Background With the progression of industrialization, an increasing number of emerging contaminants are entering aquatic environments, posing significant threats to the safety of drinking water. Therefore, establishing a system for identifying unknown hazardous factors and implementing safety warning mechanisms for drinking water is of paramount importance. Among these efforts, non-target screening plays a critical role, but its effectiveness is largely constrained by the scope of coverage of sample pre-treatment methods. Objective To integrate modern chromatography/mass spectrometry techniques with advanced data mining methods to develop a non-discriminatory sample pre-treatment method for comprehensive enrichment of unknown contaminants in drinking water, laying a technical foundation for the discovery and identification of unknown organic hazardous factors in drinking water. Methods A non-discriminatory pre-treatment method based on supramolecular and solid-phase extraction was developed. The final target compounds including 333 pesticides, 194 pharmaceuticals and personal care products (PPCPs), and 59 per- and polyfluoroalkyl substances (PFASs) were used for optimizing the pre-treatment method, confirming its coverage. The impacts of different eluents on the absolute recovery rates of target compounds were compared to select the conditions with the highest recovery for sample pre-treatment. The effects of different supramolecular solvents and salt concentrations on target compound recovery were also evaluated to determine the most suitable solvent and salt concentration. Results The solid-phase extraction elution solvents, supramolecular extraction solvents, and salt concentrations were optimized based on the target compound recovery rates. The optimal recovery conditions were achieved using 2 mL methanol, 2 mL methanol (containing 1% formic acid), 2 mL ethyl acetate, 2 mL dichloromethane, hexanediol supramolecular solvent, and 426 mg salt. The detection method developed based on these conditions showed a good linear relationship for all target compounds in the range of 0.1-100.0 ng·mL⁻¹, with R² > 0.99. The method’s limit of detection ranged from 0.01 ng⁻¹ to 0.95 ng⁻¹, and 95% of target compounds were recovered in the range of 20%-120%, with relative standard deviation (RSD) less than 30%, indicating good precision. Conclusion The combined pre-treatment method of solid-phase extraction and supramolecular solvent extraction can effectively enrich contaminants in drinking water across low, medium, and high polarities, enabling broad-spectrum enrichment of diverse trace contaminants in drinking water. It provides technical support for broad-spectrum, high-throughput screening and identification of organic pollutants in drinking water, and also serves as a reference for establishing urban drinking water public safety warning systems.

Background Per- and polyfluoroalkyl substances (PFASs) are a class of persistent organic pollutants that pose potential health risks to humans. Infants and young children have higher requirements for food safety due to the underdeveloped detoxification and immune systems. Therefore, developing a comprehensive method for determination of PFASs and their novel alternatives in infant complementary food is of great significance. Objective To develop an analytical method using liquid chromatography high-resolution mass spectrometry technology for determination of 55 PFASs in plant- and animal-derived infant complementary fruit purees. Methods Oasis WAX (200 mg, 6 CC) solid-phase extraction columns were used for sample enrichment and purification. The pH of the acetonitrile extract was adjusted using 0%, 1%, 1.5%, and 2% formic acid aqueous solutions to evaluate its impact on the recovery rate of target compounds. Additionally, the impact of a 2 mL methanol wash during the purification process on the recovery of target compounds was assessed to determine the optimal pretreatment conditions. Three types of chromatographic columns—Agilent Poroshell 120 EC-C₁₈, Thermo InfinityLab Poroshell 120 Aq-C₁₈, Acquity Waters BEH-C₁₈, and changes in mobile phase, were compared for their effects on retention time, peak shape, and response of target compounds. The method was validated in terms of selectivity, linear range, detection limit, and precision. The established method was applied to 49 commercial samples of infant complementary fruit purees. Results Adjusting the sample pH using 1.5% formic acid water and incorporating a 2 mL methanol wash during purification achieved satisfactory recovery rates. The target compounds were chromatographically separated using an Agilent Poroshell 120 EC-C₁₈ column with a gradient elution system. The mobile phase consisted of methanol-water (methanol/water: 2/98, v/v) containing 5 mmol·L⁻¹ ammonium formate as mobile phase A, and methanol as mobile phase B. Good separation was achieved within 15 min, resulting in optimal chromatographic peak shapes. The 55 target compounds exhibited good linearity across the standard curve range, with correlation coefficients (R²) greater than 0.99. The method detection limits ranged from 0.02 to 0.05 µg·L⁻¹. In the plant- and animal-based fruit puree samples, the spiked recovery rates ranged from 60% to 112% and 57% to 119%, respectively, with relative standard deviations (RSD) ≤ 30%. A total of 9 traditional PFASs and 5 novel PFASs were positive in 49 samples of infant complementary fruit purees. Conclusion This method enables comprehensive detection of 55 traditional and emerging PFASs, offering wide coverage, high accuracy, and excellent sensitivity. It provides technical support for characterizing contamination by traditional and emerging PFASs in food matrices.

Cell models can simulate a variety of life states and disease developments, including single cells, two-dimensional (2D) cell cultures, three-dimensional (3D) multicellular spheroids, and organoids. They are essential tools for addressing complex biochemical questions. With continuous advancements in biological and cellular analysis technologies, in vitro cellular models designed to answer scientific questions have evolved rapidly. Early in vitro models primarily relied on 2D systems, which failed to accurately replicate the complex cellular compositions and microenvironmental interactions observed in vivo, let alone support sophisticated investigations into cellular biological functions. Subsequent improvements in cell culture techniques led to the development of 3D culture-based models, such as cellular spheroids. The advent of pluripotent stem cell technology further advanced the development of organoid systems, which closely mimic human organ development. Compared to traditional 2D models, both 3D cellular models and organoids offer significant advantages, including personalization and enhanced physiological relevance, making them particularly suitable for exploring molecular mechanisms of disease progression, discovering novel cellular and biomolecular functions, and conducting related studies. The imaging analysis of common cellular models primarily employs labeling-based methods for in situ imaging of targeted genes, proteins, and small-molecule metabolites, enabling further research on cell types, states, metabolism, and drug efficacy. However, these approaches have drawbacks such as poor labeling specificity and complex experimental procedures. By using cells as experimental models, mass spectrometry technology combined with morphological analysis can reveal quantitative changes and spatial distributions of various biological substances at the spatiotemporal level, including metabolites, proteins, lipids, peptides, drugs, environmental pollutants, and metals. This allows for the investigation of cell-cell interactions, tumor microenvironments, and cellular bioinformational heterogeneity. The application of these cutting-edge imaging technologies generates vast amounts of cellular data, necessitating the development of rapid, efficient, and highly accurate image data algorithms for precise segmentation and identification of single cells, multi-organelle structures, rare cell subpopulations, and complex cellular morphologies. A critical focus lies in creating deep learning models and algorithms that enhance the accuracy of cellular visualization. At the same time, establishing more robust data integration tools is essential not only for analyzing and interpreting outputs but also for effectively uncovering the biological significance of spatially resolved mass spectrometry data. Developing a cell imaging platform with high versatility, operational stability, and specificity to enable data interoperability will significantly enhance its utility in clinical research, thereby advancing investigations into disease molecular mechanisms and supporting precision diagnostics and therapeutics. In contrast to genomic, transcriptomic, and proteomic information, the metabolome can rapidly respond to external stimuli and cellular physiological changes within a short timeframe. This rapid and precise reflection of ongoing cellular state alterations has positioned spatial metabolomics as a pivotal approach for exploring the molecular mechanisms underlying physiological and pathological processes in cells, tissues, and organisms. In this review, we summarize research on cell imaging based on mass spectrometry technologies, including the selection and preparation of cell models, morphological analysis of cell models, spatial omics techniques based on mass spectrometry, mass cytometry, and their applications. We also discuss the current challenges and propose future directions for development in this field.

Objective To analyze the structural and phylogenetic characteristics of the mitochondrial genome from Bulinus globosus, so as to provide a theoretical basis for classification and identification of species within the Bulinus genus, and to provide insights into understanding of Bulinus-schistosomes interactions and the mechanisms of parasite transmission. Methods B. globosus samples were collected from the Ruya River basin in Zimbabwe. Mitochondrial DNA was extracted from B. globosus samples and the corresponding libraries were constructed for high-throughput sequencing on the Illumina NovaSeq 6000 platform. After raw sequencing data were subjected to quality control using the fastp software, genome assembly was performed using the A5-miseq and SPAdes tools, and genome annotation was conducted using the MITOS online server. Circular maps and sequence plots of the mitochondrial genome were generated using the CGView and OGDRAW software, and the protein conservation motifs and structures were analyzed using the TBtools software. Base composition and codon usage bias were analyzed and visualized using the software MEGA X and the ggplot2 package in the R software. In addition, a phylogenetic tree was created in the software MEGA X after sequence alignment with the software MAFFT 7, and visualized using the software iTOL. Results The mitochondrial genome of B. globosus was a 13 730 bp double-stranded circular molecule, containing 2 ribosomal RNA (rRNA) genes, 22 transfer RNA (tRNA) genes, and 13 protein-coding genes, with a marked AT preference. The mitochondrial genome composition of B. globosus was similar to that of other species within the Bulinus genus. Phylogenetic analysis revealed that the complete mitochondrial genome sequence of B. globosus was clustered with B. truncatus, B. nasutus, and B. ugandae into the same evolutionary clade, and gene superfamily analysis showed that the metabolism-related proteins of B. globosus were highly conserved, notably the cytochrome c oxidase family, which showed a significant consistency. Conclusions This is the first whole mitochondrial genome sequencing to decode the compositional features of the mitochondrial genome of B. globosus from Zimbabwe and its evolutionary relationship within the Bulinus genus, which provides important insights for further understanding of the phylogeny and mitochondrial genome characteristics of the Bulinus genus.

Glucagon-like peptide-1 ( GLP-1 ) is secreted by gut enteroendocrine cells. GLP-1 receptor agonists ( GLP-1 RAs) control glucose-related augmentation of insulin and suppress glu-cagon secretion. GLP-lRAs also inhibit gastric emptying, food intake and limit weight gain. In the past decade, significant progresses have been made in the investigation on the effects of GLP-1 RAs on cardiovascular system. The potential advantages of oral small-molecule GLP-1 RAs could improve the application of this class of drugs. This review highlights the multiple cardiovascular profiles of GLP-1 RAs in the treatment of cardiovascular diseases to provide new insights into cardiovascular benefits of GLP-1 RAs.

Objective To analyze the seasonal characteristics of scarlet fever in Songjiang District from 2012 to 2021, and to provide references for the prevention and control of scarlet fevers. Methods The incidence data of scarlet fever in Songjiang District from 2012 to 2021 were collected through the China Disease Prevention and Control Information System. The seasonal characteristics and peak of scarlet fever incidence were analyzed using concentration and circular distribution methods. Results The average annual reported incidence rate of scarlet fever in Songjiang District from 2012 to 2021 was 20.15/100 000. The M value of the concentration analysis was 0.18. The results of the circular distribution method showed that the peak day of scarlet fever from March to August was May 12, and the epidemic peak period was from April 3 to June 20. From September to February of the next year, the peak day of scarlet fever was December 21, and the epidemic peak period was from December 2 to January 9 of the next year. The differences were all statistically significant (P values were all less than 0.05). Conclusion The peaks of scarlet fever in Songjiang District mainly occur in May and December. It is suggested that the monitoring methods and prevention strategies should be adjusted in time according to Seasonal characteristics of scarlet fever.

Esophageal cancer is an upper gastrointestinal malignancy with a bleak prognosis.It is still being explored in depth due to its complex molecular mechanisms of occurrence and development.Lipids play a crucial role in cells by participating in energy supply,biofilm formation,and signal transduction pro-cesses,and lipid metabolic reprogramming also constitutes a significant characteristic of malignant tu-mors.More and more studies have found esophageal cancer has obvious lipid metabolism abnormalities throughout its beginning,progress,and treatment resistance.The inhibition of tumor growth and the enhancement of antitumor therapy efficacy can be achieved through the regulation of lipid metabolism.Therefore,we reviewed and analyzed the research results and latest findings for lipid metabolism and associated analysis techniques in esophageal cancer,and comprehensively proved the value of lipid metabolic reprogramming in the evolution and treatment resistance of esophageal cancer,as well as its significance in exploring potential therapeutic targets and biomarkers.

OBJECTIVE To establish the ultra-high liquid chromatography （UPLC） characteristic spectrum of Uncariae Ramulus Cum Uncis from different producing areas， to conduct chemical pattern recognition analysis， and to identify the medicinal materials of their different origins and counterfeit products. METHODS UPLC method was adopted to establish the characteristic spectra of 43 batches of Uncariae Ramulus Cum Uncis from different origins； cluster analysis combined with principal component analysis were used to analyze their quality； Uncariae Ramulus Cum Uncis from different origins and counterfeit products were identified. RESULTS UPLC specific spectrum of Uncariae Ramulus Cum Uncis was established， and 13 common peaks were calibrated； peak 2 was identified as catechin， peak 3 as chlorogenic acid， peak 4 as cryptochlorogenic acid， peak 7 as isochlorogenic acid B， peak 8 as isodehydroguotenine， peak 9 as isooguotenine， peak 10 as dehydroguotenine， peak 11 as isochlorogenic acid C， peak 12 as goutenine， and peak 13 as camptothecin. Through cluster analysis， the medicinal materials of 43 batches of Uncariae Ramulus Cum Uncis could be divided into 5 categories according to their different origins. Further principal component analysis revealed that the principal component comprehensive scores of Uncariae Ramulus Cum Uncis produced in Jiangxi and Hunan were relatively high， ranging from 0.264 to 2.904. The specific chromatogram could effectively distinguish among the different origins and their counterfeit products of Uncariae Ramulus Cum Uncis. CONCLUSIONS The established UPLC specific chromatogram can be used for quality control of Uncariae Ramulus Cum Uncis， and the study found that the quality of Uncariae Ramulus Cum Uncis from Jiangxi and Hunan provinces is relatively good.

Objective To investigate the toxicokinetic differences of 3,4-methylenedioxy-N-methylamphetamine(MDMA)and its metabolite 4,5-methylene dioxy amphetamine(MDA)in rats af-ter single and continuous administration of MDMA,providing reference data for the forensic identifica-tion of MDMA.Methods A total of 24 rats in the single administration group were randomly divided into 5,10 and 20 mg/kg experimental groups and the control group,with 6 rats in each group.The ex-perimental group was given intraperitoneal injection of MDMA,and the control group was given intraperi-toneal injection of the same volume of normal saline as the experimental group.The amount of 0.5 mL blood was collected from the medial canthus 5 min,30 min,1 h,1.5 h,2 h,4 h,6 h,8 h,10 h,12 h after administration.In the continuous administration group,24 rats were randomly divided into the experi-mental group(18 rats)and the control group(6 rats).The experimental group was given MDMA 7 d by continuous intraperitoneal injection in increments of 5,7,9,11,13,15,17 mg/kg per day,respectively,while the control group was given the same volume of normal saline as the experimental group by in-traperitoneal injection.On the eighth day,the experimental rats were randomly divided into 5,10 and 20 mg/kg dose groups,with 6 rats in each group.MDMA was injected intraperitoneally,and the con-trol group was injected intraperitoneally with the same volume of normal saline as the experimental group.On the eighth day,0.5 mL of blood was taken from the medial canthus 5 min,30 min,1 h,1.5 h,2 h,4 h,6 h,8 h,10 h,12 h after administration.Liquid chromatography-triple quadrupole tandem mass spectrometry was used to detect MDMA and MDA levels,and statistical software was employed for data analysis.Results In the single-administration group,peak concentrations of MDMA and MDA were reached at 5 min and 1 h after administration,respectively,with the largest detection time limit of 12 h.In the continuous administration group,peak concentrations were reached at 30 min and 1.5 h af-ter administration,respectively,with the largest detection time limit of 10 h.Nonlinear fitting equations for the concentration ratio of MDMA and MDA in plasma and administration time in the single-administration group and continuous administration group were as follows:T=10.362C-1.183,R2=0.974 6;T=7.397 3C-0.694,R2=0.961 5(T:injection time;C:concentration ratio of MDMA to MDA in plasma).Conclusions The toxicokinetic data of MDMA and its metabolite MDA in rats,obtained through single and continuous administration,including peak concentration,peak time,detection time limit,and the relationship between concentration ratio and administration time,provide a theoretical and data foundation for relevant forensic identification.

Objective To explore the characteristic categories of presenteeism among ICU nurses and analyse the influencing factor.Methods A convenience sampling method was adopted to select 391 ICU nurses as the study subjects from four Grade IIIA hospitals in Zhejiang Province in May 2023.A general information questionnaire,the Stanford presenteeism scale-6,and Maslach burnout inventor were used in the survey.R language was used for latent profile analysis,and univariate analysis and multinomial logistic regression analysis were employed to explore the influencing factors of the latent profiles.Results A total of 391 ICU nurses completed the survey,with the score of presenteeism at 16.10±4.64,which was at medium level.The score of presenteeism was further divided into four latent classes:low work limitation-low work energy type accounted for 13.04%,high work limitation-moderate work energy type accounted for 24.55%,low work limitation-high work energy type accounted for 4.86%,moderate work limitation-moderate work energy type accounted for 57.55%.The influencing factors include average monthly income,the score of emotional exhaustion and personal fulfillment dimensions in job burnout(all P<0.05).Conclusion The incidence of presenteeism among the ICU nurses has distinctive classification characteristics.Based on the identified influencing factors,nursing managers should provide individualised interventions to the ICU nurses with different latent profiles of characteristic categories to reduce the presenteeism among the nurses and thereby to improve the quality of nursing services.