Chronic obstructive pulmonary disease （COPD）， as one of the three major causes of death， is a complex systemic disease with high prevalence， high mortality， high disability， frequent acute exacerbations， and a variety of pulmonary complications. The pathogenesis is complex. Western medicine has no effective specificity scheme for a complete cure. However， multiple-component and multiple-target characteristics of traditional Chinese medicine （TCM） demonstrate significant advantages in COPD treatment through multi-link， multi-pathway， and multi-mechanism intervention. Therefore， exploring the essence of COPD pathogenesis and discovering effective TCM treatment drugs through the application of TCM principles and prescriptions is a key focus of modern research. Animal models are of paramount importance in medical research. It is the first consideration to select appropriate animals， adopt reasonable modeling methods to replicate stable animal models that closely resemble the clinical manifestations and pathophysiological characteristics of COPD， and use appropriate evaluation methods to determine the success of COPD animal models in experimental research. The core of experimental research lies in observing the intervention effect of TCM on COPD animal models， exploring the specific pathways and regulatory mechanisms of TCM on COPD disease， and finding TCM monomers， single herbs， and TCM formulas with definite curative effects. At present， animal model research on COPD mainly involves model establishment， model evaluation， efficacy observation， mechanism exploration， and other aspects. In recent years， there has been no systematic organization， update， and reflection on the relevant research on TCM intervention in COPD animal models. This study reviewed the selection of animals for the COPD model， methods for establishing COPD animal models， model evaluation methods， and the intervention effects of TCM on COPD animal models. It aims to grasp the current research status and identify existing problems for further improvement， in order to provide evidence and support for scientific research and clinical treatment of COPD.

Chronic obstructive pulmonary disease （COPD）， as one of the three major causes of death， is a complex systemic disease with high prevalence， high mortality， high disability， frequent acute exacerbations， and a variety of pulmonary complications. The pathogenesis is complex. Western medicine has no effective specificity scheme for a complete cure. However， multiple-component and multiple-target characteristics of traditional Chinese medicine （TCM） demonstrate significant advantages in COPD treatment through multi-link， multi-pathway， and multi-mechanism intervention. Therefore， exploring the essence of COPD pathogenesis and discovering effective TCM treatment drugs through the application of TCM principles and prescriptions is a key focus of modern research. Animal models are of paramount importance in medical research. It is the first consideration to select appropriate animals， adopt reasonable modeling methods to replicate stable animal models that closely resemble the clinical manifestations and pathophysiological characteristics of COPD， and use appropriate evaluation methods to determine the success of COPD animal models in experimental research. The core of experimental research lies in observing the intervention effect of TCM on COPD animal models， exploring the specific pathways and regulatory mechanisms of TCM on COPD disease， and finding TCM monomers， single herbs， and TCM formulas with definite curative effects. At present， animal model research on COPD mainly involves model establishment， model evaluation， efficacy observation， mechanism exploration， and other aspects. In recent years， there has been no systematic organization， update， and reflection on the relevant research on TCM intervention in COPD animal models. This study reviewed the selection of animals for the COPD model， methods for establishing COPD animal models， model evaluation methods， and the intervention effects of TCM on COPD animal models. It aims to grasp the current research status and identify existing problems for further improvement， in order to provide evidence and support for scientific research and clinical treatment of COPD.

Objective: To investigate factors influencing perioperative blood transfusion in patients with scarred uterus during pregnancy undergoing cesarean section, construct and validate a transfusion risk prediction model, and provide evidence for preoperative assessment and blood management. Methods: Clinical data of 405 patients undergoing cesarean section for scarred uterus during pregnancy at the First Affiliated Hospital of Xi'an Jiaotong University from January 2020 to December 2024 were retrospectively collected. The dataset was randomly divided into a training set (n=284) and a validation set (n=121) at a 7∶3 ratio. Within the training set, Firth-penalized logistic regression was employed for multivariate analysis to identify independent factors influencing perioperative blood transfusion and construct a predictive model. Model performance was evaluated in the validation set. Results: Multivariate Firth regression analysis showed that severe placenta previa (OR=75.566, 95%CI: 8.603-9979.174) and placenta accreta (OR=4.591, 95%CI: 1.120-19.416) were independent risk factors for perioperative blood transfusion, while preoperative red blood cell count (OR=0.189, 95%CI: 0.083-0.405) and fibrinogen levels (OR=0.588, 95%CI: 0.395-0.855) were protective factors. The predictive model constructed based on these four variables demonstrated good discriminatory performance, with areas under the receiver operating characteristic curves of 0.803 (95%CI: 0.740-0.867) and 0.753 (95%CI: 0.644-0.862) in the training and validation sets, respectively. Conclusion: For patients with scarred uterus during pregnancy undergoing cesarean section, severe placenta previa and placenta accreta significantly increase the risk of transfusion, while higher preoperative red blood cell count and fibrinogen levels exert a protective effect. The predictive model established in this study facilitates the identification of patients requiring transfusion, thereby enabling preoperative blood preparation and optimized blood management.

Hepatocellular carcinoma (HCC) imposes a major health and economic burden worldwide, with disproportionate effects in low- and middle-income countries (LMICs). Surveillance in high-risk populations, typically using semiannual ultrasound and alpha-fetoprotein testing, has been shown to be cost-effective by enabling earlier detection and improving survival. Yet, its overall value is reduced by poor adherence and the limited sensitivity of ultrasound, particularly in patients with metabolic-associated steatotic liver disease. Emerging approaches—including abbreviated magnetic resonance imaging, multi-biomarker models (e.g., gender, age, AFP, AFP-L3, and DCP), and liquid biopsy assays such as methylated DNA markers—demonstrate greater diagnostic accuracy and potential economic advantages compared with conventional methods. Integration of artificial intelligence into imaging may further enhance efficiency and reduce downstream costs. Moving toward precision surveillance, guided by individualized risk stratification that incorporates etiology, fibrosis stage, and molecular profiles, can optimize allocation of resources and maximize cost-effectiveness at the population level. Interventions to improve adherence, including mailed outreach and behavioral economic incentives, have shown both clinical benefit and cost savings, underscoring the role of implementation science. Because socioeconomic disparities influence both access and outcomes, economic models must explicitly address equity to achieve sustainable impact. Future research should prioritize prospective trials that evaluate not only clinical performance but also the real-world cost-effectiveness of novel technologies and stratified surveillance strategies. For LMICs, adapting proven models into affordable, context-appropriate programs is essential. By combining prevention, precision risk assessment, innovative technologies, and equitable implementation, HCC surveillance can deliver both clinical and economic value, reducing the global burden of disease.

Objective To systematically evaluate the efficacy and safety of traditional Chinese medicine (TCM) compound in treating pulmonary nodules, providing evidence-based medical evidence for TCM intervention in pulmonary nodules. Methods Computer search of PubMed, CNKI, Wanfang, VIP, and SinoMed was conducted to select randomized controlled trials (RCTs) of TCM compound intervention in pulmonary nodules, with the retrieval time from the inception to November 29, 2023. The Cochrane bias risk assessment tool was used to evaluate the quality of the included studies, and Review Manager 5.4 was used for Meta-analysis. Results A total of 18 RCTs were included, covering 8 provinces across the country, with a total sample size of 1301 patients. The TCM compounds used in the included studies all incorporated the method of dissolving phlegm and dissipating nodules. There was a high risk of bias uncertainty in the included studies. Meta-analysis results suggested that TCM compound could significantly reduce the diameter of pulmonary nodules [MD=−1.41, 95%CI (−1.70, −1.13), P<0.001], decrease the number of nodules [MD=−0.37, 95%CI (−0.73, −0.01), P=0.05], alleviate clinical symptoms [MD=−4.84, 95%CI (−6.04, −3.64), P<0.001], and improve lung function [forced expiratory volume in one second (FEV1), MD=0.55, 95%CI (0.09, 1.01), P=0.02; FEV1/forced vital capacity, MD=6.12, 95%CI (4.47, 7.78), P<0.001]. However, there was no statistically significant difference in the probability of malignancy between the experimental group and the control group [MD=−0.01, 95%CI (−0.01, 0.00), P=0.09]. Conclusion TCM compound can significantly reduce the diameter of pulmonary nodules, decrease the number of nodules, alleviate clinical symptoms, and improve lung function, but future multicenter, large-sample, high-quality RCTs are still needed to further explore and verify this conclusion.

ObjectiveTo explore the effectiveness of health information dissemination and its influencing factors using the "Shanghai CDC" WeChat public account as a case study, providing references for public health institutions to optimize the use of official new media platforms for effective publicity. MethodsA total of 1 030 headline articles published on the "Shanghai CDC" WeChat public account between 2016 and 2019 were analyzed using content analysis and non-parametric tests to examine the impact of factors such as titles and content categories. ResultsFrom 2016 to 2019, the number of WeChat public account followers increased by 280 000, with the articles accumulating over 8.8 million views. The median (P₂₅, P₇₅) open rate of articles was 5.90% (3.69%, 10.31%), and the median (P₂₅, P₇₅) sharing and forwarding rate was 6.60% (4.25%, 9.17%). Factors such as the use of first- and second-person pronouns, degree adverbs, negative adverbs, explicit viewpoints, and title length all significantly affected the open rate of articles, with OR (95%CI) values of 0.175 (0.041‒0.756), 32.606 (2.350‒452.432), 4.079 (1.093‒15.230), 0.106 (0.028‒0.409), and 1.184 (1.063‒1.319),respectively (all P<0.05). In terms of content, statistical significant differences in dissemination effectiveness were observed across article categories and themes (P<0.05). In terms of article categories, articles related to news hotspots and service information had higher open rates of 9.58% and 14.00%, respectively. These two types of articles also obtained higher sharing and forwarding rates of 7.65% and 9.16%, respectively. In terms of article topics, compared with healthy life and health products, among the top four topics in terms of publication volume, the open rates of articles about infectious diseases and disease-causing biology and immunization programs were higher, accounting for 7.88% and 6.88%, respectively, with no significant difference in sharing and forwarding rates. ConclusionThe "Shanghai CDC" WeChat public account demonstrated good dissemination effectiveness. Enhancing article titles by increasing informational content and degree adverbs (e.g., "highly," "most," and "extremely") and negative adverbs (e.g., "no") can improve dissemination reach. Public health WeChat accounts should incorporate news hotspots or service information in their articles. While maintaining their strengths in disseminating knowledge on infectious diseases and immunization programs, they should also enhance public education in other professional fields within their scope of responsibility to improve the overall dissemination impact of health information.

ObjectiveTo preliminarily explore the active components and target pathways of Angelicae Sinensis Radix-Polygonati Rhizoma （ASR-PR） herb pair in the treatment of simple obesity through network pharmacology and molecular docking， and to verify and investigate its mechanism of action via animal experiments. MethodsThe chemical constituents and targets of ASR and PR were predicted using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）. Targets related to simple obesity were identified by retrieving the GeneCards， Online Mendelian Inheritance in Man （OMIM）， Pharmacogenomics Knowledgebase （PharmGKB）， and DisGeNET databases. The intersection of drug and disease targets was used to construct an active component-target network using Cytoscape software. This network was imported into the STRING database to construct a protein-protein interaction （PPI） network， and topological analysis was conducted to identify core genes. Gene Ontology （GO） analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis and mapping were performed using the DAVID database and the Microbioinformatics platform. AutoDock 1.5.7 software was used to perform molecular docking between the top five active components and core targets. An animal model of simple obesity was established by feeding C57BL/6J mice a high-fat diet. The mice were administered ASR （2.06 g·kg^-1）， PR （2.06 g·kg^-1）， or ASR-PR （4.11 g·kg^-1） for 10 weeks， while the model group received an equal volume of purified water by gavage. After the administration period， the mice were sacrificed to measure body fat weight and serum levels of total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein （HDL）， and low-density lipoprotein （LDL）. Hematoxylin-eosin （HE） staining was used to observe histopathological sections of liver and adipose tissue. Serum levels of leptin， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） were determined by enzyme-linked immunosorbent assay （ELISA）， and the mRNA expression levels of epidermal growth factor receptor （EGFR） and signal transducer and activator of transcription 3 （STAT3） in liver tissue were detected by real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsNetwork pharmacology and molecular docking results indicated that the treatment of simple obesity by ASR-PR may involve the regulation of protein expression of core targets EGFR and STAT3 by its main components MOL009760 （Siberian glycoside A_qt）， MOL003889 （methyl protodioscin_qt）， MOL009766 （resveratrol）， MOL006331 （4′，5-dihydroxyflavone）， and MOL004941 （baicalin）， thereby modulating the PI3K/Akt and JAK/STAT signaling pathways. The animal experiment results showed that compared with the normal group， the model group had significantly increased body weight， body fat weight， and serum levels of TG， TC， TNF-α， IL-6， and leptin （P<0.01）. EGFR mRNA expression was significantly elevated （P<0.05）， while STAT3 mRNA expression was significantly decreased （P<0.01）. Histological analysis revealed disordered hepatic architecture in the model group， with pronounced lipid vacuoles， cytoplasmic loosening， lipid accumulation， and steatosis. Adipocytes in white adipose tissue （WAT） and brown adipose tissue （BAT） of the model group exhibited markedly increased diameters， reduced cell counts per unit area， and irregular morphology. Compared with the model group， the ASR-PR group significantly reduced body weight， body fat weight， serum TC， IL-6， TNF-α， leptin levels， and EGFR mRNA expression （P<0.01）. TG levels were also significantly decreased （P<0.05）， while STAT3 mRNA expression was significantly increased （P<0.01）. Histopathological improvements included reduced size and number of hepatic lipid vacuoles and restoration of liver cell morphology toward that of the normal group. The diameter of adipocytes significantly decreased， and the number of adipocytes per unit area increased. ConclusionASR-PR may regulate the expression of key target proteins such as EGFR and STAT3 via its core active components， modulate the PI3K/Akt and JAK/STAT signaling pathways， repair damaged liver and adipose tissues， and thereby alleviate the progression of obesity in mice.

ObjectiveTo preliminarily explore the active components and target pathways of Angelicae Sinensis Radix-Polygonati Rhizoma （ASR-PR） herb pair in the treatment of simple obesity through network pharmacology and molecular docking， and to verify and investigate its mechanism of action via animal experiments. MethodsThe chemical constituents and targets of ASR and PR were predicted using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）. Targets related to simple obesity were identified by retrieving the GeneCards， Online Mendelian Inheritance in Man （OMIM）， Pharmacogenomics Knowledgebase （PharmGKB）， and DisGeNET databases. The intersection of drug and disease targets was used to construct an active component-target network using Cytoscape software. This network was imported into the STRING database to construct a protein-protein interaction （PPI） network， and topological analysis was conducted to identify core genes. Gene Ontology （GO） analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis and mapping were performed using the DAVID database and the Microbioinformatics platform. AutoDock 1.5.7 software was used to perform molecular docking between the top five active components and core targets. An animal model of simple obesity was established by feeding C57BL/6J mice a high-fat diet. The mice were administered ASR （2.06 g·kg^-1）， PR （2.06 g·kg^-1）， or ASR-PR （4.11 g·kg^-1） for 10 weeks， while the model group received an equal volume of purified water by gavage. After the administration period， the mice were sacrificed to measure body fat weight and serum levels of total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein （HDL）， and low-density lipoprotein （LDL）. Hematoxylin-eosin （HE） staining was used to observe histopathological sections of liver and adipose tissue. Serum levels of leptin， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） were determined by enzyme-linked immunosorbent assay （ELISA）， and the mRNA expression levels of epidermal growth factor receptor （EGFR） and signal transducer and activator of transcription 3 （STAT3） in liver tissue were detected by real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsNetwork pharmacology and molecular docking results indicated that the treatment of simple obesity by ASR-PR may involve the regulation of protein expression of core targets EGFR and STAT3 by its main components MOL009760 （Siberian glycoside A_qt）， MOL003889 （methyl protodioscin_qt）， MOL009766 （resveratrol）， MOL006331 （4′，5-dihydroxyflavone）， and MOL004941 （baicalin）， thereby modulating the PI3K/Akt and JAK/STAT signaling pathways. The animal experiment results showed that compared with the normal group， the model group had significantly increased body weight， body fat weight， and serum levels of TG， TC， TNF-α， IL-6， and leptin （P<0.01）. EGFR mRNA expression was significantly elevated （P<0.05）， while STAT3 mRNA expression was significantly decreased （P<0.01）. Histological analysis revealed disordered hepatic architecture in the model group， with pronounced lipid vacuoles， cytoplasmic loosening， lipid accumulation， and steatosis. Adipocytes in white adipose tissue （WAT） and brown adipose tissue （BAT） of the model group exhibited markedly increased diameters， reduced cell counts per unit area， and irregular morphology. Compared with the model group， the ASR-PR group significantly reduced body weight， body fat weight， serum TC， IL-6， TNF-α， leptin levels， and EGFR mRNA expression （P<0.01）. TG levels were also significantly decreased （P<0.05）， while STAT3 mRNA expression was significantly increased （P<0.01）. Histopathological improvements included reduced size and number of hepatic lipid vacuoles and restoration of liver cell morphology toward that of the normal group. The diameter of adipocytes significantly decreased， and the number of adipocytes per unit area increased. ConclusionASR-PR may regulate the expression of key target proteins such as EGFR and STAT3 via its core active components， modulate the PI3K/Akt and JAK/STAT signaling pathways， repair damaged liver and adipose tissues， and thereby alleviate the progression of obesity in mice.

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.