Negative mixing enthalpy solid solutions deliver high strength and ductility.

Body-centred cubic refractory multi-principal element alloys (MPEAs), with several refractory metal elements as constituents and featuring a yield strength greater than one gigapascal, are promising materials to meet the demands of aggressive structural applications1-6. Their low-to-no tensile ductility at room temperature, however, limits their processability and scaled-up application7-10. Here we present a HfNbTiVAl10 alloy that shows remarkable tensile ductility (roughly 20%) and ultrahigh yield strength (roughly 1,390 megapascals). Notably, these are among the best synergies compared with other related alloys. Such superb synergies derive from the addition of aluminium to the HfNbTiV alloy, resulting in a negative mixing enthalpy solid solution, which promotes strength and favours the formation of hierarchical chemical fluctuations (HCFs). The HCFs span many length scales, ranging from submicrometre to atomic scale, and create a high density of diffusive boundaries that act as effective barriers for dislocation motion. Consequently, versatile dislocation configurations are sequentially stimulated, enabling the alloy to accommodate plastic deformation while fostering substantial interactions that give rise to two unusual strain-hardening rate upturns. Thus, plastic instability is significantly delayed, which expands the plastic regime as ultralarge tensile ductility. This study provides valuable insights into achieving a synergistic combination of ultrahigh strength and large tensile ductility in MPEAs.

Fuse feeds as one: cross-modal framework for general identification of AMPs.

Antimicrobial peptides (AMPs) are promising candidates for the development of new antibiotics due to their broad-spectrum activity against a range of pathogens. However, identifying AMPs through a huge bunch of candidates is challenging due to their complex structures and diverse sequences. In this study, we propose SenseXAMP, a cross-modal framework that leverages semantic embeddings of and protein descriptors (PDs) of input sequences to improve the identification performance of AMPs. SenseXAMP includes a multi-input alignment module and cross-representation fusion module to explore the hidden information between the two input features and better leverage the fusion feature. To better address the AMPs identification task, we accumulate the latest annotated AMPs data to form more generous benchmark datasets. Additionally, we expand the existing AMPs identification task settings by adding an AMPs regression task to meet more specific requirements like antimicrobial activity prediction. The experimental results indicated that SenseXAMP outperformed existing state-of-the-art models on multiple AMP-related datasets including commonly used AMPs classification datasets and our proposed benchmark datasets. Furthermore, we conducted a series of experiments to demonstrate the complementary nature of traditional PDs and protein pre-training models in AMPs tasks. Our experiments reveal that SenseXAMP can effectively combine the advantages of PDs to improve the performance of protein pre-training models in AMPs tasks.

Global research trends in sexual health care: A bibliometric and visualized study.

No Patient or Public Contribution, because the relevant data of this article comes from the literature database. PURPOSE: The present study aimed to investigate the trends and research status of sexual healthcare. METHODS: We searched the Web of Science database for relevant articles concerning sexual healthcare, published between 2009 and 31 December 2022. Data collected include: the number of publications, authors, journals, countries, institutions, keywords. VOSviewer and CiteSpace were used to conduct the bibliometric study and visualise the analysis. RESULTS: A total of 1450 publications were included. The number of publications on sexual healthcare shows a fluctuating upward trend, and a stable core group of authors has been formed. The Journal of Clinical Nursing published the most articles on sexual healthcare (140 publications). The United States of America published the most articles (723, 49.86%). The research institution with the highest number of publications is the University of São Paulo. According to the keyword, timeline view and prominence mapping analysis, we believe that 'Female sexual health', 'HIV', 'LGBT' and 'Sexual Healthcare Services' may be new research hotspots in the field of sexual healthcare. CONCLUSION: This study describes the research status of sexual healthcare research over the past 14 years. The findings of this study can provide helpful reference and guidance for the development trend and research direction of sexual healthcare.

LncRNA MEG3 attenuates the malignancy of retinoblastoma cells through inactivating PI3K /Akt/mTOR signaling pathway.

Retinoblastoma (RB) is the most common neoplasm found in the eye of children. There are increasing interests to develop targeted gene therapy for this disease. This study was performed to investigate the impact of long non-coding RNA (lncRNA) MEG3 on the biological features of RB cells. Vector overexpressing MEG3 was constructed and introduced into two RB cell lines. Transfected RB cells were assessed for proliferation, apoptosis, migration ability, expression levels of important genes in the PI3K/Akt/mTOR signaling pathway using qRT-PCR and Western blot analysis. Xenograft mouse models were constructed to determine the tumorigenicity of RB cells overexpressing MEG3. MEG3 mRNA level was significantly lower in RB cells than in non-cancer cells (p < 0.01). Overexpressing MEG3 resulted in significant reduction in cell proliferation (p < 0.05), migration (p < 0.01) and significant increase in apoptosis (p < 0.01). After overexpressing MEG3, p-PI3K, p-Akt and p-mTOR levels were significantly downregulated (p < 0.01). Furthermore, in the xenograft model, RB cells overexpressing MEG3 generated significantly smaller tumors as compared to RB cells that did not overexpress MEG3 (p < 0.05). Our data suggest that MEG3 increases apoptosis and reduces tumorigenicity of RB cells through inactivating the PI3K/Akt/mTOR pathway. Therefore, MEG3 could be further investigated as a potential new therapeutic agent and target for RB therapy.

Both family-based Helicobacter pylori infection control and management strategy and screen-and-treat strategy are cost-effective for gastric cancer prevention.

BACKGROUND: Helicobacter pylori (H. pylori) infection and its related diseases are substantial public health burden for highly infected areas. Recently, a novel family-based H. pylori infection control and management (FBCM) strategy is introduced for H. pylori infection prevention and control. However, its cost-effectiveness has not been evaluated. We conducted this health economic evaluation to investigate the cost-effectiveness of FBCM, screen-and-treat, and no-screen strategies in Chinese population. MATERIALS AND METHODS: Cost-effectiveness analysis was performed using decision tree and Markov model. Parameters required for the model were from published literatures and public databases, including health state utility, screening characteristics, treatment effectiveness, and medical costs for the three strategies. Outcomes were cost, quality-adjusted life year (QALY), incremental cost-effectiveness ratio (ICER). Uncertainty analysis was performed to verify the robustness of this model. RESULTS: To prevent gastric cancer in a cohort of 1 million asymptomatic Chinese families, FBCM and screen-and-treat strategies prevented 1010 and 1201 new gastric cancer cases, reduced 2809 and 3339 gastric cancer-related death, and saved 956,971 and 1,137,549 QALYs, respectively, when compared with no-screen strategy. Cost-effectiveness analysis showed that FBCM strategy cost $9.18/QALY, and screen-and-treat strategy cost $12.08/QALY for gastric cancer prevention when compared with no-screen strategy. One-way sensitivity analysis revealed that screening from younger age by both strategies are more cost-effective. When compared with FBCM strategy, screen-and-treat strategy saved 5.98% gastric cancer cases and 5.78% of gastric cancer deaths, but costed $9348 to reduce a gastric cancer case. Results are not sensitive to any variables, and probabilistic sensitivity analysis confirmed robustness of the results. CONCLUSIONS: Both FBCM and screen-and-treat strategies are cost-effective for gastric cancer prevention compared with no-screen strategy. Since FBCM is more practical and convenient, it may be an efficient and excellent cost-effective strategy for gastric cancer prevention in H. pylori and gastric cancer prevalent areas.

Rabeprazole plus amoxicillin dual therapy is equally effective to bismuth-containing quadruple therapy for Helicobacter pylori eradication in central China: A single-center, prospective, open-label, randomized-controlled trial.

BACKGROUND: Antibiotic resistance emerges as a major issue for Helicobacter pylori (H. pylori) treatment. High-dose dual therapy has recently shown encouraging results in H. pylori eradication, but it has yet to be validated in this H. pylori highly infected area; it is also not known if this concept can be extended to antibiotics other than amoxicillin, and factors that affect the eradication. We investigate if rabeprazole plus amoxicillin or furazolidone regimens could be a first-line therapy for H. pylori eradication, and factors that affect the curing rate. METHODS: This is a single-center, prospective, open-label, randomized-controlled trial. Naive patients (n=292) were randomly treated with bismuth-containing quadruple therapy (BQT), rabeprazole plus amoxicillin (RADT), or furazolidone (RFDT) groups. RADT and FADT use three times daily regimens. H. pylori diagnosis and eradication were determined and confirmed by 13 C-urea breath test. RESULTS: In per-protocol (PP) analysis, H. pylori eradication rate was 91.2% in BQT group, 89.6% in RADT, and 51.0% in RFDT group. In intention-to-treat (ITT) analysis, infection was eradicated in 86.7% of patients in BQT group, 85.8% in RADT, and 48.1% in RFDT groups, respectively. Noninferiority was confirmed between BQT and RADT groups. The incidence of side effects in BQT group was significantly higher than that in RADT group. Successful eradication was associated with lower body surface area (BSA) and low body mass index (BMI) in BQT group. Smoking and high BSA index reduced H. pylori eradication rate in RADT group. CONCLUSIONS: Rabeprazole-amoxicillin dual therapy is equally effective to the bismuth-containing quadruple therapy for H. pylori eradication with fewer side effects and saves use of one antibiotic per each treatment. Successful eradication is also associated with low BSA and non-smoking condition, which deserves future stratified analysis for refinement and optimization.

IL-9 blockade attenuates inflammation in a murine model of mechanical ventilation-induced lung injury by inhibiting the NLRP3 inflammasome pathway.

OBJECTIVES: Ventilation-induced lung injury (VILI) causes a huge economic and social burden, and its prevention and treatment have gained increasing attention in recent years. IL-9 is an important inflammatory factor, but its potential role in VILI remains unclear. This study intended to explore whether blocking IL-9 could alleviate VILI and explore its underlying mechanism. METHODS: Lung injury was induced by mechanical ventilation (MV) in C57BL/6 mice. Changes in inflammatory factors and NLRP3-related proteins were assessed using quantitative reverse transcription-polymerase chain reaction, western blotting, and enzyme-linked immunosorbent assay. Subsequently, Nlrp3-/- mice were used to further elucidate the underlying mechanism. RESULTS: The percentage of Th9 cells in the peripheral blood, bronchoalveolar lavage fluid (BALF), and lung tissues of MV mice was increased compared to those of control mice. Treatment with anti-IL-9 mAb significantly alleviated the changes in lung histopathology, wet/dry lung proportion, total protein content, and neutrophil content in BALF induced by VILI. Additionally, administering anti-IL-9 mAb significantly downregulated the expression levels of inflammatory factors in BALF and lung tissues of mice with VILI. In addition, administering anti-IL-9 mAb inhibited NLRP3 inflammasome activation, as evidenced by the observed downregulation of NLRP3, ASC, cleaved caspase-1, and GSDMD-N. Additionally, NLRP3-deficient mice had lower lung injury induced by VILI than wild-type mice. Furthermore, the anti-IL-9 mAb only partially inhibited VILI in Nlrp3-/- mice. CONCLUSIONS: In MV mice, the anti-IL-9 mAb alleviated lung injury and reduced the secretion and expression of inflammatory factors partly by inhibiting the NLRP3 inflammasome pathway.

Whole family-based Helicobacter pylori eradication is a superior strategy to single-infected patient treatment approach: A systematic review and meta-analysis.

BACKGROUND: Two critical concerns during Helicobacter pylori (H. pylori) eradication are the successful eradication and recurrence. It is debatable whether whole family-based H. pylori treatment regimen might have any advantage over single-infected patient treatment approach in increasing eradication rate and reducing recurrence rate. We conduct systematic review and meta-analysis to compare the efficacy of these two treatment regimens in order to provide clinical practice a better option for H. pylori eradication. METHODS: Randomized controlled trials evaluating H. pylori eradication and recurrence in whole family-based treatment group (WFTG) versus single-infected patient treatment group (SPTG) were collected from published literature up to July 2020 from common databases. Pooled results were analyzed using either fixed-effect or random-effect model. Results were expressed as the odds ratio (OR) and 95% confidence interval (CI). RESULTS: A total of 1751 relevant articles were identified, and 12 studies were eligible for analysis. Among them: (a) Eight articles including 1198 patients were selected to analyze H. pylori eradication rate, pooled result showed that eradication rate of WFTG was higher than that of SPTG (OR=2.93; 95% CI 1.68-5.13). Stratified analysis showed that H. pylori eradication rate in WFTG were higher over SPTG in children subgroup, but had no difference in spouse subgroup. (b) Six studies including 881 patients were analyzed for recurrence rate between the two groups, pooled analysis showed that the overall recurrence rate of WFTG was lower than that of SPTG (OR=0.3; 95% CI 0.19-0.48). Stratified analysis showed that the recurrence rate in WFTG was lower over SPTG at 6, 12, 18, and more than 24 months post-treatment subgroups. CONCLUSION: Whole family-based H. pylori treatment can partially increase eradication rate and reduce recurrence rate over single-infected patient treatment approach, the results provide clinical practice a novel notion for H. pylori eradication and infection prevention.

Quantitative Analysis of Metabolites at the Single-Cell Level by Hydrogen Flame Desorption Ionization Mass Spectrometry.

To date, direct quantitation of cellular metabolites at the picoliter level or in a single cell is still a challenge due to tiny sampling materials, the accuracy of the sampling volume, and the ubiquitous matrix effect. Herein, picoliter magnitude quantitative analysis was performed using a pressure-assisted microsampling probe coupled to the hydrogen flame desorption ionization mass spectrometer (HFDI-MS). The sampling was accurately controlled with a picoliter pump, and the analytes were rapidly vaporized and quantitatively transferred to the gas phase by adequate heat. The vapor-phase analytes reacted with protonated water cluster ions by the proton-transfer reaction (PTR). The accurate sampling, flash thermal desorption, and proton-transfer ionization processes were conducted spatiotemporally, which could greatly reduce matrix effects to facilitate the quantitation of analytes without the internal standard. Furthermore, this workflow enabled the quantitation of cellular metabolites at the picoliter/single-cell level.

Hyperspectral Imaging Based Method for Rapid Detection of Microplastics in the Intestinal Tracts of Fish.

Microplastics (MPs) in aquatic organisms are raising increasing concerns regarding their potential damage to ecosystems. To date, Raman and Fourier transform infrared spectroscopy techniques have been widely used for detection of MPs in aquatic organisms, which requires complex protocols of tissue digestion and MP separation and are time- and reagent-consuming. This novel approach directly separates, identifies, and characterizes MPs from the hyperspectral image (HSI) of the intestinal tract content in combination with a support vector machine classification model, instead of using the real digestion/separation protocols. The procedures of HSI acquisition (1 min) and data analysis (5 min) can be completed within 6 min plus the sample preparation and drying time (30 min) where necessary. This method achieved a promising efficiency (recall >98.80%, precision >96.22%) for identifying five types of MPs (particles >0.2 mm). Moreover, the method was also demonstrated to be effective on field fish from three marine fish species, revealing satisfying detection accuracy (particles >0.2 mm) comparable to Raman analysis. The present technique omits the digestion protocol (reagent free), thereby significantly reducing reagent consumption, saving time, and providing a rapid and efficient method for MP analysis.

Pancreatic Paragonimiasis in Children: A Case Report.

ABSTRACT: A few pediatric cases of abdominal paragonimiasis have been described. Here we describe a case of pulmonary and abdominal paragonimiasis with involvement of the pancreas in a 9-year-old boy. The aim of this study was to analyze the clinical and radiological features of pancreatic paragonimiasis in children and raise the awareness of this disease.

Carbon fiber-sampling combined flame ionization mass spectrometry for direct analysis of drugs in oral fluid.

Drug-impaired driving poses a significant risk of collisions and other hazardous accidents, emphasizing the urgent need for simple and rapid roadside detection methods. Oral fluid, as an easily collectible and non-invasive test material, has gained widespread use in detecting drug-impaired driving. In this study, we have devised a method for direct sampling using a carbon fiber bundle combined with flame ionization mass spectrometry. The essence of this method lies in the synergy between the adsorption properties of carbon fiber and the plasma characteristics of the flame. Leveraging the strong adsorption capabilities of the carbon fiber bundle allows for the use of a minimal sample size (<100 µL) during sampling, presenting a distinct advantage in the roadside inspection and sampling process. Throughout the flame ionization process, proteins and salts within the oral fluid matrix adhere well to the carbon fiber bundle, while small molecule targets can be efficiently desorbed and react with charged species in the flame, leading to ionization. The results demonstrate the successful development of carbon fiber-sampling combined flame ionization mass spectrometry, capable of qualitative and quantitative analysis of drugs in oral fluid without the need for sample pre-treatment. Its quantitative capabilities are sufficient for real sample detection, providing an effective analytical method for the roadside detection of drugs in oral fluids.

PiCO+: Contrastive Label Disambiguation for Robust Partial Label Learning.

Partial label learning (PLL) is an important problem that allows each training example to be labeled with a coarse candidate set with the ground-truth label included. However, in a more practical but challenging scenario, the annotator may miss the ground-truth and provide a wrong candidate set, which is known as the noisy PLL problem. To remedy this problem, we propose the PiCO+ framework that simultaneously disambiguates the candidate sets and mitigates label noise. Core to PiCO+, we develop a novel label disambiguation algorithm PiCO that consists of a contrastive learning module along with a novel class prototype-based disambiguation method. Theoretically, we show that these two components are mutually beneficial, and can be rigorously justified from an expectation-maximization (EM) algorithm perspective. To handle label noise, we extend PiCO to PiCO+, which further performs distance-based clean sample selection, and learns robust classifiers by a semi-supervised contrastive learning algorithm. Beyond this, we further investigate the robustness of PiCO+ in the context of out-of-distribution noise and incorporate a novel energy-based rejection method for improved robustness. Extensive experiments demonstrate that our proposed methods significantly outperform the current state-of-the-art approaches in standard and noisy PLL tasks and even achieve comparable results to fully supervised learning.

Metabolic characterization of 25X-NBOH and 25X-NBOMe phenethylamines based on UHPLC-Q-Exactive Orbitrap MS in human liver microsomes.

The types and quantities of new psychoactive substances synthesized based on structural modifications have increased rapidly in recent years and pose a great challenge to clinical and forensic laboratories. N-benzyl derivatives of phenethylamines, 25B-NBOH, 25E-NBOH, 25H-NBOH, and 25iP-NBOMe have begun to flow into the black market and have caused several poisoning cases and even fatal cases. The aim of this study was to avoid false negative results by detecting the parent drug and its metabolites to extend the detection window in biological matrices and provide basic data for the simultaneous determination of illegal drugs and metabolites in forensic and emergency cases. To facilitate the comparison of metabolic characteristics, we divided the four compounds into two groups of types, 25X-NBOH and 25X-NBOMe. The in vitro phase I and phase II metabolism of these four compounds was investigated by incubating 10 mg mL-1 pooled human liver microsomes with co-substrates for 180 min at 37 â„ƒ, and then analyzing the reaction mixture using ultrahigh-performance liquid chromatography-quadrupole/electrostatic field orbitrap mass spectrometry. In total, 70 metabolites were obtained for the four compounds. The major biotransformations were O-demethylation, hydroxylation, dehydrogenation, N-dehydroxybenzyl, N-demethoxybenzyl, oxidate transformation to ketone and carboxylate, glucuronidation, and their combination reactions. We recommended the major metabolites with high peak area ratio as biomarkers, B2-1 (56.61%), B2-2 (17.43%) and B6 (17.78%) for 25B-NBOH, E2-1 (42.81%), E2-2 (34.90%) and E8-2 (10.18%) for 25E-NBOH, H5 (49.28%), H2-1 (21.54%), and H1 (18.37%) for 25H-NBOH, P3-1 (10.94%), P3-2 (33.18%), P3-3 (14.85%) and P12-2 (23.00%) for 25iP-NBOMe. This is a study to evaluate their metabolic characteristics in detail. Comparative analysis of the N-benzyl derivatives of phenethylamines provided basic data for elucidating their pharmacology and toxicity. Timely analysis of the metabolic profiles of compounds with abuse potential will facilitate the early development of regulatory measures.

Rapid screening of acetylcholinesterase active contaminants in water: A solid phase microextraction-based ligand fishing approach.

Effect-directed analysis (EDA) has been increasingly used for screening toxic contaminants in the environment, but conventional EDA procedures are often time-consuming and labor-extensive. This challenges the use of EDA for toxicant identification in the scenarios when quick answers are demanded. Herein, a solid phase microextraction ligand fishing (SPME-LF) strategy has been proposed as a rapid EDA approach for identifying acetylcholinesterase (AChE) active compounds in water. The feasibility of ligand fishing techniques for screening AChE active chemicals from environmental mixtures was first verified by a membrane separation method. Then, SPME fibers were prepared through self-assembly of boronic acid groups with AChE via co-bonding and applied for SPME-LF. As AChE coated SPME fibers selectively enriched AChE-active compounds from water, comparing sorbing compounds by the SPME fibers with and without AChE coating can quickly distinguish AChE toxicants in mixtures. Compared with conventional EDA, SPME-LF does not require repeating sample separations and bioassays, endowing SPME-LF with the merits of low-cost, labor-saving, and user-friendly. It is believed that cost-efficient and easy-to-use SPME-LF strategy can potentially be a rapid EDA method for screening receptor-specific toxicants in aquatic environment, especially applicable in time-sensitive screening.

Quantitative Analysis of Three Synthetic Cannabinoids MDMB-4en-PINACA, ADB-BUTINACA, and ADB-4en-PINACA by Thermal-Assisted Carbon Fiber Ionization Mass Spectrometry.

Recently, synthetic cannabinoids (SCs) have emerged as new psychoactive substances (NPS) and have been frequently added to e-liquids, leading to their abuse. In order to detect SCs in e-liquids quickly and accurately, a thermal-assisted carbon fiber ionization mass spectrometry technique has been developed. The introduction of a heat source helps to reduce the matrix effects. The results indicate that the ratio of the slope of the matrix curve (e-liquids matrix) and the standard curve (methanol solution) for SCs analysis is close to 1, indicating a minimized matrix effect of this method. Furthermore, this method exhibits good quantitative ability when applied to real samples. It does not require sample pretreatment and is sensitive enough to directly quantify SCs in e-liquids. Our method is characterized by the ability to achieve rapid and direct quantitative analysis with minimized matrix effects. It provides a rapid and simple method for analyzing SCs in e-liquids.

Physics Embedded Graph Convolution Neural Network for Power Flow Calculation Considering Uncertain Injections and Topology.

Probabilistic analysis tool is important to quantify the impacts of the uncertainties on power system operations. However, the repetitive calculations of power flow are time-consuming. To address this issue, data-driven approaches are proposed but they are not robust to the uncertain injections and varying topology. This article proposes a model-driven graph convolution neural network (MD-GCN) for power flow calculation with high-computational efficiency and good robustness to topology changes. Compared with the basic graph convolution neural network (GCN), the construction of MD-GCN considers the physical connection relationships among different nodes. This is achieved by embedding the linearized power flow model into the layer-wise propagation. Such a structure enhances the interpretability of the network forward propagation. To ensure that enough features are extracted in MD-GCN, a new input feature construction method with multiple neighborhood aggregations and a global pooling layer are developed. This allows us to integrate both global features and neighborhood features, yielding the complete features representation of the system-wide impacts on every single node. Numerical results on the IEEE 30-bus, 57-bus, 118-bus, and 1354-bus systems demonstrate that the proposed method achieves much better performance as compared to other approaches in the presence of uncertain power injections and system topology.

Analysis of 15 anti-obesity drugs in urine using thermal-assisted paper spray mass spectrometry.

Anti-obesity drugs, used to suppress appetite and reduce fat absorption, have been circulated and traded illegally worldwide. The traditional methods of liquid chromatography tandem mass spectrometry (LC-MS/MS) and gas chromatography-mass spectrometry (GC-MS) for analyzing these drugs in in vivo samples require complex sample pretreatment and time-consuming procedures. To address this issue, a thermal-assisted paper spray mass spectrometry (PS-MS) method was developed in this study to analyze anti-obesity drugs in raw urine. By incorporating a heat source and optimizing the spray solvent and paper substrate, this technique demonstrates reduced matrix effect and higher sensitivity compared to traditional PS-MS methodology for direct analysis of anti-obesity drugs in urine samples. A temperature range of 100-200 °C can be set for screening anti-obesity drugs in urine samples, with the flexibility to adjust the temperature according to the specific drug being analyzed. The limits of detection (LODs) for these 15 anti-obesity drugs in urine ranged between 1 and 500 ng mL-1. Furthermore, the thermal-assisted PS-MS method exhibited good linearities (R2, 0.9903-0.9997) within the range from 10-100 to 1000 ng mL-1 for the direct quantitation of anti-obesity drugs in urine samples with an internal standard. Therefore, the thermal-assisted PS-MS technique may provide a novel approach for the direct analysis of drugs in complex samples.

Metabolism of dipentylone in zebrafish and human liver microsomes determined by liquid chromatography-high resolution mass spectrometry.

The consumption of novel psychoactive substances (NPS) is exceedingly prevalent in society, as these substances are sold and distributed as "legal highs." One novel synthetic cathinone emerging in the market is 1-(1,3-benzodioxol-5-yl)-2-(dimethylamino) pentan-1-one (dipentylone). The goal of this work was to study the in vivo and in vitro metabolism of dipentylone in zebrafish and human liver microsomes (HLMs) by liquid chromatography-high resolution mass spectrometry (LC-HRMS). The zebrafish and HLM samples contained 14 dipentylone metabolites, specifically 12 phase Ⅰ metabolites and 2 phase Ⅱ metabolites. The main metabolic pathways included monohydroxylation (M1 and M2), N-dealkylation (M3), hydroxylation of the aromatic ring and dealkoxylation of M3 (M4), O-dealkylation (M5), N-dealkylation of M5 (M6), reduction of carboxide (M7), monohydroxylation of M5 (M8), dehydrogenation (M9), dealkoxylation (M10), N-dealkylation of M10 (M11), dealkoxylation of M9 (M12), glucuronidation of M5 (M13), and sulfation (M14). The monohydroxylated metabolite (M2) can be recommended as metabolic markers for dipentylone. This study is the first to identify a target compound for monitoring the abuse of dipentylone and to determine the essential chemical structure of the metabolites for further toxicological research.

Study of the Metabolic Profiles of "Indazole-3-Carboxamide" and "Isatin Acyl Hydrazone" (OXIZID) Synthetic Cannabinoids in a Human Liver Microsome Model Using UHPLC-QE Orbitrap MS.

Unregulated core structures, "isatin acyl hydrazones" (OXIZIDs), have quietly appeared on the market since China legislated to ban seven general core scaffolds of synthetic cannabinoids (SCs). The fast evolution of SCs presents clinical and forensic toxicologists with challenges. Due to extensive metabolism, the parent compounds are barely detectable in urine. Therefore, studies on the metabolism of SCs are essential to facilitate their detection in biological matrices. The aim of the present study was to elucidate the metabolism of two cores, "indazole-3-carboxamide" (e.g., ADB-BUTINACA) and "isatin acyl hydrazone" (e.g., BZO-HEXOXIZID). The in vitro phase I and phase II metabolism of these six SCs was investigated by incubating 10 mg/mL pooled human liver microsomes with co-substrates for 3 h at 37 °C, and then analyzing the reaction mixture using ultrahigh-performance liquid chromatography-quadrupole/electrostatic field orbitrap mass spectrometry. In total, 9 to 34 metabolites were detected for each SC, and the major biotransformations were hydroxylation, dihydrodiol formation (MDMB-4en-PINACA and BZO-4en-POXIZID), oxidative defluorination (5-fluoro BZO-POXIZID), hydrogenation, hydrolysis, dehydrogenation, oxidate transformation to ketone and carboxylate, N-dealkylation, and glucuronidation. Comparing our results with previous studies, the parent drugs and SC metabolites formed via hydrogenation, carboxylation, ketone formation, and oxidative defluorination were identified as suitable biomarkers.