Objective To develop and validate a machine learning model based on preoperative clinical characteristics, laboratory indices, and radiological features for the non-invasive prediction of spread through air spaces (STAS) in patients with early-stage lung adenocarcinoma. Methods Preoperative data from patients with early-stage lung adenocarcinoma who underwent surgical resection at Northern Jiangsu People's Hospital between January 2020 and August 2025 were retrospectively collected. The data included clinical characteristics, laboratory indices, and radiological features. Patients were divided into a STAS-positive and a STAS-negative group based on postoperative pathological findings. The dataset was randomly split into a training set and a testing set at a 7 : 3 ratio. Feature variables were selected using the maximum relevance and minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator (LASSO) regression. Five machine learning models were constructed: logistic regression (LR), random forest (RF), support vector machine (SVM), light gradient boosting machine (LightGBM), and extreme gradient boosting (XGBoost). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). The shapley additive explanations (SHAP) method was employed to interpret the optimal prediction model. Results A total of 377 patients were included, comprising 177 (46.9%) males and 200 (53.1%) females, with a mean age of (63.31±9.73) years. There were 261 patients in the training set and 116 patients in the testing set. In the training set, statistically significant differences were observed between the STAS-positive group (n=130) and STAS-negative group (n=131) across multiple features, including age, sex, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), clinical T stage, and maximum solid component diameter (P<0.05). A final set of 10 feature variables was selected by combining mRMR and LASSO regression, and five machine learning models (LR, RF, SVM, LightGBM, XGBoost) were developed. The XGBoost model demonstrated optimal performance in both the training and testing sets, achieving AUCs of 0.947 [95%CI (0.920, 0.975)] and 0.943 [95%CI (0.894, 0.993)], respectively. DCA indicated that the XGBoost model provided a high net clinical benefit across a wide range of threshold probabilities. SHAP analysis revealed that the vessel convergence sign, clinical T stage, age, consolidation-to-tumor ratio (CTR), and MLR were the features with the highest contributions to STAS prediction. Conclusion The XGBoost model effectively predicts preoperative STAS status in early-stage lung adenocarcinoma, exhibiting excellent discriminative performance and good clinical interpretability. Key predictors such as the vessel convergence sign, clinical T stage, age and CTR provide a crucial reference for preoperative risk assessment and the individualized selection of surgical strategies, ultimately benefiting patients.

Objective To explore the mechanism underlying the role of disulfidptosis-related genes(DRGs)in the disease progression of metabolically associated fatty liver disease(MAFLD)based on bioinformatics.Methods In this study,the GEO database was utilized to screen for eligible MAFLD expression data,conduct differential gene analysis,and identify DRGs through consistent clustering to subtype MAFLD patients.The immune infiltration status among subtypes was further evaluated,and the infiltration of immune cells was analyzed using the CIBERSORT algorithm.The gene modules related to the disease were selected through weighted gene co-expression network analysis(WGCNA).Subsequently,a diagnostic model was constructed based on DRGs using machine learning models,and the performance of the model was verified.Finally,the stability of DRGs among different subtypes was evaluated using an external dataset,and the significance of the results was analyzed using statistical tests.Results Through the analysis of the dataset GSE31803,six disulfide death genes,namely,SLC3A2,NCKAP1,CYFIP1,FLNA,MYL6 and MYH10,which were closely related to the clinical characteristics of MAFLD,were screened out.MAFLD patients were classified into two subtypes,with subtype 1 having a higher level of immune cell infiltration.Key gene modules were identified through WGCNA.Through machine learning screening,the support vector machine(SVM)model was determined as the optimal classification model.External validation confirmed the stability and effectiveness of the key genes in different subtypes of MAFLD.Conclusion Based on DRGs,two highly heterogeneous subtypes of MAFLD were identified,which exhibited significant differences in clinical characteristics,biological processes and immune status,indicating that DRGs play a crucial role in the occurrence and development of MAFLD.

Objective To explore the mechanism underlying the role of disulfidptosis-related genes(DRGs)in the disease progression of metabolically associated fatty liver disease(MAFLD)based on bioinformatics.Methods In this study,the GEO database was utilized to screen for eligible MAFLD expression data,conduct differential gene analysis,and identify DRGs through consistent clustering to subtype MAFLD patients.The immune infiltration status among subtypes was further evaluated,and the infiltration of immune cells was analyzed using the CIBERSORT algorithm.The gene modules related to the disease were selected through weighted gene co-expression network analysis(WGCNA).Subsequently,a diagnostic model was constructed based on DRGs using machine learning models,and the performance of the model was verified.Finally,the stability of DRGs among different subtypes was evaluated using an external dataset,and the significance of the results was analyzed using statistical tests.Results Through the analysis of the dataset GSE31803,six disulfide death genes,namely,SLC3A2,NCKAP1,CYFIP1,FLNA,MYL6 and MYH10,which were closely related to the clinical characteristics of MAFLD,were screened out.MAFLD patients were classified into two subtypes,with subtype 1 having a higher level of immune cell infiltration.Key gene modules were identified through WGCNA.Through machine learning screening,the support vector machine(SVM)model was determined as the optimal classification model.External validation confirmed the stability and effectiveness of the key genes in different subtypes of MAFLD.Conclusion Based on DRGs,two highly heterogeneous subtypes of MAFLD were identified,which exhibited significant differences in clinical characteristics,biological processes and immune status,indicating that DRGs play a crucial role in the occurrence and development of MAFLD.

Objective:To explore the genetic basis of a patient suspected for Loeys-Dietz syndrome (LDS).Methods:An adult male patient with aneurysmal dilation of the aortic root identified during the treatment for chronic myeloid leukemia at Anzhen Hospital of Capital Medical University in 2021 was enrolled as the study subject. Clinical data of the patient were retrospectively collected. Peripheral blood samples were collected from the patient and his family members and subjected to whole-exome sequencing (WES). Candidate variant was verified by bioinformatic analysis, with a focus on the genes associated with hereditary aortic aneurysms. Candidate variant was validated by Sanger sequencing. The online SpliceAI software was used for the prediction of protein function. The results, combined with information from public databases, were used to classify the pathogenicity of the candidate variant according to the guidelines from the American College of Medical Genetics and Genomics (ACMG). This study was approved by the Ethics Committee of Beijing Anzhen Hospital (Ethics No. 2023163X).Results:Imaging analysis revealed that the patient had aneurysmal dilation of the aortic root. Based on his clinical features and past history, a provisional diagnosis of LDS was established. WES revealed that the patient had harbored a heterozygous splice site variant c. 206+ 2T>G in the SMAD3 gene (NM_005902). The variant was not reported in public databases and was predicted to be pathogenic by SpliceAI. Sanger sequencing showed that the variant was also present in the patients mother, sister, nephew, and daughter, but not in his father. Based on the guidelines from the ACMG, the variant was classified as likely pathogenic (PVS1+ PM2_Supporting). Conclusion:The heterozygous splice site variant c. 206+ 2T>G of the SMAD3 gene probably underlay the disease of this patient. The discovery has enriched the mutational spectrum of LDS, which may facilitate delineation of the genotype-phenotype correlation and provide a basis for further risk stratification and personalized treatment of LDS.

Objective:To investigate the local hemodynamic spatial distribution of internal carotid artery stenosis and its correlation with plaque characteristics using high-resolution vessel wall imaging (HR-VWI) combined with computational fluid dynamics.Methods:This was a cross-sectional study. A retrospective analysis was conducted on the clinical and imaging data of 70 patients with moderate to severe stenosis at the initiation of the internal carotid artery in First Teaching Hospital of Tianjin University of Traditional Chinese Medicine and Tianjin First Central Hospital from March 2018 to June 2020. All patients underwent HR-VWI and CT angiography examinations. The parameters related to plaque characteristics, such as plaque length, maximum wall thickness, plaque volume, wall volume percentage and intraplaque hemorrhage (IPH) were measured and evaluated on HR-VWI images. CT angiography images were used to construct a local hemodynamic vascular model to measure various wall shear stress (WSS) derived parameters, such as time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and transverse wall shear stress (transWSS), at the narrowest, proximal, and distal parts of the lesion. The Friedman test was used to analyze the difference of hemodynamic parameters in different parts of the lesion. Spearman correlation analysis was performed to assess the correlation between plaque burden and local hemodynamic parameters. Univariate and multivariate logistic regression analyses were used to explore the independent risk factors for predicting IPH.Results:Among the 70 patients, 25 patients with IPH and 45 patients without IPH. The overall differences in TAWSS, OSI, RRT and transWSS at the narrowest, proximal, and distal parts of the lesion in 70 patients were statistically significant ( P<0.05). The TAWSS and transWSS at the narrowest parts were significantly higher than those at the proximal and distal parts ( P<0.05). The OSI at the distal part was significantly higher than that at the narrowest and the proximal parts ( P<0.05). The RRT at the proximal part was significantly lower than that at the narrowest and the distal parts ( P<0.05). Spearman correlation analysis showed RRT at the distal part was correlated with plaque volume ( r s=0.249, P=0.044) and wall volume percentage ( r s=0.286, P=0.016), respectively. In a multivariate logistic regression showed plaque length ( OR=1.315, 95% CI 1.073-1.612, P=0.008) and TAWSS at the narrowest part ( OR=1.631, 95% CI 1.308-1.854, P=0.008) were independent risk factors for predicting IPH. Conclusions:The spatial distribution of local hemodynamics of moderate to severe stenosis at the initiation of the internal carotid artery is different, and the WSS parameters in different parts of the lesion have different effects on plaque volume, wall volume percentage and IPH.

OBJECTIVE: To explore the genetic basis of a patient suspected for Loeys-Dietz syndrome (LDS). METHODS: A adult male patient with aneurysmal dilation of the aortic root identified during the treatment for chronic myeloid leukemia at Anzhen Hospital of Capital Medical University in 2021 was selected as the study subject. Clinical data of the patient were retrospectively collected. Peripheral blood samples were collected from the patient and his family members and subjected to whole-exome sequencing (WES). Candidate variant was verified by bioinformatic analysis, with a focus on the genes associated with hereditary aortic aneurysms. Candidate variant was validated by Sanger sequencing. The online SpliceAI software was used for the prediction of protein function. The results, combined with information from public databases, were used to classify the pathogenicity of the candidate variant according to the guidelines from the American College of Medical Genetics and Genomics (ACMG). This study was approved by the Ethics Committee of Beijing Anzhen Hospital (Ethics No. 2023163X). RESULTS: Imaging analysis revealed that the patient had aneurysmal dilation of the aortic root. Based on his clinical features and past history, a provisional diagnosis of LDS was established. WES revealed that the patient had harbored a heterozygous splice site variant c.206+2T>G in the SMAD3 gene (NM_005902). The variant was not reported in public databases and was predicted to be pathogenic by SpliceAI. Sanger sequencing showed that the variant was also present in the proband's mother, sister, nephew, and daughter, but not in his father. Based on the guidelines from the ACMG, the variant was classified as likely pathogenic (PVS1+PM2_Supporting). CONCLUSION The heterozygous splice site variant c.206+2T>G of the SMAD3 gene probably underlay the disease in this patient. Above discovery has enriched the mutational spectrum of LDS, which may facilitate delineation of the genotype-phenotype correlation and provide a basis for further risk stratification and personalized treatment of LDS.
Adult ; Humans ; Male ; Exome Sequencing ; Loeys-Dietz Syndrome/genetics* ; Mutation ; Pedigree ; Smad3 Protein/genetics*

Objective:To investigate the local hemodynamic spatial distribution of internal carotid artery stenosis and its correlation with plaque characteristics using high-resolution vessel wall imaging (HR-VWI) combined with computational fluid dynamics.Methods:This was a cross-sectional study. A retrospective analysis was conducted on the clinical and imaging data of 70 patients with moderate to severe stenosis at the initiation of the internal carotid artery in First Teaching Hospital of Tianjin University of Traditional Chinese Medicine and Tianjin First Central Hospital from March 2018 to June 2020. All patients underwent HR-VWI and CT angiography examinations. The parameters related to plaque characteristics, such as plaque length, maximum wall thickness, plaque volume, wall volume percentage and intraplaque hemorrhage (IPH) were measured and evaluated on HR-VWI images. CT angiography images were used to construct a local hemodynamic vascular model to measure various wall shear stress (WSS) derived parameters, such as time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and transverse wall shear stress (transWSS), at the narrowest, proximal, and distal parts of the lesion. The Friedman test was used to analyze the difference of hemodynamic parameters in different parts of the lesion. Spearman correlation analysis was performed to assess the correlation between plaque burden and local hemodynamic parameters. Univariate and multivariate logistic regression analyses were used to explore the independent risk factors for predicting IPH.Results:Among the 70 patients, 25 patients with IPH and 45 patients without IPH. The overall differences in TAWSS, OSI, RRT and transWSS at the narrowest, proximal, and distal parts of the lesion in 70 patients were statistically significant ( P<0.05). The TAWSS and transWSS at the narrowest parts were significantly higher than those at the proximal and distal parts ( P<0.05). The OSI at the distal part was significantly higher than that at the narrowest and the proximal parts ( P<0.05). The RRT at the proximal part was significantly lower than that at the narrowest and the distal parts ( P<0.05). Spearman correlation analysis showed RRT at the distal part was correlated with plaque volume ( r s=0.249, P=0.044) and wall volume percentage ( r s=0.286, P=0.016), respectively. In a multivariate logistic regression showed plaque length ( OR=1.315, 95% CI 1.073-1.612, P=0.008) and TAWSS at the narrowest part ( OR=1.631, 95% CI 1.308-1.854, P=0.008) were independent risk factors for predicting IPH. Conclusions:The spatial distribution of local hemodynamics of moderate to severe stenosis at the initiation of the internal carotid artery is different, and the WSS parameters in different parts of the lesion have different effects on plaque volume, wall volume percentage and IPH.

Objective:To explore the genetic basis of a patient suspected for Loeys-Dietz syndrome (LDS).Methods:An adult male patient with aneurysmal dilation of the aortic root identified during the treatment for chronic myeloid leukemia at Anzhen Hospital of Capital Medical University in 2021 was enrolled as the study subject. Clinical data of the patient were retrospectively collected. Peripheral blood samples were collected from the patient and his family members and subjected to whole-exome sequencing (WES). Candidate variant was verified by bioinformatic analysis, with a focus on the genes associated with hereditary aortic aneurysms. Candidate variant was validated by Sanger sequencing. The online SpliceAI software was used for the prediction of protein function. The results, combined with information from public databases, were used to classify the pathogenicity of the candidate variant according to the guidelines from the American College of Medical Genetics and Genomics (ACMG). This study was approved by the Ethics Committee of Beijing Anzhen Hospital (Ethics No. 2023163X).Results:Imaging analysis revealed that the patient had aneurysmal dilation of the aortic root. Based on his clinical features and past history, a provisional diagnosis of LDS was established. WES revealed that the patient had harbored a heterozygous splice site variant c. 206+ 2T>G in the SMAD3 gene (NM_005902). The variant was not reported in public databases and was predicted to be pathogenic by SpliceAI. Sanger sequencing showed that the variant was also present in the patients mother, sister, nephew, and daughter, but not in his father. Based on the guidelines from the ACMG, the variant was classified as likely pathogenic (PVS1+ PM2_Supporting). Conclusion:The heterozygous splice site variant c. 206+ 2T>G of the SMAD3 gene probably underlay the disease of this patient. The discovery has enriched the mutational spectrum of LDS, which may facilitate delineation of the genotype-phenotype correlation and provide a basis for further risk stratification and personalized treatment of LDS.

OBJECTIVES: Acute lung injury (ALI) is an acute respiratory failure syndrome characterized by impaired gas exchange. Due to the lack of effective targeted drugs, it is associated with high mortality and poor prognosis. Tripterygium wilfordii (TW) has demonstrated anti-inflammatory activity in the treatment of various diseases. This study aims to investigate the effects and underlying mechanisms of TW on myeloid-derived suppressor cells (MDSCs) in ALI, providing experimental evidence for TW as a potential adjuvant therapy for ALI. METHODS: Eighteen specific pathogen-free (SPF) C57BL/6 mice were randomly divided into normal control (NC; intranasal saline), lipopolysaccharide (LPS; 5 mg/kg intranasally to induce ALI), and LPS+TW (50 mg/kg TW by gavage on the first day of modeling, followed by 5 mg/kg LPS intranasally to induce ALI) groups (n=6 each). Lung injury and edema were assessed by histopathological scoring and wet-to-dry weight ratio. Cytokine levels [interleukin (IL)-1β, IL-6, IL-18, tumor necrosis factor-α (TNF-α)] in lung tissue lavage fluid were measured by enzyme-linked immunosorbent assay (ELISA). Flow cytometry was used to assess the proportions of MDSCs, polymorphonuclear MDSCs (PMN-MDSCs), and monocytic MDSCs (M-MDSCs) in bone marrow, spleen, peripheral blood, and lung tissue, as well as reactive oxygen species (ROS) levels in lung tissues. Messenger RNA (mRNA) expression levels of inducible nitric oxide synthase (iNOS) and arginase-1 (ARG-1) in lung tissues were determined by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). PMN-MDSCs sorted from the lungs of LPS-treated mice were co-cultured with splenic CD3⁺ T cells and divided into NC, triptolide (TPL)-L, and TPL-H groups, with bovine serum albumin, 25 nmol/L TPL, and 50 nmol/L TPL, respectively. Flow cytometry was used to detect the effect of PMN-MDSCs on T-cell proliferation, and RT-qPCR was used to measure iNOS and ARG-1 mRNA expression. RESULTS: Compared with the NC group, the LPS group showed marked lung pathology with significantly increased histopathological scores and wet-to-dry ratios (both P<0.001). TW treatment significantly alleviated lung injury and reduced both indices compared with the LPS group (both P<0.05). Cytokine levels were significantly decreased in the LPS+TW group compared with the LPS group (all P<0.001). The proportions of MDSCs in CD45⁺ cells from spleen, bone marrow, peripheral blood, and lung, as well as PMN-MDSCs from spleen, peripheral blood, and lung, were significantly reduced in the LPS+TW group compared with the LPS group (all P<0.05), accompanied by reduced ROS levels in lung tissues (P<0.001). iNOS and ARG-1 mRNA expression in lung tissues was significantly lower in the LPS+TW group than in the LPS group (both P<0.001). In vitro, compared with the TPL-L group, the TPL-H group showed significantly increased CD3⁺ T-cell proliferation (P<0.001), and decreased iNOS and ARG-1 mRNA expression (all P<0.05). CONCLUSIONS TW alleviates the progression of LPS-induced ALI in mice, potentially by reducing the proportion of MDSCs in lung tissues and attenuating the immunosuppressive function of PMN-MDSCs.
Animals ; Acute Lung Injury/chemically induced* ; Myeloid-Derived Suppressor Cells/cytology* ; Tripterygium/chemistry* ; Mice, Inbred C57BL ; Mice ; Cell Differentiation/drug effects* ; Male ; Lipopolysaccharides ; Nitric Oxide Synthase Type II/genetics* ; Cytokines/metabolism* ; Reactive Oxygen Species/metabolism* ; Diterpenes/pharmacology* ; Epoxy Compounds ; Phenanthrenes