ObjectiveTo explore the mechanism by which Yizhi Qingxin prescription improves mitochondrial dysfunction in Alzheimer's disease （AD） through regulating mitochondrial Ca²⁺ homeostasis and kinetic balance based on the protein kinase A （PKA）/calcineurin （CaN） signaling pathway. MethodsSixty three-month-old amyloid precursor protein （APP）/presenilin 1 （PS1） double transgenic mice were randomly divided into a model group， a donepezil group（0.65 mg·kg^-1）， a low-dose Yizhi Qingxin prescription group （YQF-L，2.6 g·kg^-1）， a medium-dose Yizhi Qingxin prescription group （YQF-M，5.2 g·kg^-1）， and a high-dose Yizhi Qingxin prescription group （YQF-H，10.4 g·kg^-1）， with 12 mice in each group. Twelve C57BL/6J mice with the same genetic background served as a normal group. Each treatment group received gavage administration daily， with the model and normal groups receiving equal volume of physiological saline. Intervention continued for 12 consecutive weeks. The learning and memory abilities of the mice were assessed using the novel object recognition （NOR） and Morris water maze （MWM） tests. Hematoxylin-eosin （HE）/Nissl staining was used to observe histopathological changes in the hippocampus. Transmission electron microscopy （TEM） was used to observe mitochondrial ultrastructure. Fluo-4 acetoxymethyl ester （Fluo-4 AM） Ca²⁺ probe was used to measure intracellular Ca²⁺ concentration in brain tissue. Western blot was used to determine the protein expression of PKA， CaN， sodium/calcium/lithium exchanger （NCLX）， mitochondrial calcium uniporter （MCU）， calmodulin （CaM）， dynamin-related protein 1 （Drp1）， and phosphorylated dynamin-related protein 1 （serine 637 site） ［p-Drp1（S637）］ in the hippocampus. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to measure the expression of PKA， CaN， CaM， NCLX， MCU， and Drp1 mRNAs. ResultsCompared with those in the normal group， the recognition index （RI） of the model group decreased （P0.01）， and the number of crossings through the original platform area， the duration of stay in the target quadrant， and the distance were reduced （P0.01）. The protein expression of PKA， NCLX， and p-DRP1 （ser637） significantly decreased （P0.05）， and the mRNA expression of PKA and NCLX significantly decreased （P0.05）. The escape latency （EL） was prolonged （P0.05）， and the intracellular Ca²⁺ level significantly increased （P0.01）. The protein expression of CaN， CaM， MCU， and Drp1， as well as the mRNA expression of CaN， MCU， and Drp1， significantly increased （P0.05）. After intervention with Donepezil and Yizhi Qingxin prescription， compared with that in the model group， the RI of the treatment group significantly increased （P0.05）， and the number of crossings through the platform and the duration of stay in the target quadrant significantly increased （P0.05）. The protein expression of PKA， NCLX， and p-Drp1 （ser637） and the mRNA expression of PKA and NCLX significantly increased （P0.05）. On the 4th and 5th days， the EL was shortened （P0.05）， and the intracellular Ca²⁺ level decreased （P0.05）. The protein expression of CaN， CaM， MCU， and Drp1 and the mRNA expression of CaN， MCU， and Drp1 significantly decreased （P0.05）. ConclusionYizhi Qingxin prescription regulates the PKA/CaN pathway， upregulates the expression of PKA， NCLX， and p-Drp1 （ser637） proteins， reduces the expression of CaN， CaM， MCU， and Drp1 proteins， and regulates Ca²⁺ homeostasis and mitochondrial dynamic balance， thereby enhancing the spatial learning and memory abilities of AD mice.

ObjectiveTo explore the mechanism by which Yizhi Qingxin prescription improves mitochondrial dysfunction in Alzheimer's disease （AD） through regulating mitochondrial Ca²⁺ homeostasis and kinetic balance based on the protein kinase A （PKA）/calcineurin （CaN） signaling pathway. MethodsSixty three-month-old amyloid precursor protein （APP）/presenilin 1 （PS1） double transgenic mice were randomly divided into a model group， a donepezil group（0.65 mg·kg^-1）， a low-dose Yizhi Qingxin prescription group （YQF-L，2.6 g·kg^-1）， a medium-dose Yizhi Qingxin prescription group （YQF-M，5.2 g·kg^-1）， and a high-dose Yizhi Qingxin prescription group （YQF-H，10.4 g·kg^-1）， with 12 mice in each group. Twelve C57BL/6J mice with the same genetic background served as a normal group. Each treatment group received gavage administration daily， with the model and normal groups receiving equal volume of physiological saline. Intervention continued for 12 consecutive weeks. The learning and memory abilities of the mice were assessed using the novel object recognition （NOR） and Morris water maze （MWM） tests. Hematoxylin-eosin （HE）/Nissl staining was used to observe histopathological changes in the hippocampus. Transmission electron microscopy （TEM） was used to observe mitochondrial ultrastructure. Fluo-4 acetoxymethyl ester （Fluo-4 AM） Ca²⁺ probe was used to measure intracellular Ca²⁺ concentration in brain tissue. Western blot was used to determine the protein expression of PKA， CaN， sodium/calcium/lithium exchanger （NCLX）， mitochondrial calcium uniporter （MCU）， calmodulin （CaM）， dynamin-related protein 1 （Drp1）， and phosphorylated dynamin-related protein 1 （serine 637 site） ［p-Drp1（S637）］ in the hippocampus. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to measure the expression of PKA， CaN， CaM， NCLX， MCU， and Drp1 mRNAs. ResultsCompared with those in the normal group， the recognition index （RI） of the model group decreased （P0.01）， and the number of crossings through the original platform area， the duration of stay in the target quadrant， and the distance were reduced （P0.01）. The protein expression of PKA， NCLX， and p-DRP1 （ser637） significantly decreased （P0.05）， and the mRNA expression of PKA and NCLX significantly decreased （P0.05）. The escape latency （EL） was prolonged （P0.05）， and the intracellular Ca²⁺ level significantly increased （P0.01）. The protein expression of CaN， CaM， MCU， and Drp1， as well as the mRNA expression of CaN， MCU， and Drp1， significantly increased （P0.05）. After intervention with Donepezil and Yizhi Qingxin prescription， compared with that in the model group， the RI of the treatment group significantly increased （P0.05）， and the number of crossings through the platform and the duration of stay in the target quadrant significantly increased （P0.05）. The protein expression of PKA， NCLX， and p-Drp1 （ser637） and the mRNA expression of PKA and NCLX significantly increased （P0.05）. On the 4th and 5th days， the EL was shortened （P0.05）， and the intracellular Ca²⁺ level decreased （P0.05）. The protein expression of CaN， CaM， MCU， and Drp1 and the mRNA expression of CaN， MCU， and Drp1 significantly decreased （P0.05）. ConclusionYizhi Qingxin prescription regulates the PKA/CaN pathway， upregulates the expression of PKA， NCLX， and p-Drp1 （ser637） proteins， reduces the expression of CaN， CaM， MCU， and Drp1 proteins， and regulates Ca²⁺ homeostasis and mitochondrial dynamic balance， thereby enhancing the spatial learning and memory abilities of AD mice.

: To analyze the prevalence of anemia and iron deficiency among primary and secondary school students in Rural Nutrition Improvement Program areas of Guizhou Province in 2023, and to explore the related factors, so as to provide evidence for Rural Nutrition Improvement Program optimization. Methods: In September 2023, a stratified random cluster sampling strategy was used to select 40 rural compulsory education schools with rural nutrition improvement program in five counties of Guizhou Province. School level questionnaire was employed to collect information of basic characteristics and school meal implementation. A total of 7 826 primary and secondary school students aged 6-16 underwent anthropometry and hemoglobin (Hb) determination; serum ferritin (SF) was additionally measured in a random subsample of 1 795 pupils. Students in Grade 3 and above also completed a questionnaire covering demographic characteristics, dietary behaviours and nutrition knowledge. Group comparisons were conducted by Chi square test or Fisher s exact test, and multivariable Logistic regression models were constructed to identify factors associated with anemia and iron deficiency. Results: The overall Hb level was (133.21±12.95)g/L, with an anemia prevalence of 7.17%. The overall SF level was (69.58±59.01)μg/L, with an iron deficiency prevalence of 2.73%. Multivariable analysis showed that stunting ( OR =1.88), school menus without nutrient calculation ( OR =1.61) and absence of menu planning software in the current semester ( OR =2.34) independently increased anemia risk, whereas obesity reduced it ( OR =0.54) (all P <0.05). Girls ( OR =4.16) and Grades 7-9 ( OR =5.93) increased iron deficiency risk (both P <0.05). Compared with rarely eating fresh vegetables, students with consuming <3 kinds per day ( OR =0.08) or exactly 3 kinds per day ( OR =0.06) had lower iron deficiency risks (both P <0.05). Conclusions Anemia and iron deficiency are prevalent among primary and secondary school students in Guizhou. Targeted intervention measures should be implemented for key populations to enhance the effectiveness of nutrition improvement program.

Objective: To develop a 24 hour physical activity index for school aged children, and to analyze the association of 24 hour physical activity index with screening myopia and obesity, so as to provide a more effective assessment tool for student health risk screening. Methods: From April to June 2024, a total of 451 students in Grades 3-4 from two monitored primary schools in Shanghai were selected using stratified cluster random sampling method. Data on eight core indicators, including daily moderate to vigorous physical activity time, total physical activity time, outdoor activity time, screen time, sleep duration, sleep efficiency, social jetlag and daytime sleepiness, were collected through questionnaires and accelerometer monitoring. Each indicator was standardized and synthesized into a 0-80 point school aged children s 24 hour physical activity index. Spearman correlation analysis and t-test were used to assess consistency between questionnaire and accelerometer derived indices. Multivariate Logistic regression was applied to analyze the association of strength of the composite index with single behavior indicators in screening myopia and overweight/obesity. Results: The compliance rates were higher for moderate to vigorous physical activity time and screen time (50.8%, 98.7%), while the compliance rate for outdoor activity time was only 42.6%, and that for sufficient sleep duration was merely 10.2%. There was no significant difference between the total scores derived from the questionnaire and accelerometer methods (45.13±5.83, 45.05±6.87, t=0.29, P >0.05), but they showed a strong positive correlation ( r=0.58, P <0.01). Multivariate Logistic regression revealed that adjusting for individual behaviors such as grade, gender and both parents being myopic, among single behavior indicators of 24 hour physical activity index, only insufficient outdoor activity time was significantly associated with screening myopia among school aged children ( OR=1.50, 95%CI =1.01-2.21); the detection risk of screening myopia and obesity in the low index group were higher than those in the high index group ( OR=2.47, 95%CI =1.02-5.96; OR=16.63,95%CI = 5.99- 46.20) (all P <0.05). Conclusion The developed 24 hour physical activity index for school aged children demonstrates good measurement accuracy and shows stronger associations with screening myopia and obesity than single behavior indicator.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

This paper systematically elaborates on the key points of diagnosis and differential diagnosis of salivary gland tumors characterized by a substantial amount of extracellular mucus as a main or prominent feature, and clarifies the core differential features. The term "mucus-rich" specifically denotes that mucus is a major component of the tumor, rather than a focal or minor one. This phenomenon is associated with distinct histogenetic mechanisms: it may result from specific genetic mutations (e.g., AKT1 E17K in mucinous adenocarcinoma) that drive ductal epithelial differentiation into mucus-secreting cells, or from myoepithelial cells secreting glycosaminoglycans that form a myxoid stroma. Salivary gland tumors with abundant extracellular mucus include mucinous cystadenoma, sialadenoma papilliferum-like intraductal papillary tumors, mucinous myoepithelioma, pleomorphic adenoma with mucin-rich stroma, mucinous adenocarcinoma, low-grade mucoepidermoid carcinoma, mucin-rich salivary duct carcinoma and intestinal-type adenocarcinoma. The diagnosis of these tumors is complicated by the dual nature of extracellular mucus: while it is a defining feature of some entities, it can also obscure key diagnostic architectural features in others, leading to histological overlap and inconspicuous diagnostic areas. Given the frequent histological morphological overlap among these tumors, immunohistochemical findings and molecular characteristics have emerged as crucial differential diagnostic criteria. Core differential diagnostic points include the following: histologically, there must be meticulous identification of typical structures obscured by mucin (such as squamoid cells in mucoepidermoid carcinoma and apocrine features in salivary duct carcinoma); in immunohistochemical staining, CK20 is useful for distinguishing intestinal-type adenocarcinoma (positive) from mucinous adenocarcinoma (negative), while androgen receptor aids in differentiating salivary duct carcinoma (positive) from mucoepidermoid carcinoma (negative); and molecular testing plays a critical role in definitive diagnosis (e.g., the AKT1 E17K mutation for mucinous adenocarcinoma, MAML2 rearrangement for mucoepidermoid carcinoma, and MEF2C::SS18 fusion for microsecretory adenocarcinoma). This paper systematically summarizes the core pathological features and differential diagnostic points of mucin-rich salivary gland tumors, aiming to provide a practical reference for clinical pathological diagnosis.

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.

Background: and Purpose In patients with large vessel occlusion (LVO), intravenous thrombolysis (IVT) frequently alters thrombus location; however, the clinical impact of this phenomenon remains unclear. We aimed to compare post-IVT thrombus dynamics between tenecteplase and alteplase and to evaluate the association between thrombus dynamics and 3-month outcomes. Methods: This retrospective study analyzed prospectively collected, multicenter data from consecutive patients with LVO who underwent bridging therapy between January 2022 and December 2024. Thrombus dynamics were classified as resolution, migration, or stability. Analyses incorporated propensity score matching with weighting to balance baseline characteristics. Results: Of the 806 initially included patients, 746 were included after matching (373 treated with tenecteplase and 373 treated with alteplase). The incidence of thrombus migration was significantly higher in the tenecteplase group than in the alteplase group (19.3% vs. 11.3%; odds ratio [OR]: 1.92; 95% confidence interval [CI] 1.27–2.91). The advantage of tenecteplase over alteplase was restricted to patients with an IVT-to-puncture time of <60 minutes (18.6% vs. 6.2%; p=0.001) and was no longer significant when the interval ≥60 minutes (19.7% vs. 15.0%; p=0.204; pinteraction=0.043). Additionally, thrombus migration was associated with a better functional outcome (OR: 1.62; 95% CI 1.04–2.53). Finally, tenecteplase was associated with improved functional independence compared with alteplase (OR: 1.43; 95% CI 1.04–1.95). Conclusions Tenecteplase demonstrated superior efficacy in inducing thrombus migration compared with alteplase, particularly within 60 minutes of IVT administration. Thrombus migration independently predicted improved functional independence. These findings support the preferential use of tenecteplase for bridging therapy in patients with LVO.

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.