Shock : molecular, cellular, and systemic pathobiological aspects and therapeutic approaches : the official journal the Shock Society, the European Shock Society, the Brazilian Shock Society, the International Federation of Shock Societies
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Purpose: This study aims to establish and validate machine learning-based models to predict death in hospital among critical orthopaedic trauma patients with sepsis or respiratory failure. Methods: This study collected 523 patients from the Medical Information Mart for Intensive Care database. All patients were randomly classified into a training cohort and a validation cohort. ⋯ However, the eXGBM model consistently outperformed the RF model across multiple evaluation metrics, establishing itself as the superior option for predictive modeling in this scenario, with the RF model as a strong secondary choice. The SHAP analysis revealed that SAPS II, age, respiratory rate, OASIS, and temperature were the most important five features contributing to the outcome. Conclusions: This study develops an artificial intelligence application to predict in-hospital mortality among critical orthopaedic trauma patients with sepsis or respiratory failure.
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Sepsis induces intestinal hyperpermeability, which is associated with higher mortality. Occludin is a tight junction protein that plays a critical role in regulating disease-associated intestinal barrier loss. This study examined the role of intestinal occludin on gut barrier function and survival in a pre-clinical model of sepsis. ⋯ Notably, 7-day mortality was significantly higher in occludin KOIEC mice following sepsis. Occludin thus plays a critical role in preserving gut barrier function and mediating survival during sepsis, associated with alterations in inflammation and bacteremia. Agents that preserve occludin function may represent a new therapeutic strategy in the treatment of sepsis.
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Background: Sepsis-induced cardiomyopathy (SIC), one of the most common complications of sepsis, seriously affects the prognosis of critically ill patients. Choline metabolism is an important biological process in the organism, and the mechanism of its interaction with SIC is unclear. The aim of this study was to reveal the choline metabolism genes (CMGs) associated with SIC and to provide effective targets for the treatment of SIC. ⋯ Subsequent differential analysis based on the high and low HIF-1α expression yielded 63 DEGs and then they were uploaded into Cytoscape software to construct a protein-protein interaction (PPI) network and 6 hub genes with the highest priority were obtained (CISH, THBS1, IMP1, MYC, SOCS3 and VCAN). Finally, a multifactorial COX analysis revealed a significant correlation between HIF-1α and survival in SIC patients, which was further validated by in vitro and in vivo experiments. Conclusion: Our findings will provide new insights into the pathogenesis of SIC, and HIF-1α may have important applications as a potential biomarker for early detection and therapeutic intervention in SIC.
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Background: Tumor necrosis factor receptor associated factor 3 (TRAF3) and deubiquitinating enzyme ubiquitin-specific protease 33 (USP33) have been identified to play important roles in inflammatory diseases, including acute pancreatitis (AP). Here, we aimed to explore whether USP33 affected AP progression by affecting TRAF3 expression through deubiquitination. Methods: Caerulein-treated HPDE6-C7 cells were used to mimic AP conditions in vitro. ⋯ Further analyses showed that USP33 knockdown reversed caerulein-induced apoptosis, oxidative stress and inflammation in HPDE6-C7 cells by TRAF3 (P < 0.05). Moreover, USP33-TRAF3 activated the NF-κB pathway (P < 0.05). Conclusion: USP33 promoted caerulein-induced apoptosis, oxidative stress and inflammation in pancreatic ductal cells by deubiquitinating TRAF3, indicating a novel insight into the pathogenesis of AP.