Objective To explore whether there is a causal relationship between intestinal flora and esophageal cancer. Methods Summary statistics of intestinal flora and esophageal cancer were obtained from the Genome-wide Association Studies (GWAS) database. Five methods, including inverse variance weighted (IVW), weighted median estimation, Mendelian randomization (MR)-Egger regression, single mode, and weighted mode, were used for analysis, with IVW as the main analysis method. Sensitivity analysis was used to evaluate the reliability of MR results. Results In the IVW method, Oxalobacteraceae [OR=1.001, 95%CI (1.000, 1.002), P=0.023], Faecalibacterium [OR=1.001, 95%CI (1.000, 1.002), P=0.028], Senegalimassilia [OR=1.002, 95%CI (1.000, 1.003), P=0.006] and Veillonella [OR=1.001, 95%CI (1.000, 1.002), P=0.018] were positively correlated with esophageal cancer, while Burkholderiales [OR=0.999, 95%CI (0.998, 1.000), P=0.002], Eubacterium oxidoreducens [OR=0.998, 95%CI (0.997, 0.999), P=0.038], Romboutsia [OR=0.999, 95%CI (0.998, 1.000), P=0.048] and Turicibacter [OR=0.998, 95%CI (0.997, 0.999), P=0.013] were negatively correlated with esophageal cancer. Sensitivity analysis showed no evidence of heterogeneity, horizontal pleiotropy and reverse causality. Conclusion Oxalobacteraceae, Faecalibacterium, Senegalimassilia and Veillonella increase the risk of esophageal cancer, while Burkholderiales, Eubacterium oxidoreducens, Romboutsia and Turicibacter decrease the risk of esophageal cancer. Further studies are needed to explore how these bacteria affect the progression of esophageal cancer.

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 role of DNAJC5B in immunotherapy for esophageal squamous cell carcinoma (ESCC). Methods Using the ESCC dataset from The Cancer Genome Atlas (TCGA) database, genes correlated with DNAJC5B expression were identified through Pearson correlation analysis. Subsequently, Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Additionally, single-cell RNA sequencing (scRNA-seq) data were utilized to analyze the expression of DNAJC5B in different T-cell subsets. The prognostic value of DNAJC5B was evaluated using Kaplan-Meier survival curves, receiver operating characteristic curves, and Cox proportional hazards models. Results DNAJC5B was highly expressed in patients with advanced-stage ESCC, particularly in males. GO and KEGG analyses revealed a significant correlation between DNAJC5B expression and immune-related processes, such as the adaptive immune response and cell surface receptor signaling pathways. Single-cell analysis results indicated that DNAJC5B expression was positively correlated with immune function, with DNAJC5B predominantly accumulating in CD8+ T cells. Kaplan-Meier survival curves showed that the median survival time for patients with high DNAJC5B expression was 681 days, significantly shorter than the 1 361 days for patients with low expression (P<0.05). Furthermore, univariate and multivariate independent prognostic analyses demonstrated that DNAJC5B was an independent risk factor, with hazard ratios (HRs) of 3.577 and 4.114, respectively (both P<0.05). Conclusion DNAJC5B may play a crucial immunomodulatory role in ESCC, particularly in regulating CD8+ T-cell function and tumor immune escape. These findings support the potential of DNAJC5B as a biomarker for the treatment and prognostic assessment of ESCC.

Objective To analyze the relationship between neuroticism and gastroesophageal reflux disease (GERD) using the Mendelian randomization (MR) method. Methods Exposure and outcome data were downloaded from the Integrative Epidemiology Unit (IEU) database in August 2023, including summary statistics from genome-wide association studies (GWAS) for neuroticism (n=374 323) and GERD (n=602 604). MR was conducted using the weighted median method, MR-Egger method, inverse variance weighted method, weighted mode method, and simple mode method. The causal relationship between the two was assessed using odds ratio (OR), and sensitivity analyses were performed to ensure the accuracy of the results. Results Neuroticism was associated with an increased risk of GERD [OR=1.229, 95%CI (1.186, 1.274), P<0.001]. Similarly, GERD was associated with an increased risk of neuroticism [OR=1.786, 95%CI (1.623, 1.965), P<0.001]. Conclusion There is a bidirectional causal relationship between neuroticism and gastroesophageal reflux disease.

Chronic obstructive pulmonary disease (COPD), which predominantly affects middle-aged and elderly individuals, is associated with a significantly reduced quality of life and often triggers various other pulmonary conditions. Lung cancer, as one of the most prevalent and deadly pulmonary malignancies worldwide, poses a severe threat to global public health. The risk of developing lung cancer is markedly higher in COPD patients compared to the general population, indicating numerous associations between the two conditions that warrant in-depth investigation. Although a substantial body of research has explored the relationship between COPD and lung cancer, studies focusing on the molecular mechanisms underlying their connection remain limited. This article reviews the latest research progress on the mechanisms of COPD complicated by lung cancer from four perspectives: the role of chronic pulmonary inflammation, programmed cell death, genetic and molecular interactions, and dysbiosis of the pulmonary microbiome. The aim of this article is to provide new insights and references for the prevention and therapeutic strategies of COPD complicated with lung cancer.

Objective To identify causal effects and potential mechanisms of oxidative stress (OS)-related genes in lung cancer. Methods OS-related genes were extracted from the GeneCards database. Integration analysis of genome-wide association study (GWAS) data for lung cancer with gene expression and DNA methylation quantitative trait locus (QTL), including eQTL and mQTL in blood was performed using the summary data-based Mendelian randomization (SMR) approach to determine the causal relationship between OS-related genes and lung cancer risk. Colocalization analysis of OS-related gene QTL and lung cancer risk locus was performed to gain insight into the potential regulatory mechanisms of lung cancer risk. Results A total of 1 188 OS-related genes were obtained from the GeneCards database. A potential causal relationship between OS-related genes and lung cancer was identified by SMR analysis. AGER expression level [OR=1.944, 95%CI (1.431, 2.640), P<0.001], and ATF6B expression level [OR=1.508, 95%CI (1.287, 1.767), P<0.001] were associated with lung cancer risk. Meanwhile, ATF6B methylation level was also associated with lung cancer risk. Conclusion OS-related genes are associated with lung cancer, which may be a potential target of anti-cancer drugs.

Objective:To explore the high-risk factors affecting the severity of neonatal necrotizing enterocolitis (NEC).Methods:This study involved 153 NEC patients admitted to the Neonatology Department of the Children's Hospital of Soochow University from January 1, 2017, to December 30, 2023. Based on the severity of NEC determined by Bell's criteria, these patients were divided into two groups: mild group (Bell stage Ⅱ, n=70) and severe group (Bell stage Ⅲ, n=83). Clinical data including general conditions, clinical treatment and disease status before the onset of NEC, laboratory test results, and perinatal conditions of the mothers were retrospectively collected. Univariate analysis (rank-sum test and Chi-square test) and multivariate analysis (logistic regression analysis) were used to explore the risk factors affecting the severity of NEC. Results:The proportion of infants with gestational age<37 weeks or birth weight<1 500 g, the rate of antibiotic usage, sepsis or shock were higher in the severe group than in the mild group [91.6% (76/83) vs. 75.7% (53/70); 55.4% (46/83) vs. 34.3% (24/70); 85.5% (71/83) vs. 71.4% (50/70); 55.4% (46/83) vs. 17.1% (12/70); 30.1% (25/83) vs. 8.6% (6/70); with χ 2 values of 7.22, 6.84, 4.57, 23.64, and 10.91, respectively, all P<0.05]. Furthermore, the severe group had a late initiation of breastfeeding and longer durations of peripherally inserted central catheter (PICC) placement and parenteral nutrition [2.00 d (1.00-2.00 d) vs. 1.00 d (1.00-2.00 d); 0.00 d (0.00-18.00 d) vs. 0.00 d (0.00-7.50 d); 14.00 d (5.00-21.00 d) vs. 10.50 d (0.00-18.25 d), with Z values of -2.90, -1.98, and -2.09, respectively, all P<0.05]. (2) Within 48 h before the onset, the severe group had higher proportions of infants with decreased white blood cell count, decreased platelet count, electrolyte imbalance, and metabolic acidosis than the mild group [53.0% (44/83) vs. 14.3% (10/70); 49.4% (41/83) vs. 10.0% (7/70); 38.6% (32/83) vs. 14.3% (10/70); 37.3% (31/83) vs. 14.3% (10/70), with χ2 values of 24.94, 27.38, 11.23, and 10.30, respectively, all P<0.05]. Besides, the levels of procalcitonin and C-reactive protein were higher in the severe group than in the mild group [2.31 ng/ml (0.26-11.71 ng/ml) vs. 0.22 ng/ml (0.00-2.19 ng/ml); 58.50 mg/L (14.34-125.25 mg/L) vs. 8.20 mg/L (0.23-34.56 mg/L), with Z values of -3.88 and -5.02, respectively, both P<0.05]. (3) Multivariate logistic regression analysis showed that prolonged duration of PICC placement, decreased platelet count, electrolyte imbalance, metabolic acidosis, and concurrent sepsis were independent risk factors affecting the severity of NEC [ OR (95% CI) values were 1.104 (1.020-1.196), 5.364 (1.667-17.253), 4.047 (1.171-13.986), 4.333 (1.290-14.556), and 3.290 (1.005-10.774), respectively, with all P<0.05]. Conclusions:Prolonged duration of PICC placement, concurrent sepsis, decreased platelet count, electrolyte imbalance, and metabolic acidosis in NEC patients are more likely to lead to severe cases. In clinical practice, attention should be paid to relevant indicators, and abnormal changes should be identified and intervened in a timely manner to reduce the occurrence of severe NEC.

Objective:To explore the high-risk factors affecting the severity of neonatal necrotizing enterocolitis (NEC).Methods:This study involved 153 NEC patients admitted to the Neonatology Department of the Children's Hospital of Soochow University from January 1, 2017, to December 30, 2023. Based on the severity of NEC determined by Bell's criteria, these patients were divided into two groups: mild group (Bell stage Ⅱ, n=70) and severe group (Bell stage Ⅲ, n=83). Clinical data including general conditions, clinical treatment and disease status before the onset of NEC, laboratory test results, and perinatal conditions of the mothers were retrospectively collected. Univariate analysis (rank-sum test and Chi-square test) and multivariate analysis (logistic regression analysis) were used to explore the risk factors affecting the severity of NEC. Results:The proportion of infants with gestational age<37 weeks or birth weight<1 500 g, the rate of antibiotic usage, sepsis or shock were higher in the severe group than in the mild group [91.6% (76/83) vs. 75.7% (53/70); 55.4% (46/83) vs. 34.3% (24/70); 85.5% (71/83) vs. 71.4% (50/70); 55.4% (46/83) vs. 17.1% (12/70); 30.1% (25/83) vs. 8.6% (6/70); with χ 2 values of 7.22, 6.84, 4.57, 23.64, and 10.91, respectively, all P<0.05]. Furthermore, the severe group had a late initiation of breastfeeding and longer durations of peripherally inserted central catheter (PICC) placement and parenteral nutrition [2.00 d (1.00-2.00 d) vs. 1.00 d (1.00-2.00 d); 0.00 d (0.00-18.00 d) vs. 0.00 d (0.00-7.50 d); 14.00 d (5.00-21.00 d) vs. 10.50 d (0.00-18.25 d), with Z values of -2.90, -1.98, and -2.09, respectively, all P<0.05]. (2) Within 48 h before the onset, the severe group had higher proportions of infants with decreased white blood cell count, decreased platelet count, electrolyte imbalance, and metabolic acidosis than the mild group [53.0% (44/83) vs. 14.3% (10/70); 49.4% (41/83) vs. 10.0% (7/70); 38.6% (32/83) vs. 14.3% (10/70); 37.3% (31/83) vs. 14.3% (10/70), with χ2 values of 24.94, 27.38, 11.23, and 10.30, respectively, all P<0.05]. Besides, the levels of procalcitonin and C-reactive protein were higher in the severe group than in the mild group [2.31 ng/ml (0.26-11.71 ng/ml) vs. 0.22 ng/ml (0.00-2.19 ng/ml); 58.50 mg/L (14.34-125.25 mg/L) vs. 8.20 mg/L (0.23-34.56 mg/L), with Z values of -3.88 and -5.02, respectively, both P<0.05]. (3) Multivariate logistic regression analysis showed that prolonged duration of PICC placement, decreased platelet count, electrolyte imbalance, metabolic acidosis, and concurrent sepsis were independent risk factors affecting the severity of NEC [ OR (95% CI) values were 1.104 (1.020-1.196), 5.364 (1.667-17.253), 4.047 (1.171-13.986), 4.333 (1.290-14.556), and 3.290 (1.005-10.774), respectively, with all P<0.05]. Conclusions:Prolonged duration of PICC placement, concurrent sepsis, decreased platelet count, electrolyte imbalance, and metabolic acidosis in NEC patients are more likely to lead to severe cases. In clinical practice, attention should be paid to relevant indicators, and abnormal changes should be identified and intervened in a timely manner to reduce the occurrence of severe NEC.

Objective     To investigate the accuracy of 18F-FDG positron emission tomography/computed tomography (PET/CT) combined with CT three-dimensional reconstruction (CT-3D) in the differential diagnosis of benign and malignant pulmonary nodules. Methods     The clinical data of patients who underwent pulmonary nodule surgery in the Department of Thoracic Surgery, Northern Jiangsu People's Hospital from July 2020 to August 2021 were retrospectively analyzed. The preoperative 18F-FDG PET/CT and chest enhanced CT-3D and other imaging data were extracted. The parameters with diagnostic significance were screened by the area under the receiver operating characteristic (ROC) curve (AUC). Three prediction models, including PET/CT prediction model (MOD PET), CT-3D prediction model (MOD CT-3D), and PET/CT combined CT-3D prediction model (MOD combination), were established through binary logistic regression, and the diagnostic performance of the models were validated by ROC curve. Results     A total of 125 patients were enrolled, including 57 males and 68 females, with an average age of 61.16±8.57 years. There were 46 patients with benign nodules, and 79 patients with malignant nodules. A total of 2 PET/CT parameters and 5 CT-3D parameters were extracted. Two PET/CT parameters, SUVmax≥1.5 (AUC=0.688) and abnormal uptake of hilar/mediastinal lymph node metabolism (AUC=0.671), were included in the regression model. Among the CT-3D parameters, CT value histogram peaks (AUC=0.694) and CT-3D morphology (AUC=0.652) were included in the regression model. Finally, the AUC of the MOD PET was verified to be 0.738 [95%CI (0.651, 0.824)], the sensitivity was 74.7%, and the specificity was 60.9%; the AUC of the MOD CT-3D was 0.762 [95%CI (0.677, 0.848)], the sensitivity was 51.9%, and the specificity was 87.0%; the AUC of the MOD combination was 0.857 [95%CI (0.789, 0.925)], the sensitivity was 77.2%, the specificity was 82.6%, and the differences were statistically significant (P<0.001). Conclusion     18F-FDG PET/CT combined with CT-3D can improve the diagnostic performance of pulmonary nodules, and its specificity and sensitivity are better than those of single imaging diagnosis method. The combined prediction model is of great significance for the selection of surgical timing and surgical methods for pulmonary nodules, and provides a theoretical basis for the application of artificial intelligence in the pulmonary nodule diagnosis.

Objective To develop a radiomics nomogram based on contrast-enhanced CT (CECT) for preoperative prediction of high-risk and low-risk thymomas. Methods Clinical data of patients with thymoma who underwent surgical resection and pathological confirmation at Northern Jiangsu People's Hospital from January 2018 to February 2023 were retrospectively analyzed. Feature selection was performed using the Pearson correlation coefficient and least absolute shrinkage and selection operator (LASSO) method. An ExtraTrees classifier was used to construct the radiomics signature model and the radiomics signature. Univariate and multivariable logistic regression was applied to analyze clinical-radiological characteristics and identify variables for developing a clinical model. The radiomics nomogram model was developed by combining the radiomics signature and clinical features. Model performance was evaluated using area under the curve (AUC), sensitivity, specificity, accuracy, negative predictive value, and positive predictive value. Calibration curves and decision curves were plotted to assess model accuracy and clinical values. Results A total of 120 patients including 59 females and 61 males with an average age of 56.30±12.10 years. There were 84 patients in the training group and 36 in the validation group, 62 in the low-risk thymoma group and 58 in the high-risk thymoma group. Radiomics features (1 038 in total) were extracted from the arterial phase of CECT scans, among which 6 radiomics features were used to construct the radiomics signature. The radiomics nomogram model, combining clinical-radiological characteristics and the radiomics signature, achieved an AUC of 0.872 in the training group and 0.833 in the validation group. Decision curve analysis demonstrated better clinical efficacy of the radiomics nomogram than the radiomics signature and clinical model. Conclusion The radiomics nomogram based on CECT showed good diagnostic value in distinguishing high-risk and low-risk thymoma, which may provide a noninvasive and efficient method for clinical decision-making.