Quantitative determination of ethanol in blood is a routine, widely used, and high-value assay in forensic toxicology. Because blood alcohol concentration results serve as key evidence for conviction and sentencing in many regions, laboratories continually prioritize within-laboratory data quality and interlaboratory consistency. Drawing on proficiency-testing data from 4073 laboratories collected from 2016 to 2023, this study evaluates how sample concentrations, quantification approaches, and analytical techniques affect accuracy and interlaboratory consistency. The results demonstrate the value of proficiency testing for interlaboratory quality control, while indicating that, when analyzing low-concentration samples that exhibit high variability, laboratories are likelier to achieve satisfactory rates if they follow standard recommendations and use headspace gas chromatography, internal standard quantification, and dual-column systems (p < 0.05). Accordingly, this study presents quality-control recommendations centered on quantitative headspace sampling with an internal standard, dual-column verification, and concentration-dependent evaluation and explains how these recommendations have informed updates to the Chinese national standard GB/T 42430-2023, examination methods for ethanol, methanol, n-propanol, acetone, isopropanol, and n-butanol in blood and urine.

精准鉴识是法医鉴定的基本要求,更是持之以恒的发展方向.当前,法医毒物学领域面临的一项重大挑战在于新发现毒物种类的剧增,与相对受限的鉴定技术及信息共享瓶颈之间存在显著矛盾[1-3].化学文摘社(Chemical Abstracts Service,CAS)数据库登记数据显示,全球已有2.19亿种化学品或化学混合物,其中大约35万种广泛使用的化学物质可能通过其生产和应用途径进入环境,且这一数据还在不断增长[4].

Nitazenes are a class of new psychoactive substances (NPS) belonging to the synthetic opioids. It has potent μ-opioid receptor agonist activity. In this study, we investigated an authentic forensic human blood and urine sample from an individual that died from the use of N, N-dimethyl etonitazene. To enable rapid analysis in authentic forensic sample, a method was developed utilizing in silico metabolite prediction and liquid chromatography high-resolution mass spectrometry (LC-HRMS) for blood and urine samples.In this study, LC-HRMS was used to analyze authentic blood and urine samples, and Sygma software was used to predict metabolites. Based on the predicted results, targeted analysis methods of LC-HRMS data were used to study the metabolites of blood and urine. N, N-dimethyl etonitazene and seven metabolites were identified in blood and urine samples. Among them, there were four phase I metabolites, which respectively correspond to four metabolic pathways: N-demethylation (M1), 5-amination (M2), 4'-hydroxylation (M4), N-oxidation (M6). There were three phase II metabolites corresponding to two metabolic pathways, respectively: acetylation (M3), glucuronidation (M5, M7). M1, M2, and M3 were identified in blood sample, and all metabolites were identified in urine sample. In this study, Sygma software was used to predict metabolites, and LC-HRMS method was employed to specifically analyze the metabolites of N, N-dimethyl etonitazene in authentic forensic human samples. The time required for data analysis was significantly reduced through in silico metabolite prediction. We recommend the 5-amination metabolite (M2) as a potential biomarker in blood and urine samples of N, N-dimethyl etonitazene. In addition, this study filled the gap in the study of N, N-dimethyl etonitazene metabolism. It also provided real data supplementation for the metabolism of nitazene analogues. The prediction of metabolites by using Sygma provided a certain reference for the future application of artificial intelligence in the field of forensic analysis.

Pregabalin is a structural derivative of the inhibitory neurotransmitter gamma-aminobutyric acid. Currently, the number of deaths related to the misuse or abuse of pregabalin is gradually increa-sing, and there is an urgent need for relevant forensic toxicological information. Based on relevant do-mestic and international research, this article systematically reviews the pharmacological effects, toxicity data, poisoning symptoms, in vivo processes of pregabalin, as well as the toxicological data of various existing typical cases, with the aim of providing a reference for forensic identification.

Chlorfenapyr is a broad-spectrum insecticide and acaricide derived from natural pyrrole derivatives. After entering the body, it is rapidly converted into the active metabolite tralopyril. At present, there is no specific antidote for chlorfenapyr poisoning. The mortality rate associated with this substance is relatively high, because of the latent period following exposure. In recent years, cases of poisoning caused by chlorfenapyr have been increasing. Based on relevant domestic and international research, this paper systematically reviews the toxicological effects, toxicity data, poisoning symptoms, in vivo processes of chlorfenapyr, as well as the toxicological data from typical cases, with the aim of providing a reference for forensic identification.

The use of hair strand drug tests has gained significant attention in clinical, environmental toxicology, and forensic applications. However, the accuracy of the test results requires the establishment of matrix reference materials (mRMs) products for internal use in laboratories. Immersion is a feasible method for preparing hair mRMs, but a lack of detailed preparation parameters often leads to unpredictable concentrations of target analytes. In this study, morphine (MOR), 6-acetylmorphine (6-AM), 3,4-methylenedioxymethamphetamine (MDMA), 3,4-methylenedioxyamphetamine (MDA), cocaine (COC), benzoylecgonine (BZE), and methamphetamine (MAMP) were selected as target analytes based on the Society of Hair Testing guidelines. The hair mRMs were prepared using the immersion method to investigate the influence of immersion time, washing protocol, and solution concentration on the resulting reference products. The preparation time should be limited to 30-45 days, which is the duration that hair analytes remain stable. The impregnated hair should be thoroughly cleansed, ideally using a combination of water and acetone, prior to hair sample testing. There is a positive correlation between the concentration of MAMP in the soaking solution and its presence in hair samples, which can be represented by the equation y = 0.2372 x - 0.347. This relationship suggests that adjusting the immersing concentration in accordance with the target hair concentration can enhance the efficiency of the preparation process, thus saving time and reducing costs. Stability results indicate that hair mRMs can be stored for at least six months under both cold storage and room temperature conditions. In the analysis of authentic hair drug samples, the application of hair mRMs significantly enhances the consistency and accuracy of the test results.

Aconitum herbs contain several highly toxic diester-diterpenoid alkaloids, including aconitine, mesaconitine, and hypaconitine. However, finding the cause of death is rather difficult for forensic pathologists during forensic autopsy of aconitine-induced death. Therefore, the ability to determine Aconitum alkaloids is important in these cases. The aim of this study was to review the data for alkaloids in postmortem specimens from 25 aconitine-induced deaths received by the Academy of Forensic Science from 2005 to 2023. Aconitum alkaloids were analyzed using an LC-MS/MS method, which was validated for blood, urine, and liver tissue. Briefly, 0.5 mL (g) of biological sample was subjected to liquid-liquid extraction with diethyl ether at pH 9.2. In 25 aconitineinduced deaths, the blood levels of aconitine, mesaconitine, and hypaconitine were 2.9-470 ng/mL (n = 22),

ObjectiveTo use uncertainty as an indicator to evaluate the main factors affecting data quality in the quantitative analysis of 12 volatile components in blood, including ethanol and toluene, and to assess the impact of different quality parameters, such as different hardware platforms on analytical results.MethodsTwo established headspace gas chromatography platforms were used following the method specified in Examination Methods for Ethanol, Methanol, n-Propanol, Acetone, Isopropanol and n-Butanol in Blood and Urine （GB/T 42430—2023） for analysis. According to the requirements of Guidance on Quantifying Uncertainty in Chemical Analysis （CNAS-GL006：2019） and Evaluation and Expression of Uncertainty in Measurement （JJF 1059.1—2012）, the uncertainty of the whole process of 12 volatile components quantitative analysis such as ethanol and toluene in blood was calculated. The differences of individual uncertainty components and the same uncertainty components across different hardware platforms were compared sequentially, and the results were verified by quantitative analysis of actual samples.ResultsThere was no significant difference in the uncertainty components of quantitative analysis of 12 volatile components, whether it was a hardware platform composed of domestic or imported instruments. Among them, the relative standard uncertainty of type A introduced by repeatability tests and analysts ranged from 2.81×10-3 to 9.28×10-3; the type B relative combined standard uncertainties introduced by the standard solution and internal standard solution were 5.65×10-3 to 1.15×10-2, 4.85×10-3, respectively, the type B relative standard uncertainties introduced by the calibration curve and equipment were 1.45×10-2 to 2.47×10-2 and 5.00×10-3, respectively. The overall relative combined standard uncertainty of each component ranged from 1.74×10-2 to 3.07×10-2.ConclusionIn the analysis of 12 volatile components in blood, including ethanol and toluene, calibration curve fitting is the dominant source of uncertainty. Reasonable parallel operation can effectively control the uncertainty. The selection of different hardware platforms and other quality parameters does not significantly affect the quantitative results of 12 volatile components in blood.

Using a single qualitative and quantitative test for ethanol consumption sometimes fails to reflect the objective facts at the beginning of the incident for a variety of reasons, such as metabolism, diffusion, collection contamination, storage losses, and decomposition. Stable isotope signatures, because they are natural properties of the substance itself, have the ability to describe the origin of the substance and therefore have the potential to directly trace ethanol. Previous studies have shown that discrimination of ethanol origins can be achieved to a certain extent by combining the measurement of δ13C values with the calculation of likelihood ratios. In this study, we analyzed 99 alcohol consumption samples (group A), 77 contamination samples (group B), and 14 decomposition samples (group C) by a gas chromatography-isotope ratio mass spectrometry method. We obtained δ13C values, δ18O values, and δ2H values for all three sample types and analyzed the data by a likelihood ratio calculation or a k-means clustering analysis-ROC curve method and compared them to 5 authentic samples to determine whether they were derived from alcohol consumption. The accuracy of the likelihood ratio method was 80 %, and the accuracy of the k-means cluster analysis-ROC curve system was 100 %. These findings demonstrated that increasing the dimensionality of the data can improve the accuracy of the likelihood rate method and that the k-means cluster analysis-ROC curve system was able to distinguish with good accuracy whether ethanol in blood samples was derived from alcohol consumption.

In urine drug testing, a cut-off value is often imposed to determine whether the sample is negative or positive. A matrix containing a reference substance helps counteract the adverse effects of the urine matrix across different laboratories to improve the consistency of final results. However, as a biological matrix, urine is prone to corruption and other problems that make it difficult to use as a reference sample. In this study, morphine, nitrazepam, lorazepam, buprenorphine, zolpidem, midazolam, diazepam, and clozapine commonly used in clinical practice were selected as target analytes, and the preparation process was further optimized to repeated lyophilization, in order to obtain more effective, stable, and accurate urine matrix reference materials (mRMs). The appropriate urine density (1.010-1.017 kg/m3) for preparing lyophilized samples was investigated through density determination. Conducting repeated lyophilizations resulted in a denser powder with reduced susceptibility to collapse and improved the quality of lyophilized urine samples. Lyophilized urine mRMs could be stored at room temperature for one month or under refrigeration conditions (4 ℃) for six months.

Accurate quantitative analyses require standardized methods to control and improve the analytical process in the laboratory. The availability of urine reference materials (RMs) may offer a feasible option to improve the accuracy of urine analysis and to control matrix effects. This paper presents the complete process of the development of matrix RMs in urine, including sample preparation, homogeneity, and stability studies, as well as uncertainty assessment. A freeze-drying process was developed, and freeze-dried human and pig urine samples were prepared and verified to have comparable homogeneity to liquid samples and higher stability than liquid human, pig, and artificial urine samples at 4℃ or room temperature and under extreme conditions. A total of 21 authentic urine samples from August 2022 were measured with freeze-dried RMs and spiked urine samples, and the reliability of the quantification of the RMs was compared. The freeze-dried human urine matrix RM appeared to be an excellent tool for daily quality control, as it showed high stability and gave the most consistent results with spiked samples.

Rapid and accurate characterization and quantitation of blood barbiturates and their combination drugs are very important for the clinical treatment of acute barbiturate poisoning. A comparison of dried blood spot (DBS) and traditional liquid-liquid extraction (LLE) in the pre-treatment stage, as well as a comparison of gas chromatography-mass spectrometry (GC-MS), gas chromatography-tandem mass spectrometry (GC-MS/MS), and liquid chromatography-tandem mass spectrometry (LC-MS/MS) as instrumental analysis methods, revealed differences in the analysis results of barbiturates and their combination drugs under different conditions. Based on these findings, we introduce a DBS-GC-MS/MS method. The developed and validated method showed good selectivity, sensitivity (LOD: 0.1 mu g mL(-1), LOQ: 0.2 mu g mL(-1)), linearity (R-2>0.9992), trueness (<15 %, except for carbamazepine, at 29.4 %), and precision (<15 %). Recovery was also good for most target compounds, but significant matrix effects were evident. Compared with the LLE method, the DBS method has the benefits of easy sample collection, storage, and transport, as well as simple pre-treatment and reduced reagent and energy consumption. Compared to LC-MS/MS, GC-MS/MS requires no switching between positive and negative ion modes and uses the MRM detection mode, meaning that more information about the sample compounds can be obtained in less analysis time. Using actual sample analysis, we have demonstrated the advantages of the DBS-GC-MS/MS method for the qualitative and quantitative analysis of barbiturates and poisoning events due to combinations of these drugs. Comparison of the three instruments and the two treatment methods revealed their analysis characteristics. From the perspective of practical application, the broad practical value and advantages of DBS should be embraced in more applications, and future analytical laboratory development should continue to recognize GC-MS/MS as a useful supplement to LC-MS/MS.

Based on the technical methods of GB/T 42430-2023 and GA/T 204-2019, this study established an analytical method for headspace injection double-column dual-detector (hydrogen flame ion detector) gas chromatography for the simultaneous analysis of at least 12 volatile compounds, including ethanol, in human blood using two different equipment platforms and chromatographic columns. A 100 mu L blood or urine sample and a 0.04 g/L tert-butanol working solution prepared as an internal standard are introduced into the headspace sample bottle and then sealed, mixed, and placed on the headspace sampler rack. Using different equipment platforms and columns, methodological parameters such as the limit of detection (LOD), limit of quantification (LOQ), precision, and accuracy of the method were systematically evaluated. The chromatographic separation of acetone, alcohols and benzenes using the established method was satisfactory. The linear ranges, linear correlation coefficients (r), and LODs of acetone and six alcohols, including ethanol, were 0.10-3.00 g/L, >0.997, and 0.05 g/L, respectively. The LOQs were 0.10 g/L for all other compounds, excluding n-propanol (0.005 g/L). Additionally, the linear ranges, r values, LODs, and LOQs of benzene and four benzene derivatives were 0.05-50 mg/L, >0.995, 0.02 mg/L, and 0.05 mg/L, respectively (Column J&W DB-BAC1 UI and Column Rtx-BAC-PLUS 2). The average recoveries of compounds on J&W DB-BAC1 UI and Rtx-BAC-PLUS 2 columns ranged from 92.2% to 111.6%, and the relative standard deviations (RSDs, n=6) ranged from 0.4% to 7.4%. The LOD, LOQ, precision, accuracy, and linearity of the established method met the requirements of relevant standards, and no significant differences arose between the methodological parameters of the two platforms. CNAS-GL006 (2019) and JJF 1059.1-2012 were used as guides to evaluate the uncertainty of ethanol on two different sets of equipment platforms and chromatographic columns. The ethanol uncertainty was mainly derived from the calibration curve; however, the confidence probability was 95% (k=2). According to the analysis of the verification samples and real samples, the established method is suitable for the high-precision quantitative analysis of acetone and six alcohols and five benzene derivatives in human blood and other body fluids. It can be used in practical scenarios such as judicial identification and the detection of poisons.

New psychoactive substances (NPS) have become a global health and social problem. Their structures are variable and can be easily modified to produce new compounds. Traditional analytical techniques mostly rely on standard substances and mass spectrometry databases. The increased structural diversity of NPS makes the mass spectrometry databases be unable to comprehensively cover the mass spectra of all possible NPS, which in turn makes it difficult to perform structural identification of completely unknown compounds. Advances in machine learning have emerged as a potential solution to this dilemma. In this study, the k-nearestneighbor (KNN), support vector machine (SVM), random forests (RF) and artificial neural network (ANN) algorithms were constructed based on a dataset of mass spectra of 871 compounds. The four algorithmic models for identifying new psychoactive substances were used for structural classification prediction. The training and test sets were divided according to the ratio of 7:3, and the fit method was invoked on the training set to construct the model and train the parameters of the model, and the generalization ability of the model was evaluated on the test set. A grid search with 5-fold cross-validation was used to optimize the hyperparameters of the models. The performance of the four classification prediction models was evaluated by using the confusion matrix, accuracy, precision, recall and f-scores for each of the four models for characterizing 261 samples from the test set. Overall, the RF prediction model has the best classification prediction for the seven NPS as well as negative samples, with an overall accuracy of 89.27%, which is higher than the other three classification prediction models. The overall accuracies of the KNN, SVM, and ANN models are 79.31%, 83.14%, and 83.52%, respectively. In addition, the RF prediction model also has high accuracy for the NPS prediction of specific classes, and the accuracies for synthetic cathinones, fentanyl, synthetic cannabinoids, and benzodiazepines are 100%, 93%, 95%, and 100%, respectively, which can warrant good prediction for the structural classes of unknown compounds. In conclusion, this study develops a strategy for rapid analysis of new psychoactive substances using machine learning algorithms based on mass spectral datasets, realizing the classification prediction of structural classes of unknown compounds, thus providing a basis for the structural identification of unknown psychoactive compounds.

Estimation of drug ingestion time (event time) and distinguishing between drug ingestion and external contamination are important for interpreting hair analysis results in forensics practice. Here, we present a matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) method for in situ analysis of intact hair. We applied a longitudinal cutting method for a single hair to analysis authentic hair samples from a victim of a drug-facilitated sexual assault (DFSA) case and zolpidem-soaked hair. MALDI-MSI showed that zolpidem-positive segments distributed at 4−6mm or 6−8mm from the root in three single hairs of a DFSA victim collected 25 days after the event, at concentrations ranging from 0.1 to 5.7pgmm-1, in agreement with the results from segmental analysis using liquid chromatography tandem mass spectrometry (LC-MS/MS). The estimation of drug intake time was about 20-30 days before sampling, which was consistent with the known time of drug intake. This MALDI-MS method allows imaging analysis of trace substances in a single hair and can realize the intuitive reflection of drug taking time. In addition, zolpidem applied by soaking was mainly distributed on both sides of the longitudinal hair shaft, whereas ingested zolpidem was found only in the middle of the hair shaft of the DFSA victim. The MALDI-MS images of unwashed and washed hair suggested that the amount of externally applied drug was decreased by washing, it was still present on surface layer (cuticle) sides although. Visualization using MALDI-MSI could therefore distinguish between drug ingestion and contamination by reflecting the distribution and deposition site of the drug in hair.

In forensic toxicology, hair has become a hot biological material for drug testing due to its wider detection window and noninvasive sampling process compared to traditional liquid biological materials (e.g., blood and urine). However, hair as a matrix differs from body fluids, as it is not as easily aliquoted for analysis. Nevertheless, pretreatment methods for hair detection have gradually improved from the first chemical methods, such as alkali digestion and acid hydrolysis, to now include the physical method of pulverization and further improvements beyond "pulverization" protocols. In a previous study, we updated and developed a "micropulverized extraction" method. In the present study, our aim was to gain a more complete understanding of the "micropulverized extraction" method by comparing pulverization temperature and hair particle size, as these two factors are known to influence the effectiveness of sample processing. The analytes we selected were those commonly encountered in traditional drug abuse cases: (±)-methamphetamine, (±)-amphetamine, morphine, 6-acetylmorphine, cocaine, benzoylecgonine, (--)-∆9-tetrahydrocannabinol, ketamine, (±)-norketamine and (±)-3,4-methylenedioxymethamphetamine. The analysis method was liquid chromatography-tandem mass spectrometry.

The proposal of the concept of Precision Science and the rapid development of technology have raised expectations for a higher demand for accurate quantitative analysis, including hair analysis in drug tests. Many details are presently constraining improvements in precision, so there is a greater need for standardized methods to control and improve the analytical process in the laboratory. Hair matrix reference materials may become a feasible option. In the present study, 34 drug-free hair samples from healthy volunteers were collected and compared with 2 certified standard hair samples. It was observed that the hair matrix of different origins did have a significant impact on hair analysis. Three reference materials were prepared using spiking and two soaking methods, and one natural reference material was collected from real cases. A total of 57 authentic hair samples were measured from March to August 2022 using these 4 reference materials. Differences in the origins of samples were found to have a significant impact on the hair analysis results. The reference material soaked in water and methanol at a 1:1 ratio (v/v) appeared to be an excellent tool for daily quality control, as it gave results closest to those of the natural matrix reference material in all aspects and supported the law principle of the Presumption of Innocence.

Biological matrix reference material is a reference material that combines the target material with the biological matrix. The biological matrix reference material has higher consistency with the authentic specimens in forensic toxicology, and its application has a positive effect on improving the accuracy of test results. This paper reviews the research on the matrix reference materials corresponding to three common biological test materials (blood, urine and hair). In order to provide reference for the development and application of biological matrix reference materials in forensic toxicology, this paper mainly introduces the research progress of preparation technology of biological matrix reference materials and some existing products and their parameters evaluation.

Rationale Mass spectrometry has evolved into a highly powerful tool for qualitative and quantitative chemical analyses. However, the identification of trace amounts of previously unknown structures in complex chemical matrix environments remains challenging. The rapid emergence of new synthetic cannabinoid substances is a typical example of this. Existing laboratory techniques are mostly based on methods used for lists of known illegal compounds. This situation poses a challenge to traditional data analysis and the risk of missing the compounds. Therefore, we propose to develop and validate a statistical model to classify newly emerging synthetic cannabinoid substances into a structural class or subclass. Methods We obtained 70 electrospray ionization spectra of indole/indazole synthetic cannabinoids from both the actual standard analysis and the SWGDRUG mass spectral library (version 3.10). Each sample consisted of 330 m/z variables and corresponding relative intensities. We first cleared the variables with a variance below 0.1. Principal component analysis (PCA) was performed on the variance‐filtered data, and the two principal components were retained to generate new data for hierarchical clustering. After hierarchical clustering, we used the receiver operating characteristic method in this cluster. Results Seventy synthetic indole/indazole cannabinoids were classified into four clusters. The side chain of cluster 1 is mainly fluorobenzyl, cluster 2 is pentyl, cluster 3 includes compounds from several structures, and cluster 4 is mainly fluoropentyl. The most relevant characteristic ions are m/z 109, m/z 252, and m/z 253 for cluster 1; m/z 144 and m/z 214 for cluster 2; and m/z 232 and m/z 233 for cluster 4. Conclusions This study provides a more objective and less time‐consuming solution for characterizing synthetic cannabinoids. And this work validates the ability of PCA to extract characteristic fragment ions.

Abstract   Natural compounds in plants are often unevenly distributed, and determining the best sampling locations to obtain the most representative results is technically challenging. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can provide the basis for formulating sampling guideline. For a succulent plant sample, ensuring the authenticity and in situ nature of the spatial distribution analysis results during MSI analysis also needs to be thoroughly considered. In this study, we developed a well-established and reliable MALDI-MSI method based on preservation methods, slice conditions, auxiliary matrices, and MALDI parameters to detect and visualize the spatial distribution of mescaline in situ in Lophophora williamsii. The MALDI-MSI results were validated using liquid chromatography–tandem mass spectrometry. Low-temperature storage at −80°C and drying of “bookmarks” were the appropriate storage methods for succulent plant samples and their flower samples, and cutting into 40 μm thick sections at −20°C using gelatin as the embedding medium is the appropriate sectioning method. The use of DCTB (trans-2-[3-(4-tert-butylphenyl)-2-methyl-2-propenylidene]malononitrile) as an auxiliary matrix and a laser intensity of 45 are favourable MALDI parameter conditions for mescaline analysis. The region of interest semi-quantitative analysis revealed that mescaline is concentrated in the epidermal tissues of L. williamsii as well as in the meristematic tissues of the crown. The study findings not only help to provide a basis for determining the best sampling locations for mescaline in L. williamsii, but they also provide a reference for the optimization of storage and preparation conditions for raw plant organs before MALDI detection. Key Points An accurate in situ MSI method for fresh water-rich succulent plants was obtained based on multi-parameter comparative experiments. Spatial imaging analysis of mescaline in Lophophora williamsii was performed using the above method. Based on the above results and previous results, a sampling proposal for forensic medicine practice is tentatively proposed.