Objective To analyze the epidemiological characteristics and molecular subtypes of typhoid and paratyphoid fever in Dalian, and to provide scientific basis for the development of effective prevention and control measures for typhoid and paratyphoid fever. Methods Descriptive epidemiological methods were used to analyze the data of typhoid and paratyphoid reported in Dalian from 2019 to 2023. Pulsed field gel electrophoresis (PFGE) was used for bacterial molecular typing and cluster analysis of the homology of strains. Results A total of 32 cases of typhoid and paratyphoid fever were reported in Dalian from 2019 to 2023. There was no statistically significant difference in the incidence rate between years ( χ²=4.41, P>0.05). There were two peaks in the time distribution. The age of onset was between 30 and 69 years old, and the difference in sex ratio between men and women was statistically significant ( χ²=4.00, P<0.05). The top two occupations with the highest number of cases of typhoid and paratyphoid fever were retired people, housework and unemployed, and the difference in the incidence rate among occupations was not statistically significant (χ²=4.59, P>0.05). PFGE experiment results showed that 32 typhoid and paratyphoid strains isolated from patients can be divided into 25 types. Conclusion The typhoid fever epidemic in Dalian remains stable at a relatively low level from 2019 to 2023. The PFGE banding patterns are relatively scattered, but there are dominant subtypes among them, which may be local epidemic strains.

Objective: To investigate the prevalence of overweight and obesity among children and adolescents in Yangzhou City, and its association with screen behaviors, so as to provide scientific evidence for weight management among students. Methods: In May 2025, an electronic questionnaire survey was conducted among children and adolescents in Yangzhou City. A total of 3 722 participants were selected from grades 4 to 12 in 18 primary and secondary schools (108 classes) by using stratified cluster random sampling. The Chi square test was used to compare the differences in the detection rates of overweight and obesity among children and adolescents with 5 types of screen behaviors (watching TV, playing electronic games, scrolling short videos, screen based learning, electronic socializing) in different time groups each day (never, >0~<2 h, ≥2 h). Multivariate Logistic regression analysis was performed to examine the associations of five types of screen behaviors, presence of electronic devices in the bedroom, and screen use during meals on the weight status of children and adolescents. Results: The prevalence of overweight and obesity among children and adolescents was 37.3%. For all five types of screen behaviors, the differences in the distribution of overweight and obesity detection rates among children and adolescents across the three time spent categories were statistically significant ( χ 2=30.76- 70.78 , all P <0.01). After adjusting for confounding factors, multivariate Logistic regression analysis revealed that frequent or always using screens during meals( OR =1.63, 95％ CI =1.14~2.31), playing video games ( OR =1.28, 95% CI =1.11-1.48), browsing short videos ( OR =1.29, 95％ CI=1.09-1.54), and screen based learning ( OR =1.26, 95％ CI =1.10-1.44) were significantly associated with overweight and obesity among children and adolescents (all P <0.05). Conclusions Excessive screen use is positively correlated with the incidence of overweight and obesity in children and adolescents. Targeted interventions on screen behaviors among children and adolescents are therefore warranted.

Background Gestational weight gain is closely related to maternal and infant health outcomes. Pregnant women are simultaneously exposed to four metals—lithium (Li), vanadium (V), uranium (U), and bismuth (Bi)—through inhalation of fine particulate matter and consumption of contaminated food and water. Existing studies suggest that exposure to these metals may be associated with gestational weight gain. However, no study has yet explored the complex relationships between exposure to mixtures of these four metals and weight gain at different stages of pregnancy. Objective To investigate the associations between mixed exposure to Li, V, U, and Bi in early pregnancy and the average weekly gestational weight gain during both early pregnancy and mid-to-late pregnancy. Methods This prospective study recruited eligible women in early pregnancy from an obstetrics clinic of a tertiary hospital in Jinan, China, between September 2021 and July 2023. Pre-pregnancy weight, current weight (at 11⁺⁰ to 13⁺⁶ weeks of gestation), and spot urine samples (≥5.0 mL) were collected at enrollment. Urinary concentrations of Li, V, Bi, and U were determined using inductively coupled plasma mass spectrometry. Participants were followed up in late pregnancy (≥28 weeks of gestation) to collect information on physical activity via questionnaire; weight measurements at the last antenatal visit (35⁺⁰ to 37⁺⁶ weeks of gestation) were obtained from the hospital information system. After adjusting for covariates, multiple linear regression and generalized additive models were used to assess the associations of individual metals with weekly weight gain in early pregnancy and in mid-to-late pregnancy. Bayesian kernel machine regression (BKMR) and quantile-based g-computation (Qgcomp) were applied to evaluate the joint effects of the metal mixture exposure on weekly weight gain at the two gestational stages. Results A total of 313 pregnant women were included. The geometric means of urinary Li, V, U, and Bi concentrations were 37.07, 0.20, 0.06, and 0.04 μg·L⁻¹, respectively; after creatinine adjustment, the corresponding values were 46.82, 0.25, 0.07, and 0.05 μg·g⁻¹ (Cr). The mean weekly gestational weight gain was (0.19±0.25) kg in early pregnancy and (0.53 ± 0.18) kg in mid-to-late pregnancy. Both multiple linear regression and generalized additive models showed that urinary V concentration was positively associated with average weekly gestational weight gain in early pregnancy, while no significant associations were found for other metals or for gestational weight gain in mid-to-late pregnancy. In the BKMR model with early-pregnancy weight gain as the outcome, V had the strongest association [posterior inclusion probability (PIP)=0.773]. When other metals were fixed at their medians, V showed a positive non-linear association with the outcome. A significant single-metal effect of V and its interaction with Li were observed. Compared with the 50th percentile of the metal mixture, the average weekly weight gain in early pregnancy increased by 0.016 (95%CI: 0.003, 0.029) and 0.018 (95%CI: 0.001, 0.036) at the 60th and 65th percentiles, respectively; conversely, at the 25th percentile, it decreased by 0.026 (95%CI: 0.002, 0.050). Overall, the joint effect of the metal mixture on early- pregnancy weight gain showed an upward trend. In the BKMR model for mid-to-late pregnancy gestational weight gain, all PIPs were<0.5, and no significant single-metal effects, interactions, or joint effects were identified. Qgcomp results confirmed a positive association between the metal mixture and early-pregnancy weight gain (b=0.031, 95%CI: 0.010, 0.051; P<0.01), with V contributing the highest positive weight (0.71). No significant association was found for weight gain in mid-to-late pregnancy (b=0.007, P=0.339). Conclusion Higher levels of co-exposure to the Li, V, Bi, and U metal mixture during early pregnancy may be associated with increased average weekly weight gain in early pregnancy. Among these metals, V exhibits a predominant role and appears to interact with Li. No association is observed between early-pregnancy metal mixture exposure and average weekly gestational weight gain in mid-to-late pregnancy. These findings suggest that monitoring and managing metal exposure during early pregnancy may be crucial for the rational regulation of gestational weight gain.

Objective To investigate the anti-intrahepatic cholangiocarcinoma （ICC） activity and mechanism of 2-heptyl-3-hydroxy-4（1H）-quinolone （PQS）, a secondary metabolite of polar marine microorganisms. Methods Patient-derived organoid （PDO） models were established using intrahepatic cholangiocarcinoma （ICC） tumor tissues obtained from Renji Hospital, Shanghai Jiao Tong University School of Medicine. Hematoxylin and eosin （HE） staining was performed to assess the histomorphological characteristics of both patient ICC tissues and corresponding PDOs. Immunohistochemistry （IHC） was employed to evaluate CYP3a expression in patient ICC tissues and PDOs. The antiproliferative activity of PQS against stably passaged PDOs was determined using an adenosine triphosphate （ATP）-based bioluminescence assay, and dose-response curves were fitted to calculate the half-maximal inhibitory concentration （IC₅₀） for assessing the anti-ICC efficacy of PQS. In the human intrahepatic cholangiocarcinoma RBE cell model, the effects of PQS on RBE cell proliferation were evaluated by the cell counting kit-8 （CCK-8） assay; colony formation capacity was assessed by the plate colony formation assay; cell cycle distribution and apoptosis were analyzed by flow cytometry; and the protein expression levels of cyclin-dependent kinase 2（CDK2）, CDK4, RelA（p65）, and nuclear factor-κB1（p50） were detected by Western blotting. Results Two ICC PDO models were successfully established. Histomorphological observation revealed that the PDO tissues after serial passaging exhibited morphological features essentially consistent with the corresponding patient ICC tissues, both presenting as cystic vesicle-like structures. Immunohistochemical analysis demonstrated that CYP3a was expressed in both PDO tissues and patient ICC tissues. ATP-based bioluminescence assay results indicated that PQS effectively suppressed ATP content in PDO tissues, with a fitted dose-response curve yielding an IC₅₀ value of 2.49 µmol/L. In the RBE cell model, PQS inhibited RBE cell viability in a concentration-dependent manner, and the fitted dose-response curve yielded an IC₅₀ value of 1.05 µmol/L. Furthermore, PQS at concentrations of 1, 2, and 4 µmol/L significantly suppressed colony formation of RBE cells, arrested the cell cycle at the S phase, induced apoptosis, and downregulated the expression of proteins associated with the NF-κB signaling pathway. Conclusion ICC PDO models were successfully established, confirming the anti-ICC activity of PQS. PQS inhibited RBE cell proliferation, potentially via the NF-κB signaling pathway, by arresting the cell cycle at the S phase and inducing apoptosis of RBE cells

Objective To investigate the anti-intrahepatic cholangiocarcinoma （ICC） activity and mechanism of 2-heptyl-3-hydroxy-4（1H）-quinolone （PQS）, a secondary metabolite of polar marine microorganisms. Methods Patient-derived organoid （PDO） models were established using intrahepatic cholangiocarcinoma （ICC） tumor tissues obtained from Renji Hospital, Shanghai Jiao Tong University School of Medicine. Hematoxylin and eosin （HE） staining was performed to assess the histomorphological characteristics of both patient ICC tissues and corresponding PDOs. Immunohistochemistry （IHC） was employed to evaluate CYP3a expression in patient ICC tissues and PDOs. The antiproliferative activity of PQS against stably passaged PDOs was determined using an adenosine triphosphate （ATP）-based bioluminescence assay, and dose-response curves were fitted to calculate the half-maximal inhibitory concentration （IC₅₀） for assessing the anti-ICC efficacy of PQS. In the human intrahepatic cholangiocarcinoma RBE cell model, the effects of PQS on RBE cell proliferation were evaluated by the cell counting kit-8 （CCK-8） assay; colony formation capacity was assessed by the plate colony formation assay; cell cycle distribution and apoptosis were analyzed by flow cytometry; and the protein expression levels of cyclin-dependent kinase 2（CDK2）, CDK4, RelA（p65）, and nuclear factor-κB1（p50） were detected by Western blotting. Results Two ICC PDO models were successfully established. Histomorphological observation revealed that the PDO tissues after serial passaging exhibited morphological features essentially consistent with the corresponding patient ICC tissues, both presenting as cystic vesicle-like structures. Immunohistochemical analysis demonstrated that CYP3a was expressed in both PDO tissues and patient ICC tissues. ATP-based bioluminescence assay results indicated that PQS effectively suppressed ATP content in PDO tissues, with a fitted dose-response curve yielding an IC₅₀ value of 2.49 µmol/L. In the RBE cell model, PQS inhibited RBE cell viability in a concentration-dependent manner, and the fitted dose-response curve yielded an IC₅₀ value of 1.05 µmol/L. Furthermore, PQS at concentrations of 1, 2, and 4 µmol/L significantly suppressed colony formation of RBE cells, arrested the cell cycle at the S phase, induced apoptosis, and downregulated the expression of proteins associated with the NF-κB signaling pathway. Conclusion ICC PDO models were successfully established, confirming the anti-ICC activity of PQS. PQS inhibited RBE cell proliferation, potentially via the NF-κB signaling pathway, by arresting the cell cycle at the S phase and inducing apoptosis of RBE cells

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To explore the safety and feasibility of 5G remote robot-assisted thoracoscopic anatomic lobectomy and segmentectomy. Methods A retrospective analysis was conducted on patients who underwent 5G remote robot-assisted thoracoscopic anatomic lobectomy or segmentectomy between July and September 2024. The surgeries were performed collaboratively by Shanghai Chest Hospital, Affiliated Hospital of Yangzhou University, and The First Affiliated Hospital of Nanchang University. Perioperative outcomes were recorded and analyzed. Results Ten patients were included, comprising 4 anatomic lobectomies and 6 segmentectomies. The median age was 61.0 (56.0, 72.0) years. The median intraoperative bi-directional network latency was 52.5 (39.0, 54.0) ms. There were no instances of network interruption, robot-related adverse events, or conversions to open thoracotomy. The median postoperative chest tube drainage volume was 500.0 (375.0, 600.0) mL, and the median hospital stay was 5.5 (4.0, 6.0) days. No complications of Clavien-Dindo grade Ⅱor higher occurred. All patients were recurrence-free and alive during the 6-month postoperative follow-up period. Conclusion 5G remote robot-assisted thoracoscopic surgery demonstrates high safety and operational stability. This technology shows promising potential for clinical application and is worthy of further development and utilization.

The surgical management of empyema (excluding those caused by mycobacterium tuberculosis and non-tuberculous mycobacteria) is rapidly evolving towards minimally invasive, precise, and stepwise approaches. The traditional three-stage classification (exudative, fibrinopurulent, and organizing) has limitations in guiding dynamic clinical decision-making. For the first time, this consensus explicitly identifies two critical junctures in the pathological progression of empyema: "early transformation" (stage Ⅰ to Ⅱ) and "late transformation" (stage Ⅱ to Ⅲ), and thereby constructs a corresponding "identification-early warning-intervention" stepwise therapeutic framework. The consensus emphasizes that proactive debridement via video-assisted thoracoscopic surgery should be performed during the early transformation phase to halt disease progression. Conversely, during the late transformation phase, therapeutic goals should be rationally adjusted to prioritize adequate drainage, avoiding futile pleural decortication. Moreover, the consensus underscores the pivotal role of precise perioperative etiological diagnosis (e.g. metagenomic nest-generation sequencing) and standardized anti-infective therapy. Integrating practical experiences from multiple thoracic surgery centers in China and relevant evidence-based literature, this consensus formulates recommendations on the precise definitions of staging, surgical indications for each phase, key technical points, perioperative management, and training systems. It aims to promote the standardized and individualized surgical management of empyema, ultimately optimizing patient prognosis.

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.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.