OBJECTIVE To evaluate the cost-effectiveness of cefiderocol versus best available therapy （BAT） or standard-of- care （SOC） for the treatment of confirmed or suspected carbapenem-resistant Gram-negative bacterial （CRGNB） serious infections from the perspective of the Chinese healthcare system， and to explore its reasonable pricing. METHODS A decision tree model was constructed based on data from two phase Ⅲ clinical trials （CREDIBLE-CR and GAME CHANGER） to simulate the cost- effectiveness of cefiderocol in two scenarios： salvage therapy for confirmed CRGNB infection （scenario 1） and empirical therapy for suspected CRGNB infection （scenario 2）. The primary outcome measure was the incremental cost-effectiveness ratio （ICER）. The willingness-to-pay （WTP） was set at 1 to 3 times China’s per capita GDP in 2024. To verify the robustness of the results， one- way and probabilistic sensitivity analyses were conducted， and based on these， a reasonable price range for cefiderocol in the Chinese market was explored. RESULTS The results for scenario 1 showed that the clinical cure rate in the cefiderocol group was higher than that in the BAT group （47.50% vs. 34.21%）， but its ICER was 415 065.03 yuan per cured case， exceeding three times China’s GDP per capita. Scenario 2 revealed that the ICER for cefiderocol relative to SOC was as high as 1 362 446.16 yuan per cured case， far exceeding the WTP. Sensitivity analysis indicated that the treatment duration and price of cefiderocol were key factors affecting its cost-effectiveness. In the two scenarios described above， the unit price of cefiderocol must fall below 683.47 and 242.00 yuan/g， respectively， to be considered cost-effective. CONCLUSIONS Based on the current market price， cefiderocol lacks sufficient cost-effectiveness for treating confirmed or suspected CRGNB serious infections within China’s healthcare system. To improve its accessibility， price negotiations or a tiered medical insurance payment strategy are required.

The digitization of traditional Chinese medicine (TCM) has generated vast amounts of data. However, these data are characterized by significant heterogeneity and complex semantic structures, posing substantial challenges for systematic integration and intelligent analysis, and limiting its potential for modern clinical and computational research. To address the challenges posed by the high heterogeneity and complex structure in TCM data, we designed and developed the TCM Data Hub platform, which is powered by the YiYuan large language models (LLMs). This platform aims to enhance intelligent data processing capabilities and unlock the potential for clinical application of TCM data through systematic integration and efficient utilization, thereby bridging the gap between traditional knowledge and modern computational research. This study first analyzed the heterogeneity and complexity of TCM information with respect to data types, structures, and semantics. A standardized data framework was constructed to enhance data integration and interoperability. Based on the TCM Intelligent Computing Platform of the China Academy of Chinese Medical Sciences, we trained the YiYuan LLMs to acquire domain-specific semantic understanding of TCM, thereby improving the platform’s comprehension of specialized terminology and knowledge systems. Leveraging the natural language processing capabilities of the LLMs, we developed a human-in-the-loop data processing system to enable efficient extraction, cleansing, and structured organization of TCM data. In addition, utilizing Vue and Java technologies, we developed multiple LLM-powered intelligent agents and systems, including a human-in-the-loop data processing system, as well as automated prescription mining and network pharmacology analysis agents. Task-specific agents tailored to TCM data processing were developed to enhance the model’s effectiveness in clinical knowledge discovery. System functionality and platform infrastructure were implemented using Java and Vue technologies.The TCM Data Hub platform has completed system construction and core functionality implementation. It supported integrated management and efficient access to 8 key types of TCM data: prescriptions, materia medica, ingredients, targets, diseases (Western medicine), diseases (TCM), syndromes, and therapeutic methods. The human-in-the-loop data processing system achieved an accuracy of 95.34% in structuring TCM data and supported annotation for data requiring manual labeling. The intelligent agent-driven big-data analytics module enabled 1-click, end-to-end workflows for TCM prescription mining, herb-syndrome association analysis, network pharmacology, and molecular biology research, completing a full data mining task in approximately 30 minutes. Users can interact with and manipulate data through a visual front-end interface. The system demonstrated stable performance, strong scalability, and a user-friendly experience. Empowered by the YiYuan LLMs, the TCM Data Hub platform significantly improves the accessibility, usability, and intelligence of TCM data. It effectively bridges traditional TCM knowledge with modern intelligent technologies, providing robust data support and intelligent tools for TCM research and clinical applications.

Objective To investigate the preventive and therapeutic effects of ethanol extracts derived from three sources of traditional Chinese medicine: Stellera chamaejasme L., Euphorbia fischeriana Steud. and Euphorbia kansuensis Prokh., on imiquimod （IMQ）-induced psoriasis in mice. Methods Thirty-six male BALB/c mice were randomly divided into the following 6 groups with 6 mice in each group: blank control, model, Stellera chamaejasme, Euphorbia fischeriana, Euphorbia kansuensis, and calcipotriol. Psoriasis area and severity index（PASI） scores were used to record the changes of skin lesions in every group; Hematoxylin-eosin（HE） staining was used to observe the pathological morphology of skin and measure the thickness of the epidermis. Immunohistochemistry was used to detect the expression of nuclear antigen Ki67 in the skin tissues of mice. Results Compared with the model group, the three kinds of ethanol extracts could reduce the PASI score, inhibit epidermal thickening, and decrease expression of Ki67 in the psoriasis mice. Among them, the therapeutic effect of Stellera chamaejasme was the most significant and it was better than the commonly used topical drug calcipotriol. Conclusion The ethanol extract of Stellera chamaejasme had good anti-psoriatic activity, which could inhibit the abnormal proliferation of keratinocytes, reduce the expression of Ki67, and significantly improve psoriasis-like skin lesions.

Objective To analyze the characteristics of TCM symptoms of aging in female insomnia patients;To provide syndrome differentiation evidence for clinical prevention and treatment of female aging.Methods A cross-sectional study method was used to include female insomnia patients who attended outpatient clinics at Dongzhimen Hospital of Beijing University of Chinese Medicine,Beijing Changping District Hospital of Traditional Chinese Medicine,and the Third Affiliated Hospital of Beijing University of Chinese Medicine from August 2021 to July 2024.The patients'clinical information was collected,and frequency analysis,factor analysis,and clustering analysis of the relevant clinical information of the 107 female insomnia patients were conducted,which,together with the experts'opinions,resulted in characteristics of TCM syndrome elements and syndrome distribution of aging in female insomnia patients.Results Totally 20 core items were screened and 7 common factors were obtained from the factor analysis.There were 5 types of syndrome elements of disease location associated with aging symptoms in female patients with insomnia,including heart,liver,spleen,kidney and lung;and there were 7 types of syndrome elements of disease property,including qi deficiency,yin deficiency,qi stagnation,blood deficiency,heat,phlegm,and dampness.There were 4 types of syndromes were obtained from the systematic clustering,including heart-kidney disharmony syndrome,heart-liver stagnation syndrome,spleen deficiency and qi stagnation syndrome,lung-spleen qi deficiency syndrome.Conclusion By analyzing the TCM syndrome characteristics of aging symptoms in female patients with insomnia,four types of syndromes are obtained.The heart-kidney disharmony syndrome is the common syndrome.The internal relationship between insomnia and aging process in female patients with insomnia is revealed from the perspective of pathogenesis,which can provide a research basis for the clinical practice of TCM anti-aging guided by syndrome differentiation and treatment in the future.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To explore the differences in the radiological features,clinical,and laboratory indicators of frequent versus infrequent gout flares in the feet and ankles using dual-energy computed tomography(DECT).Methods A retrospective selection was made on 385 gout patients,who were divided into the frequent flare group(≥2 gout attacks per year,219 cases)and the infre-quent flare group(<2 gout attacks per year,166 cases).Clinical data,laboratory indicators,and DECT imaging findings were col-lected for statistical analysis.Binary logistic regression was used to analyze the independent risk factors for frequent gout flares and receiver operating characteristic(ROC)curve was plotted.Results Statistically significant differences were found between the fre-quent flare group and the infrequent flare group in terms of disease duration,body mass index(BMI),blood pressure,triglyceride(TG),serum uric acid(SUA),monosodium urate(MSU)crystal deposition,total volume of MSU crystals,maximum diameter of individ-ual tophi,number of affected joints,bone erosion,maximum depth of bone erosion,soft tissue swelling,bone proliferation and sclero-sis,and joint space narrowing(P<0.05).SUA levels,MSU crystal deposition,total volume of MSU crystals,and maximum depth of bone erosion were identified as independent risk factors for frequent gout(P<0.05).Both the combination of four factors model and the maximum depth of bone erosion model had better diagnostic efficacy.Conclusion Gout patients with high SUA levels,MSU crystal deposition,larger total volume of MSU crystals,and greater maximum depth of bone erosion are more likely to experience frequent gout attacks.Patients with bone erosion depth>3.200 mm are more likely identified early as having frequent gout.

The exoskeleton robot for lower limb medical rehabilitation in foreign countries and China was introduced in terms of the research status,structure and working principle,and analysis was carried out over its key technologies.It's pointed out the exoskeleton robot for lower limb medical rehabilitation would be enhanced in energy endurance,safety and comfort,individualized and intelligent control,modularity and lightweight design.[Chinese Medical Equipment Journal,2025,46(1):88-100]

Aim To reveal the mechanism of CIP4 homologs protein 1(RICH1)are involved in the regu-lation of myocardial fibrosis.Methods Mouse cardiac fibroblasts(MCFs)cells were treated with transforming growth factor-β(TGF-β1)to induce the formation of a myocardial fibrosis cell model;the level of the target protein was detected by Western blotting;and the RICH1 gene was detected by transfection of the cells with plasmid.The RICH1 gene was overexpressed(RICH 1 OE)using plasmid transfection;the RICH1 gene was silenced using siRNA fragment(siRICH1);and the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3 a1,and Acta2,were de-tected using RT-qPCR.Results RICH1 was signifi-cantly down-regulated in TGF-β1-treated MCFs;the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3a1,and Acta2,were down-regu-lated in the RICH1 OE+TGF-β1 group;and in the siRICH1+TGF-β1 group,myocardial fibrosis marker genes,such as Col1 a1,Col3a1 and Acta2 were up-regulated at the expression level;phosphorylated SMAD2(p-SMAD2)and phosphorylated SMAD3(p-SMAD3)levels were down-regulated in the siRICH1 OE+TGF-β1 group.p-SMAD2 and P-SMAD3 levels were upregulated in the siRICH1+TGF-β1 group.Conclusion RICH1 inhibits TGF-β1-induced myo-cardial fibrosis;RICH1 inhibits TGF-β1-induced myo-cardial fibrosis by negatively regulating the SMAD2/3 signaling pathway.

Objective:To explore the ideological and political education elements and methods in the introduction to nursing course, so as to enhance its ideological educational effectiveness. Methods:In February 2024, based on a "three-stage" teaching model (pre-class, in-class, and post-class), this study reformed the ideological and political education plan for the introduction to nursing course by integrating online and offline case studies and resources, expanding educational materials, and organizing teaching assessments and effectiveness surveys. A semester-long ideological and political education practice was implemented for 237 first-year nursing students from four classes in Medical College of Xinjiang University of Science and Technology. The effectiveness was evaluated by exam scores and a self-designed Introduction to Nursing Teaching Effectiveness Evaluation Scale under the ideological and political education framework. Results:Among the 237 students, there were 107 males and 130 females, aged (18.50 ± 1.12) years old, 63 achieved a passing grade, 149 achieved a good grade, and 18 achieved an excellent grade, with a pass rate of 97.05% (230/237). The scores of the six dimensions of interest stimulation in teaching methods, acceptance of teaching methods, knowledge review and application, knowledge comprehension and retention, self-challenge and improvement, and satisfaction with learning outcomes within 1 week after the end of the course scores were (3.92 ± 1.11), (4.21 ± 0.82), (4.05 ± 0.97), (4.05 ± 0.89), (4.11 ± 0.94), (4.03 ± 0.90) points, which were significantly higher than 1 week before the start of the course (3.43 ± 1.00), (3.54 ± 1.03), (3.48 ± 1.08), (3.47 ± 1.04), (3.52 ± 1.05), (3.47 ± 1.01) points. The differences were statistically significant ( t values were -19.38- -13.22, all P < 0.01). Conclusions:The "three-stage" teaching model in the introduction to nursing course effectively integrates professional education with ideological and political education, improves students′ academic performance, enhances learning effectiveness in nursing practice, and strengthens the overall impact of ideological and political education.

Objective::To analyze fetal renal abnormality genetic features and the prenatal characteristics of the 17q12 microdeletion syndrome.Methods::This prospective cohort study examined prenatal ultrasound findings of renal abnormalities in pregnant women who underwent single nucleotide polymorphism (SNP) array or copy number variation sequencing (CNV-seq) testing on amniotic fluid or fetal tissue at Tianjin Central Obstetrics and Gynecology Hospital between January 2016 and August 2022. The study cohort comprised women with advanced maternal age, fetal ultrasound anomalies, high-risk non-invasive prenatal testing results, or suspected 17q12 microdeletion syndrome. Comprehensive clinical data, including maternal age, detailed ultrasound findings, and pregnancy outcomes, were systematically collected. SNP-array analysis was conducted using an Affymetrix CytoScan 750 K Array Chip to identify CNVs and loss of heterozygosity, while CNV-seq was performed on the Illumina HiSeq 2000 platform. Detected variants were classified according to the American College of Medical Genetics and Genomics guidelines. Statistical analyses were performed using SPSS version 27.0.Results::Abnormal renal development was identified in 141 patients, among whom 26 exhibited hyperechogenic kidneys (HCK). Of these, 12 cases were associated with 17q12 microdeletion syndrome, while the remaining 14 were linked to other chromosomal abnormalities. When excluding patients with HCK, those diagnosed with polycystic kidney disease demonstrated a higher prevalence of chromosomal abnormalities compared to those with multicystic dysplastic kidney and renal dysplasia. Although isolated conditions such as horseshoe kidney, hydronephrosis, ectopic kidney, and unilateral kidney typically presented with normal chromosomal findings, the incidence of chromosomal abnormalities increased when these conditions coexisted with other anomalies. A detailed analysis of the correlation between 17q12 microdeletion syndrome and HCK revealed that 12 out of the 14 patients diagnosed with 17q12 microdeletion syndrome exhibited HCK. Genetic testing confirmed the syndrome in seven patients, with five cases attributed to novel mutations and two cases resulting from inherited mutations.Conclusion::Fetal HCK was closely associated with the 17q12 microdeletion syndrome, and polycystic kidney disease showed a higher rate of chromosomal abnormalities. Chromosome test results were mostly normal in patients with other renal abnormalities, such as kidney dysplasia, horseshoe kidneys, hydronephrosis, kidney deficiency, and ectopic kidneys. Prenatal diagnosis is recommended, especially in cases of non-isolated fetal renal abnormalities. This study provides strong evidence supporting a link between fetal renal abnormalities and genetic syndromes.