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.

Based on copper death, this study investigates the effect and mechanism of Shenmai Injection on isoproterenol(ISO)-induced myocardial fibrosis(MF) in rats. SPF-grade male SD rats were randomly divided into a normal group, model group, captopril(5 mg·kg~(-1)) positive control group, and Shenmai Injection low(6 mL·kg~(-1)), medium(9 mL·kg~(-1)), and high(12 mL·kg~(-1)) dose groups. Except for the normal group, the rats in the other groups were subcutaneously injected with ISO(5 mg·kg~(-1)) once a day for 10 consecutive days to establish an MF model. Starting from the second day after successful modeling, intraperitoneal injections of the respective treatments were administered for 28 consecutive days. Hematoxylin-eosin(HE) and Masson staining were used to observe pathological changes and fibrosis levels in the myocardial tissue. Colorimetry was employed to detect serum Cu~(2+) concentration in rats. The levels of inflammatory cytokines interleukin-6(IL-6), interleukin-1β(IL-1β), interleukin-18(IL-18), tumor necrosis factor-α(TNF-α), as well as mitochondrial energy metabolites adenosine triphosphate(ATP), adenosine diphosphate(ADP), and adenosine monophosphate(AMP) in serum were measured using enzyme-linked immunosorbent assay(ELISA). Western blot was performed to detect the expression of collagen Ⅰ(Col-Ⅰ), collagen Ⅲ(Col-Ⅲ), and copper death-related proteins dihydrolipoamide acetyltransferase(DLAT), ferredoxin 1(FDX1), lipoic acid synthetase(LIAS), and heat shock protein 70(HSP70) in myocardial tissue. Immunofluorescence was used to detect the expression of DLAT, FDX1, and HSP70, while immunohistochemistry was conducted to examine the expressions of DLAT, FDX1, LIAS, and HSP70. The results showed that, compared to the model group, the myocardial structure disorder and collagen fiber deposition in the drug treatment groups were significantly improved, the cardiac index level was reduced, serum Cu~(2+), IL-6, IL-1β, IL-18, TNF-α, ADP, and AMP levels were significantly decreased, ATP levels were significantly increased, and the expressions of Col-Ⅰ, Col-Ⅲ, and HSP70 proteins in myocardial tissue were significantly reduced, while the expressions of DLAT, FDX1, and LIAS proteins were significantly elevated. In conclusion, Shenmai Injection effectively alleviates myocardial structure disorder and interstitial collagen fiber deposition in ISO-induced MF rats, promotes copper excretion, and reduces copper death in the ISO-induced rat MF model.
Animals ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Rats ; Myocardium/metabolism* ; Drug Combinations ; Fibrosis/metabolism* ; Copper/blood* ; Cardiomyopathies/genetics* ; Humans

Jiuwei Xifeng Granules have become a Chinese patent medicine in the market. Because the formula contains Os Draconis, a top-level protected fossil of ancient organisms, the formula was to be improved by replacing Os Draconis with Ostreae Concha. To evaluate whether the improved formula has the same effectiveness and safety as the original formula, a randomized, double-blind, parallel-controlled, equivalence clinical trial was conducted. This study enrolled 288 tic disorder(TD) of children and assigned them into two groups in 1∶1. The treatment group and control group took the modified formula and original formula, respectively. The treatment lasted for 6 weeks, and follow-up visits were conducted at weeks 2, 4, and 6. The primary efficacy endpoint was the difference in Yale global tic severity scale(YGTSS)-total tic severity(TTS) score from baseline after 6 weeks of treatment. The results showed that after 6 weeks of treatment, the declines in YGTSS-TSS score showed no statistically significant difference between the two groups. The difference in YGTSS-TSS score(treatment group-control group) and the 95%CI of the full analysis set(FAS) were-0.17[-1.42, 1.08] and those of per-protocol set(PPS) were 0.29[-0.97, 1.56], which were within the equivalence boundary [-3, 3]. The equivalence test was therefore concluded. The two groups showed no significant differences in the secondary efficacy endpoints of effective rate for TD, total score and factor scores of YGTSS, clinical global impressions-severity(CGI-S) score, traditional Chinese medicine(TCM) response rate, or symptom disappearance rate, and thus a complete evidence chain with the primary outcome was formed. A total of 6 adverse reactions were reported, including 4(2.82%) cases in the treatment group and 2(1.41%) cases in the control group, which showed no statistically significant difference between the two groups. No serious suspected unexpected adverse reactions were reported, and no laboratory test results indicated serious clinically significant abnormalities. The results support the replacement of Os Draconis by Ostreae Concha in the original formula, and the efficacy and safety of the modified formula are consistent with those of the original formula.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Male ; Double-Blind Method ; Drugs, Chinese Herbal/therapeutic use* ; Tic Disorders/drug therapy* ; Treatment Outcome

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

According to the work goals and tasks determined by edition outline of the Chinese Pharmacopoeia 2025 Edition, the Chinese Pharmacopoeia 2025 has been completed. Among them, 52 new pharmaceutical excipients monographs have been added, and the total number has reached 387. 245 pharmaceutical excipients monographs have been revised, of which 109 monographs have only textual revisions and 136 monographs have substantive revisions. This article focuses on the general framework and the main characteristics of the standards of pharmaceutical excipients in the Chinese Pharmacopoeia 2025, which can contribute to accurately understand and utilize the standards in Chinese Pharmacopoeia.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Xanthine oxidase (XO) is an important therapeutic target for the treatment of hyperuricemia and gout. Based on the previously identified potent XO inhibitor 1, seventeen oxadiazoles and their ring-opening analogues were designed and synthesized via the bioisostere replacement strategy. Among them, compounds 2l, 2n, and 3b showed obvious XO inhibitory activity at the concentration of 10 μmol·L^-1, and compound 3b exhibited an IC₅₀ value of 1.45 μmol·L^-1.

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.