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.

Surgical treatment is one of the key approaches for non-small cell lung cancer (NSCLC). Regular postoperative follow-up is crucial for early detection and timely management of tumor recurrence, metastasis, or second primary tumors. A scientifically sound and reasonable follow-up strategy not only extends patient survival but also significantly improves quality of life, thereby enhancing overall prognosis. This consensus aims to build upon the previous version by incorporating the latest clinical research advancements and refining postoperative follow-up protocols for early-stage NSCLC patients based on different treatment modalities. It provides a scientific and practical reference for clinicians involved in the postoperative follow-up management of NSCLC. By optimizing follow-up strategies, this consensus seeks to promote the standardization and normalization of lung cancer diagnosis and treatment in China, helping more patients receive high-quality care and long-term management. Additionally, the release of this consensus is expected to provide insights for related research and clinical practice both domestically and internationally, driving continuous development and innovation in the field of postoperative management for NSCLC.

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.

Diabetes-related cognitive impairment(DCI)is a major complication of type 2 diabetes melli-tus(T2DM).Although exercise is essential in alleviating DCI,the underlying mechanisms remain un-clear.The aim of this study is to investigate the role and mechanism of exosomal miR-126a-5p induced by exercise in ameliorating DCI.Twenty-four 16-week-old male db/db mice were randomly divided into dia-betes group(n=12;DM)and exercise intervention group(n=12;DE).The control group consisted of male m/m mice of the same age group(n=12;CON).The DE group underwent 8 weeks of moderate in-tensity treadmill training(10 m/min,5 days a week).In the MWM experiment,compared to the CON group,the DM group exhibited prolonged escape latency(P<0.01),reduced swimming speed and target quadrant time(P<0.001),and decreased expression of miR-126a-5p and EX-miR-126a-5p in hipp-ocampal tissue(P<0.001).After exercise intervention,the DE group showed improved performance with decreased escape latency(P<0.05),increased swimming speed and target quadrant time(P<0.05),and elevated levels of exosomal miR-126a-5p(P<0.001).Morphological staining revealed a de-crease in the expression and proportion of NeuN in hippocampal neurons and an increase in the expression and proportion of glial cells in the CA1 and CA3 regions of DM group mice compared to CON group mice(P<0.05),while DE group mice showed increased fluorescence intensity and proportion of neurons(P<0.05).Western blotting analysis revealed that the DM group also showed significant upregulation of amy-loid β(Aβ),high mobility group box 1(Hmgb1),and NF-κB in the hippocampus(P<0.05),which were reduced after exercise(P<0.05).Moreover,exosomal miR-126a-5p overexpression greatly de-creased the levels of Hmgb1,NF-κB,and amyloid precursor protein(APP)in HT22 cells and TNF-α,IL-1β in supernatant exposed to HG(P<0.05),while inhibition of miR-126a-5p led to increased levels of these proteins(P<0.05).In conclusion,eight weeks of treadmill exercise improved cognitive function in db/db mice,likely through the EXs-miR-126/HMGB1/NF-κB pathway to reduce inflammation in hip-pocampal tissue.

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.

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.

Working memory is an executive memory process that includes encoding, maintenance, and retrieval. These processes can be modulated by transcranial alternating current stimulation (tACS) with sinusoidal waves. However, little is known about the impact of the rate of current change on working memory. In this study, we aimed to investigate the effects of two types of tACS with different rates of current change on working memory performance and brain activity. We applied a randomized, single-blind design and divided 81 young participants who received triangular wave tACS, sinusoidal wave tACS, or sham stimulation into three groups. Participants performed n-back tasks, and electroencephalograms were recorded before, during, and after active or sham stimulation. Compared to the baseline, working memory performance (accuracy and response time) improved after stimulation under all stimulation conditions. According to drift-diffusion model analysis, triangular wave tACS significantly increased the efficiency of non-target information processing. In addition, compared with sham conditions, triangular wave tACS reduced alpha power oscillations in the occipital lobe throughout the encoding period, while sinusoidal wave tACS increased theta power in the central frontal region only during the later encoding period. The brain network connectivity results showed that triangular wave tACS improved the clustering coefficient, local efficiency, and node degree intensity in the early encoding stage, and these parameters were positively correlated with the non-target drift rate and decision starting point. Our findings on how tACS modulates working memory indicate that triangular wave tACS significantly enhances brain network connectivity during the early encoding stage, demonstrating an improvement in the efficiency of working memory processing. In contrast, sinusoidal wave tACS increased the theta power during the later encoding stage, suggesting its potential critical role in late-stage information processing. These findings provide valuable insights into the potential mechanisms by which tACS modulates working memory.
Humans ; Memory, Short-Term/physiology* ; Male ; Female ; Young Adult ; Transcranial Direct Current Stimulation/methods* ; Brain/physiology* ; Adult ; Electroencephalography ; Single-Blind Method