ObjectiveThis study aimed to provide a scientific basis for the safety management of drinking water by assessing the contamination levels of 21 per- and polyfluoroalkyl substances (PFASs) in water samples collected from the Yangtze River Delta region. MethodsSolid-phase extraction coupled with ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) was employed to determine 21 PFASs in 6 source water samples, 20 treated water samples, and 60 tap water samples collected from 5 administrative districts in the Yangtze River Delta region across four seasons in 2023. The Kruskal-Wallis H test was used to compare differences in PFAS concentrations among the three types of water samples, followed by post hoc pairwise comparisons with Bonferroni correction. Removal efficiencies of target compounds were also calculated. ResultsAmong the 86 samples, 14 PFASs were detected, with 7 compounds detected in 100% of samples. The total concentrations of PFASs in source water, treated water, and tap water ranged from 63.85 to 190.54 ng·L^-¹, 55.75 to 774.36 ng·L^-¹, and 40.72 to 689.80 ng·L^-¹, respectively. The compounds with the highest median concentrations were perfluorobutanoic acid (PFBA) (40.19, 15.20, and 14.05 ng·L^-¹), perfluorohexanoic acid (PFHxA) (29.69, 32.62, and 34.24 ng·L^-¹), perfluorooctanoic acid (PFOA) (17.65, 39.45, and 36.83 ng·L^-¹), and potassium perfluorobutanesulfonic acid (PFBS) (16.99, 24.38, and 23.89 ng·L^-¹). Notably, concentrations of PFOA (7.71‒71.63 ng·L^-¹) and PFOS (-¹) in tap water were below the regulatory limits specified in GB 5749‒2022 Standards for Drinking Water Quality (PFOA: 0.000 08 mg·L^-1, PFOS: 0.000 04 mg·L^-1). Significant seasonal variations in PFAS concentrations were observed, with total PFAS levels in March being higher than those in September and November (adjusted P<0.001, and P=0.006), and levels in May being higher than those in September (adjusted P=0.037). The removal efficiencies of PFASs in the water treatment plants ranged from -14% to 34%. ConclusionPFAS contamination is widespread in source water, treated water, and tap water in the Yangtze River Delta region, and concentrations of PFOA and PFOS in all tested water samples comply with the Chinese national standards for drinking water quality (GB 5749‒2022). The use of PFASs should be continuously regulated to ensure water safety.

In this work,four salicylhydrazone compounds(L1?L4)were designed and synthesized by using vanillin derivatives as raw material.The structures were confirmed by nuclear magnetic resonance(NMR)and high-resolution mass spectrometry(HRMS).The optical experiments showed that probe L1 and probe L3 could be used as aluminium ion(Al3+)fluorescence probes.The fluorescence color of probe L1 solution changed from colorless to blue after adding Al3+,and the limit of detection was 25.1 nmol/L.Compared with probe L1,the fluorescence color of probe L3 solution changed from colorless to green after complexing with Al3+,and the limit of detection was 17.3 nmol/L.Probe L1 and probe L3 showed the advantages of fast response speed,high selectivity and good anti-interference.The mechanism of Al3+recognition was further demonstrated by HRMS and 1H NMR.Cell imaging experiments showed that probe L1 and L3 had low cytotoxicity and had great application potential in detection of Al3+in vivo.

Arsenic is a semi-metal,and lipid-soluble arsenic compounds are one of the widespread forms in the environment and food chain,but there is a lack of standards for lipid-soluble arsenic compounds,which is one of the bottlenecks in the current analytical detection and toxicological studies of organic arsenic.In this study,four saturated arsenic-containing hydrocarbons,AsHC 318,AsHC 332,AsHC 346,and AsHC 374(The number is relative molecular mass),were successfully synthesized in three steps by using dimethylarsinic acid,potassium iodide,sodium hydroxide,and four brominated alkanes(1-Bromotetradecane,1-bromopentadecane,1-bromohexadecane,and 1-bromooctadecane)as raw materials.The structures of these four saturated arsenic-containing hydrocarbons were characterized by proton nuclear magnetic resonance(1H NMR)spectroscopy,13C nuclear magnetic resonance(13C NMR)spectroscopy,and high-resolution mass spectrometry(HR-MS).The yields of the method were 8%-10%,and the synthesized compounds could be used in subsequent toxicity evaluation experiments to assess the toxic effects and mechanisms of action of arsenic-containing hydrocarbons.This study provided an effective method for synthesis of arsenic-containing hydrocarbons,enriching the synthesis methods of arsenic-containing hydrocarbons,and provided raw materials for the subsequent toxicological studies of arsenic-containing hydrocarbons.

OBJECTIVE: Circadian rhythm disruption (CRD) is a risk factor that correlates with poor prognosis across multiple tumor types, including hepatocellular carcinoma (HCC). However, its mechanism remains unclear. This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity. METHODS: To quantify CRD, the HCC CRD score (HCCcrds) was developed. Using machine learning algorithms, we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort (n = 369), and the robustness of this method was validated. Furthermore, we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes. RESULTS: We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis. The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis, higher pathological grade, and advanced clinical stages, while the CRD-related subtype with low HCCcrds had better clinical outcomes. We also identified novel biomarkers for each subtype, such as nicotinamide n-methyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1. CONCLUSION We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers. Within these groups greater HCCcrds was associated with worse prognosis. This approach has the potential to improve prediction of an individual's prognosis, guide precision treatments, and assist clinical decision making for HCC patients. Please cite this article as: Li XJ, Chang L, Mi Y, Zhang G, Zhu SS, Zhang YX, et al. Integrated-omics analysis defines subtypes of hepatocellular carcinoma based on circadian rhythm. J Integr Med. 2025; 23(4): 445-456.
Humans ; Carcinoma, Hepatocellular/pathology* ; Liver Neoplasms/pathology* ; Circadian Rhythm/genetics* ; Prognosis ; Male ; Female ; Biomarkers, Tumor/genetics* ; Middle Aged ; Machine Learning ; Computational Biology

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective:To develop and assess a deep learning-based model for automatic segmentation of organs at risk (OARs) in postoperative brachytherapy for endometrial carcinoma (EC).Methods:A retrospective study was conducted on the computed tomography (CT) images of 108 EC patients who received high-dose-rate (HDR) 192Ir intracavitary vaginal-cuff brachytherapy (VCB) at the Peking University Third Hospital from November 2021 to October 2022. Then, the rectum, colon, small intestine, and bladder in these images were manually segmented. These patients were randomly divided into two groups using a random number table: 90 cases for training the 3D no-new-U-Net (nnU-Net) segmentation model and 18 cases for model testing. The precision and clinical applicability of the automatic segmentation model were assessed using geometric indexes including Dice similarity coefficient (DSC), Hausdorff distance (HD), and mean surface distance (MSD), as well as dose-volume parameters (DVPs) including the minimum dose to 0.1, 1.0, and 2.0 cm 3 of OARs that received the highest irradiation doses ( D0.1 cm 3, D1.0 cm 3, and D2.0 cm 3). Results:The 3D nnU-Net model yielded mean DSC values of 0.90, 0.85, 0.88, and 0.95, respectively for the segmentations of the rectum, colon, small bowel, and bladder, all of which were better than those of the 3D U-Net and V-Net models. The differences among the three models were statistically significant ( F = 21.78, 24.33, 36.00, 20.11, P < 0.001). The 3D nnU-Net exhibited statistically significant differences in HD values for the colon, small intestine, and bladder segmentations among the three method ( F = 17.33, 24.11, 6.33, P < 0.05). The 3D nnU-Net model yielded lower MSD values for the segmentations of all organs compared to the control model, with statistically significant differences ( F = 29.78, 27.11, 27.11, 14.78, P < 0.001). No statistically significant difference was found in all DVPs between the 3D nnU-Net model-based and manual segmentations ( P > 0.05). Bland-Altman analysis demonstrated great consistency between the 3D nnU-Net and manual segmentations. Conclusions:The 3D nnU-Net-based model exhibits high geometric accuracy and dosimetric consistency with manual segmentation of OARs in brachytherapy, holding potential to improve clinical efficiency.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.