Objective: To examine the prevalence of e-cigarette use and associated factors among primary and secondary school students in Pudong New Area, Shanghai, and to explore the pathways linking harm perception of e-cigarettes, interpersonal social influence, and attitudes toward e-cigarette use with experimentation behavior, in order to provide scientific basis for further optimizing the prevention and control strategies of e-cigarette among adolescents. Methods: From September to October 2025, a multi stage cluster random sampling method was used to select 5 144 primary and secondary school students aged 8-19 years from 47 primary and secondary schools in Pudong New Area, Shanghai, to conduct an anonymous questionnaire survey. The questionnaire collected information on e-cigarette use, harm perception of e-cigarette, interpersonal social influence, and attitudes toward e-cigarette use. The Chi-square test was applied to analyze the differences in cigarette and e-cigarette use behavior among primary and secondary school students with different demographic characteristics. Structural equation modeling (SEM) was constructed using Mplus 8.3 software, and the bootstrap method was utilized to test the mediating effects. Results: The reported rates of cigarette experimentation, e-cigarette experimentation, and current e-cigarette use among primary and secondary school students were 1.85%, 2.10%, and 0.70%, respectively. Higher reporting rates of e-cigarette experimentation were observed among boys (2.82%), secondary school students aged 16-19 (3.39%), senior high school students (3.05%), and those with weekly pocket money >100 yuan ( 6.11% ) ( χ 2=11.67, 8.61, 8.00, 54.18, all P <0.05). Structural pathway analysis results demonstrated that e-cigarette harm perception positively predicted interpersonal social influence ( β =0.61) and e-cigarette use attitude ( β = 0.53 ), and interpersonal social influence ( β =0.65) and e-cigarette use attitude ( β =0.25) further promoted e-cigarette experimentation behavior among primary and secondary school students (all P <0.01), with interpersonal social influence playing a major mediating role (indirect effect=0.40). Conclusions E-cigarette experimentation behavior among primary and secondary school students in Pudong New Area is jointly influenced by multiple psychosocial factors. Intervention strategies should strengthen interpersonal social factors such as family and peers on the basis of health education, thereby constructing a comprehensive prevention and control strategy for e-cigarette use among primary and secondary school students.

This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers

The precise and rapid monitoring of multiple organ dysfunction is crucial in drug discovery. Traditional methods, such as pathological analysis, are often time-consuming and inefficient. Here, we developed a multiplexed near-infrared window two (NIR-II) fluorescent bioimaging method that allows for real-time, rapid, and quantitative assessment of multiple organ dysfunctions. Given that existing probes did not fully meet requirements, we synthesized a range of NIR-II hemicyanine dyes (HDs) with varying absorption and emission wavelengths. By modifying these dyes, we achieved high spatial and temporal resolution imaging of the liver, kidneys, stomach, and intestines. This method was further applied to investigate disorders induced by cisplatin, a drug known to cause gastric emptying issues along with liver and kidney injuries. By monitoring the metabolic rate of the dyes in these organs, we accurately quantified multi-organ dysfunction, which was also confirmed by gold-standard pathological analysis. Additionally, we evaluated the effects of five aristolochic acids (AAs) on multiple organ dysfunction. For the first time, we identified that AA-I and AA-II could cause gastric emptying disorders, which was further validated through transcriptomics analysis. Our study introduces a novel approach for the simultaneous monitoring of multi-organ dysfunction, which may significantly enhance the evaluation of drug side effects.

Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus (PJ) and Panax japonicus var. major (PJvm), containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM (sMRM), and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic (ROC)) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

Metabolomics covers a wide range of applications in life sciences,biomedicine,and phytology.Data acquisition(to achieve high coverage and efficiency)and analysis(to pursue good classification)are two key segments involved in metabolomics workflows.Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups.However,insufficient feature extraction,inappropriate feature selection,overfitting,or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused.Using two ginseng varieties,namely Panax japonicus(PJ)and Panax japonicus var.major(PJvm),containing the similar ginsenosides,we integrated pseudo-targeted metabolomics and deep neural network(DNN)modeling to achieve accurate species differentiation.A pseudo-targeted metabolomics approach was optimized through data acquisition mode,ion pairs generation,comparison between multiple reaction monitoring(MRM)and scheduled MRM(sMRM),and chromatographic elution gradient.In total,1980 ion pairs were monitored within 23 min,allowing for the most comprehensive ginseng metabolome analysis.The established DNN model demonstrated excellent classification performance(in terms of accuracy,precision,recall,F1 score,area under the curve,and receiver operating characteristic(ROC))using the entire metabolome data and feature-selection dataset,exhibiting superior advantages over random forest(RF),support vector ma-chine(SVM),extreme gradient boosting(XGBoost),and multilayer perceptron(MLP).Moreover,DNNs were advantageous for automated feature learning,nonlinear modeling,adaptability,and generalization.This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples.This established approach holds promise for plant metabolomics and is not limited to ginseng.

Immune-related nephropathy (IRN) refers to immune-response-mediated glomerulonephritis and is the main cause of end-stage renal failure. The pathogenesis of IRN is not fully understood; therefore, treatment is challenging. Traditional Chinese medicines (TCMs) have potent clinical effects in the treatment of the IRN conditions immunoglobulin A nephropathy, lupus nephropathy, and diabetic nephropathy. The underlying mechanisms mainly include its inhibition of inflammation; improvements to renal interstitial fibrosis, oxidative stress, autophagy, apoptosis; and regulation of immunity. In this review, we summarize the clinical symptoms of the three IRN subtypes and the use of TCM prescriptions, herbs, and bioactive compounds in treating IRN, as well as the potential mechanisms, intending to provide a reference for the future study of TCM as IRN treatments.

Objective To understand the change in distribution and antimicrobial resistance of bacteria isolated from blood specimens of Hunan Province,and provide for the initial diagnosis and treatment of clinical bloodstream infection(BSI).Methods Data reported from member units of Hunan Province Antimicrobial Resistance Survei-llance System from 2012 to 2021 were collected.Bacterial antimicrobial resistance surveillance method was imple-mented according to the technical scheme of China Antimicrobial Resistance Surveillance System(CARSS).Bacteria from blood specimens and bacterial antimicrobial susceptibility testing results were analyzed by WHONET 5.6 soft-ware and SPSS 27.0 software.Results A total of 207 054 bacterial strains were isolated from blood specimens from member units in Hunan Province Antimicrobial Resistance Surveillance System from 2012 to 2021,including 107 135(51.7％)Gram-positive bacteria and 99 919(48.3％)Gram-negative bacteria.There was no change in the top 6 pathogenic bacteria from 2012 to 2021,with Escherichia coli(n=51 537,24.9％)ranking first,followed by Staphylococcus epidermidis(n=29 115,14.1％),Staphylococcus aureus(n=17 402,8.4％),Klebsiella pneu-moniae(17 325,8.4％),Pseudomonas aeruginosa(n=4 010,1.9％)and Acinetobacter baumannii(n=3 598,1.7％).The detection rate of methicillin-resistant Staphylococcus aureus(MRSA)decreased from 30.3％in 2015 to 20.7％in 2021,while the detection rate of methicillin-resistant coagulase-negative Staphylococcus(MRCNS)showed an upward trend year by year(57.9％-66.8％).No Staphylococcus was found to be resistant to vancomy-cin,linezolid,and teicoplanin.Among Gram-negative bacteria,constituent ratios of Escherichia coli and Klebsiella pneumoniae were 43.9％-53.9％and 14.2％-19.5％,respectively,both showing an upward trend(both P＜0.001).Constituent ratios of Pseudomonas aeruginosa and Acinetobacter baumannii were 3.6％-5.1％and 3.0％-4.5％,respectively,both showing a downward trend year by year(both P＜0.001).From 2012 to 2021,resistance rates of Escherichia coli to imipenem and ertapenem were 1.0％-2.0％and 0.6％-1.1％,respectively;presenting a downward trend(P＜0.001).The resistant rates of Klebsiella pneumoniae to meropenem and ertapenem were 7.4％-13.7％and 4.8％-6.4％,respectively,presenting a downward trend(both P＜0.001).The resistance rates of Pseudomonas aeruginosa and Acinetobacter baumannii to carbapenem antibiotics were 7.1％-15.6％and 34.7％-45.7％,respectively.The trend of resistance to carbapenem antibiotics was relatively stable,but has de-creased compared with 2012-2016.The resistance rates of Escherichia coli to the third-generation cephalosporins from 2012 to 2021 were 41.0％-65.4％,showing a downward trend year by year.Conclusion The constituent ra-tio of Gram-negative bacillus from blood specimens in Hunan Province has been increasing year by year,while the detection rate of carbapenem-resistant Gram-negative bacillus remained relatively stable in the past 5 years,and the detection rate of coagulase-negative Staphylococcus has shown a downward trend.

For the past 30 years,percutaneous balloon mitral valve dilatation has been performed under the guidance of X-rays and bedside ultrasound.However,there are still some cases of mitral valve stenosis in the large atrium where balloon dilation failed.Intraperitoneal ultrasound-guided percutaneous balloon mitral valve plasty is accurate and feasible,which can reduce the occurrence of complications and improve the success rate of such elderly complex cases.Two patients with severe mitral stenosis underwent percutaneous balloon mitral valve plasty guided by intracardiac ultrasound.The operations were successful without any complications,which can provide reference for clinical treatment of mitral stenosis.

BACKGROUND: Patients with atrial fibrillation (AF) and prior stroke history have a high risk of cardiovascular events despite anticoagulation therapy. It is unclear whether catheter ablation (CA) has further benefits in these patients. METHODS: AF patients with a previous history of stroke or systemic embolism (SE) from the prospective Chinese Atrial Fibrillation Registry study between August 2011 and December 2020 were included in the analysis. Patients were matched in a 1:1 ratio to CA or medical treatment (MT) based on propensity score. The primary outcome was a composite of all-cause death or ischemic stroke (IS)/SE. RESULTS: During a total of 4.1 ± 2.3 years of follow-up, the primary outcome occurred in 111 patients in the CA group (3.3 per 100 person-years) and in 229 patients in the MT group (5.7 per 100 person-years). The CA group had a lower risk of the primary outcome compared to the MT group [hazard ratio (HR) = 0.59, 95% CI: 0.47-0.74, P < 0.001]. There was a significant decreasing risk of all-cause mortality (HR = 0.43, 95% CI: 0.31-0.61, P < 0.001), IS/SE (HR = 0.73, 95% CI: 0.54-0.97, P = 0.033), cardiovascular mortality (HR = 0.32, 95% CI: 0.19-0.54, P < 0.001) and AF recurrence (HR = 0.33, 95% CI: 0.30-0.37, P < 0.001) in the CA group compared to that in the MT group. Sensitivity analysis generated consistent results when adjusting for time-dependent usage of anticoagulants. CONCLUSIONS In AF patients with a prior stroke history, CA was associated with a lower combined risk of all-cause death or IS/SE. Further clinical trials are warranted to confirm the benefits of CA in these patients.

Objective: To explore the relationship between low density lipoprotein cholesterol (LDL-C)/high density lipoprotein cholesterol (HDL-C) ratio with the severity of coronary artery disease and 2-yeat outcome in patients with premature coronary heart disease. Methods: This prospective, multicenter, observational cohort study is originated from the PROMISE study. Eighteen thousand seven hundred and one patients with coronary heart disease (CHD) were screened from January 2015 to May 2019. Three thousand eight hundred and sixty-one patients with premature CHD were enrolled in the current study. According to the median LDL-C/HDL-C ratio (2.4), the patients were divided into two groups: low LDL-C/HDL-C group (LDL-C/HDL-C≤2.4, n=1 867) and high LDL-C/HDL-C group (LDL-C/HDL-C>2.4, n=1 994). Baseline data and 2-year major adverse cardiovascular and cerebrovascular events (MACCE) were collected and analyzed in order to find the differences between premature CHD patients at different LDL-C/HDL-C levels, and explore the correlation between LDL-C/HDL-C ratio with the severity of coronary artery disease and MACCE. Results: The average age of the low LDL-C/HDL-C ratio group was (48.5±6.5) years, 1 154 patients were males (61.8%); the average age of high LDL-C/HDL-C ratio group was (46.5±6.8) years, 1 523 were males (76.4%). The number of target lesions, the number of coronary artery lesions, the preoperative SNYTAX score and the proportion of three-vessel coronary artery disease in the high LDL-C/HDL-C group were significantly higher than those in the low LDL-C/HDL-C group (1.04±0.74 vs. 0.97±0.80, P=0.002; 2.04±0.84 vs. 1.85±0.84, P<0.001; 13.81±8.87 vs. 11.70±8.05, P<0.001; 36.2% vs. 27.4%, respectively, P<0.001). Correlation analysis showed that there was a significant positive correlation between LDL-C/HDL-C ratio and preoperative SYNTAX score, the number of coronary artery lesions, the number of target lesions and whether it was a three-vessel coronary artery disease (all P<0.05). The 2-year follow-up results showed that the incidence of MACCE was significantly higher in the high LDL-C/HDL-C group than that in the low LDL-C/HDL-C group (6.9% vs. 9.1%, P=0.011). There was no significant difference in the incidence of all-cause death, cardiac death, myocardial infarction, stroke, revascularization and bleeding between the two groups. Cox multivariate regression analysis showed that the LDL-C/HDL-C ratio has no correlation with 2-year MACCE, death, myocardial infarction, revascularization, stroke and bleeding events above BARC2 in patients with premature CHD. Conclusion: High LDL-C/HDL-C ratio is positively correlated with the severity of coronary artery disease in patients with premature CHD. The incidence of MACCE of patients with high LDL-C/HDL-C ratio is significantly higher during 2 years follow-up; LDL-C/HDL-C ratio may be an indicator for evaluating the severity of coronary artery disease and long-term prognosis in patients with premature CHD.
Male ; Humans ; Adult ; Middle Aged ; Female ; Coronary Artery Disease/complications* ; Cholesterol, HDL ; Cholesterol, LDL ; Prospective Studies ; Myocardial Infarction/etiology* ; Stroke ; Risk Factors