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.

Background: Malignant pleural effusion (MPE), a common complication of advanced cancers, is associated with poor prognosis and reduced quality of life. Although host–tumor interactions are known to drive MPE development, the associated immune dynamics during disease progression remain unclear. Using a Lewis lung carcinoma-induced MPE model in C57BL/6JNidfc mice, we systematically evaluated general parameters and immune cell changes at two-day intervals throughout disease progression. Results: The day of Lewis lung carcinoma cell injection into the pleural space was designated as day 0. By day 10 post-injection (p.i.), MPE-bearing mice exhibited ~ 10% body weight loss, marking the experimental endpoint. Pleural tumor mass and pleural effusion volume were minimal up to day 4 p.i. but increased sharply from day 6 onward.CD45⁺ immune cell counts rose over time, and days 6, 8, and 10 p.i. marked key stages of MPE progression. On day 6, B cells, T cells, and natural killer cells, but not macrophages and neutrophils, increased significantly compared to earlier timepoints. By day 8, all immune cell subsets except T cells exceeded day 6 levels, and at day 10, natural killer cell numbers declined while others continued to increase. Besides, the numbers of CD8⁺ T cells, Th1 cells, regulatory T cells, and M2 macrophages progressively increased from day 6 to 10. Based on these data, days 6 and 10 were defined as early and advanced MPE stages, respectively, with distinct immune phenotypes. In advanced MPE, CD8⁺ T cells displayed reduced IFN-γ, TNF-α, Granzyme B, Perforin, FasL, and Ki-67, but upregulated PD-1 and CTLA-4 relative to early stage. Similarly, Th1 cells showed decreased IFN-γ, TNF-α, and IL-2 production along with reduced Ki-67 expression. Advanced-stage M2 macrophages exhibited lower MHC-II levels and impaired phagocytosis, but higher PD-L1 and IL-10 production, while neutrophils showed reduced TNF-α release and phagocytic activity. Conclusions Our findings characterize the temporal immune dynamics associated with MPE progression in a mouse model, revealing a transition from an early immunostimulatory state to a late immunosuppressive state. This study enhances our understanding of MPE immunopathogenesis and provides a foundation for developing precise, stagespecific therapeutic strategies.

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.

Objective:To evaluate the efficacy and safety of endoscopic submucosal dissection (ESD) for the treatment of ileocecal valve lipoma.Methods:A retrospective cohort study was performed on data of ileocecal lipoma patients who underwent ESD at the Endoscopy Center of Zhongshan Hospital, Fudan University from December 2013 to June 2023. According to the lesion location, the patients were divided into ileocecal valve group and cecum group. The operation time, operation speed, en bloc resection rate, complications, and follow-up outcomes between the two groups were compared.Results:A total of 59 patients with ileocecal lipoma were enrolled, including 31 patients in the ileocecal valve group and 28 patients in the cecum group.There were no significant differences in gender, age, specimen size, or lesion size between the two groups ( P>0.05). Lipomas in both the ileocecal valve group and the cecum group were successfully resected by ESD. The en bloc resection rates were 100.0% (31/31) and 92.9% (26/28) respectively, and the difference was not statistically significant ( χ2=0.033, P=0.133). Median operative duration significantly differed between the two groups ( ileocecal valve group 26 min VS cecum group 20 min, Z=-0.136, P=0.027), as did resection speed (ileocecal valve group 0.14 cm2/min VS cecum group 0.24 cm2/min, Z=-0.223, P=0.022). Adverse events included one postoperative fever in the ileocecal valve group and one delayed bleeding in the cecum group. During the median follow-up of 38 months (7-106 months), there was no case of residual tumor or recurrence. Conclusion:Despite technical challenges in ESD of ileocecal valve lipoma, it is still a safe, feasible and effective treatment method.

Aim To elucidate the underlying mecha-nism by which total triterpenoids extracted from Hove-nia dulcis(H-TP)enhance the sensitivity of A549/DDP cells to cisplatin.Methods The ARE-Nrf2 lu-ciferase reporter assay was applied to investigate the impact of H-TP on Nrf2 expression.Western blot was used to detect the protein levels of Keap-1/Nrf2/HO-1,Nrf2-GPX4 signaling pathway,apoptosis-related proteins of Bcl-2 and Bax.Further validation of its effects on Nrf2 was conducted by using Nrf2 activator/inhibitor.Results H-TP could enhance the sensitivi-ty of A549/DDP cells to cisplatin by modulating the expression of apoptosis-related proteins Bax and Bcl-2,inhibiting the Keap-1/Nrf2/HO-1/GPX4 signating pathway in A549/DDP cells,and inducing ferroptosis.Conclusion H-TP enhances the sensitivity of A549/DDP cells to cisplatin by inducing the Nrf2-mediated ferroptosis pathway.

Objective To construct a medical consumables selection indicator system based on analytic hierarchy process(AHP)and fuzzy cluster method.Methods Firstly,a medical consumables selection indicator system was established preliminarily with the literature research results and actual situation of hospital consumables management;secondly,13 experts in related fields were selected to execute two rounds of online questionnaires,the expert weights were determined with AHP,the importance of each selection indicator was scored by the expert evaluation method and fuzzy cluster method,and consistency analysis was carried out on the two rounds of expert evaluation results;finally,the final medical consumables selection indicator system was built with the 100-point scale.Results The constructed medical consumables selection indicator system was composed of 5 primary indicators,12 secondary indicators and 38 tertiary indicators.The primary indicators included consumables quality,clinical demand,cost-effectiveness,supply capacity and after-sales service,with the percentage-based scores being 27,25,14,26 and 8,respectively.Conclusion The medical consumables selection indicator system based on AHP and fuzzy cluster method with high reliability provides effective and reliable references for medical institutions to select medical consumables.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

This study aims to describe the population and regional distribution characteristics of smoking behavior among adult twins in the China Twin Registry (CNTR), as well as the concordance rates for smoking behavior in monozygotic and dizygotic twins, and estimate the heritability. The study population included adult twins in CNTR who had smoking questionnaire data. A random-effects regression model was used to describe the distribution of smoking behavior among different subgroups based on various characteristics. The concordance of smoking behavior between different zygosity groups was calculated, and heritability was estimated. A total of 28 444 twin pairs were included in this study, with an average age of (36.6±12.0) years. Among male twins, 41.2% were current smokers, while only 1.2% of females smoked. Higher smoking rates were observed among male smokers in the 50-59 age group ( z=23.0, P<0.001), northern regions ( z=2.9, P<0.01), rural areas ( z=-5.2, P<0.001), those who were divorced/widowed ( z=3.8, P<0.001), and first-born twins ( z=-4.3, P<0.001), while lower smoking rates were found in those with higher education ( z=-16.1, P<0.001) and unmarried individuals ( z=-16.0, P<0.001). The smoking concordance rate for male monozygotic twins was 69.6%, significantly higher than the 57.3% concordance rate for dizygotic twins ( χ 2=105.0, P<0.05). The heritability of smoking behavior in male twins was estimated at 28.9% (95% CI: 24.3%-33.4%). Stratified analyses showed differences in heritability across regions and age groups: the heritability in northern regions was 32.6% (95% CI: 27.3%-38.0%), higher than the 21.0% (95% CI: 12.4%-29.5%) observed in southern regions; the highest heritability of 35.1% (95% CI: 26.3%-43.9%) was found in the 18-29 age group, with heritability decreasing with age. In conclusion, the smoking rate and influencing factors in the twin population are similar to those in the general population, with unique characteristics, such as higher smoking rates in first-born twins. Genetic factors have a significant impact on smoking behavior.

Objective:To investigate the influencing factors of adult dental fluorosis in drinking water-borne endemic fluorosis areas of Inner Mongolia Autonomous Region.Methods:A case-control study was conducted in January 2024 to select adult fluorosis patients (case group) and healthy individuals (control group) from the drinking water-borne endemic fluorosis areas in Helinger County, Hohhot City, Inner Mongolia Autonomous Region as the survey subjects. Urine samples were collected to determine urinary fluoride concentration. A questionnaire survey was conducted. SPSS 25.0 software was used for χ 2 test and multivariate logistic regression analysis. Restricted cubic spline (RCS) was used to analyze the association between urinary fluoride concentration and the risk of dental fluorosis in adults. Results:A total of 161 individuals were included in the survey, including 100 in the case group and 61 in the control group. The results of univariate analysis showed that there were statistically significant differences in the distribution of gender, smoking, and urinary fluoride concentration between the case group and the control group (χ 2 = 7.54, 5.02, 9.69, P < 0.05). The results of multivariate logistic regression analysis indicated that gender ( OR = 0.36, 95% CI: 0.18 - 0.73, P = 0.005) and urinary fluoride concentration ( OR = 3.08, 95% CI: 1.46 - 6.67, P = 0.003) were the influencing factors of adult fluorosis. RCS analysis showed a significant linear dose-response relationship between the risk of dental fluorosis and urinary fluoride concentration ( Poverall trend = 0.001, Pnonlinear = 0.071). When the urinary fluoride concentration was greater than 1.57 mg/L, the risk of dental fluorosis increased with the increase of urinary fluoride concentration. Conclusion:Gender and urinary fluoride concentration are the risk factors of dental fluorosis in adults in drinking water-borne endemic fluorosis areas of Inner Mongolia Autonomous Region.

Objective:To summarize the current situation and shortcomings of China's health technology innovation policies,and provide reference for policy formulation and improvement.Methods:Text mining was used to sort out 24 policy documents related to health technology innovation issued by the national and provincial levels since the 13th Five Year Plan period.A PMC index evaluation model for health technology innovation policies was established,and a quantitative analysis of health technology innovation policies was conducted through 9 primary indicators and 43 secondary indicators.Results:Among the 24 policies,2 were rated as perfect,8 were rated as excellent,and 14 were rated as acceptable.Conclusions and Suggestions:China's policies on health and medical science and technology innovation have been basically improved.They can be further refined by focusing on core and key technologies,emphasizing clinical research and transformation,and advancing digital and intelligent strategies.