ObjectiveTo explore the potential mechanisms of Leigongteng （Tripterygium wilfordii Hook. f.） in treating rheumatoid arthritis （RA） using bioinformatics analysis and experimental validation. MethodsBioinformatics approaches， including the Gene Expression Omnibus （GEO）， the traditional Chinese medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， Gene Ontology （GO） enrichment analysis， Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment， protein-protein interaction （PPI） network analysis， molecular docking， receiver operating characteristic （ROC） analysis， and immune infiltration analysis， were used to predict the key active components of Leigongteng and its target genes for RA treatment. Experimental validation was conducted using human rheumatoid arthritis fibroblast-like synoviocytes （HFLS-RA） in vitro， with methotrexate as the positive control. A scratch assay was performed to assess cell migration after 24 hours of culture. Western blotting was used to detect protein expression levels， qPCR was used to measure target gene mRNA levels， and ELISA was conducted to evaluate inflammatory cytokine levels， including interleukin-1β （IL-1β）， interleukin-6 （IL-6）， interleukin-10 （IL-10）， and tumor necrosis factor-α （TNF-α）. ResultsA total of 117 target genes of Leigongteng were identified and intersected with RA-related genes， yielding 55 key genes. Further screening identified three core genes： PTGS2， CXCR4， and TIMP1. Based on the correspondence between potential drug targets and key components， triptolide and nobiletin were identified as the primary active compounds. Molecular docking results showed that both triptolide and nobiletin had binding energies lower than -5 kcal/mol with their respective target proteins， indicating strong interactions. In vitro experiments demonstrated that， compared with the blank control group， the triptolide， nobiletin， and positive control groups exhibited reduced cell migration rates after 24 hours of culture （P＜0.01）. The expression levels of PTGS2 and CXCR4 （both mRNA and protein） were significantly downregulated， while TIMP1 expression was upregulated. Levels of IL-1β， IL-6， and TNF-α decreased， whereas IL-10 levels increased （P＜0.01）. Compared with the positive control group， the triptolide and nobiletin groups showed increased cell migration rates， upregulated PTGS2 and CXCR4 expression （mRNA and protein）， downregulated TIMP1 expression （mRNA and protein）， increased IL-1β， IL-6， and TNF-α levels， and decreased IL-10 levels （P＜0.05 or P＜0.01）. ConclusionThe key active components of Leigongteng， triptolide and nobiletin， may alleviate RA by inhibiting PTGS2 and CXCR4 while promoting TIMP1 expression， thereby suppressing inflammatory responses.

OBJECTIVE To provide a reference for pharmaceutical care in patients with ulcerative colitis （UC） and ankylosing spondylitis （AS） who developed pustular psoriasis induced by infliximab. METHODS Clinical pharmacists participated in the pharmaceutical care process of a patient with UC and AS who developed pustular psoriasis after using infliximab. The clinical pharmacists determined， using Naranjo’s Scale， that the correlation between the patient’s pustular psoriasis and infliximab was “likely”. Regarding the patient’s development of pustular psoriasis after using infliximab， the clinical pharmacists recommended discontinuing infliximab and switching to Upadacitinib extended-release tablets. For the patient’s skin allergic reaction after using upadacitinib， the clinical pharmacists advised continuing the use of upadacitinib and closely monitoring any potential adverse reactions during the treatment period. RESULTS The clinicians adopted the clinical pharmacists’ recommendation. Following the treatment， the patient’s symptoms were significantly alleviated， and the patient was discharged with medication. The follow-up after discharge showed that the treatment was effective and well-tolerated. CONCLUSIONS The clinical pharmacists analyzed the causal relationship between infliximab and pustular psoriasis. Through pharmaceutical care measures such as dynamic monitoring of skin lesions， evaluation of treatment responses， and optimization of drug regimens， they assisted the physicians in formulating an individualized medication plan， ensuring the safety and efficacy of the patient’s medication use.

Objective:To explore the reasons for delayed medical treatment in patients with polycystic ovary syndrome (PCOS) using the treatment pathway theory as a framework, and to propose corresponding strategies to guide timely medical care for PCOS patients.Methods:Purposeful sampling was used to select 14 PCOS patients who sought treatment at Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School between November 2022 and May 2023. Semi-structured interviews were conducted, and directed content analysis was applied to analyze and extract data.Results:The delay in seeking medical treatment for PCOS patients ranged from five to 60 months. Four main themes and 11 sub-themes were identified as reasons for treatment delays: misconception and delayed recognition of the disease (misunderstanding of symptoms, intermittent symptom presentation) ; delayed seeking of medical help (mismanagement of symptoms, feelings of shame, role conflict, distance and financial constraints, lack of social support) ; delayed diagnosis by healthcare providers (misdiagnosis by healthcare providers, lack of medical resources and services) ; and delayed participation in treatment (lack of health education from medical staff, no immediate fertility needs) .Conclusions:Delays in seeking medical care for PCOS patients are common. Efforts should be made to enhance public education on PCOS for adolescent and reproductive-age women, emphasize the management of the disease in patients without immediate fertility needs, improve primary healthcare institutions' capacity for managing PCOS, and mobilize the social support system to encourage patients to seek medical treatment early, thus reducing the occurrence of delayed medical care.

Objective:To explore the association between child abuse and suicidal ideation in patients with bi-polar disorder.The mediation of self-esteem and depression in this association was also investigated.Methods:A to-tal of 292 patients with bipolar disorder who met the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition(DSM-5)were enrolled.Their child abuse,suicidal ideation,self-esteem,depres-sion,and mania were assessed with the Childhood Trauma Questionnaire(CTQ),Beck Scale for Suicide Ideation-Chinese Version(BSICV),Self-Esteem Scale(SES),17-item Hamilton Depression Rating Scale(HAMD-17)and Young Mania Rating Scale(YMRS).The mediating effects were evaluated using PROCESS for SPSS.Results:The BSICV scores were positively associated with the scores of CTQ(r=0.37,P＜0.01)and HAMD-17(r=0.53,P＜0.01)and negatively associated with SES scores(r=-0.50,P＜0.01)in patients with bipolar disorder.Self-esteem and depression played mediating roles between child abuse and suicidal ideation,respectively(95％CI:0.01-0.09,0.01-0.10).Besides,self-esteem and depression sequentially mediated the relationship between child a-buse and suicidal ideation(95％CI:0.02-0.06).Conclusion:Child abuse,low self-esteem,and depression may be related factors of suicidal ideation in patients with bipolar disorder.

The medical and health field has abundant multimode data and open and diverse medical health scenarios,which is one of the most promising fields for the application of artificial intelligence large models.Based on basic hardware,equipment,and model frameworks,the artificial intelligence model is pre-trained,fine-tuned,evaluated,optimised,and utilized through medical texts,medical images,or medical multimode datasets to complete model construction.The large medical and health model has been successfully applied in the fields of auxiliary diagnosis and treatment,medical imaging research,health management,biomedical research,drug research,medical examination and education,but it also faces challenges such as data security risks,moral and ethical risks,and technical risks.In order to regulate the development of artificial intelligence large model technology,some countries have formulated relevant laws,regulations,and standard guidelines.Opportunities and challenges coexist in the field of medical and health cooperation with artificial intelligence,and artificial intelligence large model technology still needs to be continuously optimised and developed to promote deeper integration with the medical and health field.

Abstract: Objective　To investigate the treatment outcomes of patients with pulmonary tuberculosis (PTB) in Xinjiang Production and Construction Corps and to explore the risk factors affecting these outcomes, so as to provide a scientific basis for the prevention and treatment of pulmonary tuberculosis in the corps region. Methods　TB patients registered in the Corps from 2016 to 2022 were selected, and the basic demographic and clinical data of the research objects were collected by retrospective method. Log-rank test was used for univariate analysis and the Cox multivariate regression model was used to analyze the influencing factors of treatment outcomes of patients with pulmonary tuberculosis. Results　From 2016 to 2022, a total of 8 838 TB patients were registered in the TB Management Information System of Xinjiang Production and Construction Corps, of which 495 cases were untreated, 43 cases had changed diagnoses, 301 cases had no treatment outcomes, 6 cases were diagnosed as extrapulmonary tuberculosis, 11 cases were diagnosed as tracheobronchial tuberculosis, and finally 7 982 TB patients were included in the study. Of the 7 982 patients, 7 578 (94.94%) were treated successfully, while 404 (5.06%) had adverse outcomes (including 32 cases of failure, 13 cases of TB death, 173 cases of non-TB death, 12 cases lost to follow-up, 94 cases of adverse reactions, 10 cases transferred to multi-drug resistance treatment, and 70 other cases). Multivariate Cox regression analysis showed that the >30 to 60-year-old and >60-year-old age groups (OR=1.565, P=0.009; OR=2.960, P<0.001), belonging to ethnic minorities (OR=1.526, P<0.001), being a patients with diabetes mellitus (OR=1.696, P=0.002), current address being in other areas of the province or patients from other provinces (OR=1.419, P=0.004; OR=1.624, P=0.001), receiving retreatment (OR=1.910, P<0.001), and absence of primary care management (OR=1.351, P=0.003) were the risk factors for unsuccessful treatment outcomes in the corps' pulmonary tuberculosis patients. Conclusions　The treatment success rate of pulmonary tuberculosis patients in the Corps region is relatively high, but there is still a need to strengthen the treatment and management of the elderly, ethnic minorities, diabetes patients, non-local floating population, retreatment patients and patients who did not receive primary management.

Purpose/Significance To explore the technical key points and implementation paths of relevant policies,and provide ref-erence for the planning and construction of future smart healthy cities.Method/Process It reviews and analyzes domestic and internation-al policy progress in the field of smart healthy cities,deeply analyzes policy documents,reveals the evolution trajectory,core elements,and driving effects on urban health development.Result/Conclusion Establishing a framework for health informatization,resource net-working,intelligent services,and integrated supervision can effectively address urban health challenges,provide efficient health services,and improve residents'quality of life and hygiene level.Policies such as optimizing the allocation of medical resources,promoting coordi-nation and cooperation among medical institutions,and expanding the health industry will jointly promote the sustained progress of urban health ecosystems.

Objective:To design a health state holographic perceptual intelligence operation and maintenance system,and to explore the application effect in medical equipment management of infectious disease department.Methods:The holographic perception intelligent operation and maintenance system of health status of medical equipment in the infectious disease department was built by the perception layer,transmission layer and application layer to realize the automatic alarm,active protection and real-time monitoring functions of equipment management.A total of 119 medical devices in clinical use in the Department of Infectious Diseases of The Second Affiliated Hospital of Air Force Medical University from 2021 to 2022 were selected,according to different management methods,during the equipment operation and maintenance period in 2021,the conventional medical equipment(referred to as the conventional management mode)management mode was adopted;during the equipment operation and maintenance period in 2022,the holographic perception intelligent operation and maintenance system of medical equipment health status(referred to as the intelligent operation and maintenance management mode)was adopted.The differences in the safety score,maintenance status,and ability score of equipment users between the two management modes were compared.Results:The average scores of electrical safety,biological safety,radiation safety,damage safety,diagnosis and treatment safety of medical equipment using the intelligent operation and maintenance management mode were(0.47±0.21),(0.63±0.15),(1.38±0.11),(0.83±0.34)and(0.94±0.27),respectively,which were lower than those of the conventional management mode,and the difference was statistically significant(Department of Infectious Diseases;Medical equipment;Health status;Holographic sensing;Intelligent operation and maintenance=20.609,24.003,27.127,25.135,30.762,P＜0.05).The equipment failure maintenance rate,maintenance processing time and arrival time of equipment accessories using the intelligent operation and maintenance management mode were(85.41±3.37)%,(0.77±0.14)h and(3.29±0.58)d,respectively,which were lower than those of the conventional management mode,while the average score of equipment maintenance service quality was(95.36±5.13)points,which was higher than that of the equipment score of the conventional management mode,and the differences were statistically significant(t=16.638,25.569,29.333,18.499,P＜0.05).The average scores of equipment users with respect to the sense of responsibility for using the equipment,the ability to correctly operate the equipment,the effect of responding to equipment,the ability to give an accurate and timely alarm and other operating abilities with the intelligent operation and maintenance management mode were(97.48±5.66),(91.53±4.28),(93.37±5.12)and(95.62±4.93),respectively,which were higher than the scores of conventional management mode,and the difference was statistically significant(t=10.948,17.171,6.058,7.276,P＜0.05).Conclusion:The holographic perception intelligent operation and maintenance system of medical equipment health status in the Department of Infectious Diseases can improve the quality of medical equipment management,prevent equipment failures,reduce equipment maintenance,and improve the quality of equipment services.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective To explore the clinical characteristics and risk factors of death during hospitalization in patients with community-acquired pneumonia(CAP)complicated with diabetes mellitus(DM).Methods A retrospective analysis was performed on 566 patients with CAP hospitalized in the Second Affiliated Hospital of Kunming Medical University from January 2018 to January 2022.The patients were divided into simple CAP group(n=478)and CAP combined with diabetes(CAP+DM)group(n=88)according to whether they had diabetes,and then CAP+DM group(n=88)was divided into survival group(n=69)and death group(n =19)according to whether the patients died during hospitalization.The clinical data and laboratory test indicators of patients in different groups were compared.Cox regression analysis was used to screen the risk factors of death during hospitalization in the CAP+DM group.Receiver operating characteristic(ROC)curve was plotted to evaluate the predictive value of independent risk factors on hospitalization death.Results Compared with the simple CAP group,the CAP+DM group had significant differences in age,concomitant hypertension,coronary heart disease,CURB-65 score,neutrophil to lymphocyte ratio(NLR),C-reactive protein(CRP),procalcitonin(PCT),albumin(ALB),prealbumin(PA),glucose(GLU),serum potassium(K),calcium(Ca),phosphorus(P),magnesium(Mg),lactic acid(Lac),non-invasive ventilation time,ICU occupancy rate and mortality rate(P<0.05);Compared with the survival group,there were statistically significant differences in CURB-65 score,NLR,CRP,PCT,GIU,ALB,PA,serum iron(Fe),Ca,non-invasive ventilation time,and ICU admission rate among the death group patients(P<0.05).Cox regression analysis showed that the increase of NLR level and the decrease in PA level were the risk factors for in-hospital death in patients with CAP complicated with diabetes(P<0.05).When the PA cutoff value was 91 mg/L,the AUC,sensitivity,and specificity for predicting in-hospital death of CAP patients with diabetes were 0.849,84.2%and 81.2%,respectively.Conclusion Patients with CAP combined with diabetes are more serious and have worse prognosis than those with CAP alone.PA has a good predictive value for the prognosis of these patients.Early detection and active intervention should be carried out to reduce the in-hospital mortality of patients.