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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Sepsis is a common, heterogeneous, and frequently lethal condition of organ dysfunction and immune dysregulation due to infection. The causes of its heterogeneity, including the contribution of the pathogen, remain unknown. Using cecal slurry, a widely used murine model of intraperitoneal polymicrobial sepsis, as well as 16S ribosomal RNA sequencing and measurement of immune markers, we performed a series of translational analyses to determine whether microbial variation in cecal slurry composition (representing intra-abdominal pathogens) mediated variation in septic response. ⋯ Likewise, in a human cohort of patients with intra-abdominal abscesses, Enterobacteriaceae was also associated with increased inflammatory markers. Taken together, these data demonstrate that intra-abdominal Enterobacteriaceae drives inflammation in sepsis both in animal models and human subjects. More broadly, our results demonstrate that pathogen identity is a major driver of the host response in polymicrobial sepsis and should not be overlooked as a major source of phenotypic heterogeneity.
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Introduction: We hypothesized extracellular vesicles (EVs) from preconditioned human-induced pluripotent stem cell-derived mesenchymal stem cells (iMSCs) attenuate LPS-induced acute lung injury (ALI) and endotoxemia. Methods: iMSCs were incubated with cell stimulation cocktail (CSC) and EVs were isolated. iMSC-EVs were characterized by size and EV markers. Biodistribution of intratracheal (IT), intravenous, and intraperitoneal injection of iMSC-EVs in mice was examined using IVIS. ⋯ Administration of IT iMSC-EVs 2 h after LPS downregulated the increase in proinflammatory cytokines (TNF-α/IL-6) by LPS and further increased IL-10 levels. Conclusions: iMSC-EVs attenuate the inflammatory effects of LPS on cytokine levels in ALI and IP LPS in mice. LPS-induced mortality was improved with administration of iMSC-EVs.
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Background: The association between sepsis and noninfectious respiratory diseases is well-documented, yet the specific causal link between the two remains unclear. In order to explore this relationship further, we employed a Mendelian randomization (MR) analysis utilizing data from the UK Biobank and FinnGen Biobank. Methods: We analyzed the summary statistics of a genome-wide association study summary statistics for chronic obstructive pulmonary disease (COPD), asthma, pulmonary embolism (PE), idiopathic pulmonary fibrosis (IPF), obstructive sleep apnea (OSA), lung cancer, sepsis, and sepsis-related mortality. ⋯ IPF and OSA were not significantly associated with sepsis or sepsis-related mortality ( P > 0.05). Conclusion: Our MR analysis offers new insights into potential links between noninfectious respiratory diseases and the risk of sepsis. However, additional investigation into the underlying mechanisms and clinical studies are necessary to confirm these findings.
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Background: Myocardial infarction (MI) is a severe condition that typically results from the ischemia and necrosis of heart muscle. Kruppel-like factor 6 (KLF6) can aggravate myocardial ischemia/reperfusion injury. This work aims to reveal its role and mechanism in hypoxia/reoxygenation (H/R)-induced cardiomyocyte injury. ⋯ Additionally, WTAP stabilized KLF6 mRNA by regulating its m6A modification. Furthermore, WTAP knockdown rescued H/R-induced AC16 cell apoptosis, inflammatory response, oxidative stress, and ferroptosis by decreasing KLF6 expression. Conclusion: WTAP-mediated m6A modification of KLF6 aggravated hypoxia/reoxygenation-induced apoptosis, inflammatory response, oxidative stress, and ferroptosis of human cardiomyocytes, providing a therapeutic strategy for MI.
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Sepsis is a highly prevalent and deadly disease. Currently, there is a lack of ideal biomarker prognostis models for sepsis. We attempt to construct a model capable of predicting the prognosis of sepsis patients by integrating transcriptomic and proteomic data. ⋯ Through multifactor Cox-Lasso regression analysis, a prognostic model based on these 16 genes was constructed. Kaplan-Meier survival analysis and receiver operating characteristic curve analysis were used to further validate the high stability and good predictive ability of this prognostic model with internal and external data. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of overall survival-DEGs and differentially expressed genes between high and low-risk groups based on the prognostic model revealed significant enrichment in immune-related pathways, particularly those associated with viral regulation.