Estimation of the time of zolpidem intake and differentiation between consumption and external contamination using MALDI-MSI for investigations on single hair samples.

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 4-6 mm or 6-8 mm from the root in three single hairs of a DFSA victim collected 25 days after the event, at concentrations ranging from 0.1 to 5.7 pg mm-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.

Natural or artificial: An example of topographic spatial distribution analysis of mescaline in cactus plants by matrix-assisted laser desorption/ionization mass spectrometry imaging.

Introduction: Differentiating whether plant products are natural or artificial is of great importance in many practical fields, including forensic science, food safety, cosmetics, and fast-moving consumer goods. Information about the topographic distribution of compounds is an important criterion for answering this question. However, of equal importance is the likelihood that topographic spatial distribution information may provide important and valuable information for molecular mechanism study. Methods: In this study, we took mescaline, a substance with hallucinogenic properties in cacti of the species Trichocereus pachanoi and Lophophora williamsii, as an example to characterize the spatial distribution of mescaline in plants and flowers by liquid chromatograph-mass spectrometry-matrix-assisted laser desorption/ionization mass spectrometry imaging at the macroscopic, tissue structure, and even cellular levels. Results: According to our results, the distribution of mescaline in natural plant was concentrated on the active meristems, epidermal tissues, and protruding parts of Trichocereus pachanoi and Lophophora williamsii, while artificially spiked Lophophora diffusa products showed no such difference in their topographic spatial distribution. Discussion: This difference in distribution pattern allowed us to distinguish between flowers that could synthesize mescaline on their own and those that had been artificially spiked with mescaline. The interesting topographic spatial distribution results, such as the overlap of the mescaline distribution map and micrographs of the vascular bundles, were consistent with the synthesis and transport theory of mescaline, indicating the potential for applying matrix-assisted laser desorption/ionization mass spectrometry imaging in botanical research.

Metabolic profiling of clonazolam in human liver microsomes and zebrafish models using liquid chromatography quadrupole Orbitrap mass spectrometry.

Clonazolam is a designer benzodiazepine with strong sedative and amnesic effects. As we all know, the detection of metabolites is the key to confirming the use of substances in the field of forensic toxicology. In order to better describe clonazolam metabolism completely, we performed the two different experiments exploiting the unique characteristics of the models used. In this study, in vivo and in vitro samples were analyzed with liquid chromatography-quadrupole/electrostatic field orbitrap mass spectrometry. The results showed that seven Phase I metabolites and one Phase II metabolite were detected in zebrafish model. The remaining Phase I and II metabolites were also found in the incubation solution of pooled human liver microsomes. The main types of metabolic reactions of clonazolam included hydroxylation, dealkylation, nitroreduction, dechlorination, N-Acetylation, and O-glucuronidation. In this paper, the main metabolites and metabolic pathways of clonazolam are clarified in detail in order to further improve the metabolic rule of clonazolam. Based on these results, to better detect and judge the abuse of clonazolam, we suggest that M1, its nitro reduction product, is used as its biomarker. The results of this study provide a theoretical basis for the pharmacokinetics and forensic medicine of clonazolam.

How to sample a seizure plant: the role of the visualization spatial distribution analysis of Lophophora williamsii as an example.

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.

Predicting the retention time of Synthetic Cannabinoids using a combinatorial QSAR approach.

Background: Abuse of Synthetic Cannabinoids (SCs) has become a serious threat to public health. Due to the various structural and chemical group modified by criminals, their detection is a major challenge in forensic toxicological identification. Therefore, rapid and efficient identification of SCs is important for forensic toxicology and drug bans. The prediction of an analyte's retention time in liquid chromatography is an important index for the qualitative analysis of compounds and can provide informatics solutions for the interpretation of chromatographic data. Methods: In this study, experimental data from high-resolution mass spectrometry (HRMS) are used to construct a regression model for predicting the retention time of SCs using machine learning methods. The prediction ability of the model is improved by adopting a strategy that combines different descriptors in different independent machine-learning methods. Results: The best model was obtained with a method that combined Substructure Fingerprint Count and Finger printer features and the support vector regression (SVR) method, as it exhibited an R2 value of 0.81 for the validation set and 0.83 for the test set. In addition, 4 new SCs were predicted by the optimized model, with a prediction error within 3%. Conclusions: Our study provides a model that can predict the retention time of compounds and it can be used as a filter to reduce false-positive candidates when used in combination with LC-HRMS, especially in the absence of reference standards. This can improve the confidence of identification in non-targeted analysis and the reliability of identifying unknown substances.

Baseline serum uric acid level is associated with progression-free survival, disease control rate, and safety in postoperative patients with colorectal cancer treated by FOLFOX, FOLFIRI, or XELOX.

Background: High serum uric acid (SUA) levels increase the risk of overall cancer morbidity and mortality, particularly for digestive malignancies. Nevertheless, the correlation between SUA level and clinical outcomes of the postoperative patients with colorectal cancer (CRC) treated by chemotherapy is unclear. This study aimed at exploring the relationship between baseline SUA level and progression-free survival (PFS), disease control rate (DCR), and safety in postoperative CRC patients receiving chemotherapy. Patients and Methods: We conducted a retrospective study to evaluate the relationship between baseline SUA level and PFS, DCR, and incidence of serious adverse events of 736 postoperative CRC patients treated with FOLFOX, FOLFIRI or XELOX at our center. Results: Data from our center suggested that high baseline SUA level is linked to poor PFS in non-metastatic CRC patients using FOLFOX (HR=2.59, 95%CI: 1.29-11.31, p=0.018) and in male patients using FOLFIRI (HR=3.77, 95%CI: 1.57-39.49, p=0.012). In patients treated by FOLFIRI, a high SUA is also linked to a low DCR (p=0.035). In patients using FOLFOX, high baseline SUA level is also linked to a high incidence of neutropenia (p=0.0037). For patients using XELOX, there is no significant correlation between SUA level and PFS, effectiveness, or safety. Conclusions: These findings imply that a high SUA level is a promising biomarker associated with poor PFS, DCR and safety of postoperative CRC patients when treated with FOLFOX or FOLFIRI.

Omission of Chemotherapy in HR+/HER2- Early Invasive Breast Cancer Based on Combined 6-IHC Score?

PURPOSE: Current methods of judging whether HR+/HER2- breast cancer (BC) require adjuvant therapy, such as Ki67 and multigene prognostic tests, cannot balance accuracy with the price most patients can afford. METHODS: A retrospective analysis of 330 HR+/HER2- BC patients was conducted. Six BC-related genes (Cathepsin L2, MMP11, CyclinB1, Aurora A, Survivin, and Ki67) were screened using univariate and multivariate COX regression, and correlate clinical follow-up with immunohistochemical expression (designated as 6-IHC). All the included patients were divided randomly at a 7:3 ratio into training and testing cohorts. The cutoff prognosis index (PI) of 6-IHC was determined by multivariate Cox risk regression analysis after calculating the PI of each patient in training cohort and confirmed in testing cohort. Kaplan-Meier (KM) method was used to analyze Disease-free survival (DFS) and overall survival (OS). Six-IHC score and other factors associated with survival benefit of adjuvant chemotherapy were compared with Ki67 index. RESULTS: The receiver operating characteristic curve analysis showed that the patients can be divided into 6-IHC score "High" and "Low" risk groups. The 8-year DFS and OS of the KM curves showed that chemotherapy did not significantly improve the DFS in the 6-IHC score "Low" risk group (P= 0.830), but significantly improved the DFS in the 6-IHC score "High" risk group (P = 0.012). CONCLUSIONS: Combined 6-IHC score could be a reliable tool in predicting cancer-specific recurrences and survival in HR+/HER2-breast cancer patients, with additional advantages over using immunohistochemical expression of Ki67.