With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

Over the past three decades， China has made significant progress in the prevention and control of viral hepatitis， and the incidence rates of new-onset pediatric hepatitis B virus infections and acute viral hepatitis in the population have reduced to a relatively low level； however， there is still a heavy disease burden of chronic viral hepatitis in China， which severely affects the health status of the population. This study systematically summarizes the achievements of viral hepatitis prevention and control in China， analyzes existing problems and challenges， and proposes comprehensive prevention and control strategies and measures to eliminate viral hepatitis as a public health threat based on the national conditions of China， in order to provide a reference for related departments in China on how to achieve the action targets for eliminating viral hepatitis as a public health threat by 2030.

Objective To construct and validate an interpretable machine learning model integrating contrast-enhanced venous phase CT radiomics and clinical features for preoperative prediction of central lymph node metastasis(CLNM)of papillary thyroid carcinoma(PTC).Methods A case-control study was conducted on 243 histologically confirmed PTC patients.Among them,196 patients from the First Affiliated Hospital of Army Medical University were randomly allocated into a training set(n=137)and an internal validation set(n=59)at a 7:3 ratio,while the left 47 patients from No.958 Hospital of PLA Army were assigned into an external validation set.All participants completed standardized preoperative contrast-enhanced neck CT scanning.Quantitative radiomic features were systematically extracted from venous phase CT images through an open-source big data AI platform.Six machine learning classifiers,eXtreme Gradient Boosting(XGBoost),Support Vector Machine(SVM),Random Forest(RF),Logistic Regression(LR),k-Nearest Neighbors(KNN),and Decision Tree(DT)were implemented to construct clinical-radiomics integration models.The predictive performance was quantitatively assessed through receiver operating characteristic(ROC)curve analysis,with area under the curve(AUC)values calculated for training,internal validation,and external validation sets.Model interpretability was achieved using Shapley additive explanations(SHAP)framework,with particular focus on elucidating feature contributions in the best-performing model.Results The XGBoost model had an AUC value of 0.936(95%CI:0.895～0.976),0.832(95%CI:0.724～0.941),and 0.772(95%CI:0.632～0.912)in training,internal and external validation sets,respectively.SHAP analysis revealed age as the most influential clinical predictor,with younger patients showing higher CLNM risk(OR=0.968,P=0.042).Conclusion Our machine learning-based clinic-radiomic prediction model demonstrates satisfactory performance in predicting CLNM of PTC,providing valuable references for clinical decision-making.

Arsenic is a semi-metal,and lipid-soluble arsenic compounds are one of the widespread forms in the environment and food chain,but there is a lack of standards for lipid-soluble arsenic compounds,which is one of the bottlenecks in the current analytical detection and toxicological studies of organic arsenic.In this study,four saturated arsenic-containing hydrocarbons,AsHC 318,AsHC 332,AsHC 346,and AsHC 374(The number is relative molecular mass),were successfully synthesized in three steps by using dimethylarsinic acid,potassium iodide,sodium hydroxide,and four brominated alkanes(1-Bromotetradecane,1-bromopentadecane,1-bromohexadecane,and 1-bromooctadecane)as raw materials.The structures of these four saturated arsenic-containing hydrocarbons were characterized by proton nuclear magnetic resonance(1H NMR)spectroscopy,13C nuclear magnetic resonance(13C NMR)spectroscopy,and high-resolution mass spectrometry(HR-MS).The yields of the method were 8%-10%,and the synthesized compounds could be used in subsequent toxicity evaluation experiments to assess the toxic effects and mechanisms of action of arsenic-containing hydrocarbons.This study provided an effective method for synthesis of arsenic-containing hydrocarbons,enriching the synthesis methods of arsenic-containing hydrocarbons,and provided raw materials for the subsequent toxicological studies of arsenic-containing hydrocarbons.

Objective To investigate the effects of Yishen Zhuyu Tongluo Decoction on chondrocyte pyroptosis and ferroptosis in rats with knee osteoarthritis(KOA).Methods Forty SD were divided randomly into a sham operation group(n=10)and a modeling group(n=30).A KOA model was established in the modeling group by anterior cruciate ligament transection of the right hind limb knee joint.The drawer test was used to confirm the successful establishment of the model.Post-surgery,the rats were subjected to 30 min of forced activity daily to induce KOA.Lameness and hopping movements were observed after 4 weeks,and hematoxylin and eosin staining confirmed cartilage surface damage,deformation,and inflammatory cell infiltration,indicating successful modeling.The model rats were then assigned randomly to a model group(n=8),celecoxib group(n=8),and Yishen Zhuyu Tongluo Decoction group(n=8).The sham operation and model groups received 10 mL/kg of saline by gavage,the celecoxib group received 12 mg/kg of celecoxib solution,and the Yishen Zhuyu Tongluo Decoction group received 5.4 g/kg of the herbal decoction,once daily for 8 weeks.After the interventions,the rats were anesthetized,blood was collected from the abdominal aorta and serum was separated,and the knee joints were isolated.Three samples were fixed in paraformaldehyde,while the remaining cartilage tissue was reserved.Pathological changes in joint cartilage were observed by hematoxylin and eosin and Safranin O-Fast Green staining.Bone microstructure was analyzed using micro-computed tomography.Serum interleukin(IL)-1β and IL-18 protein levels were detected by enzyme-linked immunosorbent assay.Relative mRNA expression levels of NLRP3,ASC,Caspase-1,GSDMD,IL-1β,IL-18,ACSL-4,FTH-1,GPX-4,and cyclooxygenase(COX)-2 were detected by reverse transcription quantitative real-time PCR,and protein expression of NLRP3,Caspase-1,and COX-2 were detected by immunohistochemistry.Results Compared with the sham operation group,model rats showed surface damage and deformation of cartilage tissue,disordered cell arrangement in all layers,significant loss of Safranin O-Fast Green staining,and sparse and irregular trabecular bone distribution.Serum levels of the inflammatory factors IL-1β and IL-18 were elevated(P＜0.01).mRNA expression levels of NLRP3,ASC,Caspase-1,GSDMD,IL-1β,IL-18,ACSL-4,and COX-2 were also significantly increased(all P＜0.01),while FTH-1 and GPX-4 mRNA expression levels were decreased(P＜0.01).Compared with the model group,rats in the celecoxib and Yishen Zhuyu Tongluo Decoction groups showed smoother and more intact cartilage surfaces,significantly increased cell counts,less loss of Safranin O-Fast Green staining,denser trabecular bone,and thicker cortical bone,with improved bone microstructure.Serum IL-1β and IL-18 levels were reduced(P＜0.01),NLRP3(P＜0.01,P＜0.05),ASC,Capase-1,GSDMD,IL-1β,IL-18,ACSL-4,and COX-2 mRNA levels were decreased(all P＜0.01),and relative expression levels of FTH-1 and GPX-4 mRNA were significantly increased(P＜0.01).Conclusions Yishen Zhuyu Tongluo Decoction can treat KOA by inhibiting chondroptosis and ferroptosis in chondrocytes,reducing serum IL-1β and IL-18 levels,and improving bone microstructure.

Objective To investigate the feasibility and safety of bedside transesophageal echocardiography(TEE)-guided atrial septostomy in patients undergoing extracorporeal membrane oxygenation(ECMO)support.Methods Eight patients(2 females and 6 males)who developed pulmonary edema during VA-ECMO treatment between January 2020 and October 2024 were enrolled.All patients underwent bedside TEE-guided atrial septal puncture,followed by gradual balloon dilation using an Inoue balloon(diameter:18-24 mm).The endpoint for dilation was defined as mean left atrial pressure＜15 mmHg.Post-procedure evaluation included assessment of the septal defect size,mean left atrial pressure,and improvement in bilateral pulmonary edema.Results The mean age of all 8 patients was(43.50±16.84)years old.Atrial septostomy was successfully performed in all patients.The mean balloon dilation diameter was(22.75±2.68)mm,resulting in a mean septal defect size of(6.31±0.37)mm.The mean left atrial pressure significantly decreased from(26.63±1.77)mmHg pre-procedure to(12.75±1.28)mmHg post-procedure(P＜0.001).All patients demonstrated marked improvement in bilateral pulmonary edema,and six patients also showed a significant reduction in the severity of mitral regurgitation following the procedure.No procedure-related complications were observed.Conclusions Bedside TEE-guided atrial septostomy is safe and effective for reducing left heart loading during ECMO support and improving pulmonary edema.

Objective To investigate the feasibility and safety of bedside transesophageal echocardiography(TEE)-guided atrial septostomy in patients undergoing extracorporeal membrane oxygenation(ECMO)support.Methods Eight patients(2 females and 6 males)who developed pulmonary edema during VA-ECMO treatment between January 2020 and October 2024 were enrolled.All patients underwent bedside TEE-guided atrial septal puncture,followed by gradual balloon dilation using an Inoue balloon(diameter:18-24 mm).The endpoint for dilation was defined as mean left atrial pressure＜15 mmHg.Post-procedure evaluation included assessment of the septal defect size,mean left atrial pressure,and improvement in bilateral pulmonary edema.Results The mean age of all 8 patients was(43.50±16.84)years old.Atrial septostomy was successfully performed in all patients.The mean balloon dilation diameter was(22.75±2.68)mm,resulting in a mean septal defect size of(6.31±0.37)mm.The mean left atrial pressure significantly decreased from(26.63±1.77)mmHg pre-procedure to(12.75±1.28)mmHg post-procedure(P＜0.001).All patients demonstrated marked improvement in bilateral pulmonary edema,and six patients also showed a significant reduction in the severity of mitral regurgitation following the procedure.No procedure-related complications were observed.Conclusions Bedside TEE-guided atrial septostomy is safe and effective for reducing left heart loading during ECMO support and improving pulmonary edema.

Catheter-based pulsed field ablation(PFA)for atrial fibrillation ablation has been widely adopted worldwide in recent years,accumulating substantial evidence for its efficacy and safety.However,several adverse events associated with this technology have also been observed,such as PFA-related coronary artery spasm,hemolysis,acute renal injury,and symptomatic or asymptomatic cerebrovascular events.This review summarizes the latest basic and clinical research advances in PFA over the past two years,focusing on biophysical aspects including the field intensity of PFA,the thermal effects of PFA,contact force,and the number of applications.We discuss whether PFA demonstrates tissue selectivity,the mechanisms of hemolysis and microbubble formation,as well as the lesion morphology and impact factors to lesion depth.This review aims to provide clinicians with a more in-depth understanding of PFA technology and biphasic to optimize clinical application.

The feasibility for the development of road-rail medical vehicles was discussed.The gap between China's ground medical evacuation system and medical evacuation requirements was analyzed,and the limitations of the existing mobile medical units in China were introduced.The key points for developing road-rail medical vehicles were discussed.The road-rail medical vehicle would be an ideal tool for casualty treatment and rapid evacuation at war time and peace time,which could be a future development direction of the road-rail vehicle and medical train.[Chinese Medical Equipment Journal,2025,46(10):84-90]

Given the lack of annotations for key lung organs and tissues in existing public datasets,this study collected 863 cases of chest CT scan images and constructed the first comprehensive dataset containing annotations of pulmonary vessels,airways,and nodules using a semi-automated method that combines computer vision algorithms with manual corrections by radiologists.On this basis,a lung nodule segmentation model based on multi-task learning is proposed.By incorporating annotations of pulmonary vessels(pulmonary arteries and veins)and the trachea to enhance model's ability to learn lung features,the proposed model reduces the false discovery rate in lung nodule detection,and improves generalization ability.Additionally,the use of larger image patches further optimizes model performance.The trained VAAN_128 model achieves the best performance,with a Dice coefficient of 0.694 and a false discovery rate of 0.210 for lung nodule segmentation.Moreover,it simultaneously provides accurate segmentation results of pulmonary vessels and the trachea,assisting in the formulation of more precise diagnosis and treatment plans.Based on the VAAN_128 model,a software system for navigation and localization in biopsy procedures is developed.In clinical practice,this system can assist physicians in accurately locating lung nodules,distinguishing critical tissues,and improving preoperative planning efficiency.This provides precise and efficient technical support for early diagnosis and disease monitoring of lung diseases,and is of great significance for path planning in clinical navigation system and future lung imaging research.