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.

Abstract To understand the impact of negative behavior patterns on the physical and psychological health of secondary vocational school students, the study systematically reviews the multidimensional and co-occurring characteristics of behavioral risk aggregation with physical and psychological health problems among secondary vocational school students, analyzes the intertwined influence of new and traditional behavioral risk factors, and explores a comprehensive intervention framework centered on multidimensional rhythm reshaping and individual-family-school-society multi level intervention pathways, providing theoretical reference for promoting the health of secondary vocational school students.

Objective: To investigate the association of special family structure and physical activity with psychological sub health among secondary vocational school students, so as to provide reference to inform mental health promotion in the population. Methods: From September to December 2024, a convenience sample was drawn from 16 schools including 5 141 secondary vocational school students across 8 provinces (municipalities) in China (Fujian, Chongqing, Guangdong, Guangxi, Hubei, Jiangxi, Shanghai, Zhejiang). A self developed questionnaire, Multidimensional Sub health Questionnaire of Adolescents and International Physical Activity Questionnaire Short Form were used to investigate and evaluate basic information, family structure, psychological sub health status and physical activity. Descriptive statistics and Logistic regression analysis were performed to explore relationships of special family structures and physical activity with psychological sub health in secondary vocational school students. Results: The detection rate of psychological sub health among secondary vocational school students was 11.0%. The reporting rates for secondary vocational school students who lost their father or lost their mother, whose parents divorced, whose parents remarried, and those from special family structures were 2.8%, 0.8%, 11.8%, 3.9%, and 14.7%, respectively. Moreover, the detection rates of psychological sub health and its sub dimensions significantly differed among secondary vocational school students grouped by family type (divorced parental families, remarried parental families and special family structures)( χ 2=5.90-22.67, all P <0.05). Binary Logistic regression indicated that maternal bereavement was associated with a higher risk of conduct problems [ AOR ( 95% CI )= 2.90(1.15-7.33)], and parental divorce was associated with a higher risk of psychological sub health ( AOR= 2.71 , 95%CI =1.04- 7.06 ) among secondary vocational school students (both P <0.05). Interaction analysis showed that both students with a special family structure and insufficient physical activity [ AOR (95% CI )=1.99(1.44-2.75)] and those with a non-special family structure and insufficient physical activity [ AOR (95% CI )=1.81(1.48-2.22)] were associated with increased risks of psychological sub health among secondary vocational school students (both P <0.01). Conclusion Special family structure and physical activity are associated with psychological sub health among secondary vocational school students; early identification and assessment based interventions for those with a special family structure should be strengthened, while school based physical activity should be implemented to increase physical activity levels,thereby reducing the risk of psychological sub health.

Objective: To understand the current status of psychological sub health among secondary vocational school students and explore its related factors, so as to provide a scientific basis for improving their mental health. Methods: From September to December 2024, a convenience sampling method was used to conduct a questionnaire survey among 5 141 secondary vocational school students from 16 schools across 8 provinces and municipalities (Fujian, Chongqing, Guangdong, Guangxi, Hubei, Jiangxi, Shanghai, Zhejiang). A self designed questionnaire was used to collect data on students demographic characteristics and lifestyle behaviors. The Multidimensional Sub health Questionnaire of Adolescents was adopted to assess psychological sub health status. Multivariate binary Logistic stepwise regression analysis was performed to explore the related factors of psychological sub health among secondary vocational school students. Results: The detection rate of psychological sub health among secondary vocational school students was 11.0%, with detection rates of emotional problems, conduct problems, and social adaptation difficulty being 12.3 %, 12.5%, and 9.5%, respectively. Logistic regression analysis revealed that boys and students whose fathers had an educational level of primary school or below, and junior high school, had relatively lower risks of developing psychological sub health or emotional problems, conduct problems, and social adaptation difficulty ( OR =0.55-0.64, all P <0.05). Conversely, students with urban household registration, those with left behind experience, those with poor self rated family economic status, those from other family structures, those classified as overweight and obesity, and those with sleep disorders, frequent consumption of sugar sweetened beverages, frequent consumption of takeout/delivery food, smoking, alcohol consumption, and low to moderate physical activity levels exhibited significantly higher risks across psychological sub health or emotional problems,conduct problems, and social adaptation difficulty ( OR =1.25-4.79, all P <0.05). Conclusions The psychological sub health condition of secondary vocational school students should not be neglected. Psychological sub health of secondary vocational school students is related to multiple factors such as demographic characteristics and lifestyle behaviors. Multi dimensional intervention measures should be implemented to improve their mental health.

Background: This study was performed to characterize the incidence, costs, and risk factors associated with renal and cardiovascular adverse outcomes following primary percutaneous coronary intervention (pPCI) in patients with ST-elevation myocardial infarction (STEMI). Methods: Patients with STEMI who underwent pPCI using iso-osmolar contrast were enrolled at 39 centers. The incidence of acute kidney injury (AKI) and major adverse renal and cardiovascular events (MARCE) was analyzed, as well as inpatient costs. Logistic regression analysis was performed to identify risk factors. Results: Among 2,293 patients, the incidence of AKI and MARCE within 72 hours post-pPCI was 4.14% (n = 95) and 4.40% (n = 101), respectively. AKI and/or MARCE were associated with systolic blood pressure (AKI: odds ratio [OR], 1.009; 95% confidence interval [CI], 1.000–1.018), hypertension (AKI: OR, 1.815; 95% CI, 1.133–2.906; MARCE: OR, 1.760;95% CI, 1.118–2.769), anterior wall infarction (AKI: OR, 1.895; 95% CI, 1.196–3.004; MARCE:OR, 1.939; 95% CI, 1.240–3.032), Killip class (AKI: OR, 1.465; 95% CI, 1.117–1.922; MARCE:OR, 1.467; 95% CI, 1.131–1.903), and serum creatinine (SCr; MARCE: OR, 1.006; 95% CI, 1.000–1.012). Hospitalization costs for patients with STEMI who developed AKI or MARCE were significantly higher than for those without AKI (9,595 ± 5,795 vs. 8,279 ± 3,872 USD, P = 0.003) or without MARCE (9,890 ± 5,616 vs. 8,255 ± 3,859 USD, P < 0.001). Conclusions In patients with STEMI undergoing pPCI with iso-osmolar contrast, the incidence of AKI and MARCE was associated with higher hospitalization costs. Systolic blood pressure, hypertension, anterior wall infarction, Killip class, and SCr were identified as risk factors for these outcomes.

To summarize the clinical characteristics, antibody spectrum and neuroelectrophysiological features of autoimmune nodopathy(AN), and to explore the phenotypic differences among different antibody-positive subgroups.

ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

ObjectiveChronic atrophic gastritis (CAG) is usually diagnosed by gastroscopy and histopathological biopsy. These procedures remain the reference standard, but their invasive nature and resource requirements may limit their use in large-scale population screening and repeated follow-up. A convenient and reproducible method for noninvasive auxiliary screening may help identify individuals who require further endoscopic assessment. Fingertip photoplethysmography (PPG) provides a noninvasive recording of peripheral pulse waves and allows harmonic features to be extracted from the signal. In this study, the so-called meridian-related variables were defined as PPG-derived harmonic parameters labelled according to meridian nomenclature, rather than as direct measurements of meridian physiology. This study aimed to compare these harmonic parameters between patients with CAG and non-CAG controls, identify parameters that remained different after age adjustment, and develop a multivariable model for noninvasive auxiliary screening and pre-endoscopic risk stratification of CAG. MethodsA total of 343 participants were included, comprising 171 patients with CAG and 172 non-CAG controls. CAG diagnosis was established using gastroscopy and histopathology as the reference standard. Fingertip PPG signals were collected using a PPG-based pulse acquisition device. Eight PPG-derived harmonic parameters labelled according to meridian nomenclature were extracted for analysis. Between-group differences were first assessed using nonparametric tests. Age-adjusted analyses were then performed to reduce potential confounding by age. The false discovery rate (FDR) method was applied for multiple-comparison correction. A multivariable logistic regression model integrating age and multiple harmonic parameters was constructed. Model performance was evaluated using receiver operating characteristic (ROC) analysis and the area under the curve (AUC). Internal validation performance was assessed using stratified five-fold cross-validation and bootstrap optimism correction. Threshold performance was examined using both a high-specificity strategy and a Youden index-based cutoff. Decision curve analysis was used to evaluate the model’s net clinical benefit across a range of threshold probabilities. ResultsAll eight harmonic parameters were non-normally distributed. In the univariate analysis, the stomach-labelled harmonic parameter (ST), bladder-labelled harmonic parameter (BL), and liver-labelled harmonic parameter (LR) differed between the CAG and non-CAG groups. After age adjustment and FDR correction, only ST and BL remained statistically significant. Compared with non-CAG controls, patients with CAG showed higher ST values and lower BL values. This finding indicates an associated differential harmonic pattern that was not fully explained by age distribution. However, the discriminative ability of a single harmonic parameter was limited. The best-performing single indicator was ST, with an AUC of 0.652 (95% CI: 0.595-0.707). The multivariable model integrating age and multiple harmonic parameters achieved an AUC of 0.791 (95% CI: 0.743-0.835), representing an improvement of 0.139 over ST alone. In internal validation, stratified five-fold cross-validation yielded a mean AUC of 0.753 (95% CI: 0.715-0.781), and the bootstrap optimism-corrected AUC was 0.748. These results suggest that the model retained moderate discriminative performance after internal validation.At a specificity of at least 95%, the model achieved a sensitivity of only 40.4% (95% CI: 25.7%-49.7%). This high-specificity cutoff may be suboptimal as the preferred threshold for an initial screening setting because of the potential risk of missed CAG cases. The Youden index-based optimal cutoff was 0.419, corresponding to a sensitivity of 80.7% and a specificity of 62.8%. This threshold may better match the practical aim of noninvasive auxiliary screening, where sensitivity is usually prioritized to reduce missed cases. Decision curve analysis showed that, within a threshold probability range of 10%-55%, the model provided higher net clinical benefit than the reference strategies of recommending gastroscopy for all participants or for none. ConclusionPatients with CAG showed associated harmonic differences in fingertip PPG-derived features, mainly characterized by higher ST and lower BL values after age adjustment and FDR correction. Compared with a single harmonic parameter, the multivariable model showed better overall discrimination and retained moderate internal validation performance. These findings suggest that PPG-derived harmonic parameters labelled according to meridian nomenclature may provide auxiliary information for noninvasive auxiliary screening and front-line triage before gastroscopic confirmation in CAG. The present results support further validation rather than immediate clinical implementation. External validation in independent, multicenter, and preferably prospective screening cohorts is needed to assess the model’s generalizability, screening performance, and potential clinical utility.

The technology of xenogeneic organ transplantation, as one of the core strategies to address the current contradiction between the supply and demand of transplant organs, has achieved significant breakthroughs from basic research to clinical application driven by factors such as the innovation of gene modification technology, the injection of research capital and the expansion of clinical trials, especially with the first actual clinical application of a pig heart-to-human transplant. China is also at the forefront of this field. This article intends to summarize the international research trends of xenogeneic organ transplantation (including financial support, the evolution of research stages and global clinical trial cases), and analyze the evolution and optimization of xenogeneic transplantation immunosuppression schemes, as well as the breakthroughs and unresolved scientific issues in current key clinical application technologies. The aim is to comprehensively present the progress of this field from basic research to clinical transformation, and provide references for promoting the rapid development of China's xenogeneic transplantation technology and subsequent clinical transformation and research directions.

Objective To systematically review the studies on predictive models for delayed graft function (DGF) after kidney transplantation. Methods Databases including China Biology Medicine Database, China National Knowledge Infrastructure, Wanfang Database, VIP Database, PubMed, Web of Science and CINAHL were searched to collect studies on predictive models for DGF after kidney transplantation published from the establishment of each database to June 29, 2025. Two researchers screened the literatures according to the inclusion and exclusion criteria, evaluated the quality of the literatures using the prediction model risk of bias assessment tool (PROBAST), and conducted a meta-analysis of the common predictors of the models using R software. Results A total of 12 literatures were included, involving 14 predictive models with sample sizes ranging from 103 to 24 653 cases. Donor serum creatinine level, cold ischemia time, donor age and donor body mass index were the top four common predictors. All the predictive models were at high risk of bias and low in applicability. The results of meta-analysis showed that abnormal donor body mass index, advanced donor age, prolonged cold ischemia time and elevated donor serum creatinine level were all associated with an increased risk of DGF after transplantation (all P<0.01), but there was high heterogeneity among the studies. Fixed-effect model and random-effect model were used to re-pool the effect sizes separately. The results indicated that the fixed-effect model and random-effect model had good consistency in terms of donor body mass index, donor age and cold ischemia time, while there was a significant difference in the effect sizes of the two models for donor serum creatinine level. Conclusions The predictive models for DGF risk after kidney transplantation have good predictive performance, but the overall risk of bias is high. In the future, large-sample, multicenter and high-quality prospective clinical studies should be carried out to optimize the predictive models, so as to improve their predictive ability and clinical application value.