ObjectiveTo investigate the efficacy and safety of Babaodan Capsule （BBD） in the treatment of patients with chronic hepatitis B virus （HBV） infection with damp-heat in the liver and gallbladder comorbid with gallbladder polyps. MethodsA randomized， double-blinded， placebo-controlled single-center trial was conducted among 120 patients with chronic HBV infection who were admitted to Beijing YouAn Hospital， Capital Medical University， from August 2020 to April 2023， and they were divided into treatment group （BBD） and control group （placebo）， with 60 patients in each group. The course of treatment was 24 weeks， and follow-up assessments were conducted every 4 weeks. The primary outcome measures were the number and maximum diameter of gallbladder polyps （assessed by ultrasound）， and the secondary outcome measures included traditional Chinese medicine （TCM） syndrome score， blood lipid levels， and liver function parameters. The independent-samples t test or the Wilcoxon rank-sum test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups； the Wilcoxon rank-sum test was used for comparison of ranked data between two groups； the generalized estimating equation was used to analyze repeated measures data. ResultsAfter 8 weeks of treatment， the treatment group had a significantly smaller diameter of polyps and a significantly lower number of polyps than the control group （Z=-1.76 and -1.80， both P<0.05）， and after 24 weeks of treatment， the treatment group had a significantly higher polyp reduction rate than the control group （30.51% vs 10.91%， P<0.05）. The subgroup analysis showed that patients receiving combined antiviral therapy， male patients， patients with a diameter of polyps of <5 mm， and patients with multiple polyps tended to achieve significantly greater benefits. At week 8 of treatment， the treatment group had a significantly better TCM syndrome score than the control group （Z=-2.35， P<0.05）； after treatment， compared with the control group， the treatment group had a significantly greater increase in high-density lipoprotein （Z=-1.85， P<0.05） and significantly lower levels of alanine aminotransferase （Z=-2.06， P <0.05）， aspartate aminotransferase （Z=-2.13， P<0.05）， total bilirubin （Z=-2.12， P<0.05）， and direct bilirubin （Z=-3.09， P<0.05）. No serious adverse events were reported in either group. ConclusionBBD can effectively reduce the size of gallbladder polyps， improve TCM syndrome score， and reduce the level of bilirubin in patients with chronic HBV infection with damp-heat in the liver and gallbladder， with a favorable safety profile， and it may be more suitable for patients receiving combined antiviral therapy and specific subgroups （male patients， patients with a diameter of polyps of <5 mm， and patients with multiple polyps.

OBJECTIVE To explore an intelligent shelf management scheme aimed at enhancing the effective utilization rate of shelves and reducing the risk of dispensing errors for easily confused medicine， thereby facilitating the upgrade of intelligent shelf management in inpatient pharmacies. METHODS An intelligent positioning software based on the “five-level positioning” concept was designed using informational technology. Human-machine collaboration mode was adopted to optimize the shelf management process by integrating priority information， including pharmacological action， drug dosage， packaging color， injection drug type， and label style. Then， the effectiveness of the intelligent positioning software was evaluated comprehensively from multiple aspects such as shelf location arrangement effect， internal dispensing error rate and work experience. RESULTS Compared with the application of intelligent shelf management scheme （April-May， 2025）， the proportion of injectable drugs on the middle layer increased from 59.9% to 78.2% after the application of scheme （June-July， 2025）； the average internal dispensing error rate dropped from 0.098% to 0.049%. Intelligent positioning software ensured precise warehousing positioning， simplified management， reduced dispensing errors and achieved a good experience for pharmacists. In addition， the “intelligent positioning software for pharmaceutical shelf management”， developed based on the “five-level positioning” concept， had been granted one national computer software copyright. CONCLUSIONS In summary， the intelligent positioning software fully considers the actual work needs such as shelf capacity， drug dosage and distance between similar drugs. It can provide accurate prediction of pharmaceutical shelf and optimization scheme， basically achieving dual optimization of low error rate and high dispensing efficiency.

The brain-gut interaction theory is a multidimensional integrative concept based on the brain-gut axis， involving neural， endocrine， and immune regulatory networks as well as the gut microbiota. Zang-fu organs （脏腑） theory in traditional Chinese medicine （TCM） shows a high degree of consistency with the brain-gut interaction theory， and the core functions such as the spleen and stomach governing the ascending of the clear and descending of the turbid， the liver governing the free flow of qi， and the heart governing mental and emotional activities are closely associated with the multi-level regulatory mechanisms of the brain-gut axis. TCM therapy can modulate brain-gut interactions through multiple pathways in the treatment of spleen and stomach diseases， including the regulation of gastrointestinal hormone secretion， neurotransmitter levels， the hypothalamic-pituitary-adrenal （HPA） axis， immune homeostasis and inflammatory responses， as well as the gut microecology. However， current basic research on the brain-gut interaction theory in TCM for spleen and stomach diseases still faces several challenges， such as difficulties in integrating TCM spleen-stomach theory with modern pathophysiology， lack of innovation in research concepts， and limitations in research methodologies. It is therefore proposed that multidisciplinary collaboration， multi-omics technologies， and targeted research approaches should be adopted to provide more comprehensive methods for basic research on TCM spleen and stomach diseases， thereby promoting the in-depth development of brain-gut interaction theory.

ObjectiveTo construct and evaluate various machine learning models for predicting the risk of chronic obstructive pulmonary disease （COPD） in individuals， thereby providing data support for early screening and intervention. MethodsA total of 823 subjects were selected for this study， comprising 142 individuals in the high-risk group for COPD and 681 individuals in the low-risk group. Data collected included demographic characteristics， smoking history， symptoms （such as cough and shortness of breath）， and scores from the Chronic obstructive pulmonary disease screening questionnaire. Four machine learning algorithms—Logistic regression， random forest， support vector machine， and XGBoost—were utilized to construct risk prediction models. The performance of these models was assessed using 5-fold cross-validation， with evaluation metrics including accuracy， precision， recall， F1-score， area under the receiver operating characteristic curve （AUC）， and average precision （AP）. Furthermore， a feature importance analysis was performed. ResultsThe Logistic Regression model exhibited superior performance， achieving an AUC of 0.982 and an AP of 0.939. This was closely followed by the Random Forest model， which recorded an AUC of 0.975 and an AP of 0.890. Feature importance analysis revealed that smoking history， symptoms of shortness of breath， and body weight were significant predictors. All models demonstrated robust performance in identifying low-risk populations； however， variations were observed in their efficacy in identifying high-risk populations. ConclusionMachine learning models have proven effective in identifying individuals at high risk for COPD. Among these， the Logistic regression model exhibits the best overall performance， efficiently identifying high-risk populations and serving as a valuable clinical auxiliary screening tool. Various models， each with distinct performance characteristics， are suited to different clinical screening scenarios， thereby offering targeted decision-making support for the establishment of a hierarchical and intelligent COPD screening pathway.

Aromatic inhalation therapy is a key traditional Chinese medicine （TCM） approach for preventing respiratory infectious diseases. Its foundational theory， "aromatics acting on the spleen"， is deeply rooted in TCM principles and supported by modern medical research. The theory posits that the aromatic properties of medicinals primarily act on the spleen， and the aromatic inhalation therapy achieved its protective effects by modulation of the spleen and spleen channel to enhance the regulation of wei qi， striae and interstices. In TCM， the spleen is considered the mother of the lungs， with the function of nurturing lung； it is also seen as the source of wei qi， responsible for external defense； and the root of healthy qi， forming the foundation of acquired （postnatal） constitution. Thus， preventive strategies for respiratory infectious diseases focus on strengthening the spleen. From a modern medical perspective， the spleen's role in regulating lung immune responses， the shared immune functions of the respiratory and gastrointestinal mucosa， and the spleen's overall immune modulation provide scientific evidence for using aromatic inhalation therapy to prevent respiratory infections. Additionally， aromatic inhalation therapy offers several advantages， including direct action， rapid onset， minimal side effects， controllable risks， convenience， and ease of dissemination， making it a practical and effective preventive measure for respiratory infectious diseases.

ObjectiveTo investigate the mechanism of action of Kaixinsan in the treatment of Alzheimer's disease （AD） based on network pharmacology， molecular docking， and animal experimental validation. MethodsThe Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform（TCMSP） and the Encyclopedia of Traditional Chinese Medicine（ETCM） databases were used to obtain the active ingredients and targets of Kaixinsan. GeneCards， Online Mendelian Inheritance in Man（OMIM）， TTD， PharmGKB， and DrugBank databases were used to obtain the relevant targets of AD. The intersection （common targets） of the active ingredient targets of Kaixinsan and the relevant targets of AD was taken， and the network interaction analysis of the common targets was carried out in the STRING database to construct a protein-protein interaction（PPI） network. The CytoNCA plugin within Cytoscape was used to screen out the core targets， and the Metascape platform was used to perform gene ontology（GO） functional enrichment analysis and Kyoto encyclopedia of genes and genomes（KEGG） pathway enrichment analysis. The “drug-active ingredient-target” interaction network was constructed with the help of Cytoscape 3.8.2， and AutoDock Vina was used for molecular docking. Scopolamine （SCOP） was utilized for modeling and injected intraperitoneally once daily. Thirty-two male C57/BL6 mice were randomly divided into blank control （CON） group （0.9% NaCl， n=8）， model （SCOP） group （3 mg·kg^-1·d^-1， n=8）， positive control group （3 mg·kg^-1·d^-1 of SCOP+3 mg·kg^-1·d^-1 of Donepezil， n=8）， and Kaixinsan group （3 mg·kg^-1·d^-1 of SCOP+6.5 g·kg^-1·d^-1 of Kaixinsan， n=8）. Mice in each group were administered with 0.9% NaCl， Kaixinsan， or Donepezil by gavage twice a day for 14 days. Morris water maze experiment was used to observe the learning memory ability of mice. Hematoxylin-eosin （HE） staining method was used to observe the pathological changes in the CA1 area of the mouse hippocampus. Enzyme linked immunosorbent assay（ELISA） was used to determine the serum acetylcholine （ACh） and acetylcholinesterase （AChE） contents of mice. Western blot method was used to detect the protein expression levels of signal transducer and activator of transcription 3（STAT3） and nuclear transcription factor（NF）-κB p65 in the hippocampus of mice. ResultsA total of 73 active ingredients of Kaixinsan were obtained， and 578 potential targets （common targets） of Kaixinsan for the treatment of AD were screened out. Key active ingredients included kaempferol， gijugliflozin， etc.. Potential core targets were STAT3， NF-κB p65， et al. GO functional enrichment analysis obtained 3 124 biological functions， 254 cellular building blocks， and 461 molecular functions. KEGG pathway enrichment obtained 248 pathways， mainly involving cancer-related pathways， TRP pathway， cyclic adenosine monophosphate（cAMP） pathway， and NF-κB pathway. Molecular docking showed that the binding of the key active ingredients to the target targets was more stable. Morris water maze experiment indicated that Kaixinsan could improve the learning memory ability of SCOP-induced mice. HE staining and ELISA results showed that Kaixinsan had an ameliorating effect on central nerve injury in mice. Western blot test indicated that Kaixinsan had a down-regulating effect on the levels of NF-κB p65 phosphorylation and STAT3 phosphorylation in the hippocampal tissue of mice in the SCOP model. ConclusionKaixinsan can improve the cognitive impairment function in SCOP model mice and may reduce hippocampal neuronal damage and thus play a therapeutic role in the treatment of AD by regulating NF-κB p65， STAT3， and other targets involved in the NF-κB signaling pathway.

Polycystic ovary syndrome （PCOS） is a common gynecological endocrine and reproductive disorder，with the main clinical manifestations including ovulation failure，insulin resistance，hyperandrogenism，and obesity. Its occurrence and development are closely related to cellular regulatory mechanisms such as apoptosis，autophagy，oxidative stress，and inflammatory response. Autophagy，as a clearance mechanism that maintains cellular homeostasis，plays a crucial role in maintaining the growth，development，and maturation of oocytes. Exploring the mechanism of autophagy during the occurrence and development of diseases can help develop treatment methods for PCOS by regulating autophagy. Studies have shown that autophagy plays an important role in the pathogenesis of PCOS，and it can affect the occurrence and development of PCOS through multiple pathways，levels，and targets. Traditional Chinese medicine （TCM） regulates autophagy in ovarian granulosa cells or endometrium of patients with PCOS by targeting the expression of autophagy signaling pathways，regulatory factors，and non-coding single-stranded RNA molecules，thereby alleviating inflammation，regulating metabolism disorders，and balancing hormone levels in PCOS. Accordingly，TCM can ameliorate pathological conditions such as insulin resistance，hyperandrogenism，and ovulation failure in PCOS. This article summarizes the TCM formulas and extracts for the treatment of PCOS，as well as the main autophagy pathways and regulatory factors involved，aiming to provide reference and suggestions for the future treatment of PCOS with TCM by regulating autophagy.

Objective: To review the current development of artificial intelligence (AI) technology in the field of transfusion medicine. Methods: A systematic search was conducted in the Clarivate Web of Science Database from inception to December 2024 for literature related to AI and transfusion. A total of 4 775 publications were identified. Based on inclusion and exclusion criteria, 133 original studies were ultimately included and analyzed using a narrative synthesis approach. Results: Research on AI in transfusion has surged since 2020 (accounting for 77% of all publications), with China ranking second globally in publication volume. Among the included studies, 69.2% focused on predicting individual transfusion needs, followed by inventory management (8.3%), diagnosis and prediction of adverse transfusion reactions (6.0%), factors influencing transfusion outcomes (5.3%), blood group identification (5.3%), blood quality testing (4.5%), and precise blood volume measurement (1.5%). Additionally, 4.5% of the studies were published in journals with an impact factor greater than 10; 19.5% developed software or applications; 31.5% were multi-center studies; 48.1% utilized decision tree methods, while 31.5% employed neural network approaches; and 14.2% conducted external validation of the algorithms. Conclusion: AI demonstrates significant potential in transfusion risk prediction, decision support, and blood management. However, challenges remain, including limited model generalizability, insufficient algorithm interpretability, and barriers to clinical translation. The deep integration of AI with transfusion medicine will accelerate the advent of precision transfusion era, maximizing blood resource utilization, reducing waste, and ensuring transfusion safety.

Diabetic nephropathy(DN)is a significant causative factor of end-stage renal disease globally,and its pathogenesis involves dysregulation of multiple cellular and hormonal pathways.Podocytes play crucial roles in the process of DN,with the extent of podocyte injury closely associated with key pathological manifestations of renal damage,such as proteinuria,glomerular filtration rate,and glomerulosclerosis.However,due to the complexity and interplay of mechanisms contributing to podocyte injury,such as oxidative stress,abnormal lipid metabolism,and mitochondrial damage,the precise mechanisms underlying podocyte injury remain incompletely understood.This review integrated the latest research findings from both domestic and international studies on the core mechanisms of podocyte injury in DN.Furthermore,this article summarized the implications of these mechanisms for DN treatment,particularly focusing on potential therapeutic targets and the development of related pharmacological interventions derived from targeting podocyte injury pathways,so as to provide a theoretical foundation for the development of clinical therapeutic strategies for DN.

Objective:To investigate the value of MRI combined with serum long non-coding RNA (lncRNA) KCNQ1OT1 and microRNA-204-5p (miR-204-5p) in predicting axillary lymph node metastasis in breast cancer patients.Methods:A total of 70 patients with breast cancer who were surgically diagnosed in the No.2 Hospital of Baoding, Hebei Province from January 2020 to December 2022 were selected as the study objects. Patients were divided into metastatic group ( n=31) and non-metastatic group ( n=39) according to the status of lymph node metastasis. The MRI features and the levels of serum lncRNA KCNQ1OT1 and miR-204-5p were compared between the two groups. Receiver operator characteristic (ROC) curve was used to evaluate the predictive efficacy of the three detections alone and in combination for axillary lymph node metastasis in breast cancer. Results:There were statistically significant differences in tumor maximum diameter ( χ2=4.28, P=0.039) and Ki-67 expression ( χ2=10.88, P=0.001) between the metastatic and non-metastatic groups. There were statistically significant differences between the breast cancer axillary lymph node metastatic group and the non-metastatic group in the mode of internal reinforcement type ( χ2=6.60, P=0.037), peripheral vessel diameter ( t=4.33, P<0.001), number of peripheral vessel roots ( t=4.38, P<0.001), apparent diffusion coefficient ( t=3.59, P=0.001), and MRI lymph node status ( χ2=29.70, P<0.001). The level of serum lncRNA KCNQ1OT1 in metastatic group was higher than that in non-metastatic group (1.41±0.32 vs. 0.99±0.18, t=6.94, P<0.001), and the level of miR-204-5p was lower than that in non-metastatic group (0.72±0.17 vs. 1.03±0.21, t=6.66, P<0.001). Bioinformatics analysis showed that miR-204-5p may have a targeting relationship with lncRNA KCNQ1OT1. ROC curve analysis showed the area under the curve of MRI features, serum levels of lncRNA KCNQ1OT1, miR-204-5p and their combined detection to predict lymph node metastasis of breast cancer patients were 0.823, 0.858, 0.843, 0.946, respectively. The predictive efficacy of the combined detection was better than that of MRI features and serum lncRNA KCNQ1OT1 and miR-204-5p levels alone ( Z=3.29, P=0.001; Z=2.07, P=0.038; Z=2.23, P=0.026) . Conclusions:Serum lncRNA KCNQ1OT1 level is up-regulated and the level of miR-204-5p is down-regulated in patients with axillary lymph node metastasis of breast cancer. And the combination of MRI features with serum lncRNA KCNQ1OT1 and miR-204-5p has high predictive efficacy in predicting lymph node metastasis in breast cancer patients.