Exportin 1 (XPO1) is aberrantly overexpressed in various malignant tumors and can lead to the loss of anti-tumor effects of important tumor suppressor proteins such as p53, RB1, and FOXO by mediating their nuclear export. Although XPO1 inhibitor Selinexor has entered clinical application, its single-agent anti-tumor activity remains suboptimal, which is closely related to the compensatory activation of multiple signaling pathways in response to XPO1 inhibition. Focusing on the core regulatory role of XPO1 in tumor cells, this article systematically summarizes the current landscape of combination therapies involving XPO1 inhibitors and various targeted agents, including inhibitors of CDK4/6, FLT3, BET, ATR, and BCL2/MDM2, aiming to provide some reference for the development of XPO1-centered combination therapy strategies.

Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

The evaluation of blood compatibility of biomaterials is crucial for ensuring the clinical safety of implantable medical devices. To address the limitations of traditional testing methods in real-time monitoring and electrical property analysis, this study developed a portable electrical impedance tomography (EIT) system. The system uses a 16-electrode design, operates within a frequency range of 1 to 500 kHz, achieves a signal to noise ratio (SNR) of 69.54 dB at 50 kHz, and has a data collection speed of 20 frames per second. Experimental results show that the EIT system developed in this study is highly consistent with a microplate reader ( R ²=0.97) in detecting the hemolytic behavior of industrial-grade titanium (TA3) and titanium alloy-titanium 6 aluminum 4 vanadium (TC4) in anticoagulated bovine blood. Additionally, with the support of a multimodal image fusion Gauss-Newton one-step iterative algorithm, the system can accurately locate and monitor in real-time the dynamic changes in blood permeation and coagulation caused by TC4 in vivo. In conclusion, the EIT system developed in this study provides a new and effective method for evaluating the blood compatibility of biomaterials.
Electric Impedance ; Animals ; Tomography/instrumentation* ; Biocompatible Materials ; Materials Testing/instrumentation* ; Cattle ; Titanium ; Alloys ; Prostheses and Implants

Metastasis serves as an indicator of malignancy and is a biological characteristic of carcinomas. Epithelial-mesenchymal transition (EMT) plays a key role in the promotion of tumor invasion and metastasis and in the enhancement of tumor cell aggressiveness. Prostaglandin E synthase 3 (p23) is a cochaperone for heat shock protein 90 (HSP90). Our previous study showed that p23 is an HSP90-independent transcription factor in cancer-associated inflammation. The effect and mechanism of action of p23 on lung cancer metastasis are tested in this study. By utilizing cell models in vitro and mouse tail vein metastasis models in vivo, the results provide solid evidence that p23 is critical for promoting lung cancer metastases by regulating downstream CXCL1 expression. Rather than acting independently, p23 forms a complex with RNA-binding motif protein 14 (RBM14) to facilitate EMT progression in lung cancer. Therefore, our study provides evidence for the potential role of the RBM14-p23-CXCL1-EMT axis in the metastasis of lung cancer.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Objective:To analyze the correlation between mental health status and metabolic syndrome (MetS) in health checkup people.Methods:It was a cross-sectional study, 2 920 participants who received health checkup in the Health Examination Center of Peking University Third Hospital from January 2019 to December 2023 were selected using cluster sampling method. Their general information, physical examination, biochemical indicators, body composition, and self-evaluation scores on the Symptom Checklist-90 (SCL-90) were collected. According to the inclusion and exclusion criteria, a total of 2 813 study subjects were included, and divided into the MetS group and the non-MetS group based on whether they had MetS. The differences in general demographic information, body composition, blood biochemistry, and SCL-90 scores between the two groups were compared. Binary Logistic regression analysis was used to explore the correlation between mental health status and MetS.Results:Of the 2 813 subjects included, 1 576 were males (56.0%) and 1 237 were females (44.0%), with an average age of (41.7±11.0) years, the MetS group had 586 cases (20.8%) and the non-MetS group had 2 227 cases (79.2%). The MetS group had higher levels of age, body mass index, waist circumference, systolic blood pressure, diastolic blood pressure, total cholesterol, triglycerides, low density lipoprotein cholesterol (LDL-C), fasting blood glucose, glycosylated hemoglobin (HbA 1c), free thyroxine(FT4), total triiodothyronine (TT3), free triiodothyronine (FT3), waist-to-hip ratio, visceral fat area, body fat percentage, uric acid/creatinine, homocysteine (Hcy), aspartate aminotransferases (AST), and alanine transaminase (ALT) levels, as well as higher scores for somatization, hostility, paranoia, and other factor compared to the non-MetS group (all P<0.05), while high density lipoprotein cholesterol (HDL-C) and estimated glomerular filtration rate (eGFR) levels were lower than those in the non-MetS group (all P<0.05). The proportion of male, and the positive rates of SCL-90, somatization, interpersonal sensitivity, hostility, paranoia and other factor in the MetS group were higher than those in the non-MetS group (all P<0.05). Multifactorial analysis showed that individuals with a positive SCL-90 assessment had a 1.34 times higher risk of MetS than those with a negative assessment ( OR=1.34, 95% CI: 1.06-1.68; P=0.014). Among them, individuals with positive somatization ( OR=2.02, 95% CI: 1.25-3.28; P=0.004) and hostility ( OR=1.61, 95% CI: 1.02-2.56; P=0.042) had increased risk of MetS. Conclusion:Poor mental health status increases the risk of MetS.

Objective:To construct a health management mode for functional community groups and evaluate its health management effect.Methods:This study was a non-randomized controlled trial. A cluster sampling method was adopted to select 3 352 subjects who completed three health examinations at the Physical Examination Center of Peking University Third Hospital from January 2022 to October 2024 and received health management for two consecutive years from a certain functional community (an enterprise) in Beijing as the research subjects. A health management mode for functional community groups was constructed, and a cohort of the population was established. A health management platform was built, and the research subjects were included in the health management system. Comprehensive interventions were carried out using multiple methods, including disease risk assessment, daily monitoring and reminders, exercise and nutrition assessment and intervention, personal health consultation, and health science popularization knowledge push. The subjects were classified and analyzed based on general information such as age and gender. The changes in systolic blood pressure, diastolic blood pressure, fasting blood glucose, total cholesterol, low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) were assessed using One-way Repeated Measures Analysis of Variance before the intervention and at 1 and 2 years after the intervention. The changes in triglycerides were assessed using Generalized Estimating Equations before the intervention and at 1 and 2 years after the intervention.Results:The systolic blood pressure, total cholesterol, and LDL-C levels of the total population showed a linear decreasing trend after the intervention (all P0.001). The HDL-C level showed an overall upward trend after the intervention [(1.45±0.32) vs (1.39±0.30) vs (1.47±0.33) mmol/L, F=12.746, P0.001]. However, there was no linear change trend in diastolic blood pressure, fasting blood glucose, and triglycerides after the intervention (all P0.05). The systolic blood pressure, total cholesterol and LDL-C levels of both men and women showed a linear decreasing trend after the intervention. For men, systolic blood pressure [(128.6±16.1) vs (127.6±16.3) vs (126.5±15.5) mmHg (1 mmHg=0.133 kPa); F=33.488, P0.001], total cholesterol [(5.29±1.02) vs (5.07±1.00) vs (4.94±1.03) mmol/L; F=286.525, P0.001], and LDL-C [(3.45±0.86) vs (3.43±0.84) vs (3.33±0.83) mmol/L; F=55.419, P0.001] all decreased. For women, systolic blood pressure [(118.9±15.6) vs (117.5±15.6) vs (117.2±15.8) mmHg; F=34.188, P0.001], total cholesterol [(5.13±0.94) vs (4.96±0.90) vs (4.85±0.90) mmol/L; F=274.080, P0.001], and LDL-C [(3.13±0.79) vs (3.10±0.76) vs (3.10±0.75) mmol/L; F=6.861, P=0.009] also decreased. The HDL-C level of men showed an overall upward trend after the intervention [(1.30±0.26) vs (1.25±0.25) vs (1.32±0.28) mmol/L; F=6.866, P0.05]. For men and women, diastolic blood pressure, fasting blood glucose and triglyceride levels showed no linear change trend after the intervention (all P0.05). The systolic blood pressure and total cholesterol levels of all age groups showed a linear decreasing trend after the intervention(all P0.001). In the 50-59 age group, diastolic blood pressure showed a linear decreasing trend after intervention [(81.6±11.6) vs (80.1±11.6) vs (79.9±11.6) mmHg; F=7.043, P0.05]. In the 40-49 age group, triglyceride showed an overall decreasing trend after intervention [1.29(0.91-2.01) vs 1.27(0.88-1.91) vs 1.27(0.92-1.89) mmol/L; Wald χ 2=10.062, P0.05]. In the 30-39 age group, LDL-C showed a linear decreasing trend after intervention [(3.23±0.80) vs (3.20±0.79) vs (3.19±0.77) mmol/L; F=7.702, P0.05]. In the 40-49 age group, LDL-C also showed a linear decreasing trend after intervention [(3.39±0.84) vs (3.36±0.82) vs (3.30±0.80) mmol/L; F=22.801, P0.001]. In the 50-59 age group, LDL-C showed a linear decreasing trend after intervention [(3.38±0.92) vs (3.32±0.91) vs (3.15±0.88) mmol/L; F=27.920, P0.001]. In the 30-39 age group, HDL-C showed an overall increasing trend after intervention [(1.46±0.33) vs (1.39±0.31) vs (1.48±0.34) mmol/L; F=10.047, P0.05]. In the 40-49 age group, HDL-C also showed an overall increasing trend after intervention [(1.45±0.30) vs (1.40±0.30) vs (1.47±0.32) mmol/L; F=10.118, P0.05]. However, there was no linear change trend in fasting blood glucose and triglyceride levels in all age groups after intervention ( F=1.169, 2.643, 0.663, 0.001, all P0.05). Conclusion:The functional community group health management mode constructed in this study has a good effect.

Objective:Based on the autoregressive integrated moving average (ARIMA) model, back propagation neutral network (BPNN), and ARIMA-BPNN model, select the optimal model suitable for predicting the incidence trend of hepatitis C in Taiyuan City according to the characteristics of the data.Methods:The data of reported cases of hepatitis C in Taiyuan from 2008 to 2021 were selected, and the seasonal trend decomposition chart was used to analyze the seasonal characteristics of the monthly incidence rate of hepatitis C in Taiyuan during the period, and the ARIMA model, BPNN model, and ARIMA-BPNN model were established to predict. The performance of the model was measured using four indicators: mean absolute error ( MAE), mean squared error ( MSE), root mean square error ( RMSE), and mean absolute percentage error ( MAPE). Results:A total of 20 025 cases of hepatitis C were reported, and the overall incidence trend was stable. The BPNN model performed well on MSE, MAE, and RMSE indicators, the ARIMA-BPNN model performed well on MAPE indicators, and the ARIMA model performed relatively averagely. Conclusions:The ARIMA-BPNN model is a better model for predicting the trend of hepatitis C in Taiyuan City, with a higher predictive performance than a single model. It has significant prospects in predicting the trend of infectious diseases.

Objective To investigate the correlation between PPARγ and female interstitial cystitis/bladder pain syndrome (IC/BPS) and to establish a predictive model. Methods Clinical data were collected from 89 female IC/BPS patients (observational group) admitted to the hospital from June 2022 to December 2023,and 90 healthy female volunteers undergoing physical examinations during the same period (control group). Plasma levels of inflammatory factors,total antioxidant capacity (TAC),total glutathione (GSH),malondialdehyde (MDA),and PPARγ levels were measured. Significant clinical features were identified using LASSO regression and fitted into a multivariate logistic regression model. The diagnostic efficacy was assessed through receiver operat-ing characteristic (ROC) curves. Results Compared to the control group,the observation group exhibited signifi-cantly elevated age,BMI,NLR,absolute neutrophil count,IFN-α,IL-1β,IL-6,IL-8,TNF-α and CD3+CD4+T expression levels,while absolute lymphocyte count,IL-10,TAC,GSH and plasma PPARγ expression levels were significantly decreased (all P<0.05). LASSO regression identified 8 variables,including NLR,IFN-α,absolute neutrophil count,IL-1β,IL-6,TNF-α,CD3+CD4+T and PPARγ,which were incorporated into the predictive model. Multivariate binary logistic regression analysis revealed that elevated levels of IL-1β,TNF-α and CD3+CD4+T cells,along with reduced PPARγ levels,were independent risk factors for IC/BPS. ROC curve analy-sis indicated that the diagnostic efficacy of the combined PPARγ and clinical parameters (age,IL-1β,TNF-α and CD3+CD4+T) (AUC=0.901) was superior to PPARγ alone (AUC=0.839). Conclusion Plasma PPARγ levels are significantly reduced in female IC/BPS patients and serve as a potential diagnostic marker,with combined clinical parameters enhancing diagnostic accuracy.

BACKGROUND:With the increasing degree of population aging in China,the incidence of osteoporosis is rising annually.This growing demand for screening and diagnosis poses significant challenges to the healthcare system,increasing the time costs,financial burdens,and radiation exposure risks for patients.OBJECTIVE:To develop a novel interpretable prediction method based on traditional CT examination data and demographic data,aiming to reduce the number of patient examinations and enable multiple screenings from one examination.METHODS:A two-stage interpretable framework for osteoporosis prediction was designed.In the first stage,a human-computer collaborative method was used for annotating CT images,with an innovative vertebra 7-point CT value measurement technique.Patient's sex and age were used as key demographic features to enrich the model's input.In the second stage,the LightGBM model was enhanced by SHapley Additive exPlanations for quantitative analysis of feature importance,improving the interpretability of predictions and increasing clinical trust.Systematic experiments validated the effectiveness of the framework and the stability of the optimal feature set through the comparative analysis of different feature combinations with six machine learning models.To further assess the generalization ability of the model,the model was further tested on an external dataset.RESULTS AND CONCLUSION:The experiment compared six machine learning models suitable for medical applications,and the results showed that LightGBM model achieved an F1 score of 0.902 2 and an area under the curve of 0.938 7,outperforming the other models.In terms of interpretability,the clinical application credibility and operability of the model was increased by ranking and visualizing the contribution of input features to the results.Additionally,this study realized a prototype system,and testing results indicated that the system is user-friendly,capable of quickly processing data to provide prediction results,with visualized outcomes demonstrating good interpretability.This system effectively assists doctors in clinical decision-making and provides robust support for the screening and preliminary diagnosis of osteoporosis.