ObjectiveTo explore the correlation between the occurrence of cardiovascular events in rheumatoid arthritis（RA） and traditional Chinese medicine（TCM） syndrome. MethodsThe cross-sectional study selected 6713 RA patients from 122 centres nationwide， in which general information such as name， gender， age， height， body weight， and course of disease were collected by completing a questionnaire； patients were classified into eight types of syndrome according to the information of their four examinations，i.e. wind-dampness obstruction syndrome， cold-dampness obstruction syndrome， dampness-heat obstruction syndrome， phlegm-stasis obstruction syndrome， stasis-blood obstructing collateral syndrome， qi-blood deficiency syndrome， liver-kidney insufficiency syndrome， and qi-yin deficiency syndrome. According to the occurrence of cardiovascular events， they were divided into the occurrence group and the non-occurrence group， and the condition assessment data and laboratory examination indexes were recorded. The test of difference between groups was used to analyse the possible risk factors for the occurrence of RA cardiovascular events， and binary logistic regression was used to analyse the correlation between TCM syndromes and RA cardiovascular events. ResultsA total of 6713 RA patients were included， including 256 cases in occurrence group and 6457 in non-occurrence group. There was no statistically significant difference between groups in terms of height， gender， insomnia， appetite， white blood cell（WBC）， hemoglobin（HGB）， platelets（PLT）， rheumatoid factor（RF）， anti-cyclic peptide containing citrulline（CCP）， alanine aminotransferase（ALT）， aspartate aminotransferase（AST）， γ-glutamyl transpeptidase（GGT）， urea creatinine（CREA）， and glucose（GLU）（P＞0.05）. The TCM syndromes between groups showed significant statistic differences（P＜0.05）. Patients in occurrence group had longer disease duration， heavier body weight， and older age； more severe conditions such as disease activity（DAS-28）， number of painful joints（TJC）， number of swollen joints（SJC）， health questionnaire scores（HAQ）， visual analog scores（VAS）， restlessness， and fatigue； higher blood sedimentation rate（ESR）， low-density lipoprotein（LDL-C）， triglyceride（TG）， total cholesterol（TC）， D-Dimer， and lower high-density lipoprotein（HDL-C）（P＜0.05）. The distribution of syndrome types showed that dampness-heat obstruction syndrome accounted for the largest proportion of patients in both groups and was higher in RA cardiovascular events. Logistic regression analysis showed that the occurrence of RA cardiovascular events was strongly associated with dampness-heat obstruction syndrome［OR=5.937， 95%CI （4.434， 7.949）， P＜0.001］. ConclusionThe occurrence of RA cardiovascular events were associated with TCM syndromes， and the probability of cardiovascular events in the RA patients with dampness-heat obstruction syndrome was 5.937 times higher than patients with other TCM syndromes.

To promote the standardization and normalization of perioperative care for follicular unit extraction(FUE) hair transplantation, ensure treatment efficacy, and align with advancements in the specialty, the Nursing Branch of the Chinese Association of Plastic and Aesthetics organized a panel of domestic experts. By integrating evidence-based medicine with clinical practice experience, and following thorough discussions, these experts developed the Clinical Practice Expert Consensus on Perioperative Nursing Care for Follicular Unit Extraction (2025). This consensus provides a comprehensive overview of hair transplantation, covering preoperative preparation, surgical procedures, intraoperative coordination, postoperative management, and complication prevention and treatment. It serves as a key reference and guide for implementing standardized perioperative nursing care in FUE hair transplantation.

Systemic lupus erythematosus （SLE） may lead to secondary gynecological and obstetric disorders such as decreased ovarian reserve function， menstrual abnormalities， and adverse pregnancy outcomes. Based on "bi （痹） of both body and viscera" theory， this paper proposed that the core mechanism of SLE secondary gynecological and obstetric diseases lies in the mutual transformation between "body bi" and "viscera bi"， which together affect the uterus. Physiologically， uterus forms an internal-external network with the body and viscera through the meridians and blood vessels. Pathologically， when the healthy qi is deficient， nourishment of the body and viscera is impaired； when toxins and stasis accumulate， pathogenic factors disturb the uterus through the chong （冲） and ren （任） meri-dians. The resulting obstruction in the uterus can， in turn， manifest externally and aggravate damage to the body and viscera. Therefore， the pathogenesis of SLE secondary gynecological and obstetric diseases follows a dynamic trajectory of "body bi first， body bi affecting viscera， and then bi of both body and viscera". In treatment， the principle of harmonizing and balancing the healthy qi is emphasized. The main approach is to regulate the viscera， stabilize the body， and nourish the uterus， with the coordination of nourishing the viscera through the body， thereby achieving simultaneous treatment of both body and viscera. This highlights the guiding significance of the "bi of both body and viscera" theory in preventing and treating SLE secondary gynecological and obstetric diseases.

As a major global public health concern,cancer has witnessed a continues rise in both incidence and mortality rates.It pose not only a severe threat to human health but also a heavy burden on socioeconomic systems.Despite remarkable advancements in oncology research,critical challenges such as tumor heterogeneity,drug resistance,and limitations in early screening and diagnostic technologies remain to be addressed.Against this backdrop,artificial intelligence(AI),with its unique advantages in big data analysis,pattern recognition,and predictive modeling,has opened new avenues for cancer research.By integrating multi-modal data,including omics,imaging,and clinical information,AI not only accelerates investigations into fundamental tumor mechanisms but also demonstrates immense potential in areas such as early screening,biomarker discovery,and personalized treatment.These advancements have fostered a deeper integration of precision medicine and oncology.This review provides a comprehensive overview of the most recent progresses in the application of AI in cancer diagnosis and treatment research,with a focus on its practical value across diverse data types and clinical scenarios,as well as future directions for its development.

Objective:To develop an evidence-based nursing practice program based on the Stetler model to extend the lifespan of arteriovenous fistulas (AVF) in maintenance hemodialysis (MHD) patients and evaluate its effectiveness.Methods:An evidence-based nursing practice program was constructed based on the best evidence for extending AVF lifespan in MHD patients. Expert group discussions were held to determine review indicators. A baseline survey was conducted among 100 MHD patients and 42 nurses using covenience sompling at the Blood Purification Center of Wuxi People's Hospital from January to December 2023, to identify barriers and facilitators. In the following year, from January to December 2024, the evidence-based practice was implemented at the same hospital, and the AVF surgical intervention rate and AVF self-management levels of MHD patients were compared before and after the practice.Results:No statistically significant difference was found in the AVF surgery rates before and after the evidence-based practice ( P>0.05) . However, after implementing the evidence-based practice, MHD patients' scores on the AVF self-management scale significantly improved, and the difference was statistically significant ( P<0.01) . Conclusions:The evidence-based practice based on the Stetler model is beneficial for standardizing the clinical management of AVF, reducing the need for surgical interventions, and improving MHD patients' ability to self-manage their AVF.

Objective:To develop an evidence-based nursing practice program based on the Stetler model to extend the lifespan of arteriovenous fistulas (AVF) in maintenance hemodialysis (MHD) patients and evaluate its effectiveness.Methods:An evidence-based nursing practice program was constructed based on the best evidence for extending AVF lifespan in MHD patients. Expert group discussions were held to determine review indicators. A baseline survey was conducted among 100 MHD patients and 42 nurses using covenience sompling at the Blood Purification Center of Wuxi People's Hospital from January to December 2023, to identify barriers and facilitators. In the following year, from January to December 2024, the evidence-based practice was implemented at the same hospital, and the AVF surgical intervention rate and AVF self-management levels of MHD patients were compared before and after the practice.Results:No statistically significant difference was found in the AVF surgery rates before and after the evidence-based practice ( P>0.05) . However, after implementing the evidence-based practice, MHD patients' scores on the AVF self-management scale significantly improved, and the difference was statistically significant ( P<0.01) . Conclusions:The evidence-based practice based on the Stetler model is beneficial for standardizing the clinical management of AVF, reducing the need for surgical interventions, and improving MHD patients' ability to self-manage their AVF.

As a major global public health concern,cancer has witnessed a continues rise in both incidence and mortality rates.It pose not only a severe threat to human health but also a heavy burden on socioeconomic systems.Despite remarkable advancements in oncology research,critical challenges such as tumor heterogeneity,drug resistance,and limitations in early screening and diagnostic technologies remain to be addressed.Against this backdrop,artificial intelligence(AI),with its unique advantages in big data analysis,pattern recognition,and predictive modeling,has opened new avenues for cancer research.By integrating multi-modal data,including omics,imaging,and clinical information,AI not only accelerates investigations into fundamental tumor mechanisms but also demonstrates immense potential in areas such as early screening,biomarker discovery,and personalized treatment.These advancements have fostered a deeper integration of precision medicine and oncology.This review provides a comprehensive overview of the most recent progresses in the application of AI in cancer diagnosis and treatment research,with a focus on its practical value across diverse data types and clinical scenarios,as well as future directions for its development.

Objective To explore association between childhood trauma,resilience and non-suicidal self-injury in adolescents.Methods One hundred and fifty-eight first-episode adolescent patients with mood disorders were selected and divided into NSSI group(n=94)and non-NSSI group(n=64)based on presence or absence of NSSI.The Hamilton depression scale(HAMD),Hamilton anxiety scale(HAMA),childhood trauma questionnaire(CTQ-SF)and Connor-Davidson resilience scale(CD-RISC)were used to evaluate the depression and anxiety symptoms,childhood trauma and resilience.Results There were more cases of younger age(16.17±1.67 vs.16.73±1.37),lower education level(30.9% vs.15.6% ),left behind experience(48.9% vs.29.7% ),school bullying(46.8% vs.25.0% ),suicide ideation(85.1% vs.37.5% )and history of attempted suicide(29.8% vs.6.3% )in the group with NSSI compared to those without NSSI.The HAMD score(27.99±5.94 vs.24.19±5.19),HAMA score(18.02±5.94 vs.15.45±4.99),CTQ total score(48.43±15.40 vs.41.97±9.75),emotional abuse score(12.77±6.06 vs.10.19±4.06),and emotional neglect score(11.40±5.34 vs.9.14±3.55)were higher in the group with NSSI,and the differences between the two groups were significant(P<0.05).The total scores of psychological resilience(39.83±10.27 vs.28.66±12.75),resilience(19.59±4.92 vs.12.28±6.47),strength(12.03±3.98 vs.9.99±4.67),and optimism(8.98±2.97 vs.6.47±3.73)in the group without NSSI were higher than those in the group with NSSI(P<0.05).Logistic regression analysis showed that left behind experience(OR=4.494,95% CI:1.192-16.940),school bullying(OR=5.983,95% CI:1.329-26.945),suicidal ideation(OR=13.225,95% CI:2.908-60.146),history of attempted suicide(OR=16.769,95% CI:1.845-152.379),HAMD(OR=1.264,95% CI:1.046-1.626),emotional abuse(OR=1.327,95% CI:1.093-1.612),and resilience(OR=0.468,95% CI:0.266-0.823)were significantly associated with adolescent mood disorders with NSSI(P<0.05).Conclusion Left behind experience,campus bullying,suicidal ideation and attempted suicide,emotional abuse,degree of depression,and psychological resilience may be associated with NSSI behavior in adolescents with mood disorders.

Pancreatic metastases originating in colon cancer are very rare clinically, and there are few reports on their imaging manifestations. In this paper, it improves the diagnosis of the disease by reporting a case of pancreatic head metastases and focusing on the appearance of contrast-enhanced ultrasound.

Objective To investigate the risk factors for pulmonary infection in patients with acute-on-chronic liver failure(ACLF),and to establish a predictive model.Methods A retrospective analysis was performed for 585 ACLF patients who were admitted to Department of Infectious Diseases,The Second Affiliated Hospital of Air Force Medical University,from January 2009 to September 2022,and according to the condition of pulmonary infection after admission,they were divided into infection group with 213 patients and non-infection group with 372 patients.The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups,and the chi-square test was used for comparison of categorical data between groups.The clinical data of these patients were collected.Univariate and multivariate Logistic regression analyses were used to investigate the risk factors for pulmonary infection in ACLF patients and establish a predictive model,and the receiver operating characteristic(ROC)curve was plotted to assess the predictive value of the model.The Hosmer-Lemeshow test was used to evaluate the degree of fitting of the model,and the ROC curve and the area under the ROC curve(AUC)were used to assess the predictive performance of the model.Results Among the 585 patients with ACLF,213 experienced pulmonary infection,with an infection rate of 36.41%.The multivariate logistic analysis showed that upper gastrointestinal bleeding(odds ratio[OR]=2.463,P=0.047),infection at other sites(OR=2.218,P=0.004),femoral vein catheterization(OR=2.520,P＜0.001),and combined use of two or more antibiotics(OR=2.969,P＜0.001)were risk factors for pulmonary infection in ACLF patients.These factors were included in the risk factor predictive model of Logit(P)=-1.869+0.901×upper gastrointestinal bleeding+0.755×infection at other sites+0.924×femoral vein catheterization+1.088×combined use of two or more antibiotics.The ROC curve analysis showed that the model had a good predictive value(Hosmer-Lemeshow χ2=3.839,P=0.698),with an AUC of 0.753(95%confidence interval:0.700-0.772).Conclusion There is a relatively high incidence rate of pulmonary infection in patients with ACLF,and upper gastrointestinal bleeding,spontaneous peritonitis,femoral vein catheterization,and combined use of two or more antibiotics are related risk factors.The model established based on these factors can effectively predict the onset of pulmonary infection in ACLF patients.