ObjectiveTo explore the mechanism by which Sini San （SNS） inhibits ferroptosis， alleviates inflammation and myocardial injury， and improves myocardial infarction （MI）. MethodsThe active ingredients of SNS were obtained by searching the Traditional Chinese Medicine System Pharmacology Platform （TCMSP） database， its target sites were predicted using the SwissTargetPrediction Database， and the core components were screened out using the CytoNCA plug-in. The targets of MI and ferroptosis were obtained by using GeneCards， Online Mendelian Inheritance in Man （OMIM） database， DrugBank， Therapeutic Target Database （TTD）， FerrDb database and literature review， respectively. The intersection of these targets of SNS-MI-ferroptosis was plotted as a Venn diagram. The protein-protein interaction （PPI） network was constructed using the STRING database， and the visualization graph was prepared using Cytoscape. The core targets were screened out using the CytoNCA plug-in， and the biological functions were clustered by the MCODE plug-in. Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis were performed using the David database. Molecular docking was performed using AutoDock and visualized with PyMOL2.5.2. The Kunming mice were randomly divided into the control group， the model group， the SNS group， and the trimetazidine （TMZ） group. The mice were subcutaneously injected with isoprenaline （ISO， 5 mg·kg^-1·d^-1） to establish an MI model. The drug was continuously intervened for 7 days. The ST-segment changes were recorded by electrocardiogram （ECG）， and the tissue morphology changes were observed by hematoxylin-eosin （HE） staining. Cardiomyocyte ferroptosis was investigated by transmission electron microscopy. Serum creatine kinase （CK）， creatine kinase isoenzyme （CK-MB）， lactate dehydrogenase （LDH）， reduced glutathione （GSH）， and malondialdehyde （MDA） levels were detected by biochemical assay. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum levels of interleukin （IL）-6 and 4-hydroxynonenal （4-HNE）. Immunohistochemical staining was employed to detect IL-6 and phosphorylated signal transducer and transcription activator 3 （p-STAT3） in cardiac tissues. Western blot was used to detect STAT3 and p-STAT3 in cardiac tissues. Real-time PCR was used to detect the levels of IL-6， IL-18， solute carrier family 7 member 11 （SLC7A11）， arachidonic acid 15-lipoxygenase （ALOX15）， and glutathione peroxidase 4 （GPx4） in cardiac tissues. ResultsA total of 121 active ingredients of SNS were obtained， and 58 potential targets of SNS in the treatment of MI by regulating ferroptosis were screened. The three protein modules with a score5 were mainly related to the inflammatory response. The GO function was mainly related to inflammation， and KEGG enrichment analysis showed that SNS mainly regulated ferroptosis- and inflammation- related signaling pathways. Molecular docking indicated that the core component had a higher binding force to the target site. Animal experiments confirmed that SNS reduced the level of p-STAT3 （P0.01）， down-regulated the expression of ALOX15 mRNA （P0.01）， up-regulated the level of serum GSH， and the expressions of SLC7A11 and GPx4 mRNA， reduced MDA and 4-HNE levels （P0.05， P0.01）. Additionally， SNS improved the mitochondrial injury induced by cardiomyocyte ferroptosis， reduced the area of MI， alleviated inflammation and myocardial injury， lowered the levels of serum CK， CK-MB， LDH， IL-6， and the mRNA expression levels of IL-16 and IL-18 （P0.05）， and improved ST segment elevation. ConclusionSNS can reduce ISO-induced STAT3 phosphorylation levels， inhibit ferroptosis in cardiomyocytes， alleviate inflammation and myocardial injury， thereby improving MI.

ObjectiveTo explore the mechanism by which Sini San （SNS） inhibits ferroptosis， alleviates inflammation and myocardial injury， and improves myocardial infarction （MI）. MethodsThe active ingredients of SNS were obtained by searching the Traditional Chinese Medicine System Pharmacology Platform （TCMSP） database， its target sites were predicted using the SwissTargetPrediction Database， and the core components were screened out using the CytoNCA plug-in. The targets of MI and ferroptosis were obtained by using GeneCards， Online Mendelian Inheritance in Man （OMIM） database， DrugBank， Therapeutic Target Database （TTD）， FerrDb database and literature review， respectively. The intersection of these targets of SNS-MI-ferroptosis was plotted as a Venn diagram. The protein-protein interaction （PPI） network was constructed using the STRING database， and the visualization graph was prepared using Cytoscape. The core targets were screened out using the CytoNCA plug-in， and the biological functions were clustered by the MCODE plug-in. Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis were performed using the David database. Molecular docking was performed using AutoDock and visualized with PyMOL2.5.2. The Kunming mice were randomly divided into the control group， the model group， the SNS group， and the trimetazidine （TMZ） group. The mice were subcutaneously injected with isoprenaline （ISO， 5 mg·kg^-1·d^-1） to establish an MI model. The drug was continuously intervened for 7 days. The ST-segment changes were recorded by electrocardiogram （ECG）， and the tissue morphology changes were observed by hematoxylin-eosin （HE） staining. Cardiomyocyte ferroptosis was investigated by transmission electron microscopy. Serum creatine kinase （CK）， creatine kinase isoenzyme （CK-MB）， lactate dehydrogenase （LDH）， reduced glutathione （GSH）， and malondialdehyde （MDA） levels were detected by biochemical assay. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum levels of interleukin （IL）-6 and 4-hydroxynonenal （4-HNE）. Immunohistochemical staining was employed to detect IL-6 and phosphorylated signal transducer and transcription activator 3 （p-STAT3） in cardiac tissues. Western blot was used to detect STAT3 and p-STAT3 in cardiac tissues. Real-time PCR was used to detect the levels of IL-6， IL-18， solute carrier family 7 member 11 （SLC7A11）， arachidonic acid 15-lipoxygenase （ALOX15）， and glutathione peroxidase 4 （GPx4） in cardiac tissues. ResultsA total of 121 active ingredients of SNS were obtained， and 58 potential targets of SNS in the treatment of MI by regulating ferroptosis were screened. The three protein modules with a score5 were mainly related to the inflammatory response. The GO function was mainly related to inflammation， and KEGG enrichment analysis showed that SNS mainly regulated ferroptosis- and inflammation- related signaling pathways. Molecular docking indicated that the core component had a higher binding force to the target site. Animal experiments confirmed that SNS reduced the level of p-STAT3 （P0.01）， down-regulated the expression of ALOX15 mRNA （P0.01）， up-regulated the level of serum GSH， and the expressions of SLC7A11 and GPx4 mRNA， reduced MDA and 4-HNE levels （P0.05， P0.01）. Additionally， SNS improved the mitochondrial injury induced by cardiomyocyte ferroptosis， reduced the area of MI， alleviated inflammation and myocardial injury， lowered the levels of serum CK， CK-MB， LDH， IL-6， and the mRNA expression levels of IL-16 and IL-18 （P0.05）， and improved ST segment elevation. ConclusionSNS can reduce ISO-induced STAT3 phosphorylation levels， inhibit ferroptosis in cardiomyocytes， alleviate inflammation and myocardial injury， thereby improving MI.

Objective To evaluate the predictive value of different machine learning models constructed in a multicenter environment for potential organ donors and verify their clinical application feasibility. Methods The study included 2 000 inpatients admitted to five domestic tertiary hospitals from January 2020 to December 2023, who met the criteria for potential organ donation assessment. They were randomly divided into a training set and an internal validation set (7∶3). Another 300 similar patients admitted to the First Affiliated Hospital of Harbin Medical University from January 2024 to April 2025 were included as an external validation set. The area under the curve (AUC), sensitivity, specificity, accuracy and F1-score of three models were compared, and the consistency of the potential organ donor determination process was tested. Multivariate logistic regression analysis was used to identify predictive factors of potential organ donors. Decision curve analysis (DCA) was employed to verify the resource efficiency of each model, and the threshold interval and intervention balance point were assessed. Results Apart from age, there were no significant differences in other basic characteristics among the centers (all P>0.05). The consistency of the potential organ donor determination process among researchers in each center was good [all 95% confidence interval (CI) lower limits >0]. In the internal validation set, the XGBoost model had the best predictive performance (AUC=0.92, 95% CI 0.89-0.94) and the best calibration (P=0.441, Brier score 0.099). In the external validation set, the XGBoost model also had the best predictive performance (AUC=0.91, 95% CI 0.88-0.94), outperforming logistic regression and random forest models. Multivariate logistic regression showed that mechanical ventilation had the greatest impact (odds ratio=2.06, 95% CI 1.54-2.76, P<0.001). DCA indicated that the XGBoost model had the highest net benefit in the threshold interval of 0.2-0.6. The “treat all” strategy only had a slight advantage at extremely low thresholds. The recommended threshold interval, which balances intervention costs and clinical benefits, considers ≥50% positive predictive value (PPV) and ≤50 referrals per 100 high-risk patients. Conclusions The XGBoost model established in a multicenter environment is accurate and well-calibrated in predicting potential organ donors. Combined with DCA, it may effectively guide the timing of clinical interventions and resource allocation, providing new ideas for the assessment and management of organ donation after brain death.

OBJECTIVE To investigate the application status of prescription pre-review systems in healthcare institutions of Yunnan province， evaluate their system functions and management capabilities， and provide a practical basis for promoting rational drug use. METHODS A questionnaire survey was conducted among public healthcare institutions at or above the secondary level in Yunnan province to investigate the deployment status of the systems. A capability maturity assessment framework was constructed， encompassing 6 dimensions and 39 indicators， including real-time prescription review， prescription correlation review， rule setting， evidence-based information support， prescription authority management， and system operation management. This framework was then used to evaluate the institutions that had implemented the pre-review systems. RESULTS A total of 100 valid questionnaires were collected， with 37 institutions having adopted prescription pre-review systems， mainly tertiary hospitals. The system predominantly adopted a modular architecture and was embedded into the hospital information system through application programming interfaces and middleware， providing certain capabilities for real-time prescription risk identification. Evaluation results indicated that basic functions such as reviewing indications， contraindications， and drug compatibility performed well， while deficiencies remained in functions related to parenteral nutrition prescription， review of drug dosage for specific diseases， individual patient characteristic recognition， and rule setting. Moreover， the construction of review centers and establishment of management systems were also not well-developed. CONCLUSIONS The overall application rate of prescription pre-review systems in Yunnan province remains low. System functions and management mechanisms require further improvement. It is recommended to enhance information infrastructure in lower-level institutions and explore regionally unified review models to promote standardized and intelligent development of prescription review practices.

ObjectiveIn order to provide a reference for the optimization of preparation process of stir-fried Glycyrrhizae Radix et Rhizoma（sf-GRR）， the quality changes during the processing was studied. MethodsGlycyrrhizae Radix et Rhizoma was processed by stir-frying for 17 min， and samples were collected every 1 min during the processing. The appearance color of the samples was determined by visual analysis technology， the moisture and extract of the process samples were detected by the drying method and the hot extraction method of alcohol-soluble extract in the general rules of the 2020 edition of Chinese Pharmacopoeia（part Ⅳ）， and the contents of liquiritin apioside， liquiritin， isoliquiritin apioside， isoliquiritin， licoricesaponin G₂ and glycyrrhizic acid in the process samples were determined by high performance liquid chromatography（HPLC）. Then principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and Spearman correlation analysis were used for clustering， discrimination and correlation analysis of the appearance color， moisture， extract and the contents of six internal components. Based on artificial neural network and random forest algorithm， the prediction model of processing degree of sf-GRR was established. On this basis， based on the five principles of quality marker（Q-Maker）， explore the monitoring Q-Maker of sf-GRR. ResultsThe color of Glycyrrhizae Radix et Rhizoma deepened after stir-frying， and the appearance color of the sample changed from light yellow to dark yellow during processing. During the stir-frying process， the moisture content showed a decreasing trend with the extension of processing time， while the extract content showed an increasing trend with the extension of processing time. After stir-frying， the contents of liquiritin apioside， liquiritin and licoricesaponin G₂ showed an overall decreasing trend， while the contents of isoliquiritin apioside and isoliquiritin increased， and the content of glycyrrhizic acid increased slightly. The correlation analysis showed that moisture was positively correlated with brightness（L^*） and red/green value（a^*）， and negatively correlated with yellow/blue value（b^*） and total color difference（E^*ab）. Isoliquiritin apioside and isoliquiritin had negative correlation with L^* and a^*， and positive correlation with b^* and E^*ab. The processing process of sf-GRR could be divided into two stages of the early stage（0-14 min） and the late stage（15-17 min）， and could be divided into three stages of the early stage（0-6 min）， the middle stage（7-14 min） and the late stage（15-17 min） by combining the moisture， extract， the contents of 6 components and color values. Based on artificial neural network analysis and random forest algorithm， isoliquiritin apioside， isoliquiritin， liquiritin and glycyrrhizic acid were selected as monitoring markers for sf-GRR. ConclusionBased on the analysis of the exterior-interior indicators of process samples of sf-GRR， this paper ultimately identifies four processing monitoring markers， which can provide a basis for optimizing the processing technology of sf-GRR.

Depression is a common psychiatric disorder characterized by persistent low mood or mental disorders. Current treatments primarily focus on regulating neurotransmitter levels， but their effectiveness is limited. The mechanisms underlying its onset are complex， and there is no unified consensus. Abnormal signaling pathway transmission plays a crucial role in the development of depression， involving multiple pathways， including Toll-like receptor 4/nucleotide-binding oligomerization domain-like receptor protein 3 （TLR4/NLRP3）， nuclear factor-κB （NF-κB）， Janus kinase/signal transducer and activator of transcription （JAK/STAT）， mitogen-activated protein kinase/extracellular signal-regulated kinase （MAPK/ERK）， brain-derived neurotrophic factor/tyrosine kinase receptor B （BDNF/TrkB）， cyclic AMP/protein kinase A/cAMP response element-binding protein （cAMP/PKA/CREB）， and others. Traditional Chinese medicine（TCM） is based on a holistic approach and the principle of treatment based on the differentiation of syndromes， regulating the balance of multiple systems and organ functions from a macroscopic perspective. This approach has shown unique advantages in the treatment of depression. TCM attributes the onset of depression to dysfunction of the organ systems， involving liver Qi stagnation， heart spirit deficiency， kidney essence depletion， and spleen dysfunction. TCM compound treatments focus on soothing the liver， strengthening the spleen， calming the heart， and replenishing essence， with formulas such as Xiaoyaosan， Zishui Qinggan Yin， and Chahu Jia Guizhi Longgu Muli Tang. The active components of Chinese herbs mainly aim to tonify and regulate Qi， such as salidroside， ginsenoside Rb₁， astragaloside， and muscone. External TCM treatments， primarily acupuncture， aim to open the orifices and invigorate the spirit. Acupoints such as Baihui， Shenting， and Yintang are commonly used. Additionally， massage and moxibustion therapy can intervene in depression by regulating signaling pathways. This article reviews the core role of signaling pathways in the development of depression and the mechanism of TCM regulation of signaling pathways to intervene in depression， aiming to discover new therapeutic approaches that can improve the symptoms of depressed patients.

ObjectiveTo investigate the expression level of HBV cccDNA in patients in the convalescence stage of hepatitis B virus-related acute-on-chronic liver failure （HBV-ACLF） and its correlation with HBV markers and liver histopathological changes. MethodsA total of 30 patients in the convalescence stage of HBV-ACL who were hospitalized in The Ninth Hospital of Nanchang from January 2015 to October 2023 were enrolled as liver failure group， and 9 patients with chronic hepatitis B （CHB）， matched for sex and age， were enrolled as control group. The content of HBV cccDNA in liver tissue was measured， and its correlation with clinical data and laboratory markers was analyzed. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and a one-way analysis of variance or the Kruskal-Wallis H test was used for comparison between multiple groups； the Fisher’s exact test was used for comparison of categorical data between groups. A Spearman correlation analysis was performed. ResultsThe liver failure group had a significantly lower content of HBV cccDNA in liver tissue than the control group （-0.92±0.70 log₁₀ copies/cell vs -0.13±0.91 log₁₀ copies/cell， t=2.761， P=0.009）. In the liver failure group， there was no significant difference in the content of HBV cccDNA in liver tissue between the HBeAg-positive patients and the HBeAg-negative patients （P>0.05）； there was no significant difference in the content of HBV cccDNA in liver tissue between the patients with different grades （G0-G2， G3， and G4） of liver inflammatory activity （P>0.05）； there was no significant difference in the content of HBV cccDNA in liver tissue between the patients with different stages （S0-S2， S3， and S4） of liver fibrosis （P>0.05）； there was no significant difference in the content of HBV cccDNA in liver tissue between the patients with negative HBV DNA and those with positive HBV DNA （P>0.05）. For the liver failure group， the content of HBV cccDNA in liver tissue was positively correlated with the content of HBV DNA in liver tissue （r=0.426， P=0.043） and was not significantly correlated with the content of HBV DNA in serum （P>0.05）. ConclusionThere is a significant reduction in the content of HBV cccDNA in liver tissue in the convalescence stage of HBV-ACLF. HBV cccDNA exists continuously and stably in liver tissue and can better reflect the persistent infection and replication of HBV than HBV DNA in serum and liver tissue.

Objective To analyze the disease burden of chronic kidney diseases (CKD) attributed to high body mass index (BMI) in China from 1992 to 2021 and predict the disease burden for the next decade, and to provide evidence for the prevention and treatment of CKD. Methods Using the Global Burden of Disease (GBD) database and the Joinpoint model, the average annual percentage rate change (AAPC) of the mortality rate and disability-adjusted life year (DALY) rate was calculated to describe and analyze the CKD disease burden attributed to high BMI in China from 1992 to 2021. The ARIMA model was employed to predict and analyze the change trend of the CKD disease burden. Results From 1992 to 2021, the mortality rate and DALY rate attributed to high BMI-induced chronic kidney disease showed an upward trend. Compared to 1992, the attributed number of deaths increased by 324.38%, and DALYs increased by 268.56%; the mortality rate increased by 64.00%, and the DALY rate grew by 51.62%. From 1992 to 2021, the mortality rate and DALY rate for males were lower than those for females, but the growth rate for males exceeded that of females. From 1992 to 2021, the mortality rate and DALY rate of chronic kidney disease attributed to high BMI in China increased with age. The average annual change rate of chronic kidney disease attributed to high BMI in China from 1992 to 2021 (mortality rate: 1.40 per 100,000 (95% CI: 1.04–1.76), DALY rate: 1.43 per 100 000 (95% CI: 1.17–1.70)) was higher than thHuaiyin Normal University, Huai'anher social demographic index (SDI) regions. The ARIMA model predicted that the age-standardized mortality rate increased from 2.91 per 100 000 in 2022 to 3.05 per 100 000 in 2026, and the age-standardized DALY rate increased from 69.65 per 100 000 in 2022 to 73.58 per 100 000 in 2026. Conclusion Chronic kidney disease attributed to high BMI in China is on the rise, and it will continue to grow in the future. The focus of CKD prevention and control should be on males and the elderly, while active measures should be taken to reduce the occurrence and progression of chronic kidney disease.

ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

OBJECTIVE To improve the efficiency and quality of dispensed oral drug management in the inpatient pharmacy， and ensure the safety of drug use in patients. METHODS SWOT （strength， weakness， opportunity， threat） analysis method was used to analyze the internal strengths and weaknesses， as well as the external opportunities and threats in the construction of a closed-loop management system for dispensed oral drugs in the inpatient pharmacy of our hospital， and propose improvement strategies. RESULTS & CONCLUSIONS A refined， full-process， closed-loop traceability management system for dispensed oral drugs in the inpatient pharmacies was successfully established， which is traceable in origin， trackable in destination， and accountable in responsibility. After the application of this system， the registration rate of dispensed drug information and the correctness rate of registration content both reached 100%. The proportion of overdue drug varieties in the same period of 2024 decreased by 77.78% compared to March 2020， the inventory volume decreased by 29.50% compared to the first quarter of 2020， the per-bed medication volume decreased by 32.14% compared to the first quarter of 2020； the average workload per post in the same period of 2023 increased by 49.09% compared to 2019， the dispensing accuracy rate reached 100%， and the improvement rate of quality control problem increased by 25.25% compared to 2021. This system effectively improves the safety and accuracy of dispensed oral drug management in the inpatient pharmacy.