This research aims to comprehensively assess the intervallic micro- and macroscopic changes occurring in chemically altered bones and teeth. Analyses were conducted to investigate how morphological shape and surface area-to-volume ratios may affect the degree of alteration and to evaluate the feasibility of DNA isolation and profiling. The relationships between these factors were not linear, and the results show a variable pattern of alteration and DNA yields depending on the treatment and duration of exposure. Teeth were found to be better sources for obtaining higher quality and yield of DNA compared to bones, and complete STR profiles were obtained from all tooth samples. Overall, this pilot study highlights the challenges of analyzing taphonomically altered remains and underscores the need for effective identification methods. Full article

Background/Objectives: The further application of high-coverage whole genome sequencing in fields such as paleogenomics, forensic investigations, and conservation genomics is impeded by two major barriers: extremely high costs and stringent sample requirements. Utilizing low-coverage sequencing offers a practical solution to these constraints; however, this approach introduces a primary challenge—the necessity to reconstruct distorted genomic information for downstream analysis. Methods: Analytical experiments conducted on low- to medium-coverage sequencing data confirmed the accuracy of several existing methods for inferring relationships up to the third degree and distinguishing unrelated individuals. Subsequently, efforts were made to evaluate allele-frequency-independent methods within animal genomics, where analyses are likely to encounter challenges such as uncertain allele frequencies, diverse sample types, and suboptimal sample quality. Kinship inference was performed on a total of 33 pairs of animal samples across three species, comprising nine parent–offspring pairs and four full-sibling pairs. Results: The analysis revealed that two efficient algorithm implementations (READ and KIN) successfully identified all unrelated pairs. Notably, among the various algorithms utilized, only KIN exhibited confusion between first- and second-degree relationships when subjected to. Conclusions: This study has filled a critical gap in the existing literature by conducting a comprehensive evaluation of various algorithms on low-coverage sequencing data derived from authentic human and animal samples, accompanied by detailed ground truth—a vital task that has been overlooked. Full article

Biological samples of non-human origin, commonly encountered in wildlife crime investigations, present distinct challenges regarding forensic DNA analysis efforts. Although the types of samples encountered in human identity testing can vary to some degree, analyzing DNA from one species is facilitated by unified processes, common genetic marker systems, and national DNA databases. In contrast, non-human animal species identification is confounded by a diverse range of target species and a variety of sampling materials, such as feathers, processed animal parts in traditional medicine, and taxidermy specimens, which often contain degraded DNA in low quantities, are contaminated with chemical inhibitors, and may be comingled with other species. These complexities require specialized analytical approaches. Compounding these issues is a lack of validated non-human species forensic sampling and typing kits, and the risk of human DNA contamination during evidence collection. Markers residing on the mitochondrial genome (mtDNA) are routinely sought because of the large datasets available for comparison and their greater sensitivity of detection. However, the barcoding results can be complicated at times for achieving species-level resolution, the presence of nuclear inserts of mitochondrial DNA (NUMTs), and the limitation of mtDNA analysis alone to detect hybrids. Species-specific genetic markers for identification have been developed for a few high-profile species; however, many CITES (Convention on International Trade in Endangered Species of Wild Fauna and Flora)-listed organisms lack specific, validated forensic analytical tools, creating a significant gap in investigative enforcement capabilities. This deficiency stems in part from the low commercial nature of wildlife forensics efforts, a government research-driven field, the difficulty of obtaining sufficient reference samples from wild populations, limited training and education infrastructure, and inadequate funding support. Full article

Introduction: Paternal filicide is a rare and complex form of intrafamilial homicide, frequently associated with underlying psychopathology, interpersonal conflict, and psychosocial stressors. While maternal filicide has been more extensively studied, cases involving fathers—especially those employing multiple homicidal methods—remain significantly underrepresented in the forensic literature. This paper presents an unusual case of paternal filicide involving combined lethal methods, contextualized through a narrative review of comparable cases. Methods: A comprehensive forensic-pathological and psychiatric investigation was conducted following the homicide of an 8-year-old boy, killed by his father through a combination of asphyxiation and stabbing. A narrative literature review was performed using PubMed, Scopus, and Google Scholar, focusing on case reports and case series concerning paternal filicide. Particular attention was paid to homicidal methods, motivational dynamics, psychiatric comorbidities, and post-crime behavior. Results: The child’s body was found concealed in a building, in a bed storage drawer, with packing tape tightly wrapped around the mouth and nose and a kitchen knife embedded in the neck. No defensive wounds were observed, suggesting a sudden and unopposed assault, likely facilitated by the victim’s trust in the perpetrator. Autopsy findings revealed signs of asphyxiation and three stab wounds to the chin, neck, and thorax, involving vital structures such as the thyroid cartilage and heart. The father was found in a state of acute alcohol intoxication and subsequently convicted of intentional homicide. The motive appeared to be revenge-related, stemming from a highly conflictual marital separation. The literature review confirmed the predominance of retaliatory motives, frequent substance use, and post-crime suicidal behavior. However, the use of combined homicidal methods and the concealment of the body were found to be exceedingly rare. Conclusions: This case, combined with the literature review, highlights the need for deeper scientific exploration of paternal filicide. Comprehensive forensic and psychiatric assessments are essential to identify recurring situational patterns, motivational profiles, sociocultural contexts, and psychiatric vulnerabilities. These findings are critical not only for post-crime evaluations but also for the development of interdisciplinary prevention strategies targeting early warning signs and high-risk family dynamics. Full article

Background/Objectives: The external occipital protuberance (EOP) is an anatomical landmark with radiological and anthropological implications. Although the morphology and prevalence of EOP have been studied in many populations, data remain lacking for Northeastern Thais. Population-specific characterization of EOP variation may improve diagnostic and forensic accuracy applications. Materials and Methods: This study has investigated the prevalence and morphometry of EOPs using two primary sources: CT brain scans from 750 adult patients (375 males, 375 females) and anatomical investigations of 1060 dry skulls. EOPs were classified as Type I (flat), Type II (crest), or Type III (spur). Measurements for Type II (crest-shaped) EOPs were performed using standardized linear and angular parameters. Data differences were analyzed by sex and age group; intra- and inter-observer reliability was calculated for imaging measurements. Results: The study showed that Type II EOP was most common in both CT (56.1%) and dry skull (64.6%) samples. Type I was significantly more frequent in females (CT: 37.0%; dry skull: 32.8%), while Type III prevalence was higher in males (CT: 28.5%; dry skull: 18.4%). After age 60, the incidence of Type III declined in both datasets. Type II EOPs were significantly larger in males (mean crest length in CT: males 7.1 ± 0.1 mm, females 5.6 ± 0.1 mm; p < 0.001), with notable sex- and age-associated variation in associated angular dimensions. Conclusions: These findings established the first region-specific morphometric reference database for EOP in Northeastern Thais. The demonstrated sexual dimorphism in Type II EOP measurements provided the foundational data that may support future applications in clinical assessment, radiological interpretation, and forensic sex estimation in this population. Full article

Dog bite incidents represent a significant public health concern, and DNA analysis, in addition to morphological comparison, has been recognized as a useful tool for identifying the offending dog. STR typing has been established as a reliable method for individual identification in dogs, with many successful applications reported. However, most previous studies have analyzed samples showing visible traces such as blood or saliva, and there have been no documented cases in which the offending dog was identified from clothing without apparent evidence. In the present study, STR analysis was performed on trace DNA extracted from the clothing of a victim who sustained a minor dog bite injury. The STR profile obtained from the sample completely matched that of one of the three suspected dogs, a Weimaraner, at all 19 loci examined. No visible saliva or blood contamination was observed on the clothing. This case demonstrates that even trace DNA from clothing without visible markings can yield a complete STR profile when appropriate sampling and analytical methods are applied. The findings highlight the potential of canine DNA forensics to contribute to animal-related investigations and underscore the importance of accumulating allele frequency data and standardizing analytical procedures for future applications. Full article

Background/Objectives: Cytochrome P450 (CYP) enzymes are crucial for drug metabolism, yet inter-individual variability in their activity remains a significant clinical challenge. Current phenotyping methods are often impractical or even impossible, particularly in forensic toxicology and vulnerable populations. This proof-of-concept study investigated the feasibility of using in vitro assays with human liver microsomes (HLM) and recombinant CYP enzymes (isoenzymes), combined with untargeted metabolomics, to identify potential endogenous biomarker candidates indicative of CYP phenotype. Methods: This study uses in vitro incubations of HLM and isoenzymes in tandem with targeted and untargeted LC-(HR)MS and metabolomics techniques as well as statistical processing. Results: We demonstrate that HLM and isoenzymes maintain activity in the presence of complex biological matrices (blood/plasma), enabling metabolomic profiling. Untargeted analysis of assays in plasma revealed numerous potential biomarkers, with several showing significant correlations to enzyme activity. Conclusions: While identification remains the major challenge, this approach offers a promising avenue for developing accessible and efficient methods for indirect CYP phenotyping, potentially facilitating investigations in scenarios where traditional approaches are limited. This work provides a foundation for future studies focused on further developing in vitro assays and validating the proposed biomarkers, as well as establishing their utility in clinical and forensic settings. Full article

Abductive reasoning—the search for plausible explanations—has long been central to human inquiry, from forensics to medicine and scientific discovery. Yet formal approaches in AI have largely reduced abduction to eliminative search: hypotheses are treated as mutually exclusive, evaluated against consistency constraints or probability updates, and pruned until a single “best” explanation remains. This reductionist framing fails on two critical fronts. First, it overlooks how human reasoners naturally sustain multiple explanatory lines in suspension, navigate contradictions, and generate novel syntheses. Second, when applied to complex investigations in legal or scientific domains, it forces destructive competition between hypotheses that later prove compatible or even synergistic, as demonstrated by historical cases in physics, astronomy, and geology. This paper introduces quantum abduction, a non-classical paradigm that models hypotheses in superposition, allowing them to interfere constructively or destructively, and collapses only when coherence with evidence is reached. Grounded in quantum cognition and implemented with modern NLP embeddings and generative AI, the framework supports dynamic synthesis rather than premature elimination. For immediate decisions, it models expert cognitive processes; for extended investigations, it transforms competition into “co-opetition” where competing hypotheses strengthen each other. Case studies span historical mysteries (Ludwig II of Bavaria, the “Monster of Florence”), literary demonstrations (Murder on the Orient Express), medical diagnosis, and scientific theory change. Across these domains, quantum abduction proves more faithful to the constructive and multifaceted nature of human reasoning, while offering a pathway toward expressive and transparent AI reasoning systems. Full article

In forensic veterinary investigations of suspicious animal deaths involving loss of body parts, it is essential to determine whether the wounds were caused by human intervention or by other animals. Detailed postmortem examination of the wounds, combined with DNA analysis to identify biological traces left by the offending animal, play a critical role in such cases. Two primary methods are available for sample collection: muscle tissue sampling from the wound site and surface swabbing of the wound area; however, comparative studies evaluating these two approaches remain limited. In this study, mitochondrial DNA (mtDNA) analysis was performed using both muscle tissue sampling and surface swabbing in three forensic veterinary necropsy cases involving suspicious animal deaths with wounds or missing body parts, with the aim of identifying the animal species responsible for the injuries. As a result, in Case 1, canine DNA was detected from the wound of a cat carcass using both sampling methods. In Case 2, canine DNA was detected only with the swab method from the wound of another cat carcass. In Case 3, feline DNA was detected only with the muscle tissue sampling method from the wound of a duck carcass. Muscle tissue sampling, which targets deep tissues, offers advantages in preserving DNA integrity and quality. In contrast, the surface swab sampling is non-invasive and enables sample collection over a broader surface area, making it a valuable complementary tool. Although this study is based on a small number of cases, the findings suggest that combining both sampling techniques in wound-associated DNA analysis can leverage the strengths of each method, thereby improving DNA detection efficiency and enhance the reliability of forensic examinations. Full article