Objective To investigate the detection rate of non-alcoholic fatty liver disease (NAFLD) and influencing factors in the elderly population undergoing physical examination in Nanjing. Methods People who participated in the elderly physical examination in Nanjing from 2018 to 2023 were selected as the study subjects according to the inclusion and exclusion criteria. Basic information and physical examination results were collected. The t-test and Chi-square test were used to compare the detection status of NAFLD in different characteristic populations, and multivariate logistic regression model was used to analyze influencing factors of NAFLD. Results A total of 41 066 people were included in the study, with a detection rate of 39.55%. The detection rate in males (24.12%) was significantly lower than that in females (49.75%) (χ² = 2702.442, P<0.001). Trend χ² test results showed that the detection rate of NAFLD increased gradually with BMI (χ²_trend = 4084.414, P_trend < 0.001). Multivariate logistic regression analysis showed that female (OR = 3.055, 95% CI : 2.911-3.206), primary school or below (OR = 1.075, 95% CI : 1.009-1.146), unmarried (OR = 1.107, 95% CI : 1.039-1.179), BMI (18.5kg/m²-23.9 kg/m²: OR = 4.876, 95% CI :3.340-7.119; 24.0 kg/m²-27.9 kg/m²: OR = 15.324, 95% CI : 10.503-22.358; ≥28.0 kg/m²: OR = 37.433, 95% CI : 25.591-54.753), hypertension (OR = 1.095, 95% CI : 1.040-1.153), diabetes mellitus (OR = 1.317, 95% CI :1.250-1.387), and dyslipidemia (OR = 1.574, 95% CI : 1.501-1.652) were risk factors for NAFLD (all P<0.05). Conclusion The detection rate of NAFLD in the elderly population undergoing physical examinations in Nanjing is relatively high. Women, unmarried people, people with low education, overweight and obesity, and people with hypertension, diabetes, and dyslipidemia are the high-risk groups.

OBJECTIVE To innovatively apply the pre-intelligent precision dosing and verification system （hereinafter referred to as “the system”）， and to provide a reference for the high-level “intelligent” transformation of inpatient pharmacy. METHODS The limitations of the triple-serial dispensing mode， which comprised the automatic medicine packaging machine （ATC）， intelligent tablet dispensing table （ITDT） and medication detection machine （MDM）， were analyzed. The application of the system and the adoption of the barcode scanning verification method optimized the pre-dosing management， whole-tablet drug dispensing process and ATC temporary dosing management. The comparative analysis was conducted to assess dosing time， labor cost and packaging error of the eight-month period， before and after the system application. RESULTS The triple-serial dispensing mode had a weak ability to avoid error risks in the manual dosing stage， and also had errors in the verification stage. Through the innovative application system， the pre-dosing management had been upgraded， the whole-tablet drug dispensing process had been optimized， and the ATC temporary dosing management had been improved. The average time required for each drug for pre-dosing， whole-tablet drug dispensing and ATC temporary dosing was significantly shortened after the application of the system， compared with before the application of the system （P＜0.001）. The number of pharmacists was reduced from two to one. The error rate of ATC decreased significantly from 0.220‰ to 0.029‰ （P＜0.001）. Specifically， the rate of pharmacist-related errors （pre-dosing error， ITDT dosing error， and ATC temporary dosing error） decreased from 0.116‰ to 0.001‰ （P＜0.001）， and machine-related errors decreased from 0.096‰ to 0.023‰ （P＜0.001）. CONCLUSIONS This innovative integration mode greatly improves the working efficiency and quality of inpatient pharmacy. It enhances refined management of drug expiration and inventory， saves time and labor costs， improves the accuracy of drug dispensing， and ensures patient medication safety.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective: To understand the current situation and influencing factors of comorbidity of depressive and anxiety symptoms among middle school students in Chongqing, so as to provide a scientific basis for formulating a comprehensive strategy for the co prevention of multiple diseases among middle school students. Methods: From September to December 2024, 12 327 middle school students were selected from 6 districts and counties in Chongqing by the combination of stratified cluster sampling and convenience sampling method. The current status of depressive and anxiety symptoms was investigated by using the Center for Epidemiological Survey-Depression Scale (CES-D) and the Generalized Anxiety Disorder-7 (GAD-7). The Chi-squared test was used to compare the differences between groups with comorbidity of depressive and anxiety symptoms, multivariate Logistic regression analysis was used to analyze its related factors, and a nomogram prediction model was drawn. Results: The detection rates of depressive symptoms, anxiety symptoms and comorbidity among middle school students in Chongqing were 26.34%, 34.55% and 21.16%, respectively. Among them, the detection rates of the three types of symptoms in girls (29.80%, 40.99%, 25.15%) were all higher than those in boys (23.22%, 28.73%, 17.55%) ( χ 2=68.61, 204.23, 106.51, all P <0.01). Statistical significance was observed in the distribution of depressive and anxious symptoms among middle school students across different gender, academic stage, school district, family type, physical activity levels, parental discipline, smoking, alcohol consumption, sleep deprivation, excessive screen time, Internet addiction, and bullying ( χ 2=14.49-991.46, all P <0.01). Multivariate Logistic regression analysis showed that compared with junior high school students, ordinary high school students had a higher risk of comorbidity ( OR=2.71, 95% CI = 2.41-3.05); girls ( OR=2.17, 95%CI =1.95-2.40), non-core family ( OR=1.20, 95%CI =1.08-1.32), and good neighborhood ( OR=1.16, 95%CI =1.02-1.30), campus bullying ( OR=4.88, 95%CI =4.32-5.50), Internet addiction ( OR=4.77, 95%CI = 3.41 -6.68), parental beating and scolding ( OR=3.18, 95%CI =2.72-3.71), alcohol consumption ( OR=2.10, 95%CI =1.86- 2.37 ), and insufficient sleep ( OR=1.73, 95%CI =1.54-1.95) had higher risks with comorbidity of depression and anxiety symptoms (all P <0.05). A nomogram prediction model was constructed based on significant variables shows that C-index=0.75 (AUC= 0.75 , 95% CI=0.74-0.76, P <0.05), and the model had good predictive performance. Conclusions The current situation of comorbidity of depressive and anxiety symptoms among middle school students in Chongqing is not optimistic. The nomograms can be used to effectively predict the risk of comorbidity of depressive and anxiety symptoms in middle school students.

The paper introduces Professor SUN Shentian's experience in clinical practice of Ningshen (tranquilizing the mind) point. This point is an empirical point discovered by Professor SUN on the basis of meridian differentiation, nerve function and anatomic location, and in association with the years of clinical practice. The point is located in the prefrontal area, jointed with the distribution of the governor vessel, and responded to the body surface projection area of the frontal pole. It works on regulating the mind, regaining consciousness, improving cognition, alleviating depression, mutually treating physical and mental disorders, as well as unblocking collaterals, regulating the tendons and relieving spasm. This point is widely used in treatment of mental disorders, stroke and extrapyramidal diseases and obtains the reliable therapeutic effect in clinical practice.
Humans ; Acupuncture Points ; Acupuncture Therapy/history* ; China ; Meridians ; History, 20th Century

An assay was established for detection of toxigenic Clostridioides difficile by combining microfluidic chip analysis with immunochromatography,and its performance was evaluated and compared with those of the Xpert C.difficile/Epi and VIDAS CD AB tests.Primer pairs were designed according to the tcdB and tpi genes in C.difficile.The specificity,limit of detection,reproducibility,and stability were evaluated.A total of 215 stool samples from patients with diarrhea were collected and tested in parallel with the Xpert C.difficile/Epi,VIDAS CDAB,and our assay.C.difficile was isolated from samples,and the tcdB gene was identified when discrepant results were obtained from the three above assays.Our assay showed no cross-reaction with other diarrhea-associated pathogens.Its reproducibility was 100％in testing of two standard plasmids containing tcdB and tpi genes at two concentrations(105 and 102 copies/μL).Two standard plasmids were detected after the PCR and immunochromatography reagents had been stored for 3,6,9,and 12 months,and all the results were posi-tive.The limit of detection was 10 copies/μL for toxigenic C.difficile.Testing of 33 samples positive for C.difficile with our assay(33/215,15.3％)yielded findings statistically coherent with those of the Xpert C.difficile/Epi test(kappa value=0.965).The sensitivity,specificity,positive predictive value,and negative predictive value of our assay,with respect to Xpert C.difficile/Epi as the standard,were 94.3％,100.0％,100.0％,and 98.9％;these values were significantly higher than those of VIDAS CDAB(60.0％,98.9％,91.3％,and 92.7％)(Kappa=0.714,OR=157.50,95％CI:62.03-847.28,P=0.013).In conclusion,our newly developed assay is specific,stable,and reproducible,and may be used for rapid and accu-rate detection of toxigenic C.difficile.The assay could be used for C.difficile infection screening in outpatient and emergen-cy,community medical service center,and epidemiological settings.

AIM To study the chemical constituents from the water fraction of rhizoma of Smilax trinervula Miq.and their biological activities.METHODS Polyamide,silica gel,Sephadex LH-20,ODS and semi-preparative HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antitumor activities were determined by MTT mothod,and the inhibitory activities on α-glucosidase were determined by PNPG method.RESULTS Eleven compounds were isolated and identified as tyrosine(1),uridine(2),2-(2',3',4'-trihydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(3),2-(1',2',3',4'-tetrahydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(4),2-(1',2',3',4'-tetrahydroxybutyl)-5-(2",3",4"-trihydroxybutyl)-pyrazine(5),uracil(6),2-(1',2',3',4'-tetrahydroxybutyl)-5-(1",2",3",4"-tetrahydroxybutyl)-pyrazine(7),dioscin(8),shikimic acid(9),pyrazine(10),3,4-dihydroxyphenyethyl alcohol 8-O-β-D-glycopyranoside(11).The IC50 values of compounds 8 to human breast cancer cell MCF-7 was(2.36±0.26)μg/mL,and the IC50 values of compounds 3-5 and 7 to α-glucosidase were(1.54±0.15)-(10.53±0.38)μg/mL.CONCLUSION Compounds 1-7,10 are isolated from Smilax genus for the first time,and compound 9,11 are first isolated from this plant.Compound 8 has anti-tumor activity,and compounds 3-5,7 have α-glucosidase inhibitory activities.

Objective To analyze the global literature related to functional cure of hepatitis B from 2019 to 2023 by using bibliometric analysis methods,so as to help researchers understand the research hotspots and trends in this field.Methods The literature related to the topic of functional cure of hepatitis B included in the Science Citation Index Expanded(SCI-Expanded)of the Web of Science Core Collection from 2019 to 2023 was searched.By using VOSviewer and CiteSpace visual analysis tools,analyses were conducted from the perspectives of publication trends,international research cooperation networks,and keyword emergence,and were elaborated with the specific contents of the related literature to elucidate research hotspots and trends.Results A total of 600 eligible papers in this field were included.Keyword co-occurrence and thematic clustering suggested that the main research directions of functional cure were:serum biomarkers for prediction and monitoring of functional cure,functional cure and immunity,nucleoside analog discontinuation,interferon therapy,and long-term prognosis of functional cure.The research contents of the ESI highly cited original research papers were similar to the clustering of the above,but showed more attention on the novel agents for functional cure.The content of the keyword emergence map showed that hotspots of interest changed from virologic mechanisms and serum markers,to nucleoside analog discontinuation and interferon therapy,and finally to immunologic mechanisms and new drug.Conclusion The research hotspots and trends of functional cure of hepatitis B were focused on virological mechanism,serum markers,immunological mechanism,nucleoside analog discontinuation,interferon therapy,and long-term prognosis after cure.

Objective To explore the characteristics of fine motor deficits in the elderly individuals with MCI due to AD through a new wearable inertial motion capture device,and then construct a prediction model for MCI.Methods A total of 260 elderly subjects were recruited in community from November,2022 to April,2023,and based on diagnosis,they were divided into a MCI group(134 cases)and a control group(126 cases).A new wearable inertial motion capture device,which was self-designed and developed based on MEMS inertial sensor,was used to capture the fine mo-tor movements of the hands,and the obtained data were analyzed with a computerized assessment system to make the quantitative evaluation of fine motor.LASSO learning algorithm and logistic regression analysis were employed to identify the predictive factors for MCI,and then a nomo-gram was constructed based on these factors.ROC curve was plotted to evaluate the predictive ability of the model by calculating its AUC value.DC A,CIC,and Bootstrap method were applied to evaluate and validate the clinical utility and stability of the model.Results The total score of MoCA(22.18±2.84 vs 27.60±1.10)and scores of the dimensions were significantly lower in the MCI group than the control group(all P＜0.01).In the five digital assessment tasks,the MCI group showed obviously poorer fine motor performance of both hands than the control group(P＜0.05,P＜0.01).ROC curve analysis showed that the AUC value of our nomogram model in predicting MCI was 0.762(95％CI:0.705-0.819).DCA,CIC,and Bootstrap methods demonstra-ted good and relatively stable discrimination,calibration,and clinical applicability of the model.Conclusion MEMS inertial sensor motion capture technology can make digital evaluation of fine motor.For the elderly,fine motor deficits are significantly associated with risk for MCI.Our no-mogram model based on fine motion parameters shows good predictive efficacy in assessing the risk of MCI.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.