Helicobacter pylori disrupts gastric mucosal homeostasis by stimulating macrophages to secrete CCL3.

BACKGROUND: Helicobacter pylori (H. pylori) is the predominant etiological agent of gastritis and disrupts the integrity of the gastric mucosal barrier through various pathogenic mechanisms. After H. pylori invades the gastric mucosa, it interacts with immune cells in the lamina propria. Macrophages are central players in the inflammatory response, and H. pylori stimulates them to secrete a variety of inflammatory factors, leading to the chronic damage of the gastric mucosa. Therefore, the study aims to explore the mechanism of gastric mucosal injury caused by inflammatory factors secreted by macrophages, which may provide a new mechanism for the development of H. pylori-related gastritis. METHODS: The expression and secretion of CCL3 from H. pylori infected macrophages were detected by RT-qPCR, Western blot and ELISA. The effect of H. pylori-infected macrophage culture medium and CCL3 on gastric epithelial cells tight junctions were analyzed by Western blot, immunofluorescence and transepithelial electrical resistance. EdU and apoptotic flow cytometry assays were used to detect cell proliferation and apoptosis levels. Dual-luciferase reporter assays and chromatin immunoprecipitation assays were used to study CCL3 transcription factors. Finally, gastric mucosal tissue inflammation and CCL3 expression were analyzed by hematoxylin and eosin staining and immunohistochemistry. RESULTS: After H. pylori infection, CCL3 expressed and secreted from macrophages were increased. H. pylori-infected macrophage culture medium and CCL3 disrupted gastric epithelial cells tight junctions, while CCL3 neutralizing antibody and receptor inhibitor of CCL3 improved the disruption of tight junctions between cells. In addition, H. pylori-infected macrophage culture medium and CCL3 recombinant proteins stimulated P38 phosphorylation, and P38 phosphorylation inhibitor improved the disruption of tight junctions between cells. Besides, it was identified that STAT1 was a transcription factor of CCL3 and H. pylori stimulated macrophage to secret CCL3 through the JAK1-STAT1 pathway. Finally, after mice were injected with murine CCL3 recombinant protein, the gastric mucosal injury and inflammation were aggravated, and the phosphorylation level of P38 was increased. CONCLUSIONS: In summary, our findings demonstrate that H. pylori infection stimulates macrophages to secrete CCL3 via the JAK1-STAT1 pathway. Subsequently, CCL3 damages gastric epithelial tight junctions through the phosphorylation of P38. This may be a novel mechanism of gastric mucosal injury in H. pylori-associated gastritis.

Feasibility analysis of magnetic resonance imaging-based radiomics features for preoperative prediction of nuclear grading of ductal carcinoma in situ.

Background: The nuclear grading of ductal carcinoma in situ (DCIS) affects its clinical risk. The aim of this study was to investigate the possibility of predicting the nuclear grading of DCIS, by magnetic resonance imaging (MRI)-based radiomics features. And to develop a nomogram combining radiomics features and MRI semantic features to explore the potential role of MRI radiomic features in the assessment of DCIS nuclear grading. Methods: A total of 156 patients (159 lesions) with DCIS and DCIS with microinvasive (DCIS-MI) were enrolled in this retrospective study, with 112 lesions included in the training cohort and 47 lesions included in the validation cohort. Radiomics features were extracted from Dynamic contrast-enhanced MRI (DCE-MRI) phases 1st and 5th. After feature selection, radiomics signature was constructed and radiomics score (Rad-score) was calculated. Multivariate analysis was used to identify MRI semantic features that were significantly associated with DCIS nuclear grading and combined with Rad-score to construct a Nomogram. Receiver operating characteristic curves were used to evaluate the predictive performance of Rad-score and Nomogram, and decision curve analysis (DCA) was used to evaluate the clinical utility. Results: In multivariate analyses of MRI semantic features, larger tumor size and heterogeneous enhancement pattern were significantly associated with high-nuclear grade DCIS (HNG DCIS). In the training cohort, Nomogram had an area under curve (AUC) of 0.879 and Rad-score had an AUC of 0.828. Similarly, in the independent validation cohort, Nomogram had an AUC value of 0.828 and Rad-score had an AUC of 0.772. In both the training and validation cohorts, Nomogram had a significantly higher AUC value than Rad-score (P<0.05). DCA confirmed that Nomogram had a higher net clinical benefit. Conclusions: MRI-based radiomic features can be used as potential biomarkers for assessing nuclear grading of DCIS. The nomogram constructed by radiomic features combined with semantic features is feasible in discriminating non-HNG and HNG DCIS.