Objective To analyze the effect of releasing the lower pulmonary ligament on right residual lung expansion after right upper lobe resection under different body mass index (BMI) levels. Methods The clinical data of patients who underwent thoracoscopic right upper lobe resection in the First Affiliated Hospital with Nanjing Medical University from 2021 to 2022 were retrospectively analyzed. Patients were divided into a group A (17 kg/m2＜BMI≤23 kg/m2), a group B (23 kg/m2＜BMI≤29 kg/m2) and a group C (BMI＞29 kg/m2) according to BMI. The presence of residual cavity was judged by chest X-ray at 7-10 days after operation, the degree of compensation change of the right main bronchus angle was measured, and the changes in lung volume were determined by CT three-dimensional reconstruction. Results A total of 157 patients who underwent thoracoscopic right upper lobe resection were included, including 71 males and 86 females, with an average age of (59.7±11.2) years. There were 50 patients in the group A, 75 patients in the group B, and 32 patients in the group C. In the group A, compared with those without releasing the lower pulmonary ligament, patients with releasing had a lower incidence of postoperative residual cavity (P=0.016), greater changes in bronchus angle (P<0.001), and smaller changes in lung volume (P<0.001). In the group B and C, there was no significant effect of releasing the lower pulmonary ligament on postoperative residual cavity, bronchus angle, and lung volume changes (P>0.05). Conclusion For patients with thin and long body shape and low BMI, releasing the lower pulmonary ligament is helpful to promote the expansion of the residual lung after right upper lobe resection and reduce the occurrence of postoperative residual cavity in patients.

BACKGROUND:Exosomes,as a type of extracellular vesicle,have become a key medium for cell-to-cell communication due to their nanoscale size and enrichment of various bioactive substances.The study of exosome secretion regulation not only has important scientific value,but also has broad application prospects in clinical practice,and is of great significance for promoting medical progress and improving human health.OBJECTIVE:To review the biological characteristics,biological functions,biogenesis process and biochemical regulation mechanism of exosomes,and to explore the application prospects of exosomes in disease diagnosis,treatment and vaccine development,so as to provide theoretical basis and reference for basic research and clinical transformation of exosomes.METHODS:The first author searched PubMed and CNKI databases in October 2024 for relevant literature published from January 2010 to October 2024.Key words were"exosomes,biological functions,biogenesis,secretion or release,regulatory mechanisms,application prospects"in Chinese and English.Finally,92 articles were included for analysis.RESULTS AND CONCLUSION:The secretion level of exosomes can be regulated through physical or biochemical means.Exosomes show broad application prospects in the fields of disease diagnosis,treatment,and vaccine development,and may play a key role in the treatment of cardiovascular and cerebrovascular diseases as well as cancer.This review provides valuable information for the clinical translation and application research of exosomes,helping to promote future progress in exosome research and application.

BACKGROUND:Exosomes,as a type of extracellular vesicle,have become a key medium for cell-to-cell communication due to their nanoscale size and enrichment of various bioactive substances.The study of exosome secretion regulation not only has important scientific value,but also has broad application prospects in clinical practice,and is of great significance for promoting medical progress and improving human health.OBJECTIVE:To review the biological characteristics,biological functions,biogenesis process and biochemical regulation mechanism of exosomes,and to explore the application prospects of exosomes in disease diagnosis,treatment and vaccine development,so as to provide theoretical basis and reference for basic research and clinical transformation of exosomes.METHODS:The first author searched PubMed and CNKI databases in October 2024 for relevant literature published from January 2010 to October 2024.Key words were"exosomes,biological functions,biogenesis,secretion or release,regulatory mechanisms,application prospects"in Chinese and English.Finally,92 articles were included for analysis.RESULTS AND CONCLUSION:The secretion level of exosomes can be regulated through physical or biochemical means.Exosomes show broad application prospects in the fields of disease diagnosis,treatment,and vaccine development,and may play a key role in the treatment of cardiovascular and cerebrovascular diseases as well as cancer.This review provides valuable information for the clinical translation and application research of exosomes,helping to promote future progress in exosome research and application.

ObjectiveTo explore the effect of the medical-community linkage model on activities of daily living, psychological status and motor function of stroke patients in the community. MethodsA total of 60 stroke patients admitted to two community health service centers and their affiliated stations in Fengtai District, Beijing, from January, 2024 to August, 2025 were enrolled and randomly divided into control group (n = 30) and intervention group (n = 30). The control group received routine medicine, dietary care and rehabilitation management, while the intervention group underwent rehabilitation with the medical-community linkage model, for twelve weeks. They were assessed with modified Barthel Index (MBI), Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD) and Fugl-Meyer Assessment (FMA) before and after intervention. ResultsAfter intervention, the MBI, HAMA, HAMD and FMA scores of patients improved in both groups (|t| > 5.599, P < 0.001), and improved more in the intervention group than in the control group (P < 0.05), except MBI. The HAMA and HAMD scores of family members decreased in both groups (|t| > 10.333, P < 0.001), and decreased more in the intervention group than in the control group (t > 5.681, P < 0.001). ConclusionThe medical-community linkage model can further improve the motor function of stroke patients in community, as well as the psychological status of both patients and their family members.

Objective: To explore the association role of anxiety and depressive symptoms with Internet gaming disorder (IGD) and emotional-behavioral problems among junior high school students, so as to provide references for preventing the occurrence and progression of emotional-behavioral problems in middle school students. Methods: From September to October 2024, a random cluster sampling method was adopted to select 38 069 students from 28 junior high schools in 14 counties (cities and districts) and functional areas of Jining City, Shandong Province. Surveys were conducted by Nine item Internet Gaming Disorder Scale-Short Form, Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, and Strengths and Difficulties Questionnaire. The correlation of emotional and behavioral issues, online game addiction, anxiety and depressive symptoms among junior high school students was analyzed by Speaman correlation analysis. Mediation analysis was used to explore the role of anxiety and depressive symptoms between IGD and emotional-behavioral problems among junior high school students. Results: The detection rates of emotional-behavioral problems, anxiety symptoms, depressive symptoms, and IGD among junior high school students were 19.24 %, 9.48%, 16.69%, and 19.68%, respectively. The scores of emotional-behavioral problems, anxiety symptoms, depressive symptoms and IGD were 10.00 (6.00, 15.00), 3.00 (0.00, 7.00), and 4.00 (1.00, 8.00), 13.00 (10.00, 19.00), respectively. There were positive correlations between each pair of emotional-behavioral problem, IGD, anxiety symptoms, and depressive symptoms scores ( r =0.51-0.81, all P <0.01). Anxiety and depressive symptoms played mediating roles between IGD and emotional-behavioral problems among junior high school students, with mediating effect values of 0.16 (95% CI =0.15-0.17) and 0.12 (95% CI =0.11-0.14), respectively (both P <0.01). Conclusions Anxiety and depressive symptoms mediate the relationship between IGD and emotional-behavioral problems among junior high school students. It is necessary to identify early signs of IGD among junior high school students, strengthen intervention for anxiety and depressive symptoms, to prevent the occurrence and development of emotional and behavioral issues.

ObjectiveTo explore the latent profiles of sleep patterns and their association with gastrointestinal heat accumulation syndrome in preschool children in Beijing. MethodsA cross-sectional study design was adopted， and preschool children were recruited from 57 kindergartens in Beijing using convenience sampling. Sleep characteristics and gastrointestinal heat accumulation syndrome was assessed using the Chinese version of the Sleep Disturbance Scale for Children （SDSC） and Self-rating Diagnostic Scale for Gastrointestinal Heat Retention Syndrome in children （GHRS）. Latent profile analysis （LPA） was applied to identify distinct sleep-related subgroups， and multivariate logistic regression was used to analyze the association between different sleep profiles and gastrointestinal heat accumulation syndrome. ResultsA total of 6878 preschool children were included in the study. Among them， 3.46% of the children （238/6878） had sleep disorders， while 54.42% （3743/6878） had gastrointestinal heat accumulation. Compared to children without gastrointestinal heat accumulation syndrome， those with this syndrome exhibited a higher prevalence of sleep disorders， higher SDSC scores， higher T-transformed total scores， and higher scores across all dimensions， including disorders of initiating sleep， disorders of maintaining sleep， sleep hyperhidrosis， sleep breathing disorders， parasomnias， nonrestorative sleep and excessive somnolence （P＜0.01）. Latent profile analysis identified four distinct sleep characteristic profiles， which were the mixed high-symptom group （32.39%， 2228/6878）， sleep initiation and maintenance difficulty symptom group （49.07%， 3375/6878）， low-symptom group （14.19%， 976/6878）， and the group with no significant symptoms （4.35%， 299/6878）. Multivariate logistic regression analysis demonstrated that the mixed high-symptom group， sleep initiation and maintenance difficulty symptom group， and low-symptom group were significantly associated with gastrointestinal heat accumulation syndrome. Among them， the mixed high-symptom group had the most significant association with gastrointestinal heat accumulation （OR=12.657， P＜0.001）， followed by the sleep initiation and maintenance difficulty symptom group （OR=4.964， P＜0.001）. ConclusionSleep characteristics in preschool children mainly present as composite patterns with different symptom combinations. Moreover， the sleep latent profiles of the mixed high-symptom group， the sleep initiation and maintenance difficulty symptom group， and the low-symptom group were significantly associated with gastrointestinal heat accumulation syndrome.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

Objective: To investigate the current status and influencing factors for cognitive frailty among the elderly in community, so as to provide the evidence for early identification and prevention of cognitive frailty among the elderly. Methods: Residents aged 60 years and above with local household registration from 11 counties (cities, districts) in Zhejiang Province from 2021 to 2023 were selected as study participants using a multistage random sampling method. Demographic information, lifestyle, and health status were collected through questionnaire surveys. Depressive symptoms were assessed using the Patient Health Questionnaire. Cognitive frailty was evaluated using the FRAIL Scale and the Mini-Mental State Examination. Factors affecting cognitive frailty among the elderly in community were identified using a multivariable logistic regression model. Results: A total of 16 613 individuals were surveyed, including 7 465 males (44.93%) and 9 148 females (55.07%). The average age was (70.97±7.29) years. A total of 784 individuals were detected with depressive symptoms, with a detection rate of 4.72%. A total of 724 individuals were detected with cognitive frailty, with a detection rate of 4.36%. Multivariable logistic regression analysis showed that females (OR=1.419, 95%CI: 1.179-1.708), aged ≥70 years (70-<80 years old, OR=1.869, 95%CI: 1.490-2.345; ≥80 years old, OR=5.017, 95%CI: 3.935-6.398), without a spouse (OR=1.495, 95%CI: 1.234-1.810), sedentary (OR=2.420, 95%CI: 1.829-3.202), chronic diseases (1 type, OR=1.456, 95%CI: 1.175-1.804; ≥2 types, OR=1.639, 95%CI: 1.314-2.045), and depressive symptoms (OR=4.191, 95%CI: 3.361-5.225) were associated with a higher risk of cognitive frailty among the elderly in community. Conversely, a lower risk of cognitive frailty was seen among the elderly in community who had primary school or above (primary school, OR=0.512, 95%CI: 0.389-0.676; junior high school or above, OR=0.464, 95%CI: 0.354-0.608), engaged in physical exercise (OR=0.396, 95%CI: 0.291-0.539), and were reported average or good self-rated health status (average, OR=0.641, 95%CI: 0.475-0.866; good, OR=0.150, 95%CI: 0.109-0.208). Conclusions The detection rate of cognitive frailty among the elderly in community is relatively low and is influenced by demographic factors such as gender, age, education level, as well as lifestyle like sedentary and physical exercise, and health status. It is recommended to reduce the risk of cognitive frailty among the elderly through multidimensional interventions, including health education, promotion of healthy lifestyles, and enhanced mental health support.

Objective: To establish a nomogram prediction model for Alzheimer's disease (AD) among the elderly in community, so as to provide the evidence for early screening and prevention of AD. Methods: Based on the Zhejiang Healthy Aging Cohort Study, the elderly aged 60-90 years who completed the baseline survey were selected as the study subjects. Follow-up surveys were conducted from 2015 to 2016 and from 2019 to 2021. Sociodemographic characteristics, lifestyle factors, medical history, and waist circumference were collected through questionnaire surveys and physical examinations. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), and a diagnosis of AD was made based on the Alzheimer's Disease Assessment Scale-Cognitive Subscale and medical history. The participants were randomly divided into training and validation sets at 8∶2 ratio. LASSO regression was used to screen for predictive factors. Multivariable logistic regression model was used to analyze predictive factors and construct a nomogram. The model was analyzed and evaluated using the receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 6 988 elderly were included at baseline, with a mean age of (68.19±6.63) years. There were 3 438 males (49.20%), and 3 550 females (50.80%). The median follow-up duration was 4.90 (interquartile range, 3.80) years, with 817 new cases of AD were identified, yielding an incidence of 11.69%. LASSO regression and multivariable logistic regression showed that age (OR=1.017, 95%CI: 1.005-1.030), gender (female, OR=1.820, 95%CI: 1.533-2.165), educational level (primary school, OR=0.813, 95%CI: 0.673-0.980), physical exercise (not active, OR=1.572, 95%CI: 1.260-1.980), dining companions (spouse and children, OR=0.771, 95%CI: 0.598-0.995), baseline MMSE score (OR=0.843, 95%CI: 0.821-0.866), and waist circumference (OR=0.981, 95%CI: 0.973-0.989) were risk predictors for AD among the elderly in community. The prediction model demonstrated an area under the ROC curve of 0.740 (95%CI: 0.698-0.783) in the validation set, with a sensitivity of 0.731 and a specificity of 0.667. DCA indicated that when the probability threshold was 0.060 to 0.325, the clinical net benefit was relatively high. Conclusion The AD risk prediction model constructed in this study has good discrimination and clinical practicability, can be used for early screening of AD among the elderly in the community.