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.

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, 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 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.

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.

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.

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.

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.

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.

The origins and divergence of Sino-Tibetan populations are pivotal subjects of study in linguistics, anthropology, and population genetics. While most previous research have focused on the Han and/or Tibetan populations, comprehensive studies on other Sino-Tibetan populations, such as the Qiang and Yi, are still insufficient. This study collected Y-SNP haplogroup and Y-STR haplotype data from 1151 unrelated male individuals across 12 Sino-Tibetan populations. Using methods such as principal component analysis (PCA), phylogenetic tree construction, and haplotype network analysis, this study systematically reveal the paternal genetic structure and differentiation among Sino-Tibetan populations. Analysis of 90 Y-SNP haplogroups reveals that haplogroups O-M175, D1-M174, C-M130, and N-M231 account for over 85.37% of the paternal haplogroups in the studied populations. Sub-haplogroups of each major haplogroup exhibited distinct distribution patterns across different regions and populations. PCA results indicate a strong correlation between genetic clustering, language family, and geographical distribution. Phylogenetic tree and haplotype network analyses, using 16 Y-STR markers, further support the correlation between genetic differentiation and geographical distribution, clarifying the genetic relationships among Sino-Tibetan groups. Through the combined analysis of Y-SNP and Y-STR markers, this study deeply explores the distribution, genetic substructure, and internal genetic relationships of Y-chromosome haplogroups in Sino-Tibetan populations. It provides new theoretical insights into population genetics and offers data support for Y-chromosome research applications.

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.

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 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.

Electronic data forensics plays a crucial role in modern criminal investigations. However, with the continuous enhancement of smartphone security mechanisms, user privacy protection features－such as privacy spaces and system clones－have posed significant challenges to forensic work, particularly when privacy passwords are unavailable. To address this challenge, this study combines the UFED tool with manual analysis methods to conduct a comprehensive investigation into the data storage mechanisms of privacy spaces and system clones in four smartphone brands: OPPO, Redmi, Vivo, and Honor. The experimental results demonstrate that data in the privacy space and system clone of some devices are stored in an unencrypted format within the file system. When the file systems were analyzed using three domestic forensic tools, data from the privacy space and system clone of some devices were not successfully parsed, revealing the data protection mechanisms in smartphones from different brands, as well as the challenges faced by domestic forensic tools. This study provides new insights into improving domestic smartphone forensic methods and offers new approaches to address the current challenges in privacy protection data extraction, with significant practical application value.

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.

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.

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.

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.

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.

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.

In recent years, with the rising prevalence of telecommunication network fraud cases, the law enforcement agencies have significantly increased their efforts to combat the development and utilization of fraudulent technologies. Consequently, criminal groups have heightened their counter-surveillance capabilities. To evade law enforcement, many criminal groups chose to set up their own instant messaging (IM) services on servers and encrypt the transmitted data to prevent authorities from obtaining incriminating evidence, such as registration information and chat logs, through the third-party companies. This paper introduces a case study involving the decryption of chat data encrypted with the Blowfish+CBC mode algorithm on a MongoDB database, aiming to provide a reference for the investigation of similar telecommunication network fraud cases.

In criminal cases, individuals lacking or with limited civil capacity are not often promptly aware of being raped and pregnant, causing key evidence lost over time. DNA identification of embryonic tissue in these cases is vital for investigations and court proceedings. This paper examines the current state and recent advancements in forensic DNA analysis, considering the developmental stage of the embryo, methods for terminating pregnancies, and the preservation and extraction of embryonic tissue DNA. It also explores the selection and application of molecular markers in identifying DNA from challenging miscarriage samples. The paper discusses strategies and methodologies for DNA analysis of embryonic tissue in pregnancies resulting from rape and the potential applications of various molecular genetic markers in such analyses.

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.

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.

At present, the research on gasoline poisoning mostly focused on gasoline identification and detection. However, the autopsy and internal distribution were less studied. The purpose of this article is to provide reference data and pathological information for the determination of fatal poisoning caused by gasoline. Toxicological examination was performed on a deceased case of inhaling gasoline. The automated thermal desorber-gas chromatography mass spectrometry was used for qualitative and quantitative analysis of gasoline in the in vivo samples. The detection technology, the qualitative and quantitative evaluation methods of gasoline, the symptoms and mechanisms of gasoline poisoning and the internal distribution of fatal cases were summarized. The toxicology analysis results showed that, gasoline components were detected in the oral and nasal contents, lung, stomach contents, esophageal contents, pleural effusion and heart blood of the deceased. The concentrations in the esophageal contents and pleural effusion were 23.89 μg/mL and 26.7 μg/mL, respectively. Except for the oral and nasal contents and heart blood, the gasoline components in the in vivo samples showed a pattern of more light components and less heavy components, which was slightly different from control gasoline. As a low-toxicity narcotic poison, the mechanism of gasoline poisoning is mainly related to its physical properties such as high fat-solubility and high volatility. The symptoms of gasoline poisoning are non-specific. However, gasoline poisoning is not difficult to determine basing on occupational background investigation and odor identification of clothing and environment. According to the experience, the degree of poisoning is closely related to intake, so accurate quantification and the lethal dose of gasoline are key factors. Therefore, gasoline detection of the in vivo samples and literature review contributed to accumulate forensic toxicological data, and also provided reference for forensic toxicologists to deal with similar cases.

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.

With the widespread application of high-throughput sequencing technology in the field of forensic genetics, effectively handling the large and complex datasets generated by high-throughput sequencing has become an urgent issue. This paper extends the Genome Analysis Toolkit Best Practices guidelines based on multiplex targeted sequencing, focusing on four genetic markers commonly used in forensic genetics: short tandem repeats (STR), single nucleotide polymorphisms (SNP), insertions and deletions (InDel), and mitochondrial DNA (mtDNA). It elaborates on how to analyze these four genetic markers from FastQ raw data to the final analysis report in three parts: data quality control, construction of necessary analysis files, and data analysis. A bioinformatics analysis workflow suitable for high-throughput sequencing raw data in the forensic genetics field is introduced, providing a feasible approach to effectively address the challenges of high-throughput sequencing data analysis. This workflow not only makes it possible to independently analyze high-throughput sequencing data, but also prepares for subsequent analyses such as population genetics if needed, offering more diversified technical support for the practical application of forensic genetics.

Determining the formation method of signature handwriting is the first step of handwriting examination, which plays a vital role in whether the correct appraisal opinion can be issued. This paper examines the formation of signature handwriting in a case involving 58 contracts, and sums up a method to mutually verify and analyze the formation of signature handwriting from various angles, such as writing style, ink shape, defect exposure, ink defect, pressure characteristics and spectral morphology, which has achieved good results in practical application and can provide reference for the inspection and identification of related cases.

In this study, the methods for the identification of propoxate and isopropoxate in seized e-cigarette oil by gas chromatography-mass spectrometry (GC-MS) and ultra performance liquid chromatography-quadrupole/orbitrap high resolution mass spectrometry (UPLC-Q/Orbitrap HRMS) were established. Based on established methods, two unknown components were identified as propoxate and isopropoxate through structural analysis by MS and the characteristic fragment ions information acquired by EI-MS and Full MS/dd MS² were similar to the known etomidate. The detection limits of propoxate and isopropoxate were both 0.1μg/mL for GC-MS and 0.1ng/mL for UPLC-Q/Orbitrap HRMS. This method provides a quick and simple approach for the identification of new carboxylate drugs with imidazole ring in the absence of standard substances and it could be applied to the analysis of actual cases.

In the investigation of telecom network fraud cases, law enforcement agencies frequently encounter a critical technical challenge. Crucial evidence such as fraudulent websites often becomes inaccessible due to the delay in reporting the case. Criminal organizations typically employ tactics including domain unbinding, IP address rotation, and server replacement to evade detection, thereby obstructing investigators from accessing webpage content and potential evidentiary clues, resulting in the loss of pivotal evidence. In response to this issue, this paper introduces the application methods of network asset mapping technology and related search engines based on two cases. First, conducting searches through keyword syntax based on shared characteristics and similar structures in webpage code. Second, resolve case-related domains to corresponding IP addresses and perform reverse lookups to identify newly bound domains under those IPs, and collect network intelligence through identifying homologous active webpages. This study aims to provide actionable references for investigating telecom network fraud cases.

International forensic science organizations (associations) include the International Forensic Strategic Alliance (IFSA), the International Association of Forensic Science (IAFS), and others. Since its establishment in 2004, the International Forensic Strategic Alliance has expanded into a multilateral partnership alliance of six operating regional forensic science networks and three strategic partners, as its collaborative capabilities and international influence growing. This paper introduces the basic information of the International Forensic Strategic Alliance and its members. Using the Asian Forensic Sciences Network (AFSN) and the Senior Managers Australian and New Zealand Forensic Laboratories (SMANZFL) as examples, it analyzes the connections and distinctions between alliance members, including the topics of interest at the past five annual conferences, as well as similarities and differences in the focus areas of forensic science networks in different regions. This paper also reviews China’s relationship with the International Forensic Strategic Alliance, focusing on the development trends of forensic science domestically and internationally, and looks ahead to the prospect of China’s participation in international forensic science organizations (associations), with the aim of providing insights for promoting the internationalization of forensic science in China.

This study investigates the detection capability of whole genome sequencing (WGS) technology for varying DNA input levels, aiming to establish a novel technical approach for SNP-based genealogical inference in forensic biological samples. On the SalusPro sequencing platform (China), WGS with a depth of 25× were performed on samples containing 0.5, 0.2, and 0.05 ng of DNA respectively. From these data, 645 199 autosomal SNP loci (Wegene GSA chip) were extracted and subjected to quality control. Genetic relationships were predicted by calculating the total length of identity by descent (IBD) fragments between individuals using IBD algorithms. The results demonstrated that when DNA input was ≥0.2 ng, the locus detection rate and genotype concordance rate exceeded 95% and 99%, respectively. The IBD fragment lengths showed no significant difference compared to the standard samples (P>0.05), with an average confidence interval accuracy of 91.40% for 1st- to 7th-degree relationships. In contrast, at 0.05 ng DNA input, the locus detection rate and genotype concordance rate dropped below 80% and 97%, respectively. The IBD fragment lengths and confidence interval accuracy were significantly lower than those of the standard samples (P=0.004), rendering this input level unsuitable for reliable genealogical inference.