Journal of forensic sciences最新文献

A significant portion of document fraud cases, often associated with organized crime, involves the manipulation of physical records using correction materials such as pen or fluids and tapes. Although these materials are visually similar, they differ in chemical composition. Fluids typically contain volatile organic solvents and pigments, while tapes consist of pigment-coated adhesive films. In this study, the ATR-FTIR spectroscopy as a non-destructive analytical technique was explored to obtain spectral data from 205 prepared samples of correction materials and visually similar substances. PCA was used for exploratory data reduction, followed by PLS-DA for supervised classification based on spectral patterns. Further, feature importance was interpreted using VIP and coefficient plots, highlighting key wavenumbers contributing to class separation. The developed models exhibited excellent performance, achieving 100% accuracy in external validation for differentiating correction materials from similar-looking substances, as well as discriminating between correction pen and correction tape samples. The findings demonstrate that ATR-FTIR spectroscopy coupled with chemometrics provides a fast, accurate, and non-destructive method for the forensic classification of correction materials, offering substantial utility in real-world document examination scenarios. Further, the spectral repository developed in this study offers a valuable reference resource for forensic document examiners, aiding in the identification of questioned materials and supporting the investigation of document forgery cases.

Evaluative activity level guidance cautions DNA analysts not to respond to courtroom questions asking "how" and "when" DNA was deposited. However, criminal defendants have the right to confront and cross-examine witnesses against them. Al-Atiyyat v. State is the first U.S. case to address whether a DNA analyst's refusal to answer an activity level question violates a defendant's Sixth Amendment right to confrontation. Under the circumstances described, the court ruled that it does not. This case report examines the Al-Atiyyat decision and provides a detailed description of both the trial and appellate courts' Sixth Amendment analysis, including their collective frustration with the analyst's refusal to respond to defense counsel's activity level question. That frustration is symptomatic of the tension between current scientific guidance on activity level testimony and U.S. legal standards that control such testimony-whether evaluative or informal. This case report compares existing activity level guidance with relevant case law that governs the scope of a DNA analyst's testimony. It concludes that a gap exists between current guidance and U.S. law, which considers DNA analysts both qualified to offer opinions on activity level questions and legally obligated to respond to defense questions on cross-examination. The parties should litigate anticipated activity level issues before trial, so the court can define the proper scope of anticipated questions and testimony. The U.S. forensic DNA community should publish substantive guidance for analysts faced with activity level questions first raised during trial that considers both scientific and relevant legal principles.

This study monitored the transfer of inorganic and organic gunshot residues (IGSR and OGSR) in cases where indirect exposure might be questioned, such as during arrests. Mock arrest scenarios (n = 180) were created to assess the effect of two variables on the secondary transfer. First, the level of contact between the detained and the officer (low, medium, and high) during the arrest protocols. Second, the activities preceding the arrest include situations where the officer or person of interest (POI) discharges a firearm or handles a gun without firing. Additionally, measures to mitigate the risk of GSR transfer from the arresting officer and surfaces were evaluated. This included variables like hand washing, wearing various types of gloves, and bagging the POI's hands during transport in a police vehicle (n = 70). All samples underwent screening (ECD and LIBS) and confirmatory analysis (SEM-EDS and LC-MS/MS). The results indicated that IGSR and OGSR behave differently, with their transfer and persistence varying according to the level of contact, activities, and exposure prior to arrest. Secondary transfer was observed in 69% of the experiments but was less likely to occur for OGSR than for IGSR. The OGSR was more prone to loss, as it was not detected in 93% of the medium- and high-contact scenarios. Preventive measures such as hand washing, wearing nitrile gloves, or bagging hands helped decrease the characteristic IGSR particle counts from 5-80 to none-11. These findings enhance the current knowledge of IGS/OGSR transfer and persistence while providing recommendations for arrest protocols and evidence collection.

Multifactorial age estimation is preferred over methods based on a single anatomical site. The main challenge of the multifactorial methods lies in calculating the overall prediction interval. This study compared the performance of two approaches to achieve this: the minimal age principle versus a Bayesian approach. MRI of the third molars, left hand/wrist, and sternal extremity of both clavicles were prospectively conducted in 335 healthy Austrian Caucasian males aged 13-24 years. Development was staged according to De Tobel et al. Multi-factorial age estimation: A Bayesian approach combining dental and skeletal magnetic resonance imaging. Forensic Sci Int. 2020;306:110054. Applying the minimal age principle rendered a mean absolute error of 1.47 years, root mean square error of 1.81 years, mean width of the 95% prediction interval (PI) of 4.44 ± 2.49 years, and coverage of 68.7%. For the Bayesian approach, the results were 1.41, 1.80, 5.15 ± 1.94 years, and 81.5%, respectively. Higher inconsistency between the different age indicators was linked to a lower coverage probability in the minimal age principle, but not in the Bayesian approach. Moreover, higher inconsistency between age indicators was also linked to a higher probability of obtaining an impossible PI with the minimal age principle. Furthermore, applying the minimal age principle rendered 97.9%/81.0% correctly categorized adults (based on the point prediction of age/based on the PI) and 69.2%/85.6% correctly categorized minors. For the Bayesian approach, the results were 95.2%/76.2% and 81.5%/95.9%, respectively. In conclusion, the Bayesian approach outperformed the minimal age principle for multifactorial forensic age estimation, allowing the construction of more appropriate PIs and more correctly categorized minors.

This study evaluated the performance and limitations of the ForenSeq™ MainstAY chemistry on the MiSeq FGx® Sequencing System, which is approved for National DNA Index System (NDIS) use. This study included baseline performance, sensitivity and reproducibility studies, challenging casework samples, assessments of library plexities, comparisons with capillary electrophoresis (CE), standard versus enhanced PCR1 buffers, manual versus automated library preparation, and different flow cell types. To assess reproducibility across users, 33 samples were prepared by both an experienced and a novice user. Overall, the ForenSeq™ MainstAY Kit demonstrated high reliability with pristine samples and consistent performance across users, with minimal locus dropout until 62 pg. The kit outperformed CE for low-input and degraded samples, but limitations were observed at higher plexities. Increased sample numbers on a single flow cell disproportionately reduced read counts and locus recovery in degraded casework samples, while pristine samples were less affected. Strategic adjustments, such as batching degraded samples together or lowering plexity, may help mitigate these effects. Casework samples, including blood, touched items, bone, hair, and tissue, were tested with both standard and enhanced PCR1 buffers. In a 64-sample run (32 per buffer type), increased multiplexing reduced locus recovery in standard buffer samples, while the enhanced buffer improved recovery in 16 samples. Automated library preparation on the Opentrons OT-2 produced comparable or improved recovery relative to manual preparation, with no evidence of cross-contamination. These findings provide practical guidance for forensic laboratories adopting the MainstAY Kit, particularly in optimizing workflows for challenging samples and high-throughput sequencing environments.

Bloodstain pattern types, such as wipes and swipes, are frequently encountered at crime scenes and can offer critical insight into the sequence of events. However, these pattern types can be difficult to reliably distinguish, highlighting the need for modern, objective approaches to classification that reduce the potential for human error. In this study, 50 participants were asked to classify 40 test bloodstain pattern images (20 wipes and 20 swipes). These same images were subsequently classified using Microsoft Azure Custom Vision (MACV), an artificial intelligence (AI) image recognition platform. The MACV model was trained using 5425 bloodstain pattern images, including impact, expirated, cessation cast-off, wipe, and swipe stains, across a range of background colors. At the 50th training iteration, the AI achieved 100% accuracy in classifying both wipe and swipe patterns, outperforming participants who achieved an average accuracy of 52% (47% for wipes and 57% for swipes), marking a 48% improvement in classification performance. The model was further trained to the 80th iteration using rotated images, achieving 98.75% accuracy on the rotated test set.

This study investigated links between skeletal age estimation error and lifestyle variables to better elucidate sources of interpersonal variability in the rates of skeletal aging. Skeletal age for 180 individuals from the New Mexico Decedent Image Database was estimated by applying the Suchey-Brooks method and transition analysis to 3D models of the pubic symphysis, and age estimates were compared to known age-at-death. Age estimation bias and accuracy for both methods were evaluated first with respect to single lifestyle variables, then random forest modeling was used to test variability with respect to all lifestyle variables. Age estimation bias was shown to be significantly different with respect to sex when applying transition analysis, but not when applying Suchey-Brooks, and males tended to be underaged relative to females of the same age. While no statistically significant differences in bias existed for either method between BMI categories, random forest modeling indicated that body size exerts a limited but variable influence on skeletal aging. Additional variables were highlighted as potentially influential to skeletal aging by random forests, such as socioeconomic status, but ultimately, model performance and variable importance plots demonstrated that these influences were slight and nonuniform. These data suggest that including considerations of lifestyle variables in skeletal aging methods would not improve aging estimates.

The rapid advancement of deepfake technology poses a significant threat to digital content authenticity and public trust. Deepfakes leverage artificial intelligence to generate realistic yet manipulated images and videos, often for deceptive purposes. This study introduced an enhanced version of the MesoNet convolutional neural network tailored for deepfake detection. The model incorporates two additional convolutional layers, resulting in substantial performance gains across various metrics. It achieved a precision of 96.60%, recall of 95.33%, F₁-score of 95.96%, accuracy of 95.59%, and a Matthews Correlation Coefficient (MCC) of 91.11%, outperforming baseline models such as ResNet-50, VGG variants, and AlexNet. Additionally, a real-time detection system was developed using a React frontend and Flask backend, demonstrating the model's potential for practical deployment. This research contributed a robust and scalable approach to deepfake detection and lays the groundwork for real-world applications in digital forensics and content authenticity verification.

When human remains are in an advanced stage of decomposition, drug concentrations are altered. In five decedents morphine, morphine-3-glucuronide (M3G), and morphine-6-glucuronide (M6G) concentration changes and bacterial DNA were investigated after 13 weeks of burial. Femoral blood (FB), musculus quadriceps femoris (QM), adipose tissue (AT), synovial fluid (SF), and vitreous humor (VH) were collected on arrival at the morgue (t1), 15-24 h later (t2), and after burial of 13 weeks (t3). At t3 FB, QM, AT, and BM were sampled during autopsy, along with additional samples. Morphine, M3G, and M6G concentrations were determined. The median morphine concentration change, expressed as t2/t1 ratios in FB, VH, SF, QM, and AT was 0.96 (0.87->1.1), 1.1 (0.90-1.2), 0.92 (0.86-1.02), 1.1 (0.90-1.6), and 1.4 (1.2-1.8), respectively. At t3 the concentrations showed wide variability, with the least in QM. The median(range) morphine to FB (t1) ratios in matrices collected at t3 from the torso (central) and outside the torso (peripheral) were 4.8 (1.0-70) and 1.3 (0.02->3.1), respectively, and were significantly different. The central and peripheral median M3G to morphine t3/t1 ratios were 0.31 (0.01-1.2) and 1.4 (range 0.34-13), respectively, suggesting postmortem deconjugation of M3G. Bacterial DNA was detected in all matrices. At t3 most matrices examined had a higher bacterial DNA concentration compared to t1. The measured t2/t1 morphine ratios suggest stability of morphine concentrations between t1 and t2. At t3 morphine concentrations in peripheral matrices are lower than in central matrices, where QM and BT are possible alternatives to analyze at extended PMIs.

Ecstasy tablets are commonly associated with 3,4-methylenedioxy-methamphetamine (MDMA), but they often contain diverse psychoactive substances, including new psychoactive substances (NPS), which pose significant risks to users due to unknown composition and effects. This study analyzed 150 Ecstasy tablets seized in Poland between 2020 and 2021, shaped as "Stormtrooper" heads, to identify their chemical composition. Using gas chromatography-mass spectrometry (GC-MS) and ultra-high-performance liquid chromatography with photodiode array detection (UHPLC-PDA), we detected MDMA, 3,4-methylenedioxyamphetamine (MDA), and for the first time in Polish seizures, a novel phenylethylamine derivative-3,4-methylenedioxy-N,N-dimethylamphetamine (MDDM). MDDM, a methyl analogue of MDMA and dimethyl analogue of MDA, has limited pharmacological data and reportedly mild psychoactive effects. Its presence is likely linked to impurities or by-products formed during illicit MDMA synthesis. Quantitative analysis revealed that MDA occurred in the highest concentrations per tablet (26-74 mg), followed by MDDM (11-28 mg) and MDMA (3-11 mg). Although MDDM alone is considered to have low potency, its co-occurrence with other phenylethylamines may produce synergistic effects, potentially increasing toxicity. These findings shed light on synthetic routes in illicit MDMA production and highlight the unpredictable chemical composition of street drugs. The detection of multiple active substances-even at low doses-raises significant public health concerns, highlighting the necessity for continuous forensic monitoring and increased awareness of the dynamic and complex nature of synthetic drug markets.