In this article, propoxate and isopropoxate were reported for the first time as drug substitutes. In order to systematically explore the structural characteristics of the propyl derivatives of etomidate, propoxate and isopropoxate were synthesized. Liquid chromatography, nuclear magnetic resonance spectroscopy, gas chromatography-mass spectrometry, ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry, infrared spectroscopy and Raman spectroscopy were used to analyze etomidate, propoxate and isopropoxate, respectively. The structural commonalities and differences of etomidate, propoxate and isopropoxate were compared. The similarities and differences of the three substances in chromatography, mass spectrometry and spectrum were analyzed. The ultra-high pressure liquid chromatography and gas chromatography were used to compare the retention times of the three substances. In the hydrogen nuclear magnetic resonance spectrum, ethyl of etomidate, propyl of propoxate and isopropyl of isopropoxate have significant differences in the chemical shift regions δ=0-5 ppm of ¹H NMR, and δ=10-70 ppm of ¹³C NMR. In gas chromatography-mass spectrometry, three substances can be quickly distinguished through fragment ion m/z 216.1 and molecular ion peaks. In ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry, three substances can be distinguished by comparing the quasi-molecular ion peaks of the primary mass spectrum and the abundance ratio of the fragment peaks of the secondary ion mass spectrum. The proposed fragmentation pattern of the three substances in the electron ionization of gas chromatography-mass spectrometry and in the electrospray Ionization of ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry were studied. Analyzing the distinct peaks in infrared spectroscopy and Raman spectra is challenging because the characteristics of peaks of FT-IR spectra and Raman spectra are complex. However, creating a database for the pure substances of the three substances enables direct comparison of spectral libraries. These studies provide fundamental data characterization for forensic toxicology and similar fields, providing technical support for law enforcement to identify substitutes of etomidate.

In recent years, Android system applications (hereinafter referred to as ‘APPs’) have become one of the primary ‘tools’ used by criminals for fraud. Criminals develop fraudulent apps and distribute their installation packages, known as Android application packages or APK files, to victims. After downloading and installing these apps, victims are deceived through their interactions within the apps. Therefore, the functional analysis of apps on Android devices has become a crucial source of for analyzing the processes of fraudulent activities and identifying the perpetrators of such crimes. With the development of protective technologies in recent years, an increasing number of fraudulent application files now employ various protective measures to prevent virtual machine executing and packet capturing, making dynamic analysis of these APPs increasingly difficult. This paper introduces common anti-packet capture techniques, including APK environment detection, packet capture detection, and certificate verification detection, and starts with reverse code analysis of APKs, dynamic packet capture analysis, and the underlying system code of Android, which explores the feasibility of bypassing dynamic detection and anti-packet capture mechanisms. The study of these methods for evidence collection provides valuable insights for the analysis of various types of fraudulent and malicious APPs.

This paper presents a case study of suicide involving multiple axe blows to the head, systematically analyzed through forensic pathology, bloodstain dynamics, and crime scene reconstruction techniques to provide empirical evidence for distinguishing the manner of death in sharp-force craniocerebral injuries. The deceased exhibited 28 densely distributed parallel transverse wounds on the head, with left-sided injuries demonstrating greater severity than the right. The scalp wound showed a comminuted skull fracture with brain tissue leakage. Two superficial neck incisions displayed characteristic hesitation marks, while blood spatter patterns on the right sleeve exterior corresponded with axe-swinging trajectories. Through systematic analysis of wound distribution patterns (the left-deep/right-shallow injury gradient conforming to biomechanical characteristics of right-handed axe strikes), tool-trauma morphology compatibility (axe weight, blade sharpness, and consistency with cranial injuries), and bloodstain dynamics (vertical drip patterns and elevated-arm cast-off characteristics), combined with critical scene evidence - absence of climbing/battle traces, intact entry points, and exclusive DNA presence on the tool - further excluded homicide.

Currently, smartphone screenshot images, as a swift and convenient tool for capturing and sharing information, have found widespread applications in daily life and professional work. However, simultaneously, the associated security and privacy concerns regarding these images have become increasingly salient. Due to the significant differences in their generation mechanisms between smartphone screenshots and captured images, this fact poses challenges for screenshot image traceability and forensics. In the current research and practical applications, technical research on tracing the sources of screenshot images remains in its nascent stage, with accurate tracing and identifying the source devices of specific images emerging as a pivotal research topic in the field of digital image forensics. This study focuses on developing a recognition methodology and system based on metadata features. By collecting screenshot samples from 52 smartphones of prevalent mobile phone brands in the market, metadata is extracted from the sample images, and a metadata feature database is subsequently established. The source device of the image is matched and identified by comparing multi-dimensional features, including model, device manufacturer, profile creator, rotation angle, file type, image width, and image height. Experimental results demonstrate that the proposed method exhibits high accuracy and reliability in identifying the origins of images for traceability purposes, thereby offering a novel technical approach for the field of digital forensics.

With the strict regulation of etomidate, homologues of etomidate have emerged. Among them, the more common substances are metomidate, isopropoxate and propoxate. Etomidate and its homologues are very similar in structure, which requires extreme caution in analysis and detection. In this article, a qualitative and quantitative determination method for metomidate, isopropoxate, and propoxate in electronic cigarette oil, hair and urine was developed. Samples were extracted by organic solvent, gas chromatography-mass spectrometry (GC-MS) was used to verify the qualitative results of metomidate, isopropoxate and propoxate in e-liquid. Gas chromatography (GC) was used to verify the quantitative results of e-liquid. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to verify the qualitative and quantitative results of hair and urine. The results showed that the limit of detection(LOD) by GC-MS for metomidate, isopropoxate and propoxate in e-liquid was 10 μg/mL; the limit of quantification(LOQ) by GC was 20 μg/mL; and the linearity ranged 20 to 100 μg/mL (R²>0.998 8). For the 3 substances in hair, LOD was 0.005 ng/mg, LOQ was 0.05 ng/mg, and the linearity was 0.05 to 5 ng/mg (R²>0.994 5). In urine, LOD was 1 ng/mL, LOQ was 5 ng/mL, and the linearity was 5 to 100 ng/mL (R² >0.999 0). The intra-day and inter-day precision RSD and accuracy were both less than 15%; the recovery rate ranged from 94.7% to 114.3%. The method is accurate, reliable and applicable in the analysis of practical samples.

Etomidate is a non-barbiturate intravenous anesthetic. After intravenous administration, it binds to plasma albumin and distributes into brain and heart tissues rapidly. Etomidate has the characteristics of rapid onset, short duration, and stable circulation. It is mainly used in clinical anesthesia induction or short-term surgical anesthesia. Due to its anesthetic properties, abusers make it into smoke powder, smoke oil, etc., and add them to e-cigarettes, which have widespread hazards and high concealment. Long-term use of etomidate will cause damage to the endocrine system, liver and nervous system. The toxicity to nerve cells is particularly prominent. In severe cases, apnea or even death may occur. At present, the abuse of etomidate has become a global issue, and a certain abuse trend also exists in China. Because etomidate is easy to obtain, teenagers account for the vast majority of users, which seriously endangers their physical and mental health. On September 6, 2023, the State Drug Administration, the Ministry of Public Security and the National Health Commission jointly issued the Announcement on the Adjustment of the List of Narcotic Drugs and Psychotropic Substances, which included etomidate (except for etomidate-containing drug preparations approved for marketing in China) on the list of category II psychotropic drugs, but the phenomenon of abuse is still frequent. At present, the research on etomidate mainly focuses on clinical medication, adverse reactions and detection methods. However, the research on toxicokinetics, toxicological mechanism and abuse or addiction mechanism is still insufficient. In this paper, the pharmacokinetics, anesthesia mechanism, toxicity, and abuse status of etomidate were retrospectively analyzed, and the detection methods such as gas chromatography-mass spectrometry (GC-MS), high performance liquid chromatography-mass spectrometry (HPLC-MS) and quantitative nuclear magnetic resonance spectroscopy (NMR) were summarized, in order to provide reference for the in-depth study and forensic identification of etomidate.

In recent years, telecommunications fraud cases have become increasingly prevalent, with criminals continuously refining their fraud tactics. From initially exploiting mainstream instant messaging platforms like WeChat and QQ, perpetrators have shifted to luring victims into specially crafted apps. To streamline development and reduce costs, criminals embed third-party SDK interface codes into these illicit apps, with IM (Instant Messaging) services being a common type. In these novel fraud scenarios, conducting both dynamic and static analyses of the chat-focused apk files involved can yield valuable forensic leads regarding IM services and access databases containing crucial information for investigation and prosecution. This article, taking the Android system as an example, meticulously outlines the process of mining forensic clues from instant messaging apps and subsequent data analysis, encompassing technical principles, analysis and processing steps, and case applications. It emphasizes techniques such as extracting key values through apk static analysis, validating those keys via dynamic packet capture, and utilizing SQL queries to sift through and analyze chat logs, thereby offering a professional methodological reference for evidence gathering in related cases.

In recent years, the rapid development of artificial intelligence (AI) has brought unprecedented opportunities and challenges to scientific and technological research in various fields. The cross-integration of forensic toxicology and AI has increasingly become a research hotspot of forensic science, providing new ideas and methods to solve the problems of traditional forensic toxicology. In this paper, relevant researches in recent years have been reviewed, focusing on the research progress of AI in toxicological research such as on-site investigation of poisoning, toxicant screening and qualitative and quantitative detection, toxicity prediction, toxicokinetics, toxicants interaction, as well as the identification and characterization of involved personnel in cases, and the challenges faced by AI technology in the field of forensic toxicology have also been analyzed, in order to provide reference for AI technology to better serve the research and application of forensic toxicology.

Gamma-hydroxybutyrate (GHB) is a psychotropic drug listed in the United Nations 1971 Convention on Psychotropic Substances and China’s Regulations on the Administration of Narcotic Drugs and Psychotropic Substances. GHB has a strong inhibitory effect on the central nervous system, which can cause temporary memory loss, nausea, vomiting, hypersexuality, hallucination and even death. It is a more common chemical synthetic drug in entertainment venues. In recent years, GHB and its precursor γ-butyrolactone (GBL) are often used by criminals, leading to intentional injury, traffic accidents, rape and other malignant cases, causing a series of serious public health problems and social security problems. GHB is a normal endogenous substance in human body, which can be increased by exogenous intake. This means that timely sampling is needed to ensure the accuracy of the test results. If the concentration of the biological material cannot be detected in time, it cannot be proved that the victim or suspect had exogenous GHB ingestion. At the same time, the metabolism of GHB in human body is fast, the metabolites are complex, and the test window is short, which brings challenges to the police inspection and identification. In the face of the social reality that the cases of “anesthesia rape” and “anesthesia robbery” involving GHB continue to occur frequently, it is particularly important to study the testing and identification technology of GHB. This paper introduces the abuse and control of GHB at home and abroad, points out the difficulties in the detection and identification of GHB, and then summarizes the research progress in the detection and identification technology of GHB in blood, saliva, hair and urine. The endogenous levels of GHB in the biological specimens above and the critical concentrations of GHB after exogenous intake are enumberated, which can help forensic experts to exclude false positive results and assist in determining GHB abuse, in order to provide reference for the anti-drug work of public security in China.

With the full advancement of the low-altitude economic strategy, low-altitude flight safety has increasingly become a top priority for national stability and security. Drone crimes are rapidly evolving from potential risks to real threats, with both the number of cases and the level of harm rising exponentially. In response to the critical challenges of drone governance, such as “difficulties with low-altitude surveillance, target identification, and timely disposal”, this article proposes to build a four-dimensional linkage technical investigation and prevention pathway of “global intelligent sensing network - three-dimensional forensic examination system - precise source tracing technology - coordinated rapid disposal”. This system, for the first time, proposes the focus of investigations on drone-related incidents, provides technical support for the high-quality development of drones, and provides systematic solutions to global non-traditional security governance.

In recent years, Chinese patent medicines and health care products have become more popular, but some businessmen have added illegal additions in them for profit. At present, there are many kinds of illegal additions. The objects of this study mainly include seven categories: medicines for regulating blood pressure, medicines for blood sugar regulation, medicines for blood lipid regulation and so on. These drugs may lead to a series of problems in cardiovascular, hepatic/renal function, which can be life-threatening in serious cases. In order to protect public health and rights, China has issued many standards and relevant guidelines. The main detection techniques are: immunoassay, spectroscopy, chromatography and the combination of various technologies and real-time direct analysis mass spectrometry. This paper summarized the categories of illegal additions in recent years, the commonly used sample pretreatment technology and the corresponding detection technology, and briefly introduced the characteristics of each technology. Finally, an outlook is given about the management of new illicitly added chemicals, the direction of development on related detection technologies, and the measures to deal with new illicitly added chemicals.

In the field of forensic genetics, the interpretation and analysis of mixed STR profiles have been a focal point of research due to their complexity and challenges, playing a crucial role in the investigation of difficult cases. To improve the accuracy and speed of mixed STR profile separation and to adapt to the effects of low template quantities under complex profile noise, domestic and internationall scholars have conducted a series of studies on mixed STR profile separation. In recent years, artificial intelligence methods have shown promise as a new solution for mixed STR profile separation. This paper reviews the research progress related to mixed STR profile separation, highlights the key and challenging aspects of the separation process, and proposes potential applications of artificial intelligence algorithms in this field. This paper aims to provide reference and insights for solving the problem of mixed STR profile separation using artificial intelligence methods.

Determining the sequence of intersecting lines between laser printing and stamped impression is one of the key contents of questioned document examination. Fluorescence microscope is considered to be one of the most effective ways to examine the sequence of intersecting seal and toner lines of questioned documents. However, due to various factors, determining the sequence of crossing lines has always been a challenge to forensic document examiners. Considering the influence of types of factors such as toner morphology, stamped impression fluorescence, and paper, a systematic analysis of laser printing handwriting and print timing issues was conducted using the ZMSX-05 vermilion ink timing instrument to excite fluorescence. The fluorescence phenomenon on the surface of toner was observed under two different timing conditions (“printing before stamping” and “stamping before printing”). Experiments have shown that the morphology of ink powder plays an important role in determining the sequence of intersecting lines. When the toner powder is compact and piled up on the surface of the paper and the seal ink has strong fluorescence, the sequence of the intersecting lines can be determined quickly and accurately; however, when the toner powder is non-compact and penetrates into the paper fibers, the seal ink has weak fluorescence, making it relatively difficult to determine the sequence of the intersecting lines. However, by comparing the transmitted light and fluorescence test images, it is possible to accurately determine the sequence between laser printing and stamp impression under most conditions, especially for compact and non-compact toner examination, for which 100% accuracy rate and 90% detection rate were achieved in the blind test, but some examiners made errors in determining the sequence under the interference of paper fibres, which indicates that the conclusions drawn by examiners with different professional abilities are different. This also reminds us that in actual identification, examiners should understand the principle of the fluorescence method, distinguish the effect of each element on the sequence of intersecting lines, and scientifically apply examination methods in order to make correct identification opinions. In addition, time should be another important element in determining the sequence of intersecting lines, but the time interval between laser printing and stamping, as well as the changes that occur over time after the formation of the two time sequences, require long-term detection. For example, how the fluorescence of the printed text on the surface of the toner powder changes over time, etc. This should be an important line of research for the future, so that experimental data can provide reference and clarification for document examiners.

Against the backdrop of the rapid development of big data and artificial intelligence, the field of footprint examination urgently requires advancements in professionalization and informatization. Currently, research on the identification methods of barefoot footprints has made certain progress, but the automatic recognition of shod footprints remains a tough challenge in the field. Therefore, this study introduces the Surf algorithm to explore its potential application in the automatic recognition of shod footprints. More specifically, the study employs the Surf algorithm to perform feature matching on four types of footprint images (i.e., the same person with the same shoe, the same person with different shoes, different people with the same type of shoes, and different people with different shoes), and conducts an in-depth analysis of the similarity between footprints by mapping the matching points through geometric transformations. The results show that footprints from the same person with the same shoe exhibit a significantly greater number of Surf feature point matches compared to other types; after geometric transformation mapping, footprint images from the same person, the same shoe and same time have a greater number of matching points, with accurate matching positions, while footprints from different people exhibit fewer matches. Additionally, even when considering footprints from the same person, those formed in closer time intervals have more matching points than those formed further apart in time. In summary, the Surf algorithm exhibits efficiency and reliability in recognizing footprints from the same person with the same shoe.

Exosomes, which are extracellular vesicles with a double-layer membrane, play significant roles in biological processes. They act as tiny carriers, capable of transporting a wide range of genetic materials and metabolites, including DNA, RNA, proteins, lipids, etc. Hypoxia, a state of low oxygen availability, is a powerful environmental factor that triggers significant changes in exosomes. Their composition, secretion process and overall functionality will all be drastically affected under hypoxic conditions. In the realm of forensic pathology, the precise identification of death from mechanical asphyxia (DMA) has always been a major challenge. The corpses of individuals who have died from mechanical asphyxia often lack distinct and characteristic signs that can directly point to this particular cause of death. This absence of specific indicators makes it extremely difficult for forensic pathologists to achieve precise diagnosis, which brings trouble to the criminal investigation and court trial of DMA cases. In this paper, we conducted a comprehensive review of the hypoxia-induced changes of exosomes and discussed the benefits, limitations, and feasibility of application of these changes to precise identification of DMA. Through this in-depth discussion, we hope to offer new perspectives and directions for relevant studies, thereby contributing to the advance of forensic pathology.

A gas chromatography-mass spectrometry (GC-MS) method for detection the peroxide explosive hexamethylene triperoxide diamine (HMTD) was established to address the difficulty of HMTD detection in practical cases. The samples were extracted with acetone, followed by centrifugation to obtain the supernatant which was then concentrated and diluted. Separation was achieved using an HP-5MS chromatographic column (30 m×0.25 mm×0.25 μm) at a flow rate of 4.0 mL/min. The samples were analyzed using electron impact ionization (EI) mode and quantified by an external standard method. HMTD exhibited good linearity within the concentration range of 1 to 100 μg/mL, with a correlation coefficient (R²) of at least 0.995. When employing blank dust as the matrix, the method demonstrated a detection limit of 0.4 μg/g in full scan mode (SCAN). However, in selective ion scanning mode (SIM), the detection limit was significantly lower at 0.01 μg/g, with a quantitation limit of 0.04 μg/g. The average recovery rate ranged from 89.15% to 95.41%, indicating good reliability of the method. Additionally, the intra-day precision ranged from 4.67% to 6.26%, while the inter-day precision varied between 4.59% and 12.69%, demonstrating favorable reproducibility of the assay. This method is simple, reliable, and highly sensitive, and has been successfully applied to detect HMTD in practical cases. It is suitable for the detection of HMTD in suspected explosives and explosive soil, meeting the needs of actual case investigations.

This study explored the utilization of low-altitude unmanned aerial vehicle (UAV) imagery combined with ground-based handheld photography to create a multi-scale, variable-resolution 3D realistic model of high falling incident scenes. Initially, a low-altitude UAV is employed to capture imagery data of the orientation, general overview, and fall space of the high falling incident site. Subsequently, a digital single-lens reflex (DSLR) camera is utilized to obtain detailed image data of key areas such as the starting and ending points of the fall. In the SMART 3D reconstruction software, feature points are marked and matched between the UAV imagery and the handheld camera images, aiming to rigidly correlate the aerial and ground data, thereby fusing these diverse sources to create a refined 3D model. The results demonstrate that the 3D model, constructed through the fusion of the two data sources, offers a multi-scale, comprehensive representation of the high falling incident scene. It enables users to observe both the overall orientation and layout from a distance, as well as to scrutinize key areas and detailed features up close. This technical methodology provides a direct and authentic representation of the location, texture, size, and other physical attributes of trace evidence at the scene. It offers a novel means for digitally documenting and preserving the high falling incident scene, which can then aid in reconstructing the fall sequence and enable accurate determination of the case's nature.

Gun-related cases pose extreme societal harm and urgently demand efficient and precise detection methods. This study aims to integrate the reflectance transformation imaging (RTI) technique with deep learning to apply it to the field of gun and bullet recognition. In the experiment, a total of 1 500 samples of fired cartridge cases were selected from five QSZ92 9 mm pistols. Detailed images of the markings on the base of the cartridge cases were captured using the DTV3.1 intelligent imaging system to obtain their normal maps. Thereafter, the pre-trained ResNet-50 network extracted features from the normal maps and underwent classification training. The model’s performance was evaluated by outputting AUC values, accuracy on the test set, and a confusion matrix. The experimental results reveal a total AUC value of 0.98 across the five guns, with gun No. 2 achieving the highest accuracy of 97.66% and gun No. 1 the lowest at 93.75%. This study demonstrates that the automatic recognition method of cartridge case marks based on RTI technology and deep learning yields significant results, offering valuable reference for the identification of other traces in the field of trace inspection.

Forensic document examination, a pivotal branch of forensic science, involves the meticulous analysis and authentication of various document forms, including handwriting, printed materials, and seal impressions. With the relentless progression of technology, the integration of deep learning methodologies has significantly accelerated the automation and intelligence in this field. Specifically, the employment of complex multi-layered neural network models within deep learning has facilitated a heightened level of document image recognition and analysis, surpassing the capabilities of conventional approaches. This technological breakthrough has not only enhanced the accuracy and efficiency of forensic document examination but also substantially reduced the influence of human error and subjectivity, thereby bolstering the credibility of results. This article provides a thorough review of the contributions by domestic and international researchers in leveraging deep learning for different aspects of document examination. It delves into the advancements in handwriting analysis, which involves the identification and comparative assessment of individual writing styles; printed document verification, which focuses on the authenticity of printed materials; and seal impression inspection, where the authenticity and source of seal marks are scrutinized. The discussion includes an overview of the foundational principles underpinning these methodologies, the specific applications of deep learning in these areas, and the cutting-edge research findings propelling the field forward.In addition to highlighting these advancements, the article also critically examines the existing obstacles and constraints in applying deep learning to forensic document examination. These include the demand for more robust and generalizable models capable of accommodating the extensive variability encountered in real-world documents, the necessity of extensive and diverse datasets to train these models, and the challenges associated with integrating deep learning tools into established forensic workflows. The article concludes by offering insights into the future directions for research and application, emphasizing the potential for deep learning to further revolutionize forensic document examination as the technology continues to mature.

The anonymity and decentralization of Bitcoin make it a significant medium for illicit transactions, posing challenges for traditional detection methods in handling complex transaction network structures. This study proposes a graph neural network model based on a pre-trained Conditional Variational Autoencoder (CVAE) to enhance the efficiency and accuracy of Bitcoin illicit transaction detection. The model generates K−1 feature vectors through the CVAE, which have the same number as the input features, and then combines these generated K−1 feature vectors with the original feature vector to ultimately form K feature vectors. Each feature vector undergoes multi-channel aggregation and max pooling, resulting in multiple feature vectors. These vectors are subsequently processed through linear layers and layer normalization, followed by another round of max pooling to obtain a global feature vector. Finally, the feature vectors are further processed through graph convolutional layers and linear layers to generate the final classification result. The model integrates input feature vectors at the output layer through a skip mechanism. Experimental results demonstrate that this model performs excellently in Bitcoin illicit transaction detection, significantly improving detection accuracy and robustness.

Human body odor arises from the secretion of various glands on the skin's surface, which, when acted upon by microorganisms, evaporate to produce a distinct scent. This odor contains valuable biological information, with certain compounds exhibiting strong stability and individual specificity, serving as “odor fingerprinting” that can distinguish between different populations. Machine learning is an important method for human odor research, which can not only explore the characteristic components of odor in different populations, but also investigate the differences between different individuals. This paper discusses the application of “odor fingerprinting” in individual identification and feature characterization, drawing upon recent literature. It outlines the data processing procedures involved in human odor analysis, highlights the challenges encountered, and explores current research trends. Finally, the application trends of the recognition of human odor are discussed in order to provide reference for odor recognition research.

With the improvement of living standards and an increasing awareness of personal health, the demand for health foods has surged. Consequently, the market has expanded continuously, presenting numerous regulatory challenges for the relevant authorities. The illegal addition of drugs in health foods poses a significant threat to consumer health and impedes the sustainable development of the health foods industry. Therefore, it is imperative to establish comprehensive methods for detecting these unlawful substances in health foods and to develop robust regulatory systems. Among these, health foods that claim to relieve physical fatigue are particularly vulnerable to such illegal adulterations, which primarily fall into two categories. The first is often marketed with alleged aphrodisiac or sexual enhancement benefits, while the second claims to improve cognitive function. Many unscrupulous vendors illegally add phosphodiesterase 5 inhibitors (PDE5i) or synthetic nootropics to enhance these claimed benefits. This paper provides a summary of the types, hazards, and prevalence of illicit drug additives in health foods designed for aphrodisiac or cognitive improvement, and gives an overview of the latest advancements in detection methodologies, including high-performance liquid chromatography (HPLC), liquid chromatography-mass spectrometry (LC-MS), spectroscopy, immunoassays, and electrochemical analysis. The primary methods for detecting illegal drug additives in aphrodisiac health foods include HPLC, LC-MS, spectroscopy, mass spectrometry (MS), immunoassay, and electrochemical analysis. For brain-tonifying health foods, the main detection methods are HPLC and LC-MS. Finally, this article explores the future of detecting illicit drug additives in health foods from the perspectives of standardizing preprocessing methods, expanding the application of portable instruments, employing various techniques for non-targeted screening, and utilizing artificial intelligence and machine learning technologies. The intent of this paper is to offer valuable insights and reference for law enforcement and regulatory agencies in the pursuit of monitoring and ensuring the safety of these health foods.

This paper reports a parentage testing case in which Mendelian inheritance at STR loci was violated between mother and child because the child’s chromosome 2 showed paternal uniparental disomy of the mosaic type. After analysis with three commercial autosomal STR multiplex kits, non-Mendelian patterns were observed at the loci D2S1338 and D2S441. Subsequent SNP profiling demonstrated that the child’s chromosome 2 was entirely paternal in origin and mosaic, providing a reference for recognizing mosaic uniparental disomy in parentage testing.

GC-MS and GC-MS/MS analytical methods were developed for the simultaneous detection of three 4(3H)-quinazolinone abused substances, including methaqualone, etaqualone, and 2-methoxyqualone, and applied to the analysis of suspected drugs and the hair of abusers, respectively. The standard solutions of methaqualone, etaqualone, and 2-methoxyqualone were analyzed by using the selected ion monitoring (SIM) and multiple reaction monitoring (MRM) modes, respectively, to determine the characteristic fragment ions and characteristic ion pairs of the three substances. The so established two methods were used to test the suspected drugs and hair samples in the actual cases. The established GC-MS analytical method detected components of methaqualone, etaqualone, and 2-methoxyqualone in the suspected drugs at levels of 11 μg/mg, 4.3 μg/mg, and 2.5 μg/mg, respectively. The established GC-MS/MS analytical method detected methaqualone, etaqualone, and 2-methoxyqualone in the hair at levels of 148 ng/mg, 565 pg/mg, and 58.2 ng/mg, respectively. The detection methods of GC-MS and GC-MS/MS established in this study are simple, rapid, and accurate, which can provide a reliable scientific basis for the detection of methaqualone, etaqualone, and 2-methoxyqualone in the suspected drugs and the hair of abusers.

The human ear possesses a complex three-dimensional structure and exhibits relatively high stability. Research on the morphological characteristics of ear images holds significant importance for individual identification in cases of occluded or incomplete facial images in videos and photographs. This paper categorizes the visible ear features in frontal and profile facial images into three levels: global feature, local feature, and detailed feature. Based on a self-compiled ear image dataset from the Institute of Forensic Science, Ministry of Public Security, P.R.C. (comprising 2 078 individuals and 44 826 images), the study further subdivides each feature type, providing illustrations and reference markers to depict the corresponding characteristics, thereby establishing a relatively comprehensive feature system. Using morphological comparison and statistical analysis methods, the frequencies of global features (36 feature items), local features (58 feature items), and detailed features were separately analyzed. The statistical results indicate that morphological features such as the earlobe and crus of the helix are the most frequently observed in ear images and remain relatively stable under varying lighting conditions, angles, and resolutions. Some features are relatively rare (e.g. multiple helical notches or an antitragus that is narrower at the top and wider at the bottom), and their presence can provide valuable support for individual identification.

This paper mainly introduces the research progress of deep learning technology in fingerprint information since 2018, including fingerprint image processing, fingerprint recognition, fake fingerprint detection technology, fingerprint dataset generation, and multimodal biometric recognition involving fingerprints. Fingerprint image processing includes fingerprint image segmentation, fingerprint image enhancement, and fingerprint image correction. Fingerprint recognition includes deep learning network-based fingerprint recognition, contactless fingerprint recognition, and fingerprint recognition based on three-level features of fingerprints. With the continuous deepening of research on deep learning technology, the study of fingerprint recognition algorithms using deep learning technology on large-scale fingerprint datasets will still be a research direction in the future. Moreover, using deep learning techniques to detect and identify fake fingerprints will be another direction for future research. The dataset of fake fingerprints needs to be dynamically updated and expanded in order to improve the ability of deep learning networks to detect and recognize fake fingerprints. In addition, one of the future research directions is how fingerprints, as an important biometric feature of the human body, can be integrated into multimodal biometric recognition based on large language models to achieve better identity recognition results.

This study investigates the method of using coaxial light to differentiate between laser printer and detect the addition of printed documents. Documents printed by laser printers of different brands and models are inspected using coaxial light, with the reflection of the printed text and graphics, specifically the degree of brightness or darkness, serving as a means to distinguish the printer models. The same method is used to inspect documents that have undergone additional printing on the same printer model as well as on different printer models, and the differences in the coaxial light response after the additional printing are analyzed. The experimental results show that the coaxial light response of documents printed by the same model in a single run and at different times remains basically stable, with minimal influence from paper quality and toner amount, making it a viable feature for differentiating laser printers. The coaxial light response varies significantly among documents printed by different models, with a high degree of differentiation; Moreover, the differences in the coaxial light response of the text and graphics in the added printed documents are even more pronounced, enhancing discrimination further. Overall, the study concludes that the coaxial light inspection method is a non-destructive, fast, and efficient method for forensic analysis of laser printed documents.

Routine external examination of dead body can provide information to estimate the postmortem interval (PMI) roughly by observing postmortem phenomena in situ such as corneal opacity. With the development of computer vision, these traditional direct observation methods have developed with more objective, accurate, standardized, and convenient approaches. By reviewing the relevant literature published in recent years, this article summarized the application and improvement of PMI estimation based on corneal images, from aspects of observing or detecting indicators, equipment, evolving data processing methods, models, etc., in order to show application and research progress of computer vision technology applied in the field of forensic medicine. It introduced the main animal model research and human cadaver research, focused on several parts such as research materials, methods and results, and provided some comparative analysis. Then it extracted out several key points including the influence of eyelid opening or closing, the effect of light source, the interference of diseases and injuries, the selection of regions of interest in images, and the understanding of data processing methods, etc. Lastly, several advice were put forward to make a better understanding of the future development trend which may offer reference and ideas to colleagues.

Cases of visual impairment following injury, as presented by subjects under examination, are common during forensic clinical evaluations. Certain subjects maintain a negative attitude, such as feigning blindness or visual impairment during visual activity tests, which complicates the forensic clinical evaluation process aimed at establishing the facts. Therefore, forensic experts should organize the medicolegal expertise process, deduce the mechanism of injury to the ocular region based on relevant data, consider and discuss the subjectivity of the subjects alongside the objectivity of ophthalmological laboratory tests, and ultimately reach an expert conclusion in accordance with the Technical Specification for Forensic Clinical Identification of Visual Dysfunction (SF/Z JD0103004-2016). This article presents a case regarding the forensic clinical evaluation of post-injury visual impairment and provides insights for similar medicolegal assessments.

In recent years, with the rapid development of forensic virtual anatomy technology, MSCT (multi-slice computed tomography) has gradually become an important auxiliary means of forensic examination. Concurrently, MSCT image post-processing technology has also gained widespread application in forensic pathology, clinical forensic medicine, and forensic anthropology. Image post-processing technology can transform digital images into more understandable and valuable information that is easier to comprehend and apply. It can also enable the accurate measurement of the length, angle, volume, area, CT values, and other parameters of the target part, which provides technical support for the evolution of expertise from an empirical discipline based on subjective experience to digital medicine based on objective data. Because MSCT image post-processing technologies are diverse, forensic personnel need to understand their advantages and disadvantages. They should then choose the most suitable method to achieve the best results. Practice has shown that, depending on the different observation objectives, selecting the most appropriate post-processing technology can display the target image more comprehensively and objectively. This can help to reduce missed diagnoses and misdiagnoses, thereby improving the detection and accuracy rates. In this paper, the existing image post-processing techniques are summarized, and the advantages, disadvantages and current application situations of MPR(multi-planar reconstruction), VR(volume rendering), CPR(curved planar reconstruction), SSD(shaded surface display), and MIP(maximum intensity projection) are introduced to provide technical references for related work. In daily work, MPR and VR are most frequently used. MPR is highly authentic, VR has a high data utilization, and both most closely conform to visual effects. The other post-processing techniques also have their own advantages, and it is recommended to select and use them in combination according to the characteristics of the target part. Although image post-processing technology has many advantages, it also has some limitations. Its detection rate for soft tissue injuries and hemorrhages is slightly weak, so sometimes it needs to be combined with MRI examinations or autopsies.

Industrial explosives are usually strictly controlled, with many sales links and high prices, which bring great profits to the homemade explosives. In recent years, cases of illegal manufacturing, trading, transportation and storage of ammonium nitrate explosives have frequently occurred. The raw materials for homemade ammonium nitrate explosives are widely available and easy to obtain. These result in the complex compositions and formulations. Accurate qualitative and quantitative characterization of its composition is of great significance for comparison, tracing and case investigation. Powder X-ray diffraction (PXRD) has become an efficient method to identify the component. However, it is still in the qualitative stage, i.e. matching of the phase and lack of quantitative method to illustrate the content of each substance in mixtures. In this paper, a quantitative method based on PXRD is described, including pre-processing method, sample preparation, instrument parameter settings and full spectrum fitting method. Firstly, the crystalline phase and amorphous phase components contained in the sample are accurately judged. Subsequently, Rietveld refinement method is used in which multi-dimensional factors such as structural parameters, peak parameters, instrument parameters are all included. The differences between the measured pattern and the calculated pattern is the target function and the optimization algorithm is used to obtain model parameter. After refinement fitting, the best structural parameters and other parameters including content of each component are all identified. The method can realize the quantitative characterization of powder, granular, or block solids. It can provide an important basis for the comparison and tracing of such evidences, so as to further correlate the cases.

A method for the determination of difenidol and diphenhydramine in blood samples utilizing ultrasonic-assisted ionic liquid dispersive liquid-liquid microextraction coupled with LC-MS/MS was established. 1-butyl-3-methylimidazolium hexafluorophosphate ([Bmim][PF6]) was used as the extractant, and acetone was used as the dispersant. The samples were separated by a ZORBAX Eclipse Plus C18 RRHD column. Aqueous solution containing 0.1% formic acid and methanol was used as mobile phases. A gradient elution mode was employed with a flow rate of 0.2 mL/min, followed by electrospray ion source mode (ESI⁺) analysis in scheduled multiple reaction monitoring mode (MRM). The detection limits of difenidol and diphenhydramine in blood samples were 0.01 ng/mL, and the quantification limits were 0.02 ng/mL for both. The intraday and interday precisions (relative standard deviation, RSD) were both less than 20%, and the relative recovery rates ranged from 98.38% to 115.10%. The concentrations of difenidol and diphenhydramine in the blood of a fatal case were 4.02 µg/mL and 3.78 µg/mL, respectively. This study demonstrated the feasibility of using ultrasonic-assisted ionic liquid dispersive liquid-liquid microextraction combined with LC-MS/MS for the determination of difenidol and diphenhydramine in blood samples. The method has the advantages of environmentally friendly, high enrichment efficiency, and high sensitivity, making it suitable for forensic identification of difenidol and diphenhydramine.

To detect whether four harmful heavy metals As, Pb, Cd and Hg content in fishery products and meat exceed the permitted levels, this paper provided a method for the on-site and rapid detection of these heavy metal elements. It resulted that the limit of detection (LOD) of four metals in fish were 0.03 mg/kg, 0.02 mg/kg, 0.02 mg/kg and 0.06 mg/kg; the LOD of four metals in bivalves were 0.15 mg/kg, 0.03 mg/kg, 0.30 mg/kg and 0.03 mg/kg; the LOD of four metals in meat were 0.03 mg/kg, 0.06 mg/kg, 0.03 mg/kg and 0.02 mg/kg. Besides, the relative error was As < 10%, Pb < 25%, Cd < 15%, and Hg < 30%. The linear correlation coefficient R² between the detection value and the reference method (ICP-MS) was ≥0.94. The reproducibility accuracy was investigated by comparative test in multiple laboratories, which was As < 10%, Pb < 20%, Cd < 10%, and Hg < 20%. Collectively, this method can meet the requirements of rapid detection of heavy metal elements in fishery products and meat, and the equipment is portable with simple operation, and the detection efficiency has been greatly improved.

This article investigates the post-mortem redistribution pattern of metformin in rats. Twenty-one rats were randomly divided into 7 groups, with 1 group serving as the control group and the remaining 6 groups as the experimental group. The experimental group rats were gavaged with 1mg/kg metformin, while the control group rats were gavaged with the same dose of physiological saline. After 2 hours, they were euthanized and placed in a right supine position at room temperature (15°C). Heart blood, heart, liver, spleen, lung, kidney, brain, testes, and muscles were collected at 0, 6, 12, 24, 48, and 72 h after death. The metformin content in each tissue and organ was extracted using protein precipitation method and detected by liquid chromatography-mass spectrometry. This study found that the distribution of metformin content in various time points, tissues and organs of rats showed different patterns. Metformin exhibits post-mortem redistribution in rats after gavage, therefore, the heart, muscle, and lungs are suitable samples for forensic identification of drug concentration at the time of death.

This paper aims to confirm the new psychoactive substance 1-(4-fluorobenzyl)-4-methylpiperazine (4F-MBZP) through a combination of multiple technologies. After ultrasonic extraction with methanol and separation by preparative liquid chromatography, the target was analyzed using a combination of gas chromatography-mass spectrometry (GC-MS), liquid chromatography-quadrupole/time-of-flight tandem mass spectrometry (LC-Q-TOF-MS/MS), Fourier transform infrared spectroscopy (FTIR) and nuclear magnetic resonance hydrogen spectroscopy (¹H-NMR), respectively. Through GC-MS analysis, the main characteristic fragment ions of the unknown compound with a retention time of 9.78 min were m/z 208.1, 164.1, 109.1 and 99.1; By means of LC-Q-TOF-MS/MS detection, the quasi-molecular ion peak of the unknown compound was determined to be m/z 209.286 4, and the main characteristic ion fragments obtained by MS² were m/z 189.183 0, 109.176 9, 99.452 0 and 83.387 1; The infrared characteristic absorption peaks of the target measured by FTIR analysis were 3 517.1, 2 981.5, 2 943.4, 1 603.9, 1 517.3, 1 232.0, 1 168.6, 1 080.2, 827.8 and 766.9 cm^-1, indicating that the molecular structure of the suspicious compound contains functional groups including benzene ring, methyl, methylene, and C-N; After further analysis of proton attribution in the unknown compound structure by ¹H-NMR and comparison with relevant literature that has been publicly reported, it was confirmed that the unknown compound is a new psychoactive substance called 4F-MBZP. This method is expected to be used in qualitative analysis of 4F-MBZP in seized drugs with simple operation and high accuracy, while providing reference for the detection and identification of new drugs.

Before the widespread use of digital photography technology, photographic negatives captured on photosensitive film served as crucial evidence in solving old and unresolved cases, providing important information for the successful resolution of cases. However, early black-and-white evidence negatives, taken during case proceedings, were prone to severe mold damage due to factors such as storage conditions, leading to blurred prints and significantly impeding the extraction of forensic details. This paper introduces a restoration method for severely mold-damaged negatives, which involves using a high-boiling-point liquid material with diisooctyl phenyl phosphite (DPOP) as its main component. Applying this material to the surface of the moldy negatives fills in the roughness caused by mold and eliminates the diffuse reflection of visible light caused by mold spots, effectively restoring the image quality on the damaged negatives. Meanwhile, the method is reversible. Once a clear and complete image is obtained, the applied restoration material can be removed, allowing the negative to revert to its original state and ensuring the integrity of the evidence. Employing this method, we successfully recovered the image on an evidence negative from a serious criminal case, fully reproducing the forensic information recorded on the film over 30 years ago and establishing a solid foundation for the case’s successful resolution.

Indirect fingerprint forgery refers to the creation of fake fingerprints using pre-existing finger marks as the template, which poses a great risk in reality due to the lack of need for the subject’s cooperation and its strong concealment. However, applying indirect forgery techniques to electronic evidence collection for the purpose of unlock electronic devices can significantly facilitate the forensic process. This paper investigates the effectiveness of bionic fingerprint films made by indirect forgery methods in bypassing security on various electronic devices equipped with fingerprint recognition systems. In the experiment, visible and latent fingerprints already formed were collected as samples to create ordinary silicone and capacitive silicone fingerprint films, and these were used to crack smartphones, tablet computers, fingerprint attendance machines, and smart door locks. The study also examined the impact of fingerprint sample quality, conditions for making photo-sensitive stamps, and the production conditions of fingerprint films on the effectiveness of cracking. The results show that the fingerprint film, produced by scanning, printing, and engraving photo-sensitive stamps from pre-existing real fingerprint samples, can successfully unlock a series of electronic devices equipped with fingerprint recognition systems with a high success rate. The production process of indirect forgery silicone fingerprint films is convenient and quick, providing a method to crack related electronic devices without disassembly or intrusion into the system, thus better protecting the originality and integrity of evidence. However, it is also necessary to recognize the hazard of this method and urge the public to prioritize the security of their fingerprint information in their daily lives.

This study established an analytical method suitable for the rapid on-site detection of trace methamphetamine (MET) in sewage by integrating magnetic solid phase extraction (MSPE) with immunochromatographic technology. Using magnetic nanospheres conjugated with monoclonal antibodies against methamphetamine (MET) as an immunomagnetic probe, solid-phase extraction was employed to enrich and extract methamphetamine drugs in sewage. Subsequently, the extracted methamphetamine was then quantified using colloidal gold immunochromatographic test strips. The quantitative analysis of methamphetamine was carried out by optimizing various parameters such as the amount of labeled antibody, the pH of desorption solution, the desorption time, the water sample volume, and the water sample pH. The experimental results showed that the regression equation of the standard curve of the prepared test strip was 0.999 6, and the detection limit was 0.13 ng/mL.The combination of immunomagnetic probes and colloidal gold immunochromatography enabled the detection of trace methamphetamine drugs in sewage samples within 30 minutes. The method utilized a sewage sample volume of 50 mL, achieving a concentration factor of 50 times, with a quantitative detection limit of 8 ng/L.This combined method is simple to operate, time-efficient, and has low dependence on specialized equipment. Additionally, it does not require the use of organic solvents. It is suitable for the rapid on-site detection of trace amounts of methamphetamine drugs in sewage. Additionally, it can serve as an auxiliary tool for laboratory detection of sewage samples and be applied to the monitoring of urban sewage toxicity, thus playing an important role in relevant fields.

Degradation of samples is one of the difficulties in forensic evidence examination. Affected by environmental factors such as high temperature, humidity, exposure, and microorganisms, the structure of DNA molecules is destroyed and fragmented. Large fragments of DNA are prone to failure during amplification, and complete amplification products cannot be obtained. The miniSTR technology can provide an effective solution to such problems. In this paper, a double multiplex amplification system for 25 miniSTR loci was established. Its performance indicators were tested, and its application value in degraded samples was evaluated. The technical performance indicators of the system, including balance, sensitivity, species specificity, and consistency, were compared with the VeriFiler™ Plus PCR Amplification Kit to test its detection ability for both simulated degraded samples and case work samples. The results showed that the average intra-color and inter-color balance of the miniSTR double multiplex amplification system were both more than 0.7, and the detection sensitivity for the standard 9948 DNA reached 0.05 ng. No specific amplification was observed in species detection. All 100 extracted blood samples achieved accurate typing, and all simulated degraded samples were successfully detected. The detection rate of case work samples was higher than that of the VeriFiler™ Plus PCR Amplification Kit. The miniSTR double multiplex amplification system exhibits good balance, high sensitivity, strong species specificity, and accurate typing. Its detection ability for simulated degraded samples and trace degraded samples is superior to that of the VeriFiler™ Plus PCR Amplification Kit. Particularly, the use of this amplification system can significantly increase the detection of loci in large, severely degraded fragments that are otherwise difficult to detect. At present, there are few commercial miniSTR products available, making this research even more valuable for advancing forensic DNA analysis.